增加训练yolo的代码

.gitignore

@@ -0,0 +1,3 @@
+/cpp_ext/build/
+/.cursor/
+/dist/

4g_download_manager.py

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+import re
+import hashlib
+import binascii
+from maix import time
+from power import get_bus_voltage, voltage_to_percent
+from urllib.parse import urlparse
+from hardware import hardware_manager
+
+
+class DownloadManager4G:
+    """4g下载管理器（单例）"""
+    _instance = None
+
+    def __new__(cls):
+        if cls._instance is None:
+            cls._instance = super(DownloadManager4G, cls).__new__(cls)
+            cls._instance._initialized = False
+        return cls._instance
+
+    def __init__(self):
+        if self._initialized:
+            return
+
+        # 私有状态
+        self.FRAG_SIZE = 1024
+        self.FRAG_DELAY = 10
+        self._initialized = True
+
+    def _log(self, *a):
+        if debug:
+            self.logger.debug(" ".join(str(x) for x in a))
+
+    def _pwr_log(self, prefix=""):
+        """debug 用：输出电压/电量"""
+        if not debug:
+            return
+        try:
+            v = get_bus_voltage()
+            p = voltage_to_percent(v)
+            self.logger.debug(f"[PWR]{prefix} v={v:.3f}V p={p}%")
+        except Exception as e:
+            try:
+                self.logger.debug(f"[PWR]{prefix} read_failed: {e}")
+            except:
+                pass
+
+    def _clear_http_events(self):
+        if hardware_manager.at_client:
+            while hardware_manager.at_client.pop_http_event() is not None:
+                pass
+
+    def _parse_httpid(self, resp: str):
+        m = re.search(r"\+MHTTPCREATE:\s*(\d+)", resp)
+        return int(m.group(1)) if m else None
+
+    def _get_ip(self, ):
+        r = hardware_manager.at_client.send("AT+CGPADDR=1", "OK", 3000)
+        m = re.search(r'\+CGPADDR:\s*1,"([^"]+)"', r)
+        return m.group(1) if m else ""
+
+    def _ensure_pdp(self, ):
+        ip = self._get_ip()
+        if ip and ip != "0.0.0.0":
+            return True, ip
+        hardware_manager.at_client.send("AT+MIPCALL=1,1", "OK", 15000)
+        for _ in range(10):
+            ip = self._get_ip()
+            if ip and ip != "0.0.0.0":
+                return True, ip
+            time.sleep(1)
+        return False, ip
+
+    def _extract_hdr_fields(self, hdr_text: str):
+        mlen = re.search(r"Content-Length:\s*(\d+)", hdr_text, re.IGNORECASE)
+        clen = int(mlen.group(1)) if mlen else None
+        mmd5 = re.search(r"Content-Md5:\s*([A-Za-z0-9+/=]+)", hdr_text, re.IGNORECASE)
+        md5_b64 = mmd5.group(1).strip() if mmd5 else None
+        return clen, md5_b64
+
+    def _extract_content_range(self, hdr_text: str):
+        m = re.search(r"Content-Range:\s*bytes\s*(\d+)\s*-\s*(\d+)\s*/\s*(\d+)", hdr_text, re.IGNORECASE)
+        if not m:
+            return None, None, None
+        try:
+            return int(m.group(1)), int(m.group(2)), int(m.group(3))
+        except:
+            return None, None, None
+
+    def _hard_reset_http(self, ):
+        """模块进入"坏状态"时的保守清场"""
+        self._clear_http_events()
+        for i in range(0, 6):
+            try:
+                hardware_manager.at_client.send(f"AT+MHTTPDEL={i}", "OK", 1200)
+            except:
+                pass
+        self._clear_http_events()
+
+    def _create_httpid(self, full_reset=False):
+        self._clear_http_events()
+        if hardware_manager.at_client:
+            hardware_manager.at_client.flush()
+        if full_reset:
+            self._hard_reset_http()
+        resp = hardware_manager.at_client.send(f'AT+MHTTPCREATE="{base_url}"', "OK", 8000)
+        hid = self._parse_httpid(resp)
+        if self._is_https:
+            resp = hardware_manager.at_client.send(f'AT+MHTTPCFG="ssl",{hid},1,1', "OK", 2000)
+            if "ERROR" in resp or "CME ERROR" in resp:
+                self.logger.error(f"MHTTPCFG SSL failed: {resp}")
+                # 尝试https 降级到http
+                downgraded_base_url = base_url.replace("https://", "http://")
+                resp = hardware_manager.at_client.send(f'AT+MHTTPCREATE="{downgraded_base_url}"', "OK", 8000)
+                hid = self._parse_httpid(resp)
+
+        return hid, resp
+
+    def _fetch_range_into_buf(self, start, want_len, out_buf, path, full_reset=False):
+        """
+        请求 Range [start, start+want_len)，写入 out_buf（bytearray，长度=want_len）
+        返回 (ok, msg, total_len, md5_b64, got_len)
+        """
+        end_incl = start + want_len - 1
+        hid, cresp = self._create_httpid(full_reset=full_reset)
+        if hid is None:
+            return False, f"MHTTPCREATE failed: {cresp}", None, None, 0
+
+        # 降低 URC 压力（分片/延迟）
+        hardware_manager.at_client.send(f'AT+MHTTPCFG="fragment",{hid},{self.FRAG_SIZE},{self.FRAG_DELAY}', "OK", 1500)
+        # 设置 Range header（inclusive）
+        hardware_manager.at_client.send(f'AT+MHTTPCFG="header",{hid},"Range: bytes={start}-{end_incl}"', "OK", 3000)
+
+        req = hardware_manager.at_client.send(f'AT+MHTTPREQUEST={hid},1,0,"{path}"', "OK", 15000)
+        if "ERROR" in req or "CME ERROR" in req:
+            hardware_manager.at_client.send(f"AT+MHTTPDEL={hid}", "OK", 2000)
+            return False, f"MHTTPREQUEST failed: {req}", None, None, 0
+
+        # 等 header + content
+        hdr_text = None
+        hdr_accum = ""
+        code = None
+        resp_total = None
+        total_len = None
+        md5_b64 = None
+
+        got_ranges = set()
+        last_sum = 0
+        t0 = time.ticks_ms()
+        timeout_ms = 9000
+        logged_hdr = False
+
+        while time.ticks_ms() - t0 < timeout_ms:
+            ev = hardware_manager.at_client.pop_http_event() if hardware_manager.at_client else None
+            if not ev:
+                time.sleep_ms(5)
+                continue
+
+            if ev[0] == "header":
+                _, ehid, ecode, ehdr = ev
+                if ehid != hid:
+                    continue
+                code = ecode
+                hdr_text = ehdr
+                if ehdr:
+                    hdr_accum = (hdr_accum + "\n" + ehdr) if hdr_accum else ehdr
+
+                resp_total_tmp, md5_tmp = self._extract_hdr_fields(hdr_accum)
+                if md5_tmp:
+                    md5_b64 = md5_tmp
+                cr_s, cr_e, cr_total = self._extract_content_range(hdr_accum)
+                if cr_total is not None:
+                    total_len = cr_total
+                if resp_total_tmp is not None:
+                    resp_total = resp_total_tmp
+                elif resp_total is None and (cr_s is not None) and (cr_e is not None) and (cr_e >= cr_s):
+                    resp_total = (cr_e - cr_s + 1)
+                if (not logged_hdr) and (resp_total is not None or total_len is not None):
+                    self._log(f"[HDR] id={hid} code={code} clen={resp_total} cr={cr_s}-{cr_e}/{cr_total}")
+                    logged_hdr = True
+                continue
+
+            if ev[0] == "content":
+                _, ehid, _total, _sum, _cur, payload = ev
+                if ehid != hid:
+                    continue
+                if resp_total is None:
+                    resp_total = _total
+                if resp_total is None or resp_total <= 0:
+                    continue
+                start_rel = _sum - _cur
+                end_rel = _sum
+                if start_rel < 0 or start_rel >= resp_total:
+                    continue
+                if end_rel > resp_total:
+                    end_rel = resp_total
+                actual_len = min(len(payload), end_rel - start_rel)
+                if actual_len <= 0:
+                    continue
+                out_buf[start_rel:start_rel + actual_len] = payload[:actual_len]
+                got_ranges.add((start_rel, start_rel + actual_len))
+                if _sum > last_sum:
+                    last_sum = _sum
+                if debug and (last_sum >= resp_total or (last_sum % 512 == 0)):
+                    self._log(f"[CHUNK] {start}+{last_sum}/{resp_total}")
+
+                if last_sum >= resp_total:
+                    break
+
+        # 清理实例（快路径：只删当前 hid）
+        try:
+            hardware_manager.at_client.send(f"AT+MHTTPDEL={hid}", "OK", 2000)
+        except:
+            pass
+
+        if resp_total is None:
+            return False, "no_header_or_total", total_len, md5_b64, 0
+
+        # 计算实际填充长度
+        merged = sorted(got_ranges)
+        merged2 = []
+        for s, e in merged:
+            if not merged2 or s > merged2[-1][1]:
+                merged2.append((s, e))
+            else:
+                merged2[-1] = (merged2[-1][0], max(merged2[-1][1], e))
+        filled = sum(e - s for s, e in merged2)
+
+        if filled < resp_total:
+            return False, f"incomplete_chunk got={filled} expected={resp_total} code={code}", total_len, md5_b64, filled
+
+        got_len = resp_total
+        return True, "OK", total_len, md5_b64, got_len
+
+    def download_file_via_4g(self, url, filename,
+                             total_timeout_ms=600000,
+                             retries=3,
+                             debug=False):
+        """
+        ML307R HTTP 下载（更稳的"固定小块 Range 顺序下载"，基于main109.py）：
+        - 只依赖 +MHTTPURC:"header"/"content"（不依赖 MHTTPREAD/cached）
+        - 每次只请求一个小块 Range（默认 10240B），失败就重试同一块，必要时缩小块大小
+        - 每个 chunk 都重新 MHTTPCREATE/MHTTPREQUEST，避免卡在"206 header 但不吐 content"的坏状态
+        - 使用二进制模式下载，确保文件完整性
+        """
+
+
+        # 小块策略（与main109.py保持一致）
+        CHUNK_MAX = 10240
+        CHUNK_MIN = 128
+        CHUNK_RETRIES = 12
+
+
+        t_func0 = time.ticks_ms()
+
+        parsed = urlparse(url)
+        host = parsed.hostname
+        path = parsed.path or "/"
+        if parsed.query:
+            path = f"{path}?{parsed.query}"
+        if parsed.fragment:
+            path = f"{path}#{parsed.fragment}"
+        if not host:
+            return False, "bad_url (no host)"
+
+        if isinstance(url, str) and url.startswith("https://static.shelingxingqiu.com/"):
+            base_url = "https://static.shelingxingqiu.com"
+            # TODO：使用https，看看是否能成功
+            self._is_https = True
+        else:
+            base_url = f"http://{host}"
+            self._is_https = False
+
+
+        try:
+            self._begin_ota()
+        except:
+            pass
+
+        from network import network_manager
+        with network_manager.get_uart_lock():
+            try:
+                ok_pdp, ip = self._ensure_pdp()
+                if not ok_pdp:
+                    return False, f"PDP not ready (ip={ip})"
+
+                # 先清空旧事件，避免串台
+                self._clear_http_events()
+
+                # 为了支持随机写入，先创建空文件
+                try:
+                    with open(filename, "wb") as f:
+                        f.write(b"")
+                except Exception as e:
+                    return False, f"open_file_failed: {e}"
+
+                total_len = None
+                expect_md5_b64 = None
+
+                offset = 0
+                chunk = CHUNK_MAX
+                t_start = time.ticks_ms()
+                last_progress_ms = t_start
+                STALL_TIMEOUT_MS = 60000
+                last_pwr_ms = t_start
+                self._pwr_log(prefix=" ota_start")
+                bad_http_state = 0
+
+                while True:
+                    now = time.ticks_ms()
+                    if debug and time.ticks_diff(now, last_pwr_ms) >= 5000:
+                        last_pwr_ms = now
+                        self._pwr_log(prefix=f" off={offset}/{total_len or '?'}")
+                    if time.ticks_diff(now, t_start) > total_timeout_ms:
+                        return False, f"timeout overall after {total_timeout_ms}ms offset={offset} total={total_len}"
+
+                    if time.ticks_diff(now, last_progress_ms) > STALL_TIMEOUT_MS:
+                        return False, f"timeout stalled {STALL_TIMEOUT_MS}ms offset={offset} total={total_len}"
+
+                    if total_len is not None and offset >= total_len:
+                        break
+
+                    want = chunk
+                    if total_len is not None:
+                        remain = total_len - offset
+                        if remain <= 0:
+                            break
+                        if want > remain:
+                            want = remain
+
+                    # 本 chunk 的 buffer（长度=want）
+                    buf = bytearray(want)
+
+                    success = False
+                    last_err = "unknown"
+                    md5_seen = None
+                    got_len = 0
+                    for k in range(1, CHUNK_RETRIES + 1):
+                        do_full_reset = (bad_http_state >= 2)
+                        ok, msg, tlen, md5_b64, got = self._fetch_range_into_buf(offset, want, buf, base_url, path, full_reset=do_full_reset)
+                        last_err = msg
+                        if tlen is not None and total_len is None:
+                            total_len = tlen
+                        if md5_b64 and not expect_md5_b64:
+                            expect_md5_b64 = md5_b64
+                        if ok:
+                            success = True
+                            got_len = got
+                            bad_http_state = 0
+                            break
+
+                        try:
+                            if ("no_header_or_total" in msg) or ("MHTTPREQUEST failed" in msg) or (
+                                    "MHTTPCREATE failed" in msg):
+                                bad_http_state += 1
+                            else:
+                                bad_http_state = max(0, bad_http_state - 1)
+                        except:
+                            pass
+
+                        if chunk > CHUNK_MIN:
+                            chunk = max(CHUNK_MIN, chunk // 2)
+                            want = min(chunk, want)
+                            buf = bytearray(want)
+                        self._log(f"[RETRY] off={offset} want={want} try={k} err={msg}")
+                        self._pwr_log(prefix=f" retry{k} off={offset}")
+                        time.sleep_ms(120)
+
+                    if not success:
+                        return False, f"chunk_failed off={offset} want={want} err={last_err} total={total_len}"
+
+                    # 写入文件（二进制模式）
+                    try:
+                        with open(filename, "r+b") as f:
+                            f.seek(offset)
+                            f.write(bytes(buf))
+                    except Exception as e:
+                        return False, f"write_failed off={offset}: {e}"
+
+                    offset += len(buf)
+                    last_progress_ms = time.ticks_ms()
+                    chunk = CHUNK_MAX
+                    if debug:
+                        self._log(f"[OK] offset={offset}/{total_len or '?'}")
+
+                # MD5 校验
+                if expect_md5_b64 and hashlib is not None:
+                    try:
+                        with open(filename, "rb") as f:
+                            data = f.read()
+                        digest = hashlib.md5(data).digest()
+                        got_b64 = binascii.b2a_base64(digest).decode().strip()
+                        if got_b64 != expect_md5_b64:
+                            return False, f"md5_mismatch got={got_b64} expected={expect_md5_b64}"
+                        self.logger.debug(f"[4G-DL] MD5 verified: {got_b64}")
+                    except Exception as e:
+                        return False, f"md5_check_failed: {e}"
+
+                t_cost = time.ticks_diff(time.ticks_ms(), t_func0)
+                self.logger.info(f"[4G-DL] download complete: size={offset} ip={ip} cost_ms={t_cost}")
+                return True, f"OK size={offset} ip={ip} cost_ms={t_cost}"
+
+            finally:
+                self._end_ota()

4g_upload_manager.py

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+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+4G Image Upload Manager
+Uploads images to Qiniu cloud via ML307R 4G module TCP socket (MIPOPEN + MIPSEND).
+
+AT Command Sequence (ML307R TCP socket POST):
+  AT+MIPCALL=1,1                                  // Ensure PDP context active
+  AT+MIPCLOSE=<id>                                // Close old socket (ignore error)
+  AT+MIPOPEN=<id>,"TCP","<host>",80              // Open TCP socket
+  // Wait for +MIPOPEN: <id>,0 (success)
+  AT+MIPSEND=<id>,<len>                           // Send data
+  // Wait for ">" prompt, then write raw bytes
+  // Repeat MIPSEND for all chunks
+  // Wait for +MIPURC: "rtcp" response
+  AT+MIPCLOSE=<id>                                // Close socket
+"""
+
+import re
+import os
+import json
+from maix import time
+from urllib.parse import urlparse
+from logger_manager import logger_manager
+from hardware import hardware_manager
+
+# Multipart form boundary (simple alphanumeric to avoid AT command parser issues)
+BOUNDARY = "QiniuFormBoundary" + hex(int(time.time()))[2:]
+# Chunk size for MIPSEND (max 1024 to avoid AT line buffer limits)
+SEND_CHUNK = 1024
+# Socket ID for upload (dedicated to avoid conflict with main app TCP)
+UPLOAD_SOCK_ID = 3
+
+
+class FourGUploadManager:
+    """4G image upload manager using ML307R TCP socket (MIPOPEN + MIPSEND)"""
+
+    def __init__(self, at_client):
+        """Initialize with AT client instance"""
+        self.at = at_client
+        self.logger = logger_manager.logger
+
+    # ------------------------------------------------------------------ logging
+    def _log(self, msg):
+        try:
+            self.logger.debug("[4G-UL] " + msg)
+        except Exception:
+            print("[4G-UL] " + msg)
+
+    def _log_info(self, msg):
+        try:
+            self.logger.info("[4G-UL] " + msg)
+        except Exception:
+            print("[4G-UL] " + msg)
+
+    def _log_error(self, msg):
+        try:
+            self.logger.error("[4G-UL] " + msg)
+        except Exception:
+            print("[4G-UL] " + msg)
+
+    # --------------------------------------------------------------- helpers
+    def _ensure_pdp(self):
+        """Ensure PDP context is active; returns (ok, ip)"""
+        r = self.at.send("AT+CGPADDR=1", "OK", 3000)
+        m = re.search(r'\+CGPADDR:\s*1,"([^"]+)"', r)
+        ip = m.group(1) if m else ""
+        if ip and ip != "0.0.0.0":
+            return True, ip
+        self.at.send("AT+MIPCALL=1,1", "OK", 15000)
+        for _ in range(10):
+            r = self.at.send("AT+CGPADDR=1", "OK", 3000)
+            m = re.search(r'\+CGPADDR:\s*1,"([^"]+)"', r)
+            ip = m.group(1) if m else ""
+            if ip and ip != "0.0.0.0":
+                return True, ip
+            time.sleep(1)
+        return False, ip
+
+    def _is_error(self, resp):
+        """Check AT response for any error indicators"""
+        return "ERROR" in resp or "CME ERROR" in resp
+
+    # --------------------------------------------------------- multipart body
+    def _build_multipart_body(self, image_path, upload_token, key):
+        """
+        Build multipart/form-data body as bytes for Qiniu upload.
+
+        Fields:
+          - token : Qiniu upload token
+          - key   : object key in bucket
+          - file  : binary image data
+        """
+        boundary = BOUNDARY.encode()
+
+        with open(image_path, "rb") as f:
+            file_data = f.read()
+
+        filename = os.path.basename(image_path)
+        ext = os.path.splitext(image_path)[1].lower()
+        ct_map = {
+            ".png": "image/png",
+            ".jpg": "image/jpeg",
+            ".jpeg": "image/jpeg",
+            ".bmp": "image/bmp",
+            ".webp": "image/webp",
+        }
+        content_type = ct_map.get(ext, "application/octet-stream")
+
+        body = bytearray()
+
+        # -- token field --
+        body += b"--" + boundary + b"\r\n"
+        body += b'Content-Disposition: form-data; name="token"\r\n'
+        body += b"\r\n"
+        body += upload_token.encode("utf-8") + b"\r\n"
+
+        # -- key field --
+        body += b"--" + boundary + b"\r\n"
+        body += b'Content-Disposition: form-data; name="key"\r\n'
+        body += b"\r\n"
+        body += key.encode("utf-8") + b"\r\n"
+
+        # -- file field --
+        body += b"--" + boundary + b"\r\n"
+        body += (
+            b'Content-Disposition: form-data; name="file"; filename="'
+            + filename.encode("utf-8")
+            + b'"\r\n'
+        )
+        body += b"Content-Type: " + content_type.encode("utf-8") + b"\r\n"
+        body += b"\r\n"
+        body += file_data + b"\r\n"
+
+        # -- closing boundary --
+        body += b"--" + boundary + b"--\r\n"
+
+        return bytes(body)
+
+    # --------------------------------------------------- TCP socket helpers
+    def _close_socket(self, sock_id):
+        """Close socket, ignore CME ERROR 55 (already closed)"""
+        try:
+            resp = self.at.send("AT+MIPCLOSE=" + str(sock_id), "OK", 5000)
+            self._log("socket " + str(sock_id) + " closed: " + resp)
+        except Exception as e:
+            # Ignore CME ERROR 55 (socket not open)
+            self._log("socket close (may already be closed): " + str(e))
+
+    def _open_socket(self, sock_id, host, port):
+        """
+        Open TCP socket to host:port.
+        Returns (success, error_msg)
+        """
+        cmd = 'AT+MIPOPEN=' + str(sock_id) + ',"TCP","' + host + '",' + str(port)
+        resp = self.at.send(cmd, "OK", 15000)
+
+        if self._is_error(resp):
+            return False, "MIPOPEN failed: " + resp
+
+        # Wait for +MIPOPEN: <id>,0 (success) or +MIPOPEN: <id>,<error_code>
+        # The URC may come in the same response or separately
+        mipopen_pattern = r"\+MIPOPEN:\s*" + str(sock_id) + r",(\d+)"
+        m = re.search(mipopen_pattern, resp)
+
+        if m:
+            result_code = int(m.group(1))
+            if result_code == 0:
+                return True, ""
+            else:
+                return False, "MIPOPEN error code: " + str(result_code)
+
+        # If not in initial response, wait for URC
+        try:
+            urc_resp = self.at.send("", "+MIPOPEN:", 15000)
+            m = re.search(mipopen_pattern, urc_resp)
+            if m:
+                result_code = int(m.group(1))
+                if result_code == 0:
+                    return True, ""
+                else:
+                    return False, "MIPOPEN error code: " + str(result_code)
+        except Exception as e:
+            return False, "MIPOPEN URC timeout: " + str(e)
+
+        return False, "MIPOPEN no response"
+
+    def _send_chunk(self, sock_id, chunk):
+        """
+        Send a single chunk via MIPSEND.
+        Thread safety is provided by the outer network_manager.get_uart_lock().
+        NOTE: Do NOT add self.at._cmd_lock here — self.at.send() already
+        acquires it internally and threading.Lock is not reentrant.
+        Returns (success, error_msg)
+        """
+        chunk_len = len(chunk)
+
+        # Step 1: Send AT+MIPSEND command and wait for ">" prompt
+        cmd = "AT+MIPSEND=" + str(sock_id) + "," + str(chunk_len)
+        try:
+            resp = self.at.send(cmd, ">", 3000)
+            if ">" not in resp:
+                return False, "MIPSEND no > prompt: " + resp
+        except Exception as e:
+            return False, "MIPSEND > prompt error: " + str(e)
+
+        # Step 2: Write raw binary bytes directly to UART
+        # Must be done immediately after ">" prompt, no lock re-acquisition
+        try:
+            self.at.uart.write(chunk)
+        except Exception as e:
+            return False, "MIPSEND write error: " + str(e)
+
+        # Step 3: Wait for OK or SEND OK confirmation
+        try:
+            confirm_resp = self.at.send("", "OK", 8000)
+            if self._is_error(confirm_resp):
+                return False, "MIPSEND confirmation error: " + confirm_resp
+        except Exception as e:
+            return False, "MIPSEND confirmation timeout: " + str(e)
+
+        return True, ""
+
+    def _send_data(self, sock_id, data):
+        """
+        Send data in chunks via MIPSEND.
+        Returns (success, error_msg)
+        """
+        total_len = len(data)
+        offset = 0
+        chunk_num = 0
+
+        while offset < total_len:
+            end = min(offset + SEND_CHUNK, total_len)
+            chunk = data[offset:end]
+
+            ok, err = self._send_chunk(sock_id, chunk)
+            if not ok:
+                return False, "Chunk " + str(chunk_num) + " failed: " + err
+
+            chunk_num += 1
+            offset = end
+
+            if chunk_num % 10 == 0 or offset >= total_len:
+                self._log(
+                    "send progress: "
+                    + str(offset) + "/" + str(total_len)
+                    + " bytes (" + str(chunk_num) + " chunks)"
+                )
+
+        self._log("all data sent: " + str(chunk_num) + " chunks, " + str(total_len) + " bytes")
+        return True, ""
+
+    def _wait_for_response(self, sock_id, timeout_ms=30000):
+        """
+        Wait for +MIPURC: "rtcp" response.
+        Returns (success, status_code, body, error_msg)
+        """
+        pattern = r'\+MIPURC:\s*"rtcp",\s*' + str(sock_id) + r',\s*(\d+),'
+        t0 = time.ticks_ms()
+
+        while time.ticks_diff(time.ticks_ms(), t0) < timeout_ms:
+            try:
+                # Try to get response with short timeout
+                resp = self.at.send("", "+MIPURC:", 1000)
+                m = re.search(pattern, resp)
+                if m:
+                    data_len = int(m.group(1))
+                    # Extract HTTP response data after the URC header
+                    # Format: +MIPURC: "rtcp",<sock_id>,<len>,<data>
+                    urc_end = resp.find("+MIPURC:")
+                    if urc_end >= 0:
+                        # Find the data after the length field
+                        match_end = m.end()
+                        http_data = resp[match_end:match_end + data_len]
+
+                        # Parse HTTP status line
+                        status_match = re.search(r"HTTP/\d\.\d\s+(\d+)", http_data)
+                        status_code = int(status_match.group(1)) if status_match else None
+
+                        # Extract body (after headers)
+                        header_end = http_data.find("\r\n\r\n")
+                        if header_end >= 0:
+                            body = http_data[header_end + 4:]
+                        else:
+                            body = http_data
+
+                        return True, status_code, body, ""
+            except Exception:
+                pass
+
+            time.sleep_ms(100)
+
+        return False, None, "", "Response timeout"
+
+    def _build_http_request(self, host, body_bytes):
+        """
+        Build full HTTP POST request as bytes.
+        """
+        headers = (
+            "POST / HTTP/1.1\r\n"
+            "Host: " + host + "\r\n"
+            "Content-Type: multipart/form-data; boundary=" + BOUNDARY + "\r\n"
+            "Content-Length: " + str(len(body_bytes)) + "\r\n"
+            "Connection: close\r\n"
+            "\r\n"
+        )
+        return headers.encode("utf-8") + body_bytes
+
+    # ============================================================ public API
+    def upload_file(self, file_path, upload_url, upload_token, key):
+        """Generic file upload to Qiniu cloud via 4G TCP socket POST.
+
+        Args:
+            file_path: Local path to any file
+            upload_url: Qiniu upload URL
+            upload_token: Qiniu upload token
+            key: File key in Qiniu bucket
+
+        Returns:
+            dict with 'success' bool and 'key'/'error' fields
+        """
+        return self.upload_image(file_path, upload_url, upload_token, key)
+
+    def upload_image(self, image_path, upload_url, upload_token, key):
+        """
+        Upload image to Qiniu cloud via 4G TCP socket POST.
+
+        Args:
+            image_path: Local path to image file
+            upload_url: Qiniu upload URL (e.g., "https://upload.qiniup.com")
+            upload_token: Qiniu upload token
+            key: File key in Qiniu (e.g., "shootPic/device01/shoot01.png")
+
+        Returns:
+            dict with 'success' bool and 'key'/'error' fields
+        """
+        if not self.at:
+            return {"success": False, "error": "AT client not available"}
+
+        if not os.path.exists(image_path):
+            return {"success": False, "error": "Image file not found: " + image_path}
+
+        # Force HTTP for 4G module (extract hostname, use port 80)
+        parsed = urlparse(upload_url)
+        host = parsed.hostname
+        if not host:
+            return {"success": False, "error": "Invalid upload URL: " + upload_url}
+
+        if upload_url.lower().startswith("https://"):
+            self._log_info("Converted HTTPS->HTTP for 4G module")
+
+        file_size = os.path.getsize(image_path)
+        self._log_info(
+            "upload: " + image_path + " (" + str(file_size) + "B) -> "
+            + host + " key=" + key
+        )
+
+        from network import network_manager
+        with network_manager.get_uart_lock():
+            try:
+                # ---- Step 1: Ensure PDP context ----
+                ok_pdp, ip = self._ensure_pdp()
+                if not ok_pdp:
+                    return {"success": False, "error": "PDP not ready (ip=" + str(ip) + ")"}
+
+                # ---- Step 2: Close old socket ----
+                self._close_socket(UPLOAD_SOCK_ID)
+
+                # ---- Step 3: Open TCP socket ----
+                ok, err = self._open_socket(UPLOAD_SOCK_ID, host, 80)
+                if not ok:
+                    return {"success": False, "error": "Socket open failed: " + err}
+
+                try:
+                    # ---- Step 4: Build multipart body and HTTP request ----
+                    body = self._build_multipart_body(image_path, upload_token, key)
+                    http_request = self._build_http_request(host, body)
+                    self._log("HTTP request size: " + str(len(http_request)) + " bytes")
+
+                    # ---- Step 5: Send data via MIPSEND ----
+                    ok, err = self._send_data(UPLOAD_SOCK_ID, http_request)
+                    if not ok:
+                        return {"success": False, "error": "Send failed: " + err}
+
+                    # ---- Step 6: Wait for response ----
+                    ok, status_code, resp_body, err = self._wait_for_response(UPLOAD_SOCK_ID)
+                    if not ok:
+                        return {"success": False, "error": "Response error: " + err}
+
+                    # ---- Step 7: Parse response ----
+                    if status_code is None:
+                        return {"success": False, "error": "No HTTP status in response"}
+
+                    if 200 <= status_code < 300:
+                        try:
+                            resp_json = json.loads(resp_body)
+                            resp_key = resp_json.get("key", key)
+                            self._log_info("upload success: key=" + resp_key + " code=" + str(status_code))
+                            return {"success": True, "key": resp_key}
+                        except Exception as e:
+                            self._log_error("response parse error: " + str(e))
+                            return {
+                                "success": True,
+                                "key": key,
+                                "raw": resp_body,
+                            }
+                    else:
+                        self._log_error(
+                            "HTTP error: code=" + str(status_code) + " body=" + resp_body[:200]
+                        )
+                        return {
+                            "success": False,
+                            "error": "HTTP " + str(status_code),
+                            "response": resp_body,
+                        }
+
+                finally:
+                    # ---- Step 8: Always close socket ----
+                    self._close_socket(UPLOAD_SOCK_ID)
+
+            except Exception as e:
+                self._log_error("upload exception: " + str(e))
+                return {"success": False, "error": str(e)}
+
+
+# ====================================================================== demo
+if __name__ == "__main__":
+    # Demo usage — requires actual ML307R 4G module hardware to run.
+    print("FourGUploadManager - requires ML307R 4G module hardware")
+    print()
+    print("Usage:")
+    print("  from hardware import hardware_manager")
+    print("  from at_client import ATClient")
+    print("  from maix import uart")
+    print()
+    print("  # Initialize UART and AT client (normally done in hardware init)")
+    print("  uart4g = uart.UART('/dev/ttyS1', 115200, ...)")
+    print("  at_client = ATClient(uart4g)")
+    print("  at_client.start()")
+    print()
+    print("  # Upload image to Qiniu")
+    print("  uploader = FourGUploadManager(at_client)")
+    print("  result = uploader.upload_image(")
+    print("      image_path='/maixapp/apps/t11/shoot.png',")
+    print("      upload_url='https://upload.qiniup.com',")
+    print("      upload_token='<qiniu_upload_token>',")
+    print("      key='shootPic/device01/shoot01.png'")
+    print("  )")
+    print("  print('Upload result:', result)")

S99archery

@@ -0,0 +1,79 @@
+#!/bin/sh
+# /etc/init.d/S99archery
+# 系统启动时处理致命错误恢复（仅处理无法启动的情况）
+# 注意：应用的启动由系统自动启动机制处理（通过 auto_start.txt）
+# 功能：
+# 1. 处理致命错误（无法启动）- 恢复 main.py
+# 2. 如果重启次数超过阈值，恢复 main.py 并重启系统
+
+APP_DIR="/maixapp/apps/t11"
+MAIN_PY="$APP_DIR/main.py"
+PENDING_FILE="$APP_DIR/ota_pending.json"
+BACKUP_BASE="$APP_DIR/backups"
+
+# 进入应用目录
+cd "$APP_DIR" || exit 0
+
+# 检查 pending 文件，如果存在且超过重启次数，恢复 main.py（处理致命错误）
+if [ -f "$PENDING_FILE" ]; then
+    echo "[S99] 检测到 ota_pending.json，检查重启计数..."
+    
+    # 尝试从JSON中提取重启计数（使用grep简单提取）
+    RESTART_COUNT=$(cat "$PENDING_FILE" 2>/dev/null | grep -o '"restart_count":[0-9]*' | grep -o '[0-9]*' || echo "0")
+    MAX_RESTARTS=$(cat "$PENDING_FILE" 2>/dev/null | grep -o '"max_restarts":[0-9]*' | grep -o '[0-9]*' || echo "3")
+    
+    if [ -n "$RESTART_COUNT" ] && [ "$RESTART_COUNT" -ge "$MAX_RESTARTS" ]; then
+        echo "[S99] 检测到重启次数 ($RESTART_COUNT) 超过阈值 ($MAX_RESTARTS)，恢复 main.py..."
+        
+        # 尝试从JSON中提取备份目录
+        BACKUP_DIR=$(cat "$PENDING_FILE" 2>/dev/null | grep -o '"backup_dir":"[^"]*"' | grep -o '/[^"]*' || echo "")
+        
+        if [ -n "$BACKUP_DIR" ] && [ -f "$BACKUP_DIR/main.py" ]; then
+            # 使用指定的备份目录
+            echo "[S99] 从备份目录恢复: $BACKUP_DIR/main.py"
+            cp "$BACKUP_DIR/main.py" "$MAIN_PY" 2>/dev/null && echo "[S99] 已恢复 main.py"
+        else
+            # 查找最新的备份目录
+            LATEST_BACKUP=$(ls -dt "$BACKUP_BASE"/backup_* 2>/dev/null | head -1)
+            if [ -n "$LATEST_BACKUP" ] && [ -f "$LATEST_BACKUP/main.py" ]; then
+                echo "[S99] 从最新备份恢复: $LATEST_BACKUP/main.py"
+                cp "$LATEST_BACKUP/main.py" "$MAIN_PY" 2>/dev/null && echo "[S99] 已恢复 main.py"
+            else
+                # 如果没有备份目录，尝试使用 main.py.bak
+                if [ -f "$APP_DIR/main.py.bak" ]; then
+                    echo "[S99] 从 main.py.bak 恢复"
+                    cp "$APP_DIR/main.py.bak" "$MAIN_PY" 2>/dev/null && echo "[S99] 已恢复 main.py"
+                fi
+            fi
+        fi
+        
+        # 恢复后重置重启计数，避免循环恢复
+        # 注意：不在这里删除 pending 文件，让 main.py 在心跳成功后删除
+        # 但是重置重启计数，以便恢复后的版本可以重新开始计数
+        python3 -c "
+import json, os
+try:
+    pending_path = '$PENDING_FILE'
+    if os.path.exists(pending_path):
+        with open(pending_path, 'r', encoding='utf-8') as f:
+            d = json.load(f)
+        d['restart_count'] = 0  # 重置重启计数
+        with open(pending_path, 'w', encoding='utf-8') as f:
+            json.dump(d, f)
+        print('[S99] 已重置重启计数为 0')
+except Exception as e:
+    print(f'[S99] 重置重启计数失败: {e}')
+" 2>/dev/null || echo "[S99] 无法重置重启计数（可能需要Python支持）"
+        
+        echo "[S99] 已恢复 main.py，重启系统..."
+        echo "[S99] 注意：pending 文件将在心跳成功后由 main.py 删除"
+        sleep 2
+        reboot
+        exit 0
+    fi
+fi
+
+# 不启动应用，让系统自动启动机制处理
+# 这个脚本只负责处理致命错误恢复
+exit 0
+

adc.py

@@ -4,14 +4,13 @@ from maix import time
 a = adc.ADC(0, adc.RES_BIT_12)
 
 while True:
-    raw_data = a.read()
-    print(f"ADC raw data:{raw_data}")
+    # raw_data = a.read()
+    # print(f"ADC raw data:{raw_data}")
     # if raw_data > 2450:
     #     print(f"ADC raw data:{raw_data}")
     # elif raw_data < 2000:
     #     print(f"ADC raw data:{raw_data}")
-    # time.sleep_ms(50)
+    time.sleep_ms(1)
 
-    # vol = a.read_vol()
-
-    # print(f"ADC vol:{vol}")
+    vol = int(a.read_vol() * 10) / 10
+    print(f"ADC vol:{vol:.1f}, {time.time():.4f}")

app.yaml

@@ -1,8 +1,38 @@
 id: t11
 name: t11
-version: 1.0.2
+version: 1.2.12
 author: t11
 icon: ''
 desc: t11
 files:
+  - 4g_download_manager.py
+  - 4g_upload_manager.py
+  - app.yaml
+  - archery_netcore.cpython-311-riscv64-linux-gnu.so
+  - at_client.py
+  - camera_manager.py
+  - cameraParameters.xml
+  - config.py
+  - hardware.py
+  - laser_manager.py
+  - logger_manager.py
   - main.py
+  - model_270139.cvimodel
+  - model_270139.mud
+  - model_270820.cvimodel
+  - model_270820.mud
+  - network.py
+  - ota_manager.py
+  - power.py
+  - server.pem
+  - shoot_manager.py
+  - shot_id_generator.py
+  - target_roi_yolo.py
+  - time_sync.py
+  - triangle_positions.json
+  - triangle_target.py
+  - version.py
+  - vision.py
+  - wifi_config_httpd.py
+  - wifi.py
+  - wpa_supplicant_conf.py

aruco_detector.py

@@ -0,0 +1,420 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+ArUco标记检测模块
+提供基于ArUco标记的靶心标定和激光点定位功能
+"""
+import cv2
+import numpy as np
+import math
+import config
+from logger_manager import logger_manager
+
+
+class ArUcoDetector:
+    """ArUco标记检测器"""
+    
+    def __init__(self):
+        self.logger = logger_manager.logger
+        # 创建ArUco字典和检测器参数
+        self.aruco_dict = cv2.aruco.getPredefinedDictionary(config.ARUCO_DICT_TYPE)
+        self.detector_params = cv2.aruco.DetectorParameters()
+        
+        # 设置检测参数
+        self.detector_params.minMarkerPerimeterRate = config.ARUCO_MIN_MARKER_PERIMETER_RATE
+        self.detector_params.cornerRefinementMethod = config.ARUCO_CORNER_REFINEMENT_METHOD
+        
+        # 创建检测器
+        self.detector = cv2.aruco.ArucoDetector(self.aruco_dict, self.detector_params)
+        
+        # 预定义靶纸上的标记位置（物理坐标，毫米）
+        self.marker_positions_mm = config.ARUCO_MARKER_POSITIONS_MM
+        self.marker_ids = config.ARUCO_MARKER_IDS
+        self.marker_size_mm = config.ARUCO_MARKER_SIZE_MM
+        self.target_paper_size_mm = config.TARGET_PAPER_SIZE_MM
+        
+        # 靶心偏移（相对于靶纸中心）
+        self.target_center_offset_mm = config.TARGET_CENTER_OFFSET_MM
+        
+        if self.logger:
+            self.logger.info(f"[ARUCO] ArUco检测器初始化完成，字典类型: {config.ARUCO_DICT_TYPE}")
+    
+    def detect_markers(self, frame):
+        """
+        检测图像中的ArUco标记
+        
+        Args:
+            frame: MaixPy图像帧对象
+            
+        Returns:
+            (corners, ids, rejected) - 检测到的标记角点、ID列表、被拒绝的候选
+            如果检测失败返回 (None, None, None)
+        """
+        try:
+            # 转换为OpenCV格式
+            from maix import image
+            img_cv = image.image2cv(frame, False, False)
+            
+            # 转换为灰度图（ArUco检测需要）
+            if len(img_cv.shape) == 3:
+                gray = cv2.cvtColor(img_cv, cv2.COLOR_RGB2GRAY)
+            else:
+                gray = img_cv
+            
+            # 检测标记
+            corners, ids, rejected = self.detector.detectMarkers(gray)
+            
+            if self.logger and ids is not None:
+                self.logger.debug(f"[ARUCO] 检测到 {len(ids)} 个标记: {ids.flatten().tolist()}")
+            
+            return corners, ids, rejected
+            
+        except Exception as e:
+            if self.logger:
+                self.logger.error(f"[ARUCO] 标记检测失败: {e}")
+            return None, None, None
+    
+    def get_target_center_from_markers(self, corners, ids):
+        """
+        从检测到的ArUco标记计算靶心位置
+        
+        Args:
+            corners: 标记角点列表
+            ids: 标记ID列表
+            
+        Returns:
+            (center_x, center_y, radius, ellipse_params) 或 (None, None, None, None)
+            center_x, center_y: 靶心像素坐标
+            radius: 估计的靶心半径（像素）
+            ellipse_params: 椭圆参数用于透视校正
+        """
+        if ids is None or len(ids) < 3:
+            if self.logger:
+                self.logger.debug(f"[ARUCO] 检测到的标记数量不足: {len(ids) if ids is not None else 0} < 3")
+            return None, None, None, None
+        
+        try:
+            # 将ID转换为列表便于查找
+            detected_ids = ids.flatten().tolist()
+            
+            # 收集检测到的标记中心点和对应的物理坐标
+            image_points = []  # 图像坐标 (像素)
+            object_points = []  # 物理坐标 (毫米)
+            marker_centers = {}  # 存储每个标记的中心
+            
+            for i, marker_id in enumerate(detected_ids):
+                if marker_id not in self.marker_ids:
+                    continue
+                
+                # 计算标记中心（四个角的平均值）
+                corner = corners[i][0]  # shape: (4, 2)
+                center_x = np.mean(corner[:, 0])
+                center_y = np.mean(corner[:, 1])
+                marker_centers[marker_id] = (center_x, center_y)
+                
+                # 添加到点列表
+                image_points.append([center_x, center_y])
+                object_points.append(self.marker_positions_mm[marker_id])
+            
+            if len(image_points) < 3:
+                if self.logger:
+                    self.logger.debug(f"[ARUCO] 有效标记数量不足: {len(image_points)} < 3")
+                return None, None, None, None
+            
+            # 转换为numpy数组
+            image_points = np.array(image_points, dtype=np.float32)
+            object_points = np.array(object_points, dtype=np.float32)
+            
+            # 计算单应性矩阵（Homography）
+            # 这建立了物理坐标到图像坐标的映射
+            H, status = cv2.findHomography(object_points, image_points, cv2.RANSAC, 5.0)
+            
+            if H is None:
+                if self.logger:
+                    self.logger.warning("[ARUCO] 无法计算单应性矩阵")
+                return None, None, None, None
+            
+            # 计算靶心在图像中的位置
+            # 靶心物理坐标 = 靶纸中心 + 偏移
+            target_center_mm = np.array([[self.target_center_offset_mm[0], 
+                                          self.target_center_offset_mm[1]]], dtype=np.float32)
+            target_center_mm = target_center_mm.reshape(-1, 1, 2)
+            
+            # 使用单应性矩阵投影到图像坐标
+            target_center_img = cv2.perspectiveTransform(target_center_mm, H)
+            center_x = target_center_img[0][0][0]
+            center_y = target_center_img[0][0][1]
+            
+            # 计算靶心半径（像素）
+            # 使用已知物理距离和像素距离的比例
+            # 选择两个标记计算比例尺
+            if len(marker_centers) >= 2:
+                # 使用对角线上的标记计算比例尺
+                if 0 in marker_centers and 2 in marker_centers:
+                    p1_img = np.array(marker_centers[0])
+                    p2_img = np.array(marker_centers[2])
+                    p1_mm = np.array(self.marker_positions_mm[0])
+                    p2_mm = np.array(self.marker_positions_mm[2])
+                elif 1 in marker_centers and 3 in marker_centers:
+                    p1_img = np.array(marker_centers[1])
+                    p2_img = np.array(marker_centers[3])
+                    p1_mm = np.array(self.marker_positions_mm[1])
+                    p2_mm = np.array(self.marker_positions_mm[3])
+                else:
+                    # 使用任意两个标记
+                    keys = list(marker_centers.keys())
+                    p1_img = np.array(marker_centers[keys[0]])
+                    p2_img = np.array(marker_centers[keys[1]])
+                    p1_mm = np.array(self.marker_positions_mm[keys[0]])
+                    p2_mm = np.array(self.marker_positions_mm[keys[1]])
+                
+                pixel_distance = np.linalg.norm(p1_img - p2_img)
+                mm_distance = np.linalg.norm(p1_mm - p2_mm)
+                
+                if mm_distance > 0:
+                    pixels_per_mm = pixel_distance / mm_distance
+                    # 标准靶心半径：10环半径约1.22cm = 12.2mm
+                    # 但这里我们返回一个估计值，实际环数计算在laser_manager中
+                    radius_mm = 122.0  # 整个靶纸的半径约200mm，但靶心区域较小
+                    radius = int(radius_mm * pixels_per_mm)
+                else:
+                    radius = 100  # 默认值
+            else:
+                radius = 100  # 默认值
+            
+            # 计算椭圆参数（用于透视校正）
+            # 从单应性矩阵可以推导出透视变形
+            ellipse_params = self._compute_ellipse_params(H, center_x, center_y)
+            
+            if self.logger:
+                self.logger.info(f"[ARUCO] 靶心计算成功: 中心=({center_x:.1f}, {center_y:.1f}), "
+                               f"半径={radius}px, 检测到{len(marker_centers)}个标记")
+            
+            return (int(center_x), int(center_y)), radius, "aruco", ellipse_params
+            
+        except Exception as e:
+            if self.logger:
+                self.logger.error(f"[ARUCO] 计算靶心失败: {e}")
+                import traceback
+                self.logger.error(traceback.format_exc())
+            return None, None, None, None
+    
+    def _compute_ellipse_params(self, H, center_x, center_y):
+        """
+        从单应性矩阵计算椭圆参数，用于透视校正
+        
+        Args:
+            H: 单应性矩阵 (3x3)
+            center_x, center_y: 靶心图像坐标
+            
+        Returns:
+            ellipse_params: ((center_x, center_y), (width, height), angle)
+        """
+        try:
+            # 在物理坐标系中画一个圆，投影到图像中看变成什么形状
+            # 物理圆：半径10mm
+            r_mm = 10.0
+            angles = np.linspace(0, 2*np.pi, 16)
+            circle_mm = np.array([[self.target_center_offset_mm[0] + r_mm * np.cos(a),
+                                   self.target_center_offset_mm[1] + r_mm * np.sin(a)] 
+                                  for a in angles], dtype=np.float32)
+            circle_mm = circle_mm.reshape(-1, 1, 2)
+            
+            # 投影到图像
+            circle_img = cv2.perspectiveTransform(circle_mm, H)
+            circle_img = circle_img.reshape(-1, 2)
+            
+            # 拟合椭圆
+            if len(circle_img) >= 5:
+                ellipse = cv2.fitEllipse(circle_img.astype(np.float32))
+                return ellipse
+            else:
+                # 从单应性矩阵近似估计
+                # 提取缩放和旋转
+                # H = K * [R|t] 的近似
+                # 这里简化处理：假设没有严重变形
+                scale_x = np.linalg.norm(H[0, :2])
+                scale_y = np.linalg.norm(H[1, :2])
+                avg_scale = (scale_x + scale_y) / 2
+                
+                width = r_mm * 2 * scale_x
+                height = r_mm * 2 * scale_y
+                angle = np.degrees(np.arctan2(H[1, 0], H[0, 0]))
+                
+                return ((center_x, center_y), (width, height), angle)
+                
+        except Exception as e:
+            if self.logger:
+                self.logger.debug(f"[ARUCO] 计算椭圆参数失败: {e}")
+            return None
+    
+    def transform_laser_point(self, laser_point, corners, ids):
+        """
+        将激光点从图像坐标转换到物理坐标（毫米），再计算相对于靶心的偏移
+        
+        Args:
+            laser_point: (x, y) 激光点在图像中的坐标
+            corners: 检测到的标记角点
+            ids: 检测到的标记ID
+            
+        Returns:
+            (dx_mm, dy_mm) 激光点相对于靶心的偏移（毫米），或 (None, None)
+        """
+        if laser_point is None or ids is None or len(ids) < 3:
+            return None, None
+        
+        try:
+            # 重新计算单应性矩阵（可以优化为缓存）
+            detected_ids = ids.flatten().tolist()
+            image_points = []
+            object_points = []
+            
+            for i, marker_id in enumerate(detected_ids):
+                if marker_id not in self.marker_ids:
+                    continue
+                corner = corners[i][0]
+                center_x = np.mean(corner[:, 0])
+                center_y = np.mean(corner[:, 1])
+                image_points.append([center_x, center_y])
+                object_points.append(self.marker_positions_mm[marker_id])
+            
+            if len(image_points) < 3:
+                return None, None
+            
+            image_points = np.array(image_points, dtype=np.float32)
+            object_points = np.array(object_points, dtype=np.float32)
+            
+            H, _ = cv2.findHomography(object_points, image_points, cv2.RANSAC, 5.0)
+            if H is None:
+                return None, None
+            
+            # 求逆矩阵，将图像坐标转换到物理坐标
+            H_inv = np.linalg.inv(H)
+            
+            laser_img = np.array([[laser_point[0], laser_point[1]]], dtype=np.float32)
+            laser_img = laser_img.reshape(-1, 1, 2)
+            
+            laser_mm = cv2.perspectiveTransform(laser_img, H_inv)
+            laser_x_mm = laser_mm[0][0][0]
+            laser_y_mm = laser_mm[0][0][1]
+            
+            # 计算相对于靶心的偏移
+            # 注意：Y轴方向可能需要翻转（图像Y向下，物理Y通常向上）
+            dx_mm = laser_x_mm - self.target_center_offset_mm[0]
+            dy_mm = -(laser_y_mm - self.target_center_offset_mm[1])  # 翻转Y轴
+            
+            if self.logger:
+                self.logger.debug(f"[ARUCO] 激光点转换: 图像({laser_point[0]:.1f}, {laser_point[1]:.1f}) -> "
+                                f"物理({laser_x_mm:.1f}, {laser_y_mm:.1f}) -> "
+                                f"偏移({dx_mm:.1f}, {dy_mm:.1f})mm")
+            
+            return dx_mm, dy_mm
+            
+        except Exception as e:
+            if self.logger:
+                self.logger.error(f"[ARUCO] 激光点转换失败: {e}")
+            return None, None
+    
+    def draw_debug_info(self, frame, corners, ids, target_center=None, laser_point=None):
+        """
+        在图像上绘制调试信息
+        
+        Args:
+            frame: MaixPy图像帧
+            corners: 标记角点
+            ids: 标记ID
+            target_center: 计算的靶心位置
+            laser_point: 激光点位置
+            
+        Returns:
+            绘制后的图像
+        """
+        try:
+            from maix import image
+            img_cv = image.image2cv(frame, False, False).copy()
+            
+            # 绘制检测到的标记
+            if ids is not None:
+                cv2.aruco.drawDetectedMarkers(img_cv, corners, ids)
+                
+                # 绘制标记ID和中心
+                for i, marker_id in enumerate(ids.flatten()):
+                    corner = corners[i][0]
+                    center_x = int(np.mean(corner[:, 0]))
+                    center_y = int(np.mean(corner[:, 1]))
+                    
+                    # 绘制中心点
+                    cv2.circle(img_cv, (center_x, center_y), 5, (0, 255, 0), -1)
+                    
+                    # 绘制ID
+                    cv2.putText(img_cv, f"ID:{marker_id}", 
+                               (center_x + 10, center_y - 10),
+                               cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2)
+            
+            # 绘制靶心
+            if target_center:
+                cv2.circle(img_cv, target_center, 8, (255, 0, 0), -1)
+                cv2.circle(img_cv, target_center, 50, (255, 0, 0), 2)
+                cv2.putText(img_cv, "TARGET", (target_center[0] + 15, target_center[1] - 15),
+                           cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 0, 0), 2)
+            
+            # 绘制激光点
+            if laser_point:
+                cv2.circle(img_cv, (int(laser_point[0]), int(laser_point[1])), 6, (0, 0, 255), -1)
+                cv2.putText(img_cv, "LASER", (int(laser_point[0]) + 10, int(laser_point[1]) - 10),
+                           cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)
+            
+            # 转换回MaixPy图像
+            return image.cv2image(img_cv, False, False)
+            
+        except Exception as e:
+            if self.logger:
+                self.logger.error(f"[ARUCO] 绘制调试信息失败: {e}")
+            return frame
+
+
+# 创建全局单例实例
+aruco_detector = ArUcoDetector()
+
+
+def detect_target_with_aruco(frame, laser_point=None):
+    """
+    使用ArUco标记检测靶心的便捷函数
+    
+    Args:
+        frame: MaixPy图像帧
+        laser_point: 激光点坐标（可选）
+        
+    Returns:
+        (result_img, center, radius, method, best_radius1, ellipse_params)
+        与detect_circle_v3保持相同的返回格式
+    """
+    detector = aruco_detector
+    
+    # 检测ArUco标记
+    corners, ids, rejected = detector.detect_markers(frame)
+    
+    # 计算靶心
+    center, radius, method, ellipse_params = detector.get_target_center_from_markers(corners, ids)
+    
+    # 绘制调试信息
+    result_img = detector.draw_debug_info(frame, corners, ids, center, laser_point)
+    
+    # 返回与detect_circle_v3相同的格式
+    # best_radius1用于距离估算，这里用radius代替
+    return result_img, center, radius, method, radius, ellipse_params
+
+
+def compute_laser_offset_aruco(laser_point, corners, ids):
+    """
+    使用ArUco计算激光点相对于靶心的偏移（毫米）
+    
+    Args:
+        laser_point: (x, y) 激光点图像坐标
+        corners: ArUco标记角点
+        ids: ArUco标记ID
+        
+    Returns:
+        (dx_mm, dy_mm) 偏移量（毫米），或 (None, None)
+    """
+    return aruco_detector.transform_laser_point(laser_point, corners, ids)

at_client.py

@@ -0,0 +1,307 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+AT客户端模块
+负责4G模块的AT命令通信和URC解析
+"""
+import _thread
+from maix import time
+import re
+import threading
+
+class ATClient:
+    """
+    单读者 AT/URC 客户端：唯一读取 uart4g，避免 tcp_main/at()/OTA 抢读导致 EOF / 丢包。
+    - send(cmd, expect, timeout_ms) : 发送 AT 并等待 expect
+    - pop_tcp_payload()            : 获取 +MIPURC:"rtcp" 的 payload（已按长度裁剪）
+    - pop_http_event()             : 获取 +MHTTPURC 事件（header/content）
+    """
+    def __init__(self, uart_obj):
+        self.uart = uart_obj
+        self._cmd_lock = threading.Lock()
+        self._q_lock = threading.Lock()
+        self._rx = b""
+        self._tcp_payloads = []
+        self._http_events = []
+
+        # 当前命令等待状态（仅允许单命令 in-flight）
+        self._waiting = False
+        self._expect = b"OK"
+        self._resp = b""
+
+        self._running = False
+
+    def start(self):
+        if self._running:
+            return
+        self._running = True
+        _thread.start_new_thread(self._reader_loop, ())
+
+    def stop(self):
+        self._running = False
+
+    def flush(self):
+        """清空内部缓存与队列（用于 OTA/异常恢复）"""
+        with self._q_lock:
+            self._rx = b""
+            self._tcp_payloads.clear()
+            self._http_events.clear()
+            self._resp = b""
+
+    def pop_tcp_payload(self):
+        with self._q_lock:
+            if self._tcp_payloads:
+                return self._tcp_payloads.pop(0)
+        return None
+
+    def pop_http_event(self):
+        with self._q_lock:
+            if self._http_events:
+                return self._http_events.pop(0)
+        return None
+
+    def _push_tcp_payload(self, payload: bytes):
+        # 注意：在 _reader_loop 内部解析 URC 时已经持有 _q_lock，
+        # 这里不要再次 acquire（锁不可重入，会死锁）。
+        self._tcp_payloads.append(payload)
+
+    def _push_http_event(self, ev):
+        # 同上：避免在 _reader_loop 持锁期间二次 acquire
+        self._http_events.append(ev)
+
+    def send(self, cmd: str, expect: str = "OK", timeout_ms: int = 2000):
+        """
+        发送 AT 命令并等待 expect（子串匹配）。
+        注意：expect=">" 用于等待 prompt。
+        """
+        expect_b = expect.encode() if isinstance(expect, str) else expect
+        with self._cmd_lock:
+            # 初始化等待
+            self._waiting = True
+            self._expect = expect_b
+            self._resp = b""
+
+            # 发送
+            if cmd:
+                # 注意：这里不要再用 uart4g_lock（否则外层已经持锁时会死锁）。
+                # 写入由 _cmd_lock 串行化即可。
+                self.uart.write((cmd + "\r\n").encode())
+
+            t0 = time.ticks_ms()
+            while abs(time.ticks_diff(time.ticks_ms(), t0)) < timeout_ms:
+                if (not self._waiting) or (self._expect in self._resp):
+                    self._waiting = False
+                    break
+                time.sleep_ms(5)
+
+            # 超时也返回已收集内容（便于诊断）
+            self._waiting = False
+            try:
+                return self._resp.decode(errors="ignore")
+            except:
+                return str(self._resp)
+
+    def _find_urc_tag(self, tag: bytes):
+        """
+        只在"真正的 URC 边界"查找 tag，避免误命中 HTTP payload 内容。
+        规则：tag 必须出现在 buffer 开头，或紧跟在 b"\\r\\n" 后面。
+        """
+        try:
+            i = 0
+            rx = self._rx
+            while True:
+                j = rx.find(tag, i)
+                if j < 0:
+                    return -1
+                if j == 0:
+                    return 0
+                if j >= 2 and rx[j - 2:j] == b"\r\n":
+                    return j
+                i = j + 1
+        except:
+            return -1
+
+    def _parse_mipurc_rtcp(self):
+        """
+        解析：+MIPURC: "rtcp",<link_id>,<len>,<payload...>
+        之前硬编码 link_id=0 会导致在多连接/重连场景下收不到数据。
+        """
+        prefix = b'+MIPURC: "rtcp",'
+        i = self._find_urc_tag(prefix)
+        if i < 0:
+            return False
+        # 丢掉前置噪声
+        if i > 0:
+            self._rx = self._rx[i:]
+            i = 0
+
+        j = len(prefix)
+        # 解析 link_id
+        k = j
+        while k < len(self._rx) and 48 <= self._rx[k] <= 57:
+            k += 1
+        if k == j or k >= len(self._rx):
+            return False
+        if self._rx[k:k+1] != b",":
+            self._rx = self._rx[1:]
+            return True
+        try:
+            link_id = int(self._rx[j:k].decode())
+        except:
+            self._rx = self._rx[1:]
+            return True
+
+        # 解析 len
+        j2 = k + 1
+        k2 = j2
+        while k2 < len(self._rx) and 48 <= self._rx[k2] <= 57:
+            k2 += 1
+        if k2 == j2 or k2 >= len(self._rx):
+            return False
+        if self._rx[k2:k2+1] != b",":
+            self._rx = self._rx[1:]
+            return True
+        try:
+            n = int(self._rx[j2:k2].decode())
+        except:
+            self._rx = self._rx[1:]
+            return True
+
+        payload_start = k2 + 1
+        payload_end = payload_start + n
+        if len(self._rx) < payload_end:
+            return False  # payload 未收齐
+
+        payload = self._rx[payload_start:payload_end]
+        # 把 link_id 一起带上，便于上层过滤（如果需要）
+        self._push_tcp_payload((link_id, payload))
+        self._rx = self._rx[payload_end:]
+        return True
+
+    def _parse_mhttpurc_header(self):
+        tag = b'+MHTTPURC: "header",'
+        i = self._find_urc_tag(tag)
+        if i < 0:
+            return False
+        if i > 0:
+            self._rx = self._rx[i:]
+            i = 0
+
+        # header: +MHTTPURC: "header",<id>,<code>,<hdr_len>,<hdr_text...>
+        j = len(tag)
+        comma_count = 0
+        k = j
+        while k < len(self._rx) and comma_count < 3:
+            if self._rx[k:k+1] == b",":
+                comma_count += 1
+            k += 1
+        if comma_count < 3:
+            return False
+
+        prefix = self._rx[:k]
+        m = re.search(rb'\+MHTTPURC: "header",\s*(\d+),\s*(\d+),\s*(\d+),', prefix)
+        if not m:
+            self._rx = self._rx[1:]
+            return True
+        urc_id = int(m.group(1))
+        code = int(m.group(2))
+        hdr_len = int(m.group(3))
+
+        text_start = k
+        text_end = text_start + hdr_len
+        if len(self._rx) < text_end:
+            return False
+
+        hdr_text = self._rx[text_start:text_end].decode("utf-8", "ignore")
+        self._push_http_event(("header", urc_id, code, hdr_text))
+        self._rx = self._rx[text_end:]
+        return True
+
+    def _parse_mhttpurc_content(self):
+        tag = b'+MHTTPURC: "content",'
+        i = self._find_urc_tag(tag)
+        if i < 0:
+            return False
+        if i > 0:
+            self._rx = self._rx[i:]
+            i = 0
+
+        # content: +MHTTPURC: "content",<id>,<total>,<sum>,<cur>,<payload...>
+        j = len(tag)
+        comma_count = 0
+        k = j
+        while k < len(self._rx) and comma_count < 4:
+            if self._rx[k:k+1] == b",":
+                comma_count += 1
+            k += 1
+        if comma_count < 4:
+            return False
+
+        prefix = self._rx[:k]
+        m = re.search(rb'\+MHTTPURC: "content",\s*(\d+),\s*(\d+),\s*(\d+),\s*(\d+),', prefix)
+        if not m:
+            self._rx = self._rx[1:]
+            return True
+        urc_id = int(m.group(1))
+        total_len = int(m.group(2))
+        sum_len = int(m.group(3))
+        cur_len = int(m.group(4))
+
+        payload_start = k
+        payload_end = payload_start + cur_len
+        if len(self._rx) < payload_end:
+            return False
+
+        payload = self._rx[payload_start:payload_end]
+        self._push_http_event(("content", urc_id, total_len, sum_len, cur_len, payload))
+        self._rx = self._rx[payload_end:]
+        return True
+
+    def _reader_loop(self):
+        while self._running:
+            # 关键：UART 驱动偶发 read failed，必须兜住，否则线程挂了 OTA/TCP 都会卡死
+            try:
+                d = self.uart.read(4096)  # 8192 在一些驱动上更容易触发 read failed
+            except Exception as e:
+                try:
+                    print("[ATClient] uart read failed:", e)
+                except:
+                    pass
+                time.sleep_ms(50)
+                continue
+
+            if not d:
+                time.sleep_ms(1)
+                continue
+
+            with self._q_lock:
+                self._rx += d
+                if self._waiting:
+                    self._resp += d
+
+                while True:
+                    progressed = (
+                        self._parse_mipurc_rtcp()
+                        or self._parse_mhttpurc_header()
+                        or self._parse_mhttpurc_content()
+                    )
+                    if not progressed:
+                        break
+
+                # 使用 ota_manager 访问 ota_in_progress
+                try:
+                    from ota_manager import ota_manager
+                    ota_flag = ota_manager.ota_in_progress
+                except:
+                    ota_flag = False
+
+                has_http_hint = (b"+MHTTP" in self._rx) or (b"+MHTTPURC" in self._rx)
+                if ota_flag or has_http_hint:
+                    if len(self._rx) > 512 * 1024:
+                        self._rx = self._rx[-256 * 1024:]
+                else:
+                    if len(self._rx) > 16384:
+                        self._rx = self._rx[-4096:]
+
+
+

cameraParameters.xml

@@ -0,0 +1,33 @@
+<?xml version="1.0"?>
+<opencv_storage>
+<calibrationDate>"Sat Apr 11 12:05:27 2026"</calibrationDate>
+<framesCount>29</framesCount>
+<cameraResolution>
+  640 480</cameraResolution>
+<camera_matrix type_id="opencv-matrix">
+  <rows>3</rows>
+  <cols>3</cols>
+  <dt>d</dt>
+  <data>
+    2207.9058323074869 0. 328.90661220953149 0. 2207.9058323074869
+    205.49515894111076 0. 0. 1.</data></camera_matrix>
+<camera_matrix_std_dev type_id="opencv-matrix">
+  <rows>4</rows>
+  <cols>1</cols>
+  <dt>d</dt>
+  <data>
+    0. 11.687428265309892 3.6908895632668468 3.597571733110271</data></camera_matrix_std_dev>
+<distortion_coefficients type_id="opencv-matrix">
+  <rows>1</rows>
+  <cols>5</cols>
+  <dt>d</dt>
+  <data>
+    -0.63036604771649651 3.3832710000807449 0. 0. -0.45113389267675552</data></distortion_coefficients>
+<distortion_coefficients_std_dev type_id="opencv-matrix">
+  <rows>5</rows>
+  <cols>1</cols>
+  <dt>d</dt>
+  <data>
+    0.025002349846111244 1.0651877135605927 0. 0. 0.04021252864120229</data></distortion_coefficients_std_dev>
+<avg_reprojection_error>0.28992233810828955</avg_reprojection_error>
+</opencv_storage>

camera_manager.py

@@ -0,0 +1,137 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+相机管理器模块
+提供相机和显示的统一管理和线程安全访问
+"""
+import threading
+import config
+from logger_manager import logger_manager
+
+
+class CameraManager:
+    """相机管理器（单例）"""
+    _instance = None
+    
+    def __new__(cls):
+        if cls._instance is None:
+            cls._instance = super(CameraManager, cls).__new__(cls)
+            cls._instance._initialized = False
+        return cls._instance
+    
+    def __init__(self):
+        if self._initialized:
+            return
+        
+        # 私有对象
+        self._camera = None
+        self._display = None
+        
+        # 线程安全锁
+        self._camera_lock = threading.Lock()
+        self._display_lock = threading.Lock()
+        
+        # 相机配置
+        self._camera_width = 640
+        self._camera_height = 480
+        
+        self._initialized = True
+    
+    # ==================== 初始化方法 ====================
+    
+    @property
+    def logger(self):
+        """获取 logger 对象"""
+        return logger_manager.logger
+    
+    def init_camera(self, width=640, height=480):
+        """初始化相机"""
+        if self._camera is not None:
+            return self._camera
+        
+        from maix import camera
+        
+        self._camera_width = width
+        self._camera_height = height
+        
+        with self._camera_lock:
+            if self._camera is None:
+                self._camera = camera.Camera(width, height)
+        
+        return self._camera
+    
+    def init_display(self):
+        """初始化显示"""
+        if self._display is not None:
+            return self._display
+        
+        from maix import display
+        
+        with self._display_lock:
+            if self._display is None:
+                self._display = display.Display()
+        
+        return self._display
+    
+    # ==================== 访问方法 ====================
+    
+    @property
+    def camera(self):
+        """获取相机实例（懒加载）"""
+        if self._camera is None:
+            self.init_camera()
+        return self._camera
+    
+    @property
+    def display(self):
+        """获取显示实例（懒加载）"""
+        if self._display is None:
+            self.init_display()
+        return self._display
+    
+    # ==================== 业务方法 ====================
+    
+    def read_frame(self):
+        """
+        线程安全地读取一帧图像
+        
+        Returns:
+            frame: 图像帧对象
+        """
+        with self._camera_lock:
+            if self._camera is None:
+                self.init_camera()
+            return self._camera.read()
+    
+    def show(self, image):
+        """
+        线程安全地显示图像
+        
+        Args:
+            image: 要显示的图像对象
+        """
+        with self._display_lock:
+            if self._display is None:
+                self.init_display()
+            self._display.show(image)
+    
+    def release(self):
+        """释放相机和显示资源（如果需要）"""
+        with self._camera_lock:
+            if self._camera is not None:
+                # MaixPy 的 Camera 可能不需要显式释放，但可以在这里清理
+                self._camera = None
+        
+        with self._display_lock:
+            if self._display is not None:
+                # MaixPy 的 Display 可能不需要显式释放
+                self._display = None
+
+
+# 创建全局单例实例
+camera_manager = CameraManager()
+
+
+
+
+

config.py

@@ -0,0 +1,337 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+系统配置常量
+这些值在程序运行期间基本不变，或只在配置时改变
+"""
+from version import VERSION
+
+# ==================== 应用配置 ====================
+APP_VERSION = VERSION
+APP_DIR = "/maixapp/apps/t11"
+LOCAL_FILENAME = APP_DIR + "/main_tmp.py"
+
+# ==================== 相机配置 ====================
+# 相机初始化分辨率（CameraManager / main.py 使用）
+CAMERA_WIDTH = 640
+CAMERA_HEIGHT = 480
+
+# 三角形检测缩图比例：默认按相机最长边缩到 1/2（性能更稳；可按需调整）
+# 取值范围建议 (0.25 ~ 1.0]；1.0 表示不缩图
+TRIANGLE_DETECT_SCALE = 0.4
+
+# ==================== 服务器配置 ====================
+# SERVER_IP = "stcp.shelingxingqiu.com"
+SERVER_IP = "www.shelingxingqiu.com"
+SERVER_PORT = 50005
+HEARTBEAT_INTERVAL = 15  # 心跳间隔（秒）
+
+# WiFi 质量评估（开机先尝试 WiFi；质量差且 4G 可用则切到 4G，本次上电直至关机锁定 4G）
+WIFI_QUALITY_RTT_SAMPLES = 3  # 到业务服务器 TCP 建连耗时采样次数，取中位数
+WIFI_QUALITY_RTT_BAD_MS = 600.0  # 中位数超过此值认为延迟过高
+WIFI_QUALITY_RTT_WARN_MS = 350.0  # 与 RSSI 联合：超过此值且信号弱也判为差
+WIFI_QUALITY_RSSI_BAD_DBM = -80.0  # 低于此 dBm（更负更差）视为信号弱
+WIFI_QUALITY_USE_RSSI = True  # 是否把 RSSI 纳入综合判定
+
+# WiFi 热点配网（手机连设备 AP，浏览器提交路由器 SSID/密码；仅 GET/POST，标准库 socket）
+WIFI_CONFIG_AP_FALLBACK = True # # WiFi 配网失败时，是否退回热点模式，并等待重新配网
+WIFI_AP_FALLBACK_WAIT_SEC = 5 # 等待5秒后再检测STA/4G
+WIFI_CONFIG_AP_TIMEOUT = 5  # 热点模式超时时间（秒）
+WIFI_CONFIG_AP_ENABLED = True  # True=启动时开热点并起迷你 HTTP 配网服务
+WIFI_CONFIG_AP_SSID = "ArcherySetup"       # 设备发出的热点名称
+WIFI_CONFIG_AP_PASSWORD = "12345678"       # 热点密码（WPA2 通常至少 8 位）
+WIFI_CONFIG_HTTP_HOST = "0.0.0.0"          # HTTP 监听地址
+WIFI_CONFIG_HTTP_PORT = 8080               # 默认 8080，避免占用 80 需 root
+WIFI_CONFIG_AP_IP = "192.168.66.1"         # 与 MaixPy Wifi.start_ap 默认一致，手机访问 http://192.168.66.1:8080/
+                                           # 这个地址需要和 /boot/wifi.ipv4_prefix 配合，才能正确访问。
+                                           # 比如说 /boot/wifi.ipv4_prefix 需要写成 192.168.66 
+# ===== TCP over SSL(TLS) 配置 =====
+USE_TCP_SSL = True          # True=按手册走 MSSLCFG/MIPCFG 绑定 SSL
+TCP_LINK_ID = 2             # 
+TCP_SSL_PORT = 50006          # TLS 端口（不一定必须 443，以服务器为准）
+
+# SSL profile
+SSL_ID = 1                  # ssl_id=1
+SSL_AUTH_MODE = 1           # 1=单向认证（验证服务器），2=双向
+SSL_VERIFY_MODE = 1         # 0=不验（仅测试用）；1=写入并使用 CA 证书
+
+SSL_CERT_FILENAME = "server.pem"      # 模组里证书名（MSSLCERTWR / MSSLCFG="cert" 用）
+SSL_CERT_PATH = APP_DIR + "/server.pem"    # 设备文件系统里 CA 证书路径（你自己放进去）
+# MIPOPEN 末尾的参数在不同固件里含义可能不同；按你手册例子保留
+MIPOPEN_TAIL = ",,0"
+
+# ==================== 文件路径配置 ====================
+CONFIG_FILE = "/root/laser_config.json"
+LOG_FILE = APP_DIR + "/app.log"
+BACKUP_BASE = APP_DIR + "/backups"
+
+# ==================== 硬件配置 ====================
+# UART配置
+UART4G_DEVICE = "/dev/ttyS2"
+UART4G_BAUDRATE = 115200
+DISTANCE_SERIAL_DEVICE = "/dev/ttyS1"
+DISTANCE_SERIAL_BAUDRATE = 9600
+
+# I2C：板载 WiFi 方案固定 I2C5，引脚 A15(SCL) / A27(SDA)，供 INA226 等
+I2C_BUS_NUM = 5
+
+INA226_ADDR = 0x40
+# False=完全不访问 INA226（无电源计量板或未供电时避免 ~2.5s writeto 重试与底层 write failed 日志）；量产有芯片时设为 True
+INA226_ENABLE = True
+# True=整总线 I2C scan 探测 INA226（在部分平台上极慢，可达 ~90s+）；False=仅对 INA226_ADDR 快速探测（writeto 空写）
+INA226_PROBE_FULL_BUS_SCAN = False
+REG_CONFIGURATION = 0x00
+REG_BUS_VOLTAGE = 0x02
+REG_CURRENT = 0x04  # 电流寄存器
+REG_CALIBRATION = 0x05
+CALIBRATION_VALUE = 0x1400
+
+# ==================== 空气传感器配置 ====================
+ADC_TRIGGER_THRESHOLD = 2700 # TODO:4096只是用于测试，因为最大值是4095，这个值是永远不会触发的，最终需要改为正常值
+AIR_PRESSURE_lOG = False # TODO: 在正式环境中关闭
+AIR_PRESSURE_HARDWARE_MAX = 10
+# ADC配置
+ADC_CHANNEL = 0
+ADC_LASER_THRESHOLD = 3000
+
+# ==================== 激光配置 ====================
+MODULE_ADDR = 0x00
+LASER_ON_CMD = bytes([0xAA, MODULE_ADDR, 0x01, 0xBE, 0x00, 0x01, 0x00, 0x01, 0xC1])
+LASER_OFF_CMD = bytes([0xAA, MODULE_ADDR, 0x01, 0xBE, 0x00, 0x01, 0x00, 0x00, 0xC0])
+DISTANCE_QUERY_CMD = bytes([0xAA, MODULE_ADDR, 0x00, 0x20, 0x00, 0x01, 0x00, 0x00, 0x21])  # 激光测距查询命令
+DISTANCE_RESPONSE_LEN = 13  # 激光测距响应数据长度（字节）
+DEFAULT_LASER_POINT =  (320, 245)   # 默认激光中心点
+
+# 硬编码激光点配置
+HARDCODE_LASER_POINT = True  # 是否使用硬编码的激光点（True=使用硬编码值，False=使用校准值）
+HARDCODE_LASER_POINT_VALUE = (320, 296) # 硬编码的激光点坐标(315, 245) #   # 硬编码的激光点坐标 (x, y)
+
+# 激光点检测配置
+LASER_DETECTION_THRESHOLD = 140  # 红色通道阈值（默认120，可调整，范围建议：100-150）
+LASER_RED_RATIO = 1.5  # 红色相对于绿色/蓝色的倍数要求（默认1.5，可调整，范围建议：1.3-2.0）
+LASER_SEARCH_RADIUS = 50  # 搜索半径（像素），从图像中心开始搜索（默认20，限制激光点不能偏离中心太远）
+LASER_MAX_DISTANCE_FROM_CENTER = 50  # 激光点距离中心的最大允许距离（像素），超过此距离则拒绝（默认20）
+LASER_OVEREXPOSED_THRESHOLD = 200  # 过曝红色判断阈值（默认200，接近白色时的阈值）
+LASER_OVEREXPOSED_DIFF = 10  # 过曝红色时，r 与 g/b 的最小差值（默认10）
+LASER_REQUIRE_IN_ELLIPSE = False  # 是否要求激光点必须在黄心椭圆内（True=必须，False=不要求）
+LASER_USE_ELLIPSE_FITTING = True  # 是否使用椭圆拟合方法查找激光点（True=椭圆拟合更准确，False=最亮点方法）
+LASER_MIN_AREA = 5  # 激光点区域的最小面积（像素），小于此值认为是噪声（默认5）
+LASER_DRAW_ELLIPSE = True  # 是否在图像上绘制激光点的拟合椭圆（True=绘制，False=不绘制）
+
+# ==================== 视觉检测配置 ====================
+FOCAL_LENGTH_PIX = 2250.0    # 焦距（像素）
+REAL_RADIUS_CM = 20          # 靶心实际半径（厘米）
+
+# 图像清晰度检测配置
+IMAGE_SHARPNESS_THRESHOLD = 100.0  # 清晰度阈值，低于此值认为图像模糊
+                                    # 清晰图像通常 > 200，模糊图像通常 < 100
+
+# 激光与摄像头物理位置配置
+LASER_CAMERA_OFFSET_CM = 1.4  # 激光在摄像头下方的物理距离（厘米），正值表示激光在摄像头下方
+IMAGE_CENTER_X = 320  # 图像中心 X 坐标
+IMAGE_CENTER_Y = 240  # 图像中心 Y 坐标
+
+# ==================== 三角形四角标记：单应性偏移 + PnP 估距 ====================
+# 依赖 cameraParameters.xml（相机内参）与 triangle_positions.json（四角物方坐标，厘米或毫米见 JSON 约定）。
+# 部署时请把这两个文件放到 APP_DIR（与 main 同应用目录），或改下面路径为设备上的实际绝对路径。
+USE_TRIANGLE_OFFSET = True  # False 时仅走黄心圆/椭圆 + 半径估距，不使用三角形路径
+CAMERA_CALIB_XML = APP_DIR + "/cameraParameters.xml"
+TRIANGLE_POSITIONS_JSON = APP_DIR + "/triangle_positions.json"
+# 检测到的三角形边长在图像中的像素范围，分辨率或靶纸占比变化时可微调
+TRIANGLE_SIZE_RANGE = (8, 500)
+# PnP 距离合理性检查（可选）：超出范围时认为本次检测有误，回退圆心算法
+# 设为 0 表示不启用（主要防线是单应矩阵 sx/sy 比值检查，无需提前知道距离）
+# 如果射箭距离很固定，可设具体范围（如 min=2.5, max=6.0）作为额外保险
+TRIANGLE_DISTANCE_MIN_M = 0.0   # 0=不启用下限检查
+TRIANGLE_DISTANCE_MAX_M = 0.0   # 0=不启用上限检查
+# 三角形检测兜底增强：CLAHE（更鲁棒但更慢）。颜色阈值修复后通常不需要，保持关闭以优先速度。
+TRIANGLE_ENABLE_CLAHE_FALLBACK = False
+# 三角形检测调试：保存 Otsu 二值化图像（临时调试用，定位后关闭）
+TRIANGLE_SAVE_DEBUG_IMAGE = False
+# 三角形颜色过滤阈值（三角形内部灰度判定）
+# 如果三角形标记印刷较浅/环境较亮，可放宽：
+#   max_interior_gray: 三角形内部平均灰度上限（越大越宽松，90→130 适应浅色印刷）
+#   dark_pixel_gray: "暗像素"灰度判定阈值（越大越宽松，80→130）
+#   min_dark_ratio: 暗像素占比下限（越小越宽松，0.70→0.30）
+TRIANGLE_MAX_INTERIOR_GRAY = 130
+TRIANGLE_DARK_PIXEL_GRAY = 130
+TRIANGLE_MIN_DARK_RATIO = 0.30
+# 三角形相对对比度阈值：内部比周围暗多少灰度值才认为有效（0=禁用相对对比度）
+TRIANGLE_MIN_CONTRAST_DIFF = 15
+# 三角形形状约束容差（等腰直角判定松紧度）
+# 增大可容忍轮廓轻微变形（印刷不均、阴影局部切角），减少"差一点点就失败"的漏检
+# 建议范围：0.20（原始/严格） ~ 0.30（宽松）；超过 0.35 容易误检非三角形
+TRIANGLE_SHAPE_LEG_TOLERANCE = 0.25    # 两直角边长度比例容差（原 0.20）
+TRIANGLE_SHAPE_HYP_TOLERANCE = 0.25    # 斜边与期望长度比例容差（原 0.20）
+TRIANGLE_SHAPE_COS_TOLERANCE = 0.25    # 直角余弦绝对值上限（原 0.20，越小越严格）
+# 三角形检测主超时（毫秒）：join 等待子线程的最长时间。
+# 整段 try_triangle_scoring 含「多路径二值化 + C(n,4) 四角评分 + 单应性 + PnP」，往往比黄心圆检测慢。
+# 建议设为实测最坏耗时的 1.2 倍；超时后圆心检测仍会并行跑完，跑完后若三角形已结束则优先用三角形。
+TRIANGLE_TIMEOUT_MS = 1000
+# True=打印各阶段耗时(ms)，用于定位瓶颈；稳定后可 False 减少日志
+TRIANGLE_TIMING_LOG = True
+# True=Stage2 每个子框内传统三角失败时打一条统计（Otsu/Adaptive 下轮廓数与各拒绝原因计数）
+TRIANGLE_LOG_STAGE2_PATCH_REJECT = True
+
+# 仅检出 3 个真实三角时：是否在预测位置附近做小 ROI（Otsu/adaptive）再搜第 4 个真实三角。
+# False=跳过该搜索，直接用几何推算的虚拟第 4 点（offset_method=triangle_homography_3pt），省 ~10~120ms；若实测偏移可接受可关。
+TRIANGLE_FOURTH_ROI_SEARCH_ENABLE = False
+
+# ── 轻量锐化（Unsharp Mask）──────────────────────────────────────────────────
+# 目的：轻度/中度模糊时增强边缘，让三角形轮廓更易被 approxPolyDP 检出。
+# 严重运动模糊时反而会放大噪声，建议搭配 sharpness 检测自动触发（见下）。
+# YOLO 裁切后图已较清晰时可 False，省去 Unsharp 开销并减轻振铃。
+TRIANGLE_SHARPEN_ENABLE = False     # False=关闭锐化（彻底跳过计算，最省时）
+# 仅当帧清晰度（Laplacian 方差）低于此值时才锐化；高于此值说明图片本身够清晰，不动
+# 0=总是锐化；建议 50~150；对应日志中 [TRI] sharpness=xxx
+TRIANGLE_SHARPEN_THRESHOLD = 0.0  # 0=总是锐化（不做 Laplacian 判断，省去计算）
+# Unsharp Mask 高斯核 sigma（越大锐化越强，通常 1.0~3.0）
+TRIANGLE_SHARPEN_SIGMA = 2.0
+# Unsharp Mask 强度系数（越大锐化越猛，通常 1.2~2.0；>2 易产生振铃）
+TRIANGLE_SHARPEN_STRENGTH = 1.5
+
+# 三角形检测用灰度来源（ROI 裁切、缩放到 img_det 之后；与 vision 一致按 RGB 输入）
+# rgb — 常规 cv2.cvtColor RGB2GRAY
+# v_suppress — HSV 的 V：亮度 >= TRIANGLE_HSV_V_SUPPRESS_ABOVE 的像素灰度强制为 255，压制黄/红/蓝等亮环后再走原有 Otsu 流水线
+# fallback_v_suppress — 先用 rgb 跑 detect；若检出三角形 <3，再用 v_suppress 重跑一遍（省平均耗时，坏帧可多救一点）
+# try_both — rgb 与 v_suppress 各完整跑一遍 detect_triangle_markers，取检出数更多一侧（平局保留 rgb）；耗时约 2 倍，用于对比效果
+TRIANGLE_GRAY_MODE = "v_suppress"
+TRIANGLE_HSV_V_SUPPRESS_ABOVE = 200  # 0~255；偏高则环残留多，偏低则可能伤到暗三角边缘，建议 180~220 扫一圈
+
+# 三角形检测性能/鲁棒性参数（偏向速度的默认值）
+# 说明：
+# - Otsu 是最快的全局阈值；adaptiveThreshold 更鲁棒但更慢
+# - filtered 候选过多时，枚举 C(n,4) 会变慢，需限幅
+TRIANGLE_EARLY_EXIT_CANDIDATES = 3          # 找到3个候选即停（第4个由几何推算）；原来4需跑完全adaptive
+TRIANGLE_ADAPTIVE_BLOCK_SIZES = (11,)       # 只用1个block_size；原(11,21)跑两遍adaptive
+TRIANGLE_MAX_FILTERED_FOR_COMBO = 10        # 参与四点组合评分的最大候选数（超过则截断到最可能的一部分）
+
+# ROI 局部阈值：四个象限各自 Otsu（+ 可选 ROI 内 adaptive），再合并候选。
+# 顺序：紧接在全局 Otsu 之后、整图 adaptive 之前（见 triangle_target.detect_triangle_markers）。
+# 用途：阴阳脸/大阴影下往往比「先整图 adaptive」更省时间且更稳；整图 adaptive 最慢，作补充。
+#
+# YOLO 已裁到靶区时，整幅小图上单一全局 Otsu 容易把环与四角揉在一个阈值里；可跳过第一轮「全局轮廓提取」，
+# 直接进入下面四象限 ROI Otsu（仍会算全局 b_otsu 供 relaxed approxPolyDP 回退）。整图模式勿开。
+TRIANGLE_SKIP_GLOBAL_OTSU_EXTRACT_ON_YOLO_ROI = True
+
+TRIANGLE_ROI_ENABLED = False
+TRIANGLE_ROI_MIN_CANDIDATES = 3  # 候选数低于此值时启用 ROI 局部阈值（需至少 3 个点才能三角解算）
+TRIANGLE_ROI_OVERLAP_RATIO = 0.08  # 象限 ROI 的重叠比例（避免角标落在分割边界被切断）
+TRIANGLE_ROI_USE_ADAPTIVE = False  # ROI 内关闭 adaptive（只跑ROI Otsu，省去4×adaptive）；遇到阴阳脸再开
+
+# 多路径融合：不同二值化路径若得到相近中心（dedup 格点），累加 path_votes，后续优先参与四点组合。
+TRIANGLE_MULTI_PATH_VOTE = True
+
+# 失败回退（仍不足 TRIANGLE_FALLBACK_MIN_CANDIDATES 时按序尝试，每条仅在前序仍不足时执行）
+TRIANGLE_FALLBACK_MIN_CANDIDATES = 3
+# 对同一幅 Otsu 二值图用更宽松的 approxPolyDP，找回被“切角”的轮廓
+TRIANGLE_FALLBACK_RELAXED_EPS = True
+TRIANGLE_RELAXED_POLY_EPS_SCALE = 1.65
+# Black-hat（顶帽逆）：突出比周围暗的斑块，再 Otsu；对阴影/照度不均往往有效，略慢于纯 Otsu
+TRIANGLE_FALLBACK_BLACKHAT = True
+TRIANGLE_BLACKHAT_KERNEL_FRAC = 0.018  # 核大小 ≈ min(h,w)*frac，取奇数，范围约 [7, 31]
+
+# ── YOLO(NPU) 靶环 ROI → 裁剪后再跑三角形（减小 CPU 处理面积）──────────────────
+# 日志里 net_in=W×H 来自 .mud 模型（det.input_width/height），不是这里配置的。
+TRIANGLE_YOLO_ROI_ENABLE = True
+TRIANGLE_YOLO_MODEL_PATH = APP_DIR + "/model_270139.mud"
+# 参与 ROI 的类别：多类时只填「整靶/靶环」的 id；不要填角标类，否则 union 仍可对，但 largest 会偏小。
+TRIANGLE_YOLO_RING_CLASS_IDS = (0,)
+TRIANGLE_YOLO_CONF_TH = 0.7
+TRIANGLE_YOLO_IOU_TH = 0.45
+# YOLO 首次/临界帧可能在高阈值下 0 框；启用后仅在 0 候选时用较低阈值重试一次。
+# 后续仍会经过 min_box_side、ROI aspect、三角形几何校验，避免直接放大假阳性。
+TRIANGLE_YOLO_RETRY_ON_EMPTY = True
+TRIANGLE_YOLO_RETRY_CONF_TH = 0.5
+TRIANGLE_YOLO_ROI_MARGIN_FRAC = 0.11
+# union: 所有候选框外接矩形（一类多框：环+四角）；largest: 只取面积最大的框
+TRIANGLE_YOLO_ROI_MERGE_MODE = "union"
+# native: Maix 已将框映射到相机分辨率；letterbox: 框在网络输入坐标需逆变换（重复映射会出细条 ROI）
+TRIANGLE_YOLO_COORD_MODE = "native"
+# 参与 ROI 合并前丢弃过小的框（低 conf 时边角 1×1 假阳性）
+TRIANGLE_YOLO_MIN_BOX_SIDE_PX = 8
+TRIANGLE_YOLO_REJECT_BAD_ROI = True
+# try_triangle_scoring 收到 ROI 后裁剪的最小边长（像素），过小则退回整图
+TRIANGLE_CROP_ROI_MIN_SIDE_PX = 64
+# 射箭保存图 / 预览上绘制 YOLO 靶环 ROI 矩形 (x0,y0,x1,y1)，核对是否裁准；不需要时改 False
+TRIANGLE_YOLO_DRAW_ROI_ON_SHOT = True
+# 开机阶段预加载 YOLO detector；detect 使用 dual_buff=False，避免返回上一帧结果。
+TRIANGLE_YOLO_PRELOAD_ON_BOOT = True
+
+# ── 第二段 YOLO：仅在 Stage1 裁切出的靶环图上推理（与合成 stage2 训练数据一致）→ 子框内传统算法取直角点 ──
+# Stage1 靶环裁切内如何找黑三角标记（对比耗时时可切换）：
+# "yolo" — 调 Stage2 黑三角模型得子框，再子框内传统提取（需 TRIANGLE_BLACK_YOLO_ENABLE=True）。
+# "traditional" — 不调 Stage2 模型；仅在 Stage1 ROI 整幅上跑传统 detect_triangle_markers（与 yolo 路径对比用）。
+TRIANGLE_BLACK_TRIANGLE_LOCATE_MODE = "traditional"
+# True 时每箭另打一枪端到端耗时：yolo_ring + yolo_black + try_triangle_scoring 墙钟（毫秒）
+TRIANGLE_LOG_E2E_TIMING = True
+TRIANGLE_BLACK_YOLO_ENABLE = True
+TRIANGLE_BLACK_YOLO_MODEL_PATH = APP_DIR + "/model_270820.mud"
+TRIANGLE_BLACK_YOLO_CLASS_IDS = (0,)
+TRIANGLE_BLACK_YOLO_CONF_TH = 0.5
+TRIANGLE_BLACK_YOLO_IOU_TH = 0.45
+# Maix YOLOv5 detect 返回的框已映射到传入的 Stage1 裁切图坐标；contain/letterbox 是模型内部预处理。
+TRIANGLE_BLACK_YOLO_COORD_MODE = "native"
+# 子框相对 YOLO 框的扩展（在靶环裁切图坐标系下），利于传统算法取边
+TRIANGLE_BLACK_YOLO_BOX_MARGIN_FRAC = 0.08
+TRIANGLE_BLACK_YOLO_MIN_BOX_SIDE_PX = 6.0
+# 子框传统检测不足 3 个时是否回退为「整幅靶环 ROI」上的原 detect_triangle_markers
+TRIANGLE_BLACK_YOLO_FALLBACK_ON_PATCH_FAIL = True
+# Stage2 子框内传统提取使用的灰度（有缩略时默认在 Stage1 全分辨率灰度上切片）：
+# "rgb" — 仅用 RGB→灰度（不再做 Unsharp、不做 V 抑制），最省 CPU（推荐子框已对准黑三角时）。
+# "global" — 与整幅 ROI 三角流程同一张 gray（含 TRIANGLE_GRAY_MODE 的 v_suppress 与锐化）；更稳但更耗时。
+TRIANGLE_BLACK_YOLO_PATCH_GRAY_SOURCE = "rgb"
+# Stage2 子框内轮廓→三角形：approxPolyDP 的 ε=周长×FRAC×mult。边模糊时略增大 FRAC 或保留多级 mult。
+TRIANGLE_PATCH_APPROXPOLY_FRAC = 0.055
+TRIANGLE_PATCH_APPROXPOLY_RELAX_MULTS = (1.0, 1.3, 1.65)
+# Otsu/Adaptive 前对子框灰度轻模糊：0=关闭；3 或 5=Gaussian ksize（须为奇数），压锯齿利于收成 3 顶点
+TRIANGLE_PATCH_PRE_BLUR_KSIZE = 0
+TRIANGLE_BLACK_YOLO_PRELOAD_ON_BOOT = True
+# 每箭是否在日志中打印黑三角 detect 统计（raw/类过滤/是否在环内）；调通后可 False 减日志
+TRIANGLE_BLACK_YOLO_LOG_EACH_SHOT = True
+# True=每次射箭将 Stage1 裁切图（黑三角模型输入）存为 JPEG；调试用，量产请 False
+TRIANGLE_BLACK_YOLO_SAVE_ROI_CROP = True
+# 存盘目录；空字符串表示使用 PHOTO_DIR + "/stage2_roi"
+TRIANGLE_BLACK_YOLO_ROI_CROP_DIR = ""
+# 存盘 JPEG 上绘制 Stage2（黑三角 YOLO）最终子框（绿框 + s2_0… 标签）
+TRIANGLE_BLACK_YOLO_SAVE_ROI_DRAW_BOXES = True
+
+FLASH_LASER_WHILE_SHOOTING = False  # 是否在拍摄时闪一下激光（True=闪，False=不闪）
+FLASH_LASER_DURATION_MS = 1000  # 闪一下激光的持续时间（毫秒）
+
+# ==================== 显示配置 ====================
+LASER_COLOR = (0, 255, 0)  # RGB颜色
+LASER_THICKNESS = 1
+LASER_LENGTH = 2
+
+# ==================== 图像保存配置 ====================
+SAVE_IMAGE_ENABLED = True  # 是否保存图像（True=保存，False=不保存）
+PHOTO_DIR = "/root/phot"    # 照片存储目录
+MAX_IMAGES = 1000
+# Stage2 调试目录（默认 PHOTO_DIR/stage2_roi）内 JPEG 最多保留张数；None 表示与 MAX_IMAGES 相同
+TRIANGLE_BLACK_YOLO_STAGE2_ROI_MAX_IMAGES = None
+
+SHOW_CAMERA_PHOTO_WHILE_SHOOTING = False  # 是否在拍摄时显示摄像头图像（True=显示，False=不显示），建议在连着USB测试过程中打开
+
+# ==================== OTA配置 ====================
+MAX_BACKUPS = 5
+LOG_MAX_BYTES = 10 * 1024 * 1024  # 10MB
+LOG_BACKUP_COUNT = 5
+
+# ==================== 引脚映射配置（板载 WiFi，I2C5）====================
+PIN_MAPPINGS = {
+    "A18": "UART1_RX",
+    "A19": "UART1_TX",
+    "A29": "UART2_RX",
+    "A28": "UART2_TX",
+    "A15": "I2C5_SCL",
+    "A27": "I2C5_SDA",
+    "A24": "GPIOA24",  # 电源板关机控制
+}
+
+# ==================== 电源配置 ====================
+AUTO_POWER_OFF_IN_SECONDS = 10 * 60  # 自动关机时间（秒），0表示不自动关机
+
+BATTERY_SOC_LPF_ALPHA = 0.5
+BATTERY_SOC_AVG_WINDOW = 5
+

cpp_ext/CMakeLists.txt

@@ -0,0 +1,72 @@
+cmake_minimum_required(VERSION 3.16)
+project(archery_netcore CXX)
+
+set(CMAKE_SYSTEM_NAME Linux)
+set(CMAKE_SYSTEM_PROCESSOR riscv64)
+set(CMAKE_CXX_STANDARD 17)
+set(CMAKE_POSITION_INDEPENDENT_CODE ON)
+
+if(NOT DEFINED PY_INCLUDE_DIR)
+  message(FATAL_ERROR "PY_INCLUDE_DIR not set")
+endif()
+if(NOT DEFINED PY_LIB)
+  message(FATAL_ERROR "PY_LIB not set")
+endif()
+if(NOT DEFINED PY_EXT_SUFFIX)
+  message(FATAL_ERROR "PY_EXT_SUFFIX not set")
+endif()
+if(NOT DEFINED MAIXCDK_PATH)
+  message(FATAL_ERROR "MAIXCDK_PATH not set (need components/3rd_party/pybind11)")
+endif()
+
+add_library(archery_netcore MODULE 
+  archery_netcore.cpp
+  native_logger.cpp
+  utils.cpp
+  decrypt_ota_file.cpp
+  msg_handler.cpp
+  tcp_ssl_password.cpp
+)
+
+target_include_directories(archery_netcore PRIVATE
+  "${PY_INCLUDE_DIR}"
+  "${MAIXCDK_PATH}/components/3rd_party/pybind11/pybind11/include"
+  "${MAIXCDK_PATH}/components/3rd_party/openssl/include"
+  "${CMAKE_CURRENT_SOURCE_DIR}/third_party"  # 添加 nlohmann/json 路径
+)
+
+# 尽量减少 .so 体积并增加逆向成本
+target_compile_options(archery_netcore PRIVATE
+  -Os
+  -ffunction-sections
+  -fdata-sections
+  -fvisibility=hidden
+  -fvisibility-inlines-hidden
+)
+target_link_options(archery_netcore PRIVATE
+  -Wl,--gc-sections
+  -Wl,-s
+)
+
+set_target_properties(archery_netcore PROPERTIES
+  PREFIX ""
+  SUFFIX "${PY_EXT_SUFFIX}"
+)
+
+# OpenSSL (for AES-256-GCM decrypt)
+# 使用 MaixCDK 提供的 OpenSSL 库（在 so/maixcam 目录下）
+set(OPENSSL_LIB_DIR "${MAIXCDK_PATH}/components/3rd_party/openssl/so/maixcam")
+if(EXISTS "${OPENSSL_LIB_DIR}/libcrypto.so")
+    target_link_directories(archery_netcore PRIVATE "${OPENSSL_LIB_DIR}")
+    target_link_libraries(archery_netcore PRIVATE "${PY_LIB}" crypto ssl)
+    message(STATUS "Using OpenSSL from MaixCDK: ${OPENSSL_LIB_DIR}")
+else()
+    # Fallback: 尝试 find_package 或系统库
+    find_package(OpenSSL QUIET)
+    if(OpenSSL_FOUND)
+        target_link_libraries(archery_netcore PRIVATE "${PY_LIB}" OpenSSL::Crypto OpenSSL::SSL)
+    else()
+        message(WARNING "OpenSSL not found in MaixCDK, trying system libraries (may fail)")
+        target_link_libraries(archery_netcore PRIVATE "${PY_LIB}" crypto ssl)
+    endif()
+endif()

cpp_ext/archery_netcore.cpp

@@ -0,0 +1,117 @@
+#include <pybind11/pybind11.h>
+#include <pybind11/stl.h>  // 支持 std::vector, std::map 等
+#include <nlohmann/json.hpp>
+#include <cstring>
+#include <cstdint>
+#include <vector>
+#include <string>
+#include <fstream>
+#include <array>
+
+#include "msg_handler.hpp"
+#include "native_logger.hpp"
+#include "decrypt_ota_file.hpp"
+#include "utils.hpp"
+#include "tcp_ssl_password.hpp"
+
+namespace py = pybind11;
+using json = nlohmann::json;
+
+namespace {
+    // 配置项
+    const std::string _cfg_server_ip = "www.shelingxingqiu.com";
+    const int _cfg_server_port = 50005;
+    const std::string _cfg_device_id_file = "/device_key";
+
+
+}
+
+// 定义获取配置的函数
+py::dict get_config() {
+    py::dict config;
+    config["SERVER_IP"] = _cfg_server_ip;
+    config["SERVER_PORT"] = _cfg_server_port;
+    return config;
+}
+
+
+
+
+
+PYBIND11_MODULE(archery_netcore, m) {
+    m.doc() = "Archery net core (native, pybind11).";
+
+    // Optional: configure native logger from Python.
+    // Default log file: /maixapp/apps/t11/netcore.log
+    m.def("set_log_file", [](const std::string& path) { netcore::set_log_file(path); }, py::arg("path"));
+    m.def("set_log_level", [](int level) {
+        if (level < 0) level = 0;
+        if (level > 3) level = 3;
+        netcore::set_log_level(static_cast<netcore::LogLevel>(level));
+    }, py::arg("level"));
+    m.def("log_test", [](const std::string& msg) {
+        netcore::log_info(std::string("log_test: ") + msg);
+    }, py::arg("msg"));
+
+    m.def("make_packet", &netcore::make_packet,
+          "Pack TCP packet: header (len+type+checksum) + JSON body",
+          py::arg("msg_type"), py::arg("body_dict"));
+    
+    m.def("parse_packet", &netcore::parse_packet,
+          "Parse TCP packet, return (msg_type, body_dict)");
+
+    m.def("get_config", &get_config, "Get system configuration");
+
+    m.def(
+        "calculate_tcp_ssl_password",
+        &netcore::calculate_tcp_ssl_password,
+        "Calculate TCP SSL password: hex(md5(hex(md5(device_id)) + iccid))",
+        py::arg("device_id"),
+        py::arg("iccid")
+    );
+
+    m.def(
+        "decrypt_ota_file",
+        [](const std::string& input_path, const std::string& output_zip_path) {
+            netcore::log_info(std::string("decrypt_ota_file in=") + input_path + " out=" + output_zip_path);
+            return netcore::decrypt_ota_file_impl(input_path, output_zip_path);
+        },
+        py::arg("input_path"),
+        py::arg("output_zip_path"),
+        "Decrypt OTA encrypted file (MAGIC|nonce|ciphertext|tag) to plaintext zip."
+    );
+
+    // Minimal demo: return actions for inner_cmd=41 (manual trigger + ack)
+    m.def("actions_for_inner_cmd", [](int inner_cmd) {
+        py::list actions;
+
+        if (inner_cmd == 41) {
+            // 1) set manual trigger flag
+            {
+                py::dict a;
+                a["type"] = "SET_FLAG";
+                py::dict args;
+                args["name"] = "manual_trigger_flag";
+                args["value"] = true;
+                a["args"] = args;
+                actions.append(a);
+            }
+
+            // 2) enqueue trigger_ack
+            {
+                py::dict a;
+                a["type"] = "ENQUEUE";
+                py::dict args;
+                args["msg_type"] = 2;
+                args["high"] = false;
+                py::dict body;
+                body["result"] = "trigger_ack";
+                args["body"] = body;
+                a["args"] = args;
+                actions.append(a);
+            }
+        }
+
+        return actions;
+    });
+}

cpp_ext/decrypt_ota_file.cpp

@@ -0,0 +1,135 @@
+#include <pybind11/pybind11.h>
+#include <pybind11/stl.h>  // 支持 std::vector, std::map 等
+#include <nlohmann/json.hpp>
+#include <cstring>
+#include <cstdint>
+#include <vector>
+#include <string>
+#include <fstream>
+#include <array>
+#include <openssl/evp.h>
+#include <algorithm>
+#include "native_logger.hpp"
+
+namespace netcore{
+
+    // OTA AEAD format: MAGIC(7) | nonce(12) | ciphertext(N) | tag(16)
+    constexpr const char* kOtaMagic = "AROTAE1";
+    constexpr size_t kOtaMagicLen = 7;
+    constexpr size_t kGcmNonceLen = 12;
+    constexpr size_t kGcmTagLen = 16;
+
+    // 固定 32-byte AES-256-GCM key（提高被直接查看的成本；不是绝对安全）
+    // 注意：需要与打包端传入的 --aead-key-hex 保持一致。
+    static std::array<uint8_t, 32> ota_key_bytes() {
+        // 简单拆分混淆：key = a XOR b
+        static const std::array<uint8_t, 32> a = {
+            0x92,0x99,0x4d,0x06,0x6f,0xb6,0xa6,0x3d,0x85,0x08,0xbe,0x73,0x5e,0x73,0x4d,0x8a,
+            0x53,0x88,0xe6,0x99,0xfc,0x10,0x29,0xb9,0x16,0x9b,0xe7,0x0c,0x65,0x21,0x1c,0xce
+        };
+        static const std::array<uint8_t, 32> b = {
+            0xcf,0x60,0xa2,0xc2,0x32,0x7a,0x61,0xb0,0x4c,0x8e,0x8a,0x62,0x31,0xc7,0x82,0xff,
+            0xec,0xac,0xa1,0x04,0x2a,0x4d,0xaa,0xf2,0xb0,0x5b,0x39,0x2b,0xf4,0xb3,0xad,0xad
+        };
+        std::array<uint8_t, 32> k{};
+        for (size_t i = 0; i < k.size(); i++) k[i] = static_cast<uint8_t>(a[i] ^ b[i]);
+        return k;
+    }
+
+    static bool read_file_all(const std::string& path, std::vector<uint8_t>& out) {
+        std::ifstream ifs(path, std::ios::binary);
+        if (!ifs) return false;
+        ifs.seekg(0, std::ios::end);
+        std::streampos size = ifs.tellg();
+        if (size <= 0) return false;
+        ifs.seekg(0, std::ios::beg);
+        out.resize(static_cast<size_t>(size));
+        if (!ifs.read(reinterpret_cast<char*>(out.data()), size)) return false;
+        return true;
+    }
+
+    static bool write_file_all(const std::string& path, const uint8_t* data, size_t len) {
+        std::ofstream ofs(path, std::ios::binary | std::ios::trunc);
+        if (!ofs) return false;
+        ofs.write(reinterpret_cast<const char*>(data), static_cast<std::streamsize>(len));
+        return static_cast<bool>(ofs);
+    }
+
+    bool decrypt_ota_file_impl(const std::string& input_path, const std::string& output_zip_path) {
+        std::vector<uint8_t> in;
+        if (!netcore::read_file_all(input_path, in)) {
+            netcore::log_error(std::string("decrypt_ota_file: read failed: ") + input_path);
+            return false;
+        }
+
+        const size_t min_len = kOtaMagicLen + kGcmNonceLen + kGcmTagLen + 1;
+        if (in.size() < min_len) {
+            netcore::log_error("decrypt_ota_file: too short");
+            return false;
+        }
+        if (!std::equal(in.begin(), in.begin() + kOtaMagicLen, reinterpret_cast<const uint8_t*>(kOtaMagic))) {
+            netcore::log_error("decrypt_ota_file: bad magic");
+            return false;
+        }
+
+        const uint8_t* nonce = in.data() + kOtaMagicLen;
+        const uint8_t* ct_and_tag = in.data() + kOtaMagicLen + kGcmNonceLen;
+        const size_t ct_and_tag_len = in.size() - (kOtaMagicLen + kGcmNonceLen);
+        if (ct_and_tag_len <= kGcmTagLen) {
+            netcore::log_error("decrypt_ota_file: no ciphertext");
+            return false;
+        }
+        const size_t ciphertext_len = ct_and_tag_len - kGcmTagLen;
+        const uint8_t* ciphertext = ct_and_tag;
+        const uint8_t* tag = ct_and_tag + ciphertext_len;
+
+        std::vector<uint8_t> plain(ciphertext_len);
+        int out_len1 = 0;
+        int out_len2 = 0;
+
+        EVP_CIPHER_CTX* ctx = EVP_CIPHER_CTX_new();
+        if (!ctx) {
+            netcore::log_error("decrypt_ota_file: EVP_CIPHER_CTX_new failed");
+            return false;
+        }
+
+        bool ok = false;
+        auto key = ota_key_bytes();
+
+        do {
+            if (1 != EVP_DecryptInit_ex(ctx, EVP_aes_256_gcm(), nullptr, nullptr, nullptr)) {
+                netcore::log_error("decrypt_ota_file: DecryptInit failed");
+                break;
+            }
+            if (1 != EVP_CIPHER_CTX_ctrl(ctx, EVP_CTRL_GCM_SET_IVLEN, static_cast<int>(kGcmNonceLen), nullptr)) {
+                netcore::log_error("decrypt_ota_file: set ivlen failed");
+                break;
+            }
+            if (1 != EVP_DecryptInit_ex(ctx, nullptr, nullptr, key.data(), nonce)) {
+                netcore::log_error("decrypt_ota_file: set key/iv failed");
+                break;
+            }
+            if (1 != EVP_DecryptUpdate(ctx, plain.data(), &out_len1, ciphertext, static_cast<int>(ciphertext_len))) {
+                netcore::log_error("decrypt_ota_file: update failed");
+                break;
+            }
+            if (1 != EVP_CIPHER_CTX_ctrl(ctx, EVP_CTRL_GCM_SET_TAG, static_cast<int>(kGcmTagLen), const_cast<uint8_t*>(tag))) {
+                netcore::log_error("decrypt_ota_file: set tag failed");
+                break;
+            }
+            if (1 != EVP_DecryptFinal_ex(ctx, plain.data() + out_len1, &out_len2)) {
+                netcore::log_error("decrypt_ota_file: final failed (auth tag mismatch?)");
+                break;
+            }
+            const size_t plain_len = static_cast<size_t>(out_len1 + out_len2);
+            if (!netcore::write_file_all(output_zip_path, plain.data(), plain_len)) {
+                netcore::log_error(std::string("decrypt_ota_file: write failed: ") + output_zip_path);
+                break;
+            }
+            ok = true;
+        } while (false);
+
+        EVP_CIPHER_CTX_free(ctx);
+        return ok;
+    }
+}

cpp_ext/decrypt_ota_file.hpp

@@ -0,0 +1,7 @@
+#pragma once
+
+#include <string>
+
+namespace netcore{
+    bool decrypt_ota_file_impl(const std::string& input_path, const std::string& output_zip_path);
+}

cpp_ext/msg_handler.cpp

@@ -0,0 +1,113 @@
+#include <nlohmann/json.hpp>
+#include <string>
+#include <cstring>
+#include <cstdint>
+#include <vector>
+#include "native_logger.hpp"
+#include "msg_handler.hpp"
+#include "utils.hpp"
+
+namespace py = pybind11;
+using json = nlohmann::json;
+
+namespace netcore {
+    // 打包 TCP 数据包
+    py::bytes make_packet(int msg_type, py::dict body_dict) {
+        netcore::log_debug(std::string("make_packet msg_type=") + std::to_string(msg_type));
+        // 1) 将 py::dict 转为 JSON 字符串
+        json j = netcore::py_dict_to_json(body_dict);
+        std::string body_str = j.dump();
+
+        // 2) 计算 body_len 和 checksum
+        uint32_t body_len = body_str.size();
+        uint32_t checksum = body_len + msg_type;
+
+        // 3) 打包头部（大端序）
+        std::vector<uint8_t> packet;
+        packet.reserve(12 + body_len);
+
+        // body_len (big-endian, 4 bytes)
+        packet.push_back((body_len >> 24) & 0xFF);
+        packet.push_back((body_len >> 16) & 0xFF);
+        packet.push_back((body_len >> 8) & 0xFF);
+        packet.push_back(body_len & 0xFF);
+
+        // msg_type (big-endian, 4 bytes)
+        packet.push_back((msg_type >> 24) & 0xFF);
+        packet.push_back((msg_type >> 16) & 0xFF);
+        packet.push_back((msg_type >> 8) & 0xFF);
+        packet.push_back(msg_type & 0xFF);
+
+        // checksum (big-endian, 4 bytes)
+        packet.push_back((checksum >> 24) & 0xFF);
+        packet.push_back((checksum >> 16) & 0xFF);
+        packet.push_back((checksum >> 8) & 0xFF);
+        packet.push_back(checksum & 0xFF);
+
+        // 4) 追加 body
+        packet.insert(packet.end(), body_str.begin(), body_str.end());
+
+        netcore::log_debug(std::string("make_packet done bytes=") + std::to_string(packet.size()));
+        return py::bytes(reinterpret_cast<const char*>(packet.data()), packet.size());
+    }
+
+    // 解析 TCP 数据包
+    py::tuple parse_packet(py::bytes data) {
+        // 1) 转换为 bytes view
+        py::buffer_info buf = py::buffer(data).request();
+        if (buf.size < 12) {
+            netcore::log_error(std::string("parse_packet too_short len=") + std::to_string(buf.size));
+            return py::make_tuple(py::none(), py::none());
+        }
+
+        const uint8_t* ptr = static_cast<const uint8_t*>(buf.ptr);
+
+        // 2) 解析头部（大端序）
+        uint32_t body_len = (ptr[0] << 24) | (ptr[1] << 16) | (ptr[2] << 8) | ptr[3];
+        uint32_t msg_type = (ptr[4] << 24) | (ptr[5] << 16) | (ptr[6] << 8) | ptr[7];
+        uint32_t checksum = (ptr[8] << 24) | (ptr[9] << 16) | (ptr[10] << 8) | ptr[11];
+
+        // 3) 校验 checksum（可选，你现有代码不强制校验）
+        // if (checksum != (body_len + msg_type)) {
+        //     return py::make_tuple(py::none(), py::none());
+        // }
+
+        // 4) 检查长度
+        uint32_t expected_len = 12 + body_len;
+        if (buf.size < expected_len) {
+            // 半包
+            netcore::log_warn(std::string("parse_packet incomplete got=") + std::to_string(buf.size) +
+                              " expected=" + std::to_string(expected_len));
+            return py::make_tuple(py::none(), py::none());
+        }
+
+        // 5) 防御性检查：如果 data 比预期长，说明可能有粘包
+        // （只解析第一个包，忽略多余数据）
+        if (buf.size > expected_len) {
+            netcore::log_warn(std::string("parse_packet concat got=") + std::to_string(buf.size) +
+                              " expected=" + std::to_string(expected_len) +
+                              " body_len=" + std::to_string(body_len) +
+                              " msg_type=" + std::to_string(msg_type));
+        }
+
+        // 6) 提取 body 并解析 JSON
+        std::string body_str(reinterpret_cast<const char*>(ptr + 12), body_len);
+
+        try {
+            json j = json::parse(body_str);
+            py::dict body_dict = netcore::json_to_py_dict(j);
+            return py::make_tuple(py::int_(msg_type), body_dict);
+        } catch (const json::parse_error& e) {
+            // JSON 解析失败，返回 raw（兼容你现有的逻辑）
+            netcore::log_error(std::string("parse_packet json_parse_error: ") + e.what());
+            py::dict raw_dict;
+            raw_dict["raw"] = body_str;
+            return py::make_tuple(py::int_(msg_type), raw_dict);
+        } catch (const std::exception& e) {
+            netcore::log_error(std::string("parse_packet json_parse_error: ") + e.what());
+            py::dict raw_dict;
+            raw_dict["raw"] = body_str;
+            return py::make_tuple(py::int_(msg_type), raw_dict);
+        }
+    }
+}

cpp_ext/msg_handler.hpp

@@ -0,0 +1,14 @@
+#pragma once
+
+#include <pybind11/pybind11.h>
+#include <pybind11/stl.h>  // 支持 std::vector, std::map 等
+
+namespace py = pybind11;
+
+namespace netcore {
+
+    // 打包 TCP 数据包
+    py::bytes make_packet(int msg_type, py::dict body_dict);
+    // 解包 TCP 数据包
+    py::tuple parse_packet(py::bytes data);
+}

cpp_ext/native_logger.cpp

@@ -0,0 +1,100 @@
+#include "native_logger.hpp"
+
+#include <cerrno>
+#include <cstring>
+#include <mutex>
+#include <string>
+
+#include <fcntl.h>
+#include <sys/stat.h>
+#include <sys/types.h>
+#include <time.h>
+#include <unistd.h>
+
+namespace netcore {
+
+static std::mutex g_mu;
+static int g_fd = -1;
+static std::string g_path = "netcore.log";
+static LogLevel g_level = LogLevel::kDebug; //LogLevel::kInfo;
+
+static const char* level_name(LogLevel lvl) {
+    switch (lvl) {
+        case LogLevel::kError: return "E";
+        case LogLevel::kWarn:  return "W";
+        case LogLevel::kInfo:  return "I";
+        case LogLevel::kDebug: return "D";
+        default: return "?";
+    }
+}
+
+static void ensure_open_locked() {
+    if (g_path.empty()) return;
+    if (g_fd >= 0) return;
+    g_fd = ::open(g_path.c_str(), O_CREAT | O_WRONLY | O_APPEND, 0644);
+}
+
+void set_log_file(const std::string& path) {
+    std::lock_guard<std::mutex> lk(g_mu);
+    g_path = path;
+    if (g_fd >= 0) {
+        ::close(g_fd);
+        g_fd = -1;
+    }
+    ensure_open_locked();
+}
+
+void set_log_level(LogLevel level) {
+    std::lock_guard<std::mutex> lk(g_mu);
+    g_level = level;
+}
+
+void log(LogLevel level, const std::string& msg) {
+    std::lock_guard<std::mutex> lk(g_mu);
+    if (static_cast<int>(level) > static_cast<int>(g_level)) return;
+    if (g_path.empty()) return;
+
+    ensure_open_locked();
+    if (g_fd < 0) {
+        // Last resort: stderr (avoid any Python APIs)
+        ::write(STDERR_FILENO, msg.c_str(), msg.size());
+        ::write(STDERR_FILENO, "\n", 1);
+        return;
+    }
+
+    // Timestamp: epoch milliseconds (simple and cheap)
+    struct timespec ts;
+    clock_gettime(CLOCK_REALTIME, &ts);
+//    long long ms = (long long)ts.tv_sec * 1000LL + ts.tv_nsec / 1000000LL;
+    // 1. 将秒数转换为本地时间结构体 struct tm
+    struct tm *tm_info = localtime(&ts.tv_sec);
+
+    // 2. 准备一个缓冲区来存储时间字符串
+    char buffer[30];
+
+    // 3. 格式化秒的部分
+    // 格式: 年-月-日 时:分:秒
+    strftime(buffer, sizeof(buffer), "%Y-%m-%d %H:%M:%S", tm_info);
+
+    // 4. 计算毫秒部分并追加到字符串中
+    // ts.tv_nsec 是纳秒，除以 1,000,000 得到毫秒
+    char ms_buffer[8];
+    snprintf(ms_buffer, sizeof(ms_buffer), ".%03ld", ts.tv_nsec / 1000000);
+
+    // Build one line to keep writes atomic-ish
+    char head[256];
+    int n = ::snprintf(head, sizeof(head), "[%s%s] [%s] ", buffer, ms_buffer, level_name(level));
+    if (n < 0) n = 0;
+
+    ::write(g_fd, head, (size_t)n);
+    ::write(g_fd, msg.c_str(), msg.size());
+    ::write(g_fd, "\n", 1);
+}
+
+void log_debug(const std::string& msg) { log(LogLevel::kDebug, msg); }
+void log_info (const std::string& msg) { log(LogLevel::kInfo,  msg); }
+void log_warn (const std::string& msg) { log(LogLevel::kWarn,  msg); }
+void log_error(const std::string& msg) { log(LogLevel::kError, msg); }
+
+} // namespace netcore
+

cpp_ext/native_logger.hpp

@@ -0,0 +1,28 @@
+#pragma once
+
+#include <string>
+
+namespace netcore {
+
+enum class LogLevel : int {
+    kError = 0,
+    kWarn  = 1,
+    kInfo  = 2,
+    kDebug = 3,
+};
+
+// Set log file path. If empty, logging is disabled.
+void set_log_file(const std::string& path);
+
+// Set minimum log level to write (default: kInfo).
+void set_log_level(LogLevel level);
+
+// Log helpers (thread-safe, never calls into Python).
+void log(LogLevel level, const std::string& msg);
+void log_debug(const std::string& msg);
+void log_info(const std::string& msg);
+void log_warn(const std::string& msg);
+void log_error(const std::string& msg);
+
+} // namespace netcore
+

cpp_ext/utils.cpp

@@ -0,0 +1,95 @@
+#include <fstream>
+#include <cstring>
+#include <cstdint>
+#include <string>
+#include <fstream>
+#include "utils.hpp"
+
+namespace netcore {
+// 辅助函数：将 py::dict 转为 nlohmann::json
+json py_dict_to_json(py::dict d) {
+    json j;
+    for (auto item : d) {
+        std::string key = py::str(item.first);
+        py::object val = py::reinterpret_borrow<py::object>(item.second);
+
+        if (py::isinstance<py::dict>(val)) {
+            j[key] = py_dict_to_json(py::cast<py::dict>(val));
+        } else if (py::isinstance<py::list>(val)) {
+            py::list py_list = py::cast<py::list>(val);
+            json arr = json::array();
+            for (auto elem : py_list) {
+                py::object elem_obj = py::reinterpret_borrow<py::object>(elem);
+                if (py::isinstance<py::dict>(elem_obj)) {
+                    arr.push_back(py_dict_to_json(py::cast<py::dict>(elem_obj)));
+                } else if (py::isinstance<py::int_>(elem_obj)) {
+                    arr.push_back(py::cast<int64_t>(elem_obj));
+                } else if (py::isinstance<py::float_>(elem_obj)) {
+                    arr.push_back(py::cast<double>(elem_obj));
+                } else {
+                    arr.push_back(py::str(elem_obj));
+                }
+            }
+            j[key] = arr;
+        } else if (py::isinstance<py::int_>(val)) {
+            j[key] = py::cast<int64_t>(val);
+        } else if (py::isinstance<py::float_>(val)) {
+            j[key] = py::cast<double>(val);
+        } else if (py::isinstance<py::bool_>(val)) {
+            j[key] = py::cast<bool>(val);
+        } else if (val.is_none()) {
+            j[key] = nullptr;
+        } else {
+            j[key] = py::str(val);
+        }
+    }
+    return j;
+}
+
+// 辅助函数：将 nlohmann::json 转为 py::dict
+py::dict json_to_py_dict(const json& j) {
+    py::dict d;
+    if (j.is_object()) {
+        for (auto& item : j.items()) {
+            std::string key = item.key();
+            json val = item.value();
+
+            if (val.is_object()) {
+                d[py::str(key)] = json_to_py_dict(val);
+            } else if (val.is_array()) {
+                py::list py_list;
+                for (auto& elem : val) {
+                    if (elem.is_object()) {
+                        py_list.append(json_to_py_dict(elem));
+                    } else if (elem.is_number_integer()) {
+                        py_list.append(py::int_(elem.get<int64_t>()));
+                    } else if (elem.is_number_float()) {
+                        py_list.append(py::float_(elem.get<double>()));
+                    } else if (elem.is_boolean()) {
+                        py_list.append(py::bool_(elem.get<bool>()));
+                    } else if (elem.is_null()) {
+                        py_list.append(py::none());
+                    } else {
+                        py_list.append(py::str(elem.get<std::string>()));
+                    }
+                }
+                d[py::str(key)] = py_list;
+            } else if (val.is_number_integer()) {
+                d[py::str(key)] = py::int_(val.get<int64_t>());
+            } else if (val.is_number_float()) {
+                d[py::str(key)] = py::float_(val.get<double>());
+            } else if (val.is_boolean()) {
+                d[py::str(key)] = py::bool_(val.get<bool>());
+            } else if (val.is_null()) {
+                d[py::str(key)] = py::none();
+            } else {
+                d[py::str(key)] = py::str(val.get<std::string>());
+            }
+        }
+    }
+    return d;
+}
+
+
+
+}

cpp_ext/utils.hpp

@@ -0,0 +1,15 @@
+#pragma once
+
+#include <pybind11/pybind11.h>
+#include <pybind11/stl.h>  // 支持 std::vector, std::map 等
+#include <nlohmann/json.hpp>
+#include <string>
+
+namespace py = pybind11;
+using json = nlohmann::json;
+
+namespace netcore {
+
+json py_dict_to_json(py::dict d);
+py::dict json_to_py_dict(const json& j);
+}

design_doc/algo.md

@@ -0,0 +1,184 @@
+1. 系统目标
+# 检测靶纸四角的等腰直角三角形标记（每个角一个）
+# 计算激光落点在靶面上的二维偏移（厘米）
+# 通过PnP算法估算靶面到相机的距离（米）
+
+2. 核心算法流程
+2.1 三角形检测 (detect_triangle_markers)
+采用多策略级联保证鲁棒性：
+图像输入 → 多阈值策略 → 候选三角形过滤 → 四点匹配
+检测策略（按优先级）：
+
+1.全局Otsu二值化（最快，~10ms）
+2.自适应阈值（多种block size，光照不均时）
+3.ROI局部阈值（候选不足3个时，分象限独立处理）
+4.Black-Hat形态学增强（仍不足时，突出暗色标记）
+
+三角形几何验证：
+# 必须是直角三角形（检查勾股定理，容差20%）
+# 两直角边长度差<20%
+# 内部像素足够暗（灰度≤130，暗像素比例≥30%）
+# 与周围背景对比度≥15灰度级
+
+四点匹配算法：
+# 从候选三角形中枚举所有4点组合
+# 计算四边形评分：(对角比-1)*3 + (水平比-1) + (垂直比-1) + (边长偏差)*2
+# 选择评分最低的组合作为四角标记
+
+2.2 单应性落点计算 (homography_calibration)
+建立图像坐标系 → 靶面坐标系（二维平面）的透视变换
+
+将激光点像素坐标映射到靶面坐标（厘米）
+
+使用RANSAC提高鲁棒性（阈值1像素）
+
+2.3 PnP距离估计 (pnp_distance_meters)
+已知四个标记点的三维坐标（x,y,z，单位cm）
+
+通过solvePnP求解相机外参（旋转+平移）
+
+距离 = ‖平移向量‖ / 100（转换为米）
+
+3. 关键优化策略
+3.1 多路径投票
+同一图像区域被不同二值化方法检测到时，path_votes++
+
+选择投票数高的候选，提高检测可信度
+
+3.2 早退机制
+候选≥3个 且 覆盖3个以上象限 → 停止更多阈值尝试
+
+大幅降低嵌入式设备计算开销
+
+3.3 3点补全机制
+当只检测到3个角时，通过仿射变换估算第4个角位置
+
+公式：P_missing = M_inv @ [x_target, y_target, 1]
+
+3.4 图像缩放
+默认缩放到0.5倍进行检测（由config控制）
+
+坐标还原时乘以inv_scale，保持与标定矩阵一致
+
+4. 数据流示例
+python
+输入:
+  - img_rgb: H×W×3 图像
+  - laser_xy: (x_px, y_px) 激光点像素坐标
+  - marker_positions: {0:[0,0,0], 1:[0,30,0], 2:[30,30,0], 3:[30,0,0]} # 4角3D坐标(cm)
+
+输出:
+  {
+    "ok": True,
+    "dx_cm": 2.5,        # 靶面X偏移(cm，向右为正)
+    "dy_cm": -3.2,       # 靶面Y偏移(cm，向上为正)
+    "distance_m": 5.43,  # 相机到靶面距离(米)
+    "offset_method": "triangle_homography",
+    "distance_method": "pnp_triangle"
+  }
+5. 鲁棒性设计
+5.1 参数自适应
+从config.py动态读取所有阈值（可在线调整）
+
+三角形边长范围、灰度阈值、对比度要求等均可配置
+
+5.2 异常处理
+角点退化检测（距离<3像素判定为重复）
+
+NaN/Inf校验（单应性矩阵、偏移量、距离）
+
+距离合理性检查（0.3~20米）
+
+5.3 降级策略
+PnP失败 → 只输出偏移，距离置None
+
+4角检测失败 → 尝试3角补全
+
+快速路径失败 → CLAHE增强兜底（可选）
+
+6. 性能特点
+CPU友好：默认Otsu单次处理，多数场景10-30ms完成检测
+
+内存可控：最大候选数截断（默认10个），避免组合爆炸
+
+嵌入式适配：支持图像缩放、早退机制降低计算量
+
+7. 局限性
+依赖四个等腰直角三角形（需靶纸特殊设计）
+
+要求三角形内部足够暗、与背景有对比度
+
+单应性假设靶面为平面（实际靶纸可能有轻微起伏）
+
+这套算法在射击训练系统中作为主要定位手段。
+
+8. 为了加速单应性的计算，引入了yolo模型，一共做了两个模型，一个为靶纸和黑色三角形一体的识别模型，用于做原照片上快速找到靶纸区域。另一个模型是黑色三角形的模型，用于做靶纸区域再找黑色三角形。但是经过对比发现，引入黑色三角形模型反而更慢。入下面的流程A和流程B：
+        yolo靶纸+传统（流程B） 	 yolo靶纸+yolo黑色三角形（流程A）
+平均值   646.08	                916.4457143	
+标准差   94.61300968	          57.40401849	
+
+公共前置（两条路都一样）
+是否用靶环模型裁 Stage1
+
+TRIANGLE_YOLO_ROI_ENABLE=True 时：跑 靶环 YOLO，得到全图上的 roi_xyxy，后面的三角形都在 img_work = 全图[roi] 上做（必要时再缩成 img_det 给整图传统分支用）。
+False 时：roi_xyxy=None，三角形在 整幅相机图 上当 img_work。
+之后都进入 try_triangle_scoring(img_cv, …, roi_xyxy=…, black_yolo_boxes_work=…)
+
+在里面先做灰度、v_suppress、锐化、det_scale 缩略图等 prep（与是否黑三角模型无关）。
+差别从 black_yolo_boxes_work 有没有有效子框列表 开始。
+
+流程 A：用黑色三角形模型（Stage2 黑三角 YOLO）
+配置要点：TRIANGLE_BLACK_YOLO_ENABLE=True，且 TRIANGLE_BLACK_TRIANGLE_LOCATE_MODE="yolo"，并且 已有 Stage1 裁切（roi_xyxy 不能为 None，否则根本不会跑黑三角 YOLO）。
+
+步骤概要：
+
+try_black_triangle_boxes_work
+
+输入：全图 RGB + Stage1 的 ring_roi_xyxy。
+在 Stage1 裁切图（与训练一致的 slab）上跑 黑三角 YOLO，得到若干个 子框（black_boxes_work，坐标在 裁切图/work 系）。
+try_triangle_scoring 内
+
+若 black_yolo_boxes_work 非空：
+按配置在 Stage1 全分辨率灰度（或缩略灰度，视 det_scale / TRIANGLE_BLACK_YOLO_PATCH_GRAY_SOURCE）上，对每个子框裁 patch，跑 _extract_triangle_from_yolo_patch（子框内：Otsu → 失败再单次 Adaptive + 轮廓 + 形状/颜色）。
+median_leg 过滤，再 四点分配 ID。
+若 ≥3 个（通常 4 个）有效：认为 Stage2 成功，跳过 整幅 Stage1 上的 detect_triangle_markers。
+若 不足 3 个 且未关 fallback：在 缩略后的整幅 work 灰度上再走 detect_triangle_markers（整图 Otsu + 整图 Adaptive×block_sizes + 各类 fallback），与「不用黑三角模型时的传统主路径」同类。
+后续
+
+角点从 det 坐标 ×inv_scale 回到 work，再 +roi 原点 回到全图；单应性、补第 4 点、PnP 等与另一条路相同。
+耗时上多出来的部分：黑三角 YOLO 推理 + 每个子框一遍传统小流水线（成功时通常 不再付整图 detect_triangle_markers）。
+
+流程 B：不用黑色三角形模型（纯传统定位三角）
+典型配置（任一即可达到「不用黑三角模型」的效果）：
+
+TRIANGLE_BLACK_YOLO_ENABLE=False，或
+TRIANGLE_BLACK_TRIANGLE_LOCATE_MODE="traditional"（即使模型开关开着也不跑黑三角 YOLO），或
+没有 Stage1 ROI（roi_xyxy is None）时，当前逻辑下 也不会跑 Stage2 黑三角 YOLO。
+此时 black_yolo_boxes_work=None（或不等价于「有子框」）。
+
+步骤概要：
+
+try_triangle_scoring 内
+不跑 子框 _extract_triangle_from_yolo_patch。
+直接在 img_det（缩略后的 work） 上调用 detect_triangle_markers：
+全局 Otsu（若 TRIANGLE_SKIP_GLOBAL_OTSU_EXTRACT_ON_YOLO_ROI 在有 ROI 时可能 不算 Otsu 轮廓，但仍会生成 Otsu 图供后续用）；
+可选 象限 ROI（TRIANGLE_ROI_ENABLED）；
+整图 Adaptive（TRIANGLE_ADAPTIVE_BLOCK_SIZES，例如 (11,)）；
+不足再走 放宽 approxPolyDP、BlackHat 等。
+后面同样是过滤、四点组合/象限分配、单应性、PnP 等。
+特点：没有黑三角 NPU 时间，也 没有「按框重复 4 次子框传统」；但要在 一整张（缩略）ROI 图 上跑一套更重的 整图 pipeline。
+
+对照一句话
+用黑三角 YOLO（流程 A）	不用黑三角 YOLO（流程 B）
+Stage2
+黑三角模型给子框 → 子框内 Otsu + 至多一次 Adaptive
+无 Stage2 模型
+三角角点从哪来
+优先 子框传统；不够再 整图 detect_triangle_markers
+只有 整图 detect_triangle_markers
+和「全图是否只做 Adaptive」
+子框 不是只做 Adaptive；整图回退时也与全图路径一致（先 Otsu 等）
+整图路径 也不是只做 Adaptive
+靶环 YOLO（Stage1 裁切）在 A/B 里都可以开或关，与「黑三角模型」是独立开关。
+
+

design_doc/command_record.md

@@ -0,0 +1,102 @@
+
+1. CPP构建命令：
+
+cd /mnt/d/code/archery/cpp_ext
+rm -rf build && mkdir build && cd build
+
+TOOLCHAIN_BIN=/mnt/d/code/MaixCDK/dl/extracted/toolchains/maixcam/host-tools/gcc/riscv64-linux-musl-x86_64/bin
+PYDEV=/mnt/d/code/shooting/python3_lib_maixcam_musl_3.11.6
+MAIXCDK=/mnt/d/code/MaixCDK
+
+cmake .. -G Ninja \
+  -DCMAKE_C_COMPILER="${TOOLCHAIN_BIN}/riscv64-unknown-linux-musl-gcc" \
+  -DCMAKE_CXX_COMPILER="${TOOLCHAIN_BIN}/riscv64-unknown-linux-musl-g++" \
+  -DCMAKE_BUILD_TYPE=Release \
+  -DCMAKE_C_FLAGS="-mcpu=c906fdv -march=rv64imafdcv0p7xthead -mcmodel=medany -mabi=lp64d" \
+  -DCMAKE_CXX_FLAGS="-mcpu=c906fdv -march=rv64imafdcv0p7xthead -mcmodel=medany -mabi=lp64d" \
+  -DPY_INCLUDE_DIR="${PYDEV}/include/python3.11" \
+  -DPY_LIB="${PYDEV}/lib/libpython3.11.so" \
+  -DPY_EXT_SUFFIX=".cpython-311-riscv64-linux-gnu.so" \
+  -DMAIXCDK_PATH="${MAIXCDK}"
+
+ninja
+
+
+2. Maixvision 直接跑项目的时候，是复制到板子上的这个目录：/tmp/maixpy_run
+
+3. 4g 模块的终端测试方法：
+    3.1 一个窗口 ssh 到maixcam的板子上之后，通过 printf 输入命令到 /dev/ttyS2, 然后另外一个窗口通过 cat /dev/ttyS2 输出
+# 1. 确保 PDP 激活
+printf 'AT+CGPADDR=1\r\n' > /dev/ttyS2
+# 2. 开启日志监听（另一个 SSH 窗口）
+cat /dev/ttyS2
+# 3. 发送下载命令（原窗口）
+printf 'AT+MHTTPDLFILE="http://static.shelingxingqiu.com/shoot/v1/main.py","downloaded.py",5120\r\n' > /dev/ttyS2
+
+4. wifi的启动条件，在 /boot 目录下，看看是否有 wifi.sta 和 wifi.ssid， wifi.pass 这些文件。其中 wifi.sta 是开关文件。
+   如果没有了它就不会启动wifi流程。具体的wifi流程 由 /etc/init.d/S30wifi 控制。它会判断 wifi.sta 是否存在，然后是否启动wifi，还是启动热点。
+
+5. 给自己的程序打包到基础镜像中，参考：https://wiki.sipeed.com/maixpy/doc/zh/pro/compile_os.html
+    5.1. 按照链接中的步骤，去github上获取了基础镜像，这次使用的是 v4.12.4，把Assets中的下面几样东西下载下来，我是在windows的wsl中执行的，注意，
+         假如是在windows中下载的文件，在wsl中编译会很慢，所以我采用的是直接在wsl中下载，放到wsl的自己的文件系统中。
+         1）maixcam-2025-12-31-maixpy-v4.12.4.img.xz
+         2）maixcam_builtin_files.tar.xz 
+         3）MaixPy-4.12.4-py3-none-any.whl
+         4）Source code(zip)
+    5.2. 把自己的文件放到 buildtin_files中：
+         1）我把项目文件目录 t11 放到了 maixcam_builtin_files\maixapp\apps 这个目录下。
+         2）为了能让它自启动，我把 auto_start.txt 放到了 maixcam_builtin_files\maixapp 这个目录下。
+         
+    5.3. 然后在解压后的源码中找到tools/os目录下 /home/saga/maixcam/MaixPy-4.12.4/tools/os/maixcam
+        执行
+        export MAIXCDK_PATH=/home/saga/maixcam/MaixCDK
+        编译：
+        ./gen_os.sh ../../../../../maixcam/maixcam-2025-12-31-maixpy-v4.12.4.img ../../../../../maixcam/MaixPy-4.12.4-py3-none-any.whl ../../../../../maixcam/maixcam_builtin_files 0 maixcam
+        注意，在编译过程中，也会去 github 下载内容，所以需要打开梯子。
+    5.4. 等待编译完成，会编译成镜像文件，然后根据 https://wiki.sipeed.com/hardware/zh/maixcam/os.html 这个指引来烧录系统。
+    5.5. 烧录完系统后，需要安装 runtime， 可以按照  https://wiki.sipeed.com/maixpy/doc/zh/README_no_screen.html 这个来升级运行库，或者直接在 Maixvision 中链接的时候安装 runtime。
+    5.6. 安装 runtime 之后，重启，我们的系统就会自己启动起来了。
+
+   遇到问题：
+   /mnt/d/code/shooting/compile_maixcam/MaixPy-4.12.4/MaixPy-4.12.4/tools/os/maixcam/fuse2fs: error while loading shared libraries: libfuse.so.2: cannot open shared object file: No such file or directory
+   解决办法：
+    安装 libfuse2
+    sudo apt update
+     sudo apt install libfuse2
+
+   遇到问题：
+    python 缺少  yaml
+    解决办法：
+    pip install pyyaml
+
+   遇到问题：
+   ./build_all.sh: line 56: maixtool: command not found
+   解决办法：
+   pip install maixtool
+
+    遇到问题：
+    ./update_img.sh: line 80: mcopy: command not found
+    解决办法：
+    sudo apt update
+    sudo apt install mtools
+
+6. 相机标定：
+然后在板子上跑 test 目录下的 test_camera_rtsp.py ，让相机启动了一个服务，然后在电脑上接收这个视频流，并且跑opencv 内置的标定程序：
+set OPENCV_FFMPEG_CAPTURE_OPTIONS="rtsp_transport;tcp"
+opencv_interactive-calibration -t=chessboard -w=9 -h=6 -sz=0.025 -v="http://192.168.1.81:8000/stream" 2>nul
+
+
+7. 生成训练图片：在test目录下，执行以下命令。注意，其中 D:\code\shooting\target_photo\write.png 是靶纸的图片。
+ D:\data\test_target_photo 是用来叠加的背景图
+
+ 7.1 生成靶纸及黑色三角形的截图的图片，带动动，但1.12的外框
+bak
+python .\synth_compose_yolo.py  --perspective 0.04 --perspective-prob 0.8 --color-jitter 0.6  --bg-dir D:\data\test_target_photo --fg D:\code\shooting\target_photo\write.png --out ./synth_out --class-name triangle --zip ./maix_dataset.zip --num 60 --triangles-json archery_triangles_default.json --format voc  --stage2-crop  --stage2-pad-min 0.03  --stage2-pad-max 0.18 --motion-prob 0.9 --motion-kernel-max 8 --blur-max 0 --triangle-bbox-pad-frac 0.12
+
+bak_2
+python synth_keypoints_right_angle.py   --bg-dir D:\data\test_target_photo --fg D:\code\shooting\target_photo\write.png  --triangles-json archery_triangles_default.json --out ./synth_out --num 1000  --offscreen-shift-prob 0.3  --offscreen-shift-frac 0.4   --offscreen-min-visible 1  --stage2-crop  --stage2-pad-min 0.03  --stage2-pad-max 0.18 --motion-prob 0.9 --motion-kernel-max 8 --blur-max 0   --perspective-mode planar   --yaw-max-deg 10 --pitch-max-deg 8   --roll-max-deg 4   --planar-focal-frac 1.45   --perspective-prob 0.4
+
+python synth_keypoints_right_angle.py   --bg-dir D:\data\test_target_photo --fg D:\code\shooting\target_photo\write.png  --triangles-json archery_triangles_default.json --out ./synth_out --num 1000  --offscreen-shift-prob 0.3  --offscreen-shift-frac 0.4   --offscreen-min-visible 1  --stage2-crop  --stage2-pad-min 0.03  --stage2-pad-max 0.18 --motion-prob 1.0 --motion-kernel-max 8 --blur-max 0   --perspective-mode planar   --yaw-max-deg 10 --pitch-max-deg 8   --roll-max-deg 4   --planar-focal-frac 1.45   --perspective-prob 0.4
+
+
+ python pose_pixel_metrics.py --model D:\code\archery\runs\pose\runs\pose\target_pose_train\weights\best.pt --data D:\code\archery\datasets\dataset_pose.yaml --imgsz 640

design_doc/debug.md

@@ -0,0 +1,41 @@
+1. 问题描述：开机失败，一直遇到Traceback (most recent call last):
+      File "/tmp/maixpy_run/main.py", line 525, in <module>
+        cmd_str()
+      File "/tmp/maixpy_run/main.py", line 102, in cmd_str
+        camera_manager.init_camera(640, 480)
+      File "/tmp/maixpy_run/camera_manager.py", line 59, in init_camera
+        self._camera = camera.Camera(width, height)
+                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+        RuntimeError: : Runtime error: mmf vi init failed
+    解决方案：
+    根据过往经验，极有可能是摄像头的接线有问题。因为在测试环境，摄像头是通过一个24针转22针的线出来的，然后再通过一个接线中继，连接到一个22针
+    的fpc线到Maixcam。接线中继如果是24针的，多了两针，需要选好一边然后对连。但这里很容易出错或者松动。可以先用摄像头本身的金色接线直接接到
+    Maixcam，然后跑test目录下的test_cammera.py，看看能不能正常启动，如果正常，就确定是中继接线的问题。
+    
+2. 问题描述：202609 批次的拓展版，在连接 202601 批次的电源板，或者不链接电源板的时候，开机后不久，出错，程序退出，日志是：
+ [v1.2.10] [INFO] network.py:1078 - [NET] TCP主线程启动
+ [v1.2.10] [INFO] network.py:406 - [NET] WiFi不可用或无法连接服务器，使用4G网络
+ [v1.2.10] [INFO] network.py:475 - 连接到服务器,使用4G...
+ [v1.2.10] [INFO] network.py:527 - [4G-TCP] AT+MIPCLOSE=2 response:
+ OK
+ +MIPCLOSE: 2
+ -- [E] read failed
+ Trigger signal, code:SIGSEGV(11)!
+ maix multi-media driver released.
+ ISP Vipipe(0) Free pa(0x8a52c000) va(0x0x3fbeb5e000)
+ program exit failed. exit code: 1. 
+
+    解决方案：
+    从日志看，就是开始发送登录信息之后就崩溃了。出发了底层的read failed。经过排查，是一定要插上电源板的数据连线，以及电源板要插上电池。这个应该是登录时需要读电源电压数据。后面我们已经优化了日志，而且增加了对ina226的试探，但发现ina226不存在的时候，就直接返回电压和电流为0.0。而且，一定要注意，在新配套的电源板和核心板上面，才能正常读到电流和电压。
+
+3. a）问题描述：202609 批次的拓展版，有一块maixcam的蓝灯常亮，询问maixcam的人，他们觉得应该是卡没有插好。但是拓展版上的激光口挡住了数据卡的出口，
+    没法拔出检查，
+    解决方案：需要做拓展版的公司（深链鑫创）在做好板子之后，确定系统能正常启动
+
+    b）问题描述：2022609 批次的拓展板，有一次maixcam的蓝灯亮的时候很长，不会闪烁，后面把sd卡插进去一点，又恢复正常了，初步怀疑是射箭时没有缓冲，
+        导致了sd 卡被撞松了
+
+4. 问题描述：4G模块不可用，模块的绿灯没有闪亮
+    解决方案：有这样的一种情况，就是4G模块的天线，触碰到了旁边的电容，导致短路，所以模块启动失败。需要保证电容和天线的金属头不会触碰
+5. 
+    

design_doc/solution_record.md

@@ -0,0 +1,276 @@
+1.  4G OTA 下载的时候，为什么使用十六进制下载，读取 URC 事件？
+    因为使用二进制下载的时候，经常会出现错误，并且会失败？然后最稳定传输的办法，是每次传输的时候，是分块，而且每次分块都要“删/建”http实例。推测原因是因为我们现在是直接传输文件的源代码，代码中含有了一些字符串可能和 AT指令重复，导致了 AT 模块在解释的时候出错。而使用 16 进制的方式，可以避免这个问题。因为十六进制直接把数据先转成了字符串，然后在设备端再把字符串转成数据，这样就不可能出现 AT的指令，从而减少了麻烦。
+2.  4G OTA 下载的时候，为什么不用 AT 模块里 HTTPDLFILE 的指令？
+    因为在测试中发现，使用 HTTPDLFILE，其实是下载到了 4G 模块内部，需要重新从模块内部转到存储卡，而且 4G 模块的存储较小，大概只有 40k，所以还需要分块来下载和转存，比较麻烦，于是最终使用了使用读取串口事件的模式。
+3.  4G OTA 下载的时候，为什么不用 AT 模块里 HTTPREAD 的指令？
+    因为之前测试发现，READ模式其实是需要多步：
+    3.1. AT+MHTTPCREATE
+    3.2. AT+MHTTPCFG
+    3.3. AT+MHTTPREQUEST
+    3.4. AT+MHTTPREAD
+    它其实也是把数据下载到 4g 模块的缓存里，然后再从缓存里读取出来。所以也是比较繁琐的，还不如 HTTPDLFILE 简单。
+4.  WiFi OTA 流程（ota_manager.handle_wifi_and_update()）
+    * 解析 ota_url 得到 host:port
+    * 调用 network_manager.connect_wifi(ssid, password, verify_host=host, verify_port=port, persist=True)
+    * 只有“能连上 WiFi 且能访问 OTA host:port”才会把新凭证保留在 /boot
+    * 连接成功后开始下载 OTA 文件（download_file()）
+    * 下载成功则 apply_ota_and_reboot()
+5.  TCP 通信
+    1) 平时 TCP 通信主流程（network_manager.tcp_main()）
+        外层无限循环：一直尝试保持与服务器的 TCP 会话。
+        每轮开始：
+            如果 OTA 正在进行：暂停（避免抢占资源/串口）。
+            connect_server()：建立 TCP 连接（自动选 WiFi 或 4G）。
+            发送“登录包”（msg_type=1），等待服务器返回“登录成功”。
+        登录成功后进入内层循环：
+            接收数据：
+                WiFi：非阻塞 recv()；没数据返回 b""；有数据进入缓冲区拼包解析。
+                4G：从 ATClient 的队列 pop_tcp_payload() 取数据。
+            处理命令/ACK：
+                登录响应、心跳 ACK、OTA 命令、关机命令、日志上传命令等。
+            发送业务队列：
+                从高优/普通队列取 1 条，发送失败会放回队首，并断线重连（不再丢消息）。
+            发送心跳：
+                按 HEARTBEAT_INTERVAL 发心跳包。
+                心跳失败会计数（当前为连续失败到阈值才重连）。
+        任何发送/接收致命失败：
+    关闭 socket/断开连接 → 跳出内层循环 → 外层等待一会儿后重新 connect_server() → 重新登录。
+6. “WiFi 连接/验证”
+    TCP 连接建立与网络选择（connect_server() / select_network()）
+    * select_network()：WiFi 优先，但要求：
+        is_wifi_connected() 为 True（系统层面有 WiFi IP 或 Maix WLAN connected）
+        且能连到 TCP 服务器 SERVER_IP:SERVER_PORT
+        否则回退到 4G
+    * connect_server()：
+        若已有连接：WiFi 会做 _check_wifi_connection() 轻量检查；4G 直接认为 OK（由 AT 层维护）。
+        否则按网络类型走：
+            WiFi：创建 socket → connect → setblocking(False)（接收用非阻塞）
+            4G：AT+MIPOPEN 建链
+    WiFi 链接（connect_wifi()）
+    当前 connect_wifi() 的关键特点是：必须让 /etc/init.d/S30wifi restart 真正用新 SSID 去连，所以会临时写 /boot/wifi.ssid 和 /boot/wifi.pass，失败自动回滚。
+    流程是：
+        (1) 备份旧配置
+            * /boot/wifi.ssid、/boot/wifi.pass
+            * /etc/wpa_supplicant.conf（尽量备份）
+        (2) 写入新凭证
+            * 把新 ssid/pass 写到 /boot/*
+            -（同时尽量写 /etc/wpa_supplicant.conf，但不强依赖）
+        (3) 重启 WiFi 服务：/etc/init.d/S30wifi restart
+        (4) 等待获取 IP（默认 20 秒，可调）
+        (5) 验证可用性，连到 verify_host:verify_port
+        (6) 成功
+            * persist=True：保留 /boot/*（持久化）
+            * persist=False：回滚 /boot/* 到旧值（不重启，当前连接仍可继续）
+        (7) 失败
+            * 回滚 /boot/* + 回滚 /etc/wpa_supplicant.conf（如果有备份）
+            * 再 S30wifi restart 恢复旧网络
+            * 返回错误
+
+7. 日志上传（inner_cmd == 43），当前只支持 wifi 上传日志
+    命令带 ssid/password/url 时：
+        * 若 WiFi 未连接：先 connect_wifi(..., verify_host=upload_host, verify_port=upload_port, persist=True)
+    上传内容：
+        * sync # 把日志从内存同步到文件
+        * 快照 app.log* 到 /tmp staging
+        * 打包成 tar.gz（默认）或 zip
+        * 以 multipart/form-data 的 file 字段 POST 到 url
+
+8. 自动关机：
+    hardware中设定了开停表，然后再增加了获取idle的时间。
+    自动关机的时机： 超过配置的idle时长，
+    禁止自动关机的情况：1.校准中，2.OTA中
+    重启计时的时机：1.校准完成，2.命令触发射箭，3.真实触发射箭，4.初始化完成
+9. Wifi网络监控：
+有两次发现wifi网络下，有些消息发送很慢，但具体是什么缘故还不清楚，现在增加了wifi网络下的检测，并一旦发现wifi的网络质量差，就会切换到4G。
+WiFi 连接成功
+    ↓
+启动后台监测线程
+    ↓
+每 5 秒循环：
+    测量 RTT (1 样本，600ms timeout)
+    获取 RSSI
+    更新缓存
+    判断是否差：
+        - RTT >= 600ms → 差
+        - RTT >= 350ms 且 RSSI <= -80dBm → 差
+    ↓
+如果质量差：
+    快速重试2次，如果其中任意一次网络恢复了，继续使用wifi。否则，
+    调用 _switch_to_4g_due_to_poor_wifi()
+    关闭 WiFi socket
+    重置连接状态
+    尝试切换到 4G
+    ↓
+上层检测到连接断开：
+    重新 connect_server() → 自动选择 4G
+
+10. 现在使用的相机，其实是支持更大的分辨率的，比如说1920*1280，但是由于我们的图像处理，拍照处理之后很容易触发OOM。
+
+11. 环数计算流程：
+现在设备侧的目标是：算出箭点相对靶心的偏移(dx,dy)，单位是物理厘米（cm），然后把它作为 x,y 上报给后端；后端再去算环。
+设备侧本身不直接算环数，它算的是偏移与距离，并上报。
+
+算法流程（一次射箭从触发到上报）
+1) 触发后取一帧图
+    在 process_shot() 里读取相机帧并调用 analyze_shot(frame)
+2) 确定激光点（laser_point） 
+
+    analyze_shot() 第一步先确定激光点 (x,y)（像素坐标）：
+
+   硬编码：config.HARDCODE_LASER_POINT=True → 用 laser_manager.laser_point
+   已校准：laser_manager.has_calibrated_point() → 用校准值
+   动态模式：先 detect_circle_v3(frame, None) 粗估距离，再根据距离反推激光点
+   代码在：
+
+   if config.HARDCODE_LASER_POINT:
+       ...
+   elif laser_manager.has_calibrated_point():
+       ...
+   else:
+       _, _, _, _, best_radius1_temp, _ = detect_circle_v3(frame, None)
+       distance_m_first = estimate_distance(best_radius1_temp) ...
+       laser_point = laser_manager.calculate_laser_point_from_distance(distance_m_first)
+3) 优先走三角形路径（成功就直接用于上报 x/y）
+如果 config.USE_TRIANGLE_OFFSET=True，先尝试识别靶面四角三角形标记：
+
+if getattr(config, "USE_TRIANGLE_OFFSET", False):
+    K, dist_coef, pos = _get_triangle_calib()
+    img_rgb = image.image2cv(frame, False, False)
+    tri = try_triangle_scoring(img_rgb, (x, y), pos, K, dist_coef, ...)
+    if tri.get("ok"):
+        return {... "dx": tri["dx_cm"], "dy": tri["dy_cm"], "distance_m": tri.get("distance_m"), ...}
+这一步里 try_triangle_scoring() 做了两件事（都在 triangle_target.py）：
+
+单应性（homography）：把激光点从图像坐标映射到靶面坐标系，得到(dx,dy)（cm）
+PnP：用识别到的角点与相机标定，估算 相机到靶的距离 distance_m
+关键代码：
+
+ok_h, tx, ty, _H = homography_calibration(...)
+out["dx_cm"] = tx
+out["dy_cm"] = -ty
+out["distance_m"] = dist_m
+out["distance_method"] = "pnp_triangle"
+注意：这里 dy_cm 取了负号，是为了和现网约定一致（laser_manager.compute_laser_position 的坐标方向）。
+
+4) 三角形失败 → 回退圆形/椭圆靶心检测（兜底）
+如果三角形不可用或识别失败，就走传统靶心检测：
+
+detect_circle_v3(frame, laser_point) 找黄心/红心、半径、椭圆参数
+用 laser_manager.compute_laser_position() 把像素偏移换算成厘米偏移(dx,dy)
+在 shoot_manager.py：
+
+result_img, center, radius, method, best_radius1, ellipse_params = detect_circle_v3(frame, laser_point)
+if center and radius:
+    dx, dy = laser_manager.compute_laser_position(center, (x, y), radius, method)
+    distance_m = estimate_distance(best_radius1) ...
+在 laser_manager.compute_laser_position()（核心换算逻辑）：
+
+r = radius * 5
+target_x = (lx-cx)/r*100
+target_y = (ly-cy)/r*100
+return (target_x, -target_y)
+这里 (像素差)/(radius*5)*100 是你们旧约定下的“像素→厘米”比例模型（并且 y 方向同样取负号）。
+
+5) 上报数据：把(dx,dy) 作为 x/y 发给后端
+最终上报发生在 process_shot()，直接把 dx,dy 填到 inner_data["x"],["y"]：
+
+srv_x = round(float(dx), 4) if dx is not None else 200.0
+srv_y = round(float(dy), 4) if dy is not None else 200.0
+inner_data = {
+    "x": srv_x,
+    "y": srv_y,
+    "d": round((distance_m or 0.0) * 100),
+    "m": method if method else "no_target",
+    "offset_method": offset_method,
+    "distance_method": distance_method,
+    ...
+}
+network_manager.safe_enqueue(...)
+x,y：物理厘米（cm）
+d：相机到靶距离（m→cm，乘 100；三角形成功时来自 PnP）
+m/offset_method/distance_method：标记本次用的算法路径（triangle / yellow / pnp 等）
+后端收到 x,y 后，再用你之前给的 Go 公式 CalculateRingNumber(x,y,tenRingRadius) 计算环数。
+
+你现在的“环数计算”实际依赖关系
+最好路径（快+稳）：三角形 → dx,dy（单应性） + distance_m（PnP）
+兜底路径：圆/椭圆靶心 → dx,dy（基于黄心半径比例/透视校正） + distance_m（黄心半径估距）
+
+12. 4g模块上传文件：
+
+Upload images from MaixCam to Qiniu cloud via ML307R 4G module's AT commands. The HTTP body requires multipart/form-data with real CR/LF bytes (0x0D 0x0A) in boundaries.
+Methods Tried
+#	Method	AT Commands	Result	Root Cause
+1	Raw binary, no encoding	MHTTPCONTENT with raw bytes + length param	ERROR at first chunk	CR/LF in binary data terminates AT command parser
+2	Encoding mode 2 (escape)	MHTTPCFG="encoding",0,2 + \r\n escapes	Server 400 Bad Request	Module sends literal text \r\n to server, NOT actual 0x0D 0x0A bytes. Multipart body is garbled
+3	Encoding mode 1 (hex)	MHTTPCFG="encoding",0,1 + hex-encoded data	CME ERROR: 650/50	Firmware doesn't properly support hex mode for MHTTPCONTENT
+4	No chunked mode	Skip MHTTPCFG="chunked"	CME ERROR: 65	Module requires chunked mode to accept MHTTPCONTENT at all
+5	Single large MHTTPCONTENT	All data in one command (2793 bytes)	+MHTTPURC: "err",0,5 (timeout)	Possible buffer limit; module hangs then times out
+6	Per-chunk HTTP instance (OTA style)	CREATE→POST→DELETE per chunk	Not feasible	Each instance = separate HTTP request; Qiniu needs complete body in single POST
+Conclusion: AT HTTP layer (MHTTPCONTENT) is fundamentally broken for binary uploads.
+The Solution: Raw TCP Socket (MIPOPEN + MIPSEND)
+Bypass the AT HTTP layer entirely. Open a raw TCP connection and send a hand-crafted HTTP POST:
+plaintext
+AT+MIPCLOSE=3                                    // Clean up old socket
+AT+MIPOPEN=3,"TCP","upload.qiniup.com",80        // Raw TCP connection
+AT+MIPSEND=3,1024  →  ">"  →  [raw bytes]  →  OK  // Binary-safe!
+AT+MIPSEND=3,1024  →  ">"  →  [raw bytes]  →  OK
+AT+MIPSEND=3,766   →  ">"  →  [raw bytes]  →  OK
+// Response: +MIPURC: "rtcp",3,<len>,HTTP/1.1 200 OK...
+AT+MIPCLOSE=3
+Why it works:
+MIPSEND enters prompt mode (>) — after the >, the AT parser treats ALL bytes as data, including CR/LF
+We construct the complete HTTP request ourselves (headers + Content-Length + multipart body) with real CRLF bytes
+
+Key bug found during integration: _send_chunk() wrapped calls in self.at._cmd_lock, but self.at.send() also acquires the same lock internally — threading.Lock() is not reentrant, causing deadlock. Fixed by removing the outer lock (the network_manager.get_uart_lock() already provides thread safety).Trade-off: UART is locked during the entire upload, so heartbeats pause. For small JPEG files (~2-80KB), this is 5-20 seconds — acceptable if server heartbeat timeout is generous
+
+
+13. 算环数算法1：「黄心 + 红心」椭圆/圆：主要在 vision.py 的 detect_circle_v3() 里完成：颜色先用 HSV 做掩码，再在轮廓上做面积、圆度筛选，黄圈用椭圆拟合，红圈预先筛成候选，最后用几何关系配对。
+
+    1. 黄色怎么判、范围是什么？
+    图像先转 HSV（cv2.COLOR_RGB2HSV，注意输入是 RGB）。
+    饱和度 S 整体乘 1.1 并限制在 0–255（让黄色更「显」一点）。
+    黄色 inRange（OpenCV HSV，H 多为 0–179）：
+    通道	下限	上限
+    H       7       32
+    S       80      255
+    V       0       255
+    在黄掩码上找轮廓后，还要满足：面积 > 50，圆度 > 0.7（circularity = 4π·面积/周长²），且点数 ≥5 才 fitEllipse 当黄心椭圆。
+
+    2. 红色怎么判、范围是什么？
+    红色在 HSV 里跨 0°，所以用 两段 H 做并集：
+    两段分别是：
+    H 0–10，S 80–255，V 0–255
+    H 170–180，S 80–255，V 0–255
+    红轮廓候选：面积 > 50，圆度 > 0.6（比黄略松），再拟合椭圆或最小外接圆得到圆心和半径。
+
+    3. 「黄心」和「红心」怎样算一对？（几何范围）
+    对每个黄圈，在红色候选里找第一个满足：
+
+    两圆心距离 dist_centers < yellow_radius * 1.5
+    红半径 red_radius > yellow_radius * 0.8（红在外圈、略大）
+                dist_centers = math.hypot(ddx, ddy)
+                if dist_centers < yellow_radius * 1.5 and rc["radius"] > yellow_radius * 0.8:
+    小结：黄色 = HSV H∈[7,32]、S≥80（且 S 放大 1.1）+ 形态学闭运算 + 面积/圆度；红色 = 两段 H（0–10 与 170–180）、S≥80 + 闭运算 + 面积/圆度；配对用 同心/包含 的距离与半径比例阈值。若你还关心 laser_manager.py 里「激光红点」的另一套阈值（LASER_*），那是另一条链路，和靶心黄/红 HSV 可以分开看。
+
+14. 算环数算法2：
+    使用单应性矩阵计算：镜头中心点（照片中心像素）到虚拟平面的转换。它不需要知道相机在 3D 空间中的具体位置，直接通过单应性矩阵 H的逆运算，将 2D 像素“翻译”成虚拟平面上的 2D 坐标。
+
+    一、转换的本质：2D 到 2D 的“查字典”
+    单应性变换（Homography）是平面到平面的映射。它不处理 3D 空间中的“投影线”，而是直接建立图像像素 (u,v)​ 与虚拟平面坐标 (x,y)​ 的一一对应关系。
+    你可以把单应性矩阵 H想象成一本“翻译字典”：
+    正变换 H：已知靶纸上的真实位置 (x,y)，查字典得到它在照片上哪个像素 (u,v)。
+    逆变换 H−1：已知照片上的像素 (u,v)（如镜头中心点），查字典反推它在靶纸上的真实位置 (x,y)。
+    这个“虚拟平面”就是你的靶纸平面（Z=0 的世界坐标系）。算法没有在物理上移动任何点，只是在做坐标系的换算。
+
+    二、详细步骤：镜头中心点如何“落地”
+
+    相机分辨率是 640x480，镜头中心点（光轴与图像的交点）通常是 (u0,v0)=(320,240)。
+    1. 输入：镜头中心点（像素）
+    2. 核心运算：乘以逆矩阵
+    通过 4 个黑色三角形的角点（已知真实坐标）计算出了单应性矩阵 H。现在使用它的逆矩阵 H−1
+    3. 输出：虚拟平面上的落点（物理坐标）
+    计算后，你会得到：(xhit,yhit)
+    这就是镜头中心点对应的靶纸上的真实位置（单位：毫米）。
+    4. 计算环数
+    由于虚拟平面原点 (0,0)就是靶纸圆心，直接计算欧氏距离。​
+    这个 d就是箭着点偏离圆心的真实物理距离，直接用于环数判定。

design_doc/todo.md

@@ -0,0 +1,25 @@
+你现在要防的是“别人拿到设备/拿到代码包后，能伪造请求、刷接口、下发恶意 OTA、甚至劫持通信”。单靠隐藏 Python 源码只能提高门槛，真正的安全要靠协议和密钥设计。结合你仓库里实际内容，建议你重点隐藏/整改这些点（按风险排序）。
+
+
+1.4 OTA 下发“url”如果缺少强校验，就是远程代码执行入口
+你 OTA 逻辑里从服务器指令拿到 url 就去下载并替换文件/重启（这是正常 OTA），但安全性取决于：
+是否只允许白名单域名/路径
+是否强制 https 并校验服务器证书
+是否对 OTA 包做签名校验（最关键）
+你这里能看到固定域名 static.shelingxingqiu.com 的特殊处理（ota_manager.py 里还在纠结 http/https），这块一定要“服务端签名 + 设备端验签”，否则隐藏源码也没用。
+
+2. 建议隐藏（中风险，但很容易被人利用）
+2.1 所有服务器地址/端口/API 路径（可被用于扫描、压测、撞库、协议逆向）
+这些在 config.py 是明文：
+SERVER_IP = "stcp.shelingxingqiu.com"SERVER_PORT = 50005HTTP_URL = "http://ws.shelingxingqiu.com"HTTP_API_PATH = "/home/shoot/device_fire/arrow/fire"
+注意：即使你把它们藏进 .so，攻击者仍可能通过抓包/观察 DNS/SNI/流量拿到域名或 IP，所以“隐藏”只能降低静态分析风险，不能替代鉴权/签名。
+
+
+
+3. 最有效的“防黑”措施（比隐藏更关键）
+
+所有上报/控制命令加签名 + nonce/timestamp + 服务端防重放（别人抓到一次包也不能复用）
+OTA 包必须做签名校验（设备端内置公钥，下载后验签通过才应用）
+
+如果你告诉我：你们服务端目前能不能改协议（例如新增签名字段、下发 challenge、做 OTA 签名），我可以按“最小改动但提升最大安全”的顺序，帮你规划一套从现状平滑升级的方案。
+

hardware.py

@@ -0,0 +1,133 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+硬件管理器模块
+提供硬件对象的统一管理和访问
+"""
+from maix import time
+import config
+from at_client import ATClient
+
+
+class HardwareManager:
+    """硬件管理器（单例）"""
+    _instance = None
+    
+    def __new__(cls):
+        if cls._instance is None:
+            cls._instance = super(HardwareManager, cls).__new__(cls)
+            cls._instance._initialized = False
+        return cls._instance
+    
+    def __init__(self):
+        if self._initialized:
+            return
+        
+        # 私有硬件对象
+        self._uart4g = None              # 4G模块UART
+        self._bus = None                 # I2C总线
+        self._adc_obj = None             # ADC对象
+        self._at_client = None            # AT客户端
+
+        self._last_active_time = 0       # 用于记录用户的最后一次活跃的时间
+        self._stop_timer = False         # 用于停止定时器的标志
+
+        self._initialized = True
+
+
+    
+    # ==================== 硬件访问（只读属性）====================
+    
+    @property
+    def uart4g(self):
+        """4G模块UART（只读）"""
+        return self._uart4g
+    
+    @property
+    def bus(self):
+        """I2C总线（只读）"""
+        return self._bus
+    
+    @property
+    def adc_obj(self):
+        """ADC对象（只读）"""
+        return self._adc_obj
+    
+    @property
+    def at_client(self):
+        """AT客户端（只读）"""
+        return self._at_client
+    
+    # ==================== 初始化方法 ====================
+    
+    def init_uart4g(self, device=None, baudrate=None):
+        """初始化4G模块UART"""
+        from maix import uart
+        if device is None:
+            device = config.UART4G_DEVICE
+        if baudrate is None:
+            baudrate = config.UART4G_BAUDRATE
+        self._uart4g = uart.UART(device, baudrate)
+        return self._uart4g
+    
+    def init_bus(self, bus_num=None):
+        """初始化I2C总线"""
+        from maix import i2c
+        if bus_num is None:
+            bus_num = config.I2C_BUS_NUM
+        self._bus = i2c.I2C(bus_num, i2c.Mode.MASTER)
+        return self._bus
+    
+    def init_adc(self, channel=None, res_bit=None):
+        """初始化ADC"""
+        from maix.peripheral import adc
+        if channel is None:
+            channel = config.ADC_CHANNEL
+        if res_bit is None:
+            res_bit = adc.RES_BIT_12
+        self._adc_obj = adc.ADC(channel, res_bit)
+        return self._adc_obj
+    
+    def init_at_client(self, uart_obj=None):
+        """初始化AT客户端"""
+        if uart_obj is None:
+            if self._uart4g is None:
+                raise ValueError("uart4g must be initialized before at_client")
+            uart_obj = self._uart4g
+        self._at_client = ATClient(uart_obj)
+        self._at_client.start()
+        return self._at_client
+
+    def power_off(self):
+        """关闭电源板"""
+        try:
+            # 物理引脚是 A24，对应 GPIO 功能是 GPIOA24
+            # 注意：这里需要先在 config.PIN_MAPPINGS 中配置好 "A24": "GPIOA24"
+            from maix import gpio
+            # 输出高电平关闭
+            gpio.GPIO("GPIOA24", gpio.Mode.OUT).value(1)
+        except Exception as e:
+            print(f"关机失败: {e}")
+
+    def start_idle_timer(self):
+        self._stop_timer = False
+        self._last_active_time = time.time()
+
+    def stop_idle_timer(self):
+        self._stop_timer = True
+
+    def get_idle_time_in_sec(self):
+        if self._stop_timer:
+            return 0
+        diff = time.time() - self._last_active_time
+        if diff < 0:
+            # 时间可能被重置了，重新计时
+            self._last_active_time = time.time()
+            return 0
+        return diff
+
+
+# 创建全局单例实例
+hardware_manager = HardwareManager()
+
+

keygen.py

@@ -0,0 +1,52 @@
+import os
+
+
+def generate_key_pair():
+    """
+    生成一对新的密钥a和b，使得a XOR b等于原始key
+    :return: (a, b, key) 元组，每个元素都是32字节的字节数组
+    """
+    # 原始key值
+    key = bytes([
+        0x5d, 0xf9, 0xef, 0xc4, 0x5d, 0xcc, 0xc7, 0x8d, 0xc9, 0x86, 0x34, 0x11, 0x6f, 0xb4, 0xcf, 0x75,
+        0xbf, 0x24, 0x47, 0x9d, 0xd6, 0x5d, 0x83, 0x4b, 0xa6, 0xc0, 0xde, 0x27, 0x91, 0x92, 0xb1, 0x63
+    ])
+
+    # 随机生成a
+    a = os.urandom(32)
+
+    # 计算b = key XOR a
+    b = bytes([key[i] ^ a[i] for i in range(32)])
+
+    return a, b, key
+
+
+def format_hex_array(data):
+    """
+    将字节数组格式化为C++风格的十六进制数组
+    :param data: 字节数组
+    :return: 格式化后的字符串
+    """
+    return "{" + ",".join([f"0x{b:02x}" for b in data]) + "}"
+
+
+def generate_new_key_pair():
+    """
+    生成新的密钥对并打印出来
+    """
+    a, b, key = generate_key_pair()
+
+    print("原始key:")
+    print(format_hex_array(key))
+    print("\n新的密钥对:")
+    print("a =", format_hex_array(a))
+    print("b =", format_hex_array(b))
+
+    # 验证a XOR b是否等于key
+    verify_key = bytes([a[i] ^ b[i] for i in range(32)])
+    assert verify_key == key, "验证失败：a XOR b 不等于 key"
+    print("\n验证成功：a XOR b 等于 key")
+
+
+if __name__ == "__main__":
+    generate_new_key_pair()

laser.py

@@ -1,826 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-激光射击系统主程序（激光测距版）
-功能：目标检测、激光校准、4G TCP 通信、OTA 升级、M01 激光测距、INA226 电量监测
-平台：MaixPy (Sipeed MAIX)
-作者：ZZH
-最后更新：2025-11-21
-"""
-
-from maix import camera, display, image, app, time, key, uart, pinmap, i2c, network, err
-import cv2
-import numpy as np
-import json
-import struct
-import re
-from maix.peripheral import adc
-import _thread
-import os
-import requests
-import socket
-import binascii
-
-# ==============================
-# 全局配置
-# ==============================
-# OTA 升级地址（建议后续改为动态下发）
-url = "https://static.shelingxingqiu.com/shoot/202511031031/main.py"
-local_filename = "/maixapp/apps/t11/main.py"
-
-DEVICE_ID = None
-PASSWORD = None
-SERVER_IP = "www.shelingxingqiu.com"
-SERVER_PORT = 50005
-HEARTBEAT_INTERVAL = 2  # 心跳间隔（秒）
-
-CONFIG_FILE = "/root/laser_config.json"
-DEFAULT_POINT = (640, 480)  # 图像中心点
-laser_point = DEFAULT_POINT
-
-# HTTP API（当前未使用，保留备用）
-URL = "http://ws.shelingxingqiu.com"
-API_PATH = "/home/shoot/device_fire/arrow/fire"
-
-# UART 设备初始化
-uart4g = uart.UART("/dev/ttyS2", 115200)        # 4G 模块（TCP 透传）
-distance_serial = uart.UART("/dev/ttyS1", 9600)  # M01 激光测距模块
-
-# 消息类型常量
-MSG_TYPE_LOGIN_REQ = 1   # 登录请求
-MSG_TYPE_STATUS = 2      # 状态上报
-MSG_TYPE_HEARTBEAT = 4   # 心跳包
-# 引脚功能映射
-pinmap.set_pin_function("A18", "UART1_RX")
-pinmap.set_pin_function("A19", "UART1_TX")
-pinmap.set_pin_function("A29", "UART2_RX")
-pinmap.set_pin_function("A28", "UART2_TX")
-pinmap.set_pin_function("P18", "I2C1_SCL")
-pinmap.set_pin_function("P21", "I2C1_SDA")
-# pinmap.set_pin_function("A15", "I2C5_SCL")
-# pinmap.set_pin_function("A27", "I2C5_SDA")#ota升级要修改的
-# ADC 触发阈值（用于检测扳机/激光触发）
-ADC_TRIGGER_THRESHOLD = 3000
-ADC_LASER_THRESHOLD = 3000
-# 显示参数
-color = image.Color(255, 100, 0)  # 橙色十字线
-thickness = 1
-length = 2
-
-# ADC 扳机触发阈值（0~4095）
-ADC_TRIGGER_THRESHOLD = 3000
-
-# I2C 电源监测（INA226）
-adc_obj = adc.ADC(0, adc.RES_BIT_12)
-bus = i2c.I2C(1, i2c.Mode.MASTER)
-# bus = i2c.I2C(5, i2c.Mode.MASTER)#ota升级总线
-INA226_ADDR = 0x40
-REG_CONFIGURATION = 0x00
-REG_BUS_VOLTAGE = 0x02
-REG_CALIBRATION = 0x05
-CALIBRATION_VALUE = 0x1400
-
-# M01 激光模块指令
-MODULE_ADDR = 0x00 
-LASER_ON_CMD = bytes([0xAA, MODULE_ADDR, 0x01, 0xBE, 0x00, 0x01, 0x00, 0x01, 0xC1])
-LASER_OFF_CMD = bytes([0xAA, MODULE_ADDR, 0x01, 0xBE, 0x00, 0x01, 0x00, 0x00, 0xC0])
-DISTANCE_QUERY_CMD = bytes([0xAA, MODULE_ADDR, 0x00, 0x20, 0x00, 0x01, 0x00, 0x00, 0x21])
-DISTANCE_RESPONSE_LEN = 13
-
-# TCP / 线程状态
-tcp_connected = False
-send_queue = []
-update_thread_started = False  # 防止重复 OTA
-send_queue_lock = _thread.allocate_lock()
-laser_calibration_data_lock = _thread.allocate_lock()
-laser_calibration_active = False
-laser_calibration_result = None
-
-
-# ==============================
-# 网络工具函数
-# ==============================
-
-def is_server_reachable(host, port=80, timeout=5):
-    """检查能否连接到指定主机和端口（用于 OTA 前网络检测）"""
-    try:
-        addr_info = socket.getaddrinfo(host, port)[0]
-        s = socket.socket(addr_info[0], addr_info[1], addr_info[2])
-        s.settimeout(timeout)
-        s.connect(addr_info[-1])
-        s.close()
-        return True
-    except Exception as e:
-        print(f"[NET] 无法连接 {host}:{port} - {e}")
-        return False
-
-
-def download_file(url, filename):
-    """
-    从指定 URL 下载文件并保存为 UTF-8 文本。
-    注意：此操作会覆盖本地 main.py！
-    """
-    try:
-        print(f"[OTA] 正在从 {url} 下载文件...")
-        response = requests.get(url, timeout=10)  # ⏱️ 防止卡死
-        response.raise_for_status()
-        response.encoding = 'utf-8'
-        with open(filename, 'w', encoding='utf-8') as file:
-            file.write(response.text)
-        return f"下载成功！文件已保存为: {filename}"
-    except requests.exceptions.RequestException as e:
-        return f"下载失败！网络请求错误: {e}"
-    except OSError as e:
-        return f"下载失败！文件写入错误: {e}"
-    except Exception as e:
-        return f"下载失败！发生未知错误: {e}"
-
-
-def connect_wifi(ssid, password):
-    """
-    连接 Wi-Fi 并持久化凭证到 /boot/ 目录，使设备重启后自动连接。
-    返回 (ip, error) 元组。
-    """
-    conf_path = "/etc/wpa_supplicant.conf"
-    ssid_file = "/boot/wifi.ssid"
-    pass_file = "/boot/wifi.pass"
-
-    try:
-        # 生成 wpa_supplicant 配置
-        net_conf = os.popen(f'wpa_passphrase "{ssid}" "{password}"').read()
-        if "network={" not in net_conf:
-            return None, "Failed to generate wpa config"
-
-        # 写入运行时配置
-        with open(conf_path, "w") as f:
-            f.write("ctrl_interface=/var/run/wpa_supplicant\n")
-            f.write("update_config=1\n\n")
-            f.write(net_conf)
-
-        # 持久化保存（供开机脚本读取）
-        with open(ssid_file, "w") as f:
-            f.write(ssid.strip())
-        with open(pass_file, "w") as f:
-            f.write(password.strip())
-
-        # 重启 Wi-Fi 服务
-        os.system("/etc/init.d/S30wifi restart")
-
-        # 等待获取 IP（最多 20 秒）
-        for _ in range(20):
-            ip = os.popen("ifconfig wlan0 2>/dev/null | grep 'inet ' | awk '{print $2}'").read().strip()
-            if ip:
-                return ip, None
-            time.sleep(1)
-
-        return None, "Timeout: No IP obtained"
-
-    except Exception as e:
-        return None, f"Exception: {str(e)}"
-
-def direct_ota_download():
-    """
-    直接执行 OTA 下载（假设已有网络）
-    用于 cmd=7 触发
-    """
-    global update_thread_started
-    try:
-        # 再次确认网络可达（可选但推荐）
-        from urllib.parse import urlparse
-        parsed_url = urlparse(url)
-        host = parsed_url.hostname
-        port = parsed_url.port or (443 if parsed_url.scheme == 'https' else 80)
-
-        if not is_server_reachable(host, port, timeout=8):
-            safe_enqueue({"result": "ota_failed", "reason": f"无法连接 {host}:{port}"}, MSG_TYPE_STATUS)
-            return
-
-        print(f"[OTA] 开始直接下载固件...")
-        result_msg = download_file(url, local_filename)
-        print(f"[OTA] {result_msg}")
-        safe_enqueue({"result": result_msg}, MSG_TYPE_STATUS)
-
-    except Exception as e:
-        error_msg = f"OTA 异常: {str(e)}"
-        print(error_msg)
-        safe_enqueue({"result": "ota_failed", "reason": error_msg}, MSG_TYPE_STATUS)
-    finally:
-        update_thread_started = False  # 允许下次 OTA
-
-
-def handle_wifi_and_update(ssid, password):
-    """
-    OTA 更新线程入口。
-    注意：必须在 finally 中重置 update_thread_started！
-    """
-    global update_thread_started
-    try:
-        ip, error = connect_wifi(ssid, password)
-        if error:
-            safe_enqueue({"result": "wifi_failed", "error": error}, MSG_TYPE_STATUS)
-            return
-
-        safe_enqueue({"result": "wifi_connected", "ip": ip}, MSG_TYPE_STATUS)
-
-        from urllib.parse import urlparse
-        parsed_url = urlparse(url)
-        host = parsed_url.hostname
-        port = parsed_url.port or (443 if parsed_url.scheme == 'https' else 80)
-
-        if not is_server_reachable(host, port, timeout=8):
-            err_msg = f"网络不通：无法连接 {host}:{port}"
-            safe_enqueue({"result": err_msg}, MSG_TYPE_STATUS)
-            return
-
-        print(f"[OTA] 已确认可访问 {host}:{port}，开始下载...")
-        try:
-            cs = download_file(url, local_filename)
-        except Exception as e:
-            cs = f"下载失败: {str(e)}"
-        print(cs)
-        safe_enqueue({"result": cs}, MSG_TYPE_STATUS)
-
-    finally:
-        # ✅ 关键修复：允许下次 OTA
-        update_thread_started = False
-        print("[UPDATE] OTA 线程执行完毕，标志已重置。")
-
-
-# ==============================
-# 工具函数
-# ==============================
-
-def read_device_id():
-    """从 /device_key 读取设备唯一 ID"""
-    try:
-        with open("/device_key", "r") as f:
-            device_id = f.read().strip()
-            if device_id:
-                print(f"[INFO] 从 /device_key 读取到 DEVICE_ID: {device_id}")
-                return device_id
-            else:
-                raise ValueError("文件为空")
-    except Exception as e:
-        print(f"[ERROR] 无法读取 /device_key: {e}")
-        return "DEFAULT_DEVICE_ID"
-
-
-def safe_enqueue(data_dict, msg_type=MSG_TYPE_STATUS):
-    """线程安全地将消息加入发送队列"""
-    global send_queue, send_queue_lock
-    with send_queue_lock:
-        send_queue.append((msg_type, data_dict))
-
-
-def at(cmd, wait="OK", timeout=2000):
-    """向 4G 模块发送 AT 指令并等待响应"""
-    if cmd:
-        uart4g.write((cmd + "\r\n").encode())
-    t0 = time.ticks_ms()
-    buf = b""
-    while time.ticks_ms() - t0 < timeout:
-        data = uart4g.read()
-        if data:
-            buf += data
-            if wait.encode() in buf:
-                return buf.decode(errors="ignore")
-    return buf.decode(errors="ignore")
-
-
-def make_packet(msg_type: int, body_dict: dict) -> bytes:
-    """构造二进制数据包：[body_len][msg_type][checksum][body]"""
-    body = json.dumps(body_dict, ensure_ascii=False).encode('utf-8')
-    body_len = len(body)
-    checksum = body_len + msg_type
-    header = struct.pack(">III", body_len, msg_type, checksum)
-    return header + body
-
-
-def parse_packet(data: bytes):
-    """解析二进制数据包"""
-    if len(data) < 12:
-        return None, None
-    body_len, msg_type, checksum = struct.unpack(">III", data[:12])
-    body = data[12:12 + body_len]
-    try:
-        # ✅ 显式指定 UTF-8 编码
-        return msg_type, json.loads(body.decode('utf-8'))
-    except Exception as e:
-        print(f"[ERROR] 解析包体失败: {e}")
-        return msg_type, {"raw": body.decode('utf-8', errors='ignore')}
-
-
-def tcp_send_raw(data: bytes, max_retries=2) -> bool:
-    """通过 4G 模块发送原始 TCP 数据（仅在 tcp_main 线程调用）"""
-    global tcp_connected
-    if not tcp_connected:
-        return False
-
-    for attempt in range(max_retries):
-        cmd = f'AT+MIPSEND=0,{len(data)}'
-        if ">" not in at(cmd, ">", 1500):
-            time.sleep_ms(100)
-            continue
-
-        time.sleep_ms(10)
-        full = data + b"\x1A"
-        try:
-            sent = uart4g.write(full)
-            if sent != len(full):
-                time.sleep_ms(100)
-                continue
-        except:
-            time.sleep_ms(100)
-            continue
-
-        if "OK" in at("", "OK", 1000):
-            return True
-        time.sleep_ms(100)
-
-    return False
-
-
-def load_laser_point():
-    """从配置文件加载激光点坐标"""
-    global laser_point
-    try:
-        if "laser_config.json" in os.listdir("/root"):
-            with open(CONFIG_FILE, "r") as f:
-                data = json.load(f)
-                if isinstance(data, list) and len(data) == 2:
-                    laser_point = (int(data[0]), int(data[1]))
-                    print(f"[INFO] 加载激光点: {laser_point}")
-                else:
-                    raise ValueError
-        else:
-            laser_point = DEFAULT_POINT
-    except:
-        laser_point = DEFAULT_POINT
-
-
-def save_laser_point(point):
-    """保存激光点坐标到文件"""
-    global laser_point
-    try:
-        with open(CONFIG_FILE, "w") as f:
-            json.dump([point[0], point[1]], f)
-        laser_point = point
-    except:
-        pass
-
-
-def turn_on_laser():
-    """发送激光开启指令"""
-    distance_serial.write(LASER_ON_CMD)
-    time.sleep_ms(10)
-    resp = distance_serial.read(20)
-    if resp:
-        if resp == LASER_ON_CMD:
-            print("✅ 激光指令已确认")
-    else:
-        print("🔇 无回包（正常或模块不支持）")
-    return resp
-
-
-# ==============================
-# M01 激光测距模块
-# ==============================
-
-def parse_bcd_distance(bcd_bytes: bytes) -> float:
-    """将 4 字节 BCD 码转换为距离（米）"""
-    if len(bcd_bytes) != 4:
-        return 0.0
-    try:
-        hex_string = binascii.hexlify(bcd_bytes).decode()
-        distance_int = int(hex_string)
-        return distance_int / 1000.0
-    except Exception as e:
-        print(f"[ERROR] BCD 解析失败: {e}")
-        return 0.0
-
-
-def read_distance_from_laser_sensor():
-    """发送测距指令并返回距离（米）"""
-    global distance_serial
-    try:
-        distance_serial.read()  # 清空缓冲区
-        distance_serial.write(DISTANCE_QUERY_CMD)
-        time.sleep_ms(500)
-        response = distance_serial.read(DISTANCE_RESPONSE_LEN)
-
-        if response and len(response) == DISTANCE_RESPONSE_LEN:
-            if response[3] != 0x20:
-                if response[0] == 0xEE:
-                    err_code = (response[7] << 8) | response[8]
-                    print(f"[LASER] 模块错误代码: {hex(err_code)}")
-                return 0.0
-
-            bcd_bytes = response[6:10]
-            distance_value_m = parse_bcd_distance(bcd_bytes)
-            signal_quality = (response[10] << 8) | response[11]
-            print(f"[LASER] 测距成功: {distance_value_m:.3f} m, 信号质量: {signal_quality}")
-            return distance_value_m
-
-        print(f"[LASER] 无效响应: {response.hex() if response else 'None'}")
-        return 0.0
-    except Exception as e:
-        print(f"[ERROR] 读取激光测距失败: {e}")
-        return 0.0
-
-
-# ==============================
-# 激光点校准
-# ==============================
-
-def find_red_laser(frame, threshold=150):
-    """在图像中查找最亮的红色点（简单 RGB 判定）"""
-    w, h = frame.width(), frame.height()
-    img_bytes = frame.to_bytes()
-    max_sum = 0
-    best_pos = None
-    for y in range(0, h, 2):
-        for x in range(0, w, 2):
-            idx = (y * w + x) * 3
-            r, g, b = img_bytes[idx], img_bytes[idx+1], img_bytes[idx+2]
-            if r > threshold and r > g * 2 and r > b * 2:
-                rgb_sum = r + g + b
-                if rgb_sum > max_sum:
-                    max_sum = rgb_sum
-                    best_pos = (x, y)
-    return best_pos
-
-
-def calibrate_laser_position():
-    """拍摄一帧并识别激光点位置"""
-    time.sleep_ms(80)
-    cam = camera.Camera(640, 480)
-    frame = cam.read()
-    pos = find_red_laser(frame)
-    if pos:
-        save_laser_point(pos)
-        return pos
-    return None
-
-
-# ==============================
-# 电量监测（INA226）
-# ==============================
-
-def write_register(reg, value):
-    data = [(value >> 8) & 0xFF, value & 0xFF]
-    bus.writeto_mem(INA226_ADDR, reg, bytes(data))
-
-
-def read_register(reg):
-    data = bus.readfrom_mem(INA226_ADDR, reg, 2)
-    return (data[0] << 8) | data[1]
-
-
-def init_ina226():
-    write_register(REG_CONFIGURATION, 0x4527)
-    write_register(REG_CALIBRATION, CALIBRATION_VALUE)
-
-
-def get_bus_voltage():
-    raw = read_register(REG_BUS_VOLTAGE)
-    return raw * 1.25 / 1000
-
-
-def voltage_to_percent(voltage):
-    points = [
-        (4.20, 100), (4.10, 95), (4.05, 85), (4.00, 75), (3.95, 65),
-        (3.90, 55), (3.85, 45), (3.80, 35), (3.75, 25), (3.70, 15),
-        (3.65, 5), (3.60, 0)
-    ]
-    if voltage >= points[0][0]: return 100
-    if voltage <= points[-1][0]: return 0
-    for i in range(len(points) - 1):
-        v1, p1 = points[i]; v2, p2 = points[i + 1]
-        if v2 <= voltage <= v1:
-            ratio = (voltage - v1) / (v2 - v1)
-            percent = p1 + (p2 - p1) * ratio
-            return max(0, min(100, int(round(percent))))
-    return 0
-
-
-# ==============================
-# 目标检测
-# ==============================
-
-def detect_circle(frame):
-    """检测靶心圆（清晰/模糊两种模式）"""
-    img_cv = image.image2cv(frame, False, False)
-    gray = cv2.cvtColor(img_cv, cv2.COLOR_BGR2GRAY)
-    blurred = cv2.GaussianBlur(gray, (5, 5), 0)
-    edged = cv2.Canny(blurred, 50, 150)
-    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
-    ceroded = cv2.erode(cv2.dilate(edged, kernel), kernel)
-
-    contours, _ = cv2.findContours(ceroded, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
-    best_center = best_radius = method = None
-
-    for cnt in contours:
-        area = cv2.contourArea(cnt)
-        perimeter = cv2.arcLength(cnt, True)
-        if perimeter < 100 or area < 100: continue
-        circularity = 4 * np.pi * area / (perimeter ** 2)
-        if circularity > 0.75 and len(cnt) >= 5:
-            center, axes, angle = cv2.fitEllipse(cnt)
-            radius = (axes[0] + axes[1]) / 4
-            best_center = (int(center[0]), int(center[1]))
-            best_radius = int(radius)
-            method = "清晰"
-            break
-
-    if not best_center:
-        hsv = cv2.cvtColor(img_cv, cv2.COLOR_BGR2HSV)
-        h, s, v = cv2.split(hsv)
-        s = np.clip(s * 2, 0, 255).astype(np.uint8)
-        hsv = cv2.merge((h, s, v))
-        lower_yellow = np.array([7, 80, 0])
-        upper_yellow = np.array([32, 255, 182])
-        mask = cv2.inRange(hsv, lower_yellow, upper_yellow)
-        kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
-        mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
-        mask = cv2.morphologyEx(mask, cv2.MORPH_DILATE, kernel)
-        contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-        if contours:
-            largest = max(contours, key=cv2.contourArea)
-            if cv2.contourArea(largest) > 50:
-                (x, y), radius = cv2.minEnclosingCircle(largest)
-                best_center = (int(x), int(y))
-                best_radius = int(radius)
-                method = "模糊"
-
-    result_img = image.cv2image(img_cv, False, False)
-    return result_img, best_center, best_radius, method, best_radius
-
-
-def compute_laser_position(circle_center, laser_point, radius, method):
-    """计算激光相对于靶心的偏差（单位：厘米）"""
-    if not all([circle_center, radius, method]):
-        return None, None
-    cx, cy = circle_center
-    lx, ly = laser_point
-    # 根据检测模式估算实际半径（单位：像素 → 厘米）
-    circle_r_cm = (radius / 4.0) * 20.0 if method == "模糊" else (68 / 16.0) * 20.0
-    dx = lx - cx
-    dy = ly - cy
-    scale = circle_r_cm / radius if radius != 0 else 1.0
-    return dx * scale, -dy * scale
-
-
-# ==============================
-# TCP 通信主线程
-# ==============================
-
-def connect_server():
-    """连接服务器（通过 4G 模块 AT 指令）"""
-    global tcp_connected
-    if tcp_connected:
-        return True
-    print("正在连接服务器...")
-    at("AT+MIPCLOSE=0", "OK", 1000)
-    res = at(f'AT+MIPOPEN=0,"TCP","{SERVER_IP}",{SERVER_PORT}', "+MIPOPEN", 8000)
-    if "+MIPOPEN: 0,0" in res:
-        tcp_connected = True
-        return True
-    return False
-
-
-def tcp_main():
-    """TCP 通信主循环（独立线程）"""
-    global tcp_connected, send_queue, laser_calibration_active, laser_calibration_result,update_thread_started
-
-    while not app.need_exit():
-        if not connect_server():
-            time.sleep_ms(5000)
-            continue
-
-        login_data = {"deviceId": DEVICE_ID, "password": PASSWORD}
-        if not tcp_send_raw(make_packet(MSG_TYPE_LOGIN_REQ, login_data)):
-            tcp_connected = False
-            time.sleep_ms(2000)
-            continue
-
-        print("➡️ 登录包已发送，等待确认...")
-        logged_in = False
-        last_heartbeat_ack_time = time.ticks_ms()
-        last_heartbeat_send_time = time.ticks_ms()
-        rx_buf = b""
-
-        while True:
-            data = uart4g.read()
-            if data:
-                rx_buf += data
-                while b'+MIPURC: "rtcp"' in rx_buf:
-                    try:
-                        match = re.search(b'\+MIPURC: "rtcp",0,(\d+),(.+)', rx_buf, re.DOTALL)
-                        if match:
-                            payload_len = int(match.group(1))
-                            payload = match.group(2)[:payload_len]
-                            msg_type, body = parse_packet(payload)
-
-                            if not logged_in and msg_type == MSG_TYPE_LOGIN_REQ:
-                                if body and body.get("cmd") == 1 and body.get("data") == "登录成功":
-                                    logged_in = True
-                                    last_heartbeat_ack_time = time.ticks_ms()
-                                    print("✅ 登录成功")
-                                else:
-                                    break
-
-                            elif logged_in and msg_type == MSG_TYPE_HEARTBEAT:
-                                last_heartbeat_ack_time = time.ticks_ms()
-                                print("✅ 收到心跳确认")
-
-                            elif logged_in and isinstance(body, dict):
-                                inner_data = body.get("data", {})
-                                if isinstance(inner_data, dict) and "cmd" in inner_data:
-                                    inner_cmd = inner_data["cmd"]
-                                    if inner_cmd == 2:
-                                        turn_on_laser()
-                                        time.sleep_ms(100)
-                                        laser_calibration_active = True
-                                        safe_enqueue({"result": "calibrating"}, MSG_TYPE_STATUS)
-                                    elif inner_cmd == 3:
-                                        distance_serial.write(LASER_OFF_CMD)
-                                        laser_calibration_active = False
-                                        safe_enqueue({"result": "laser_off"}, MSG_TYPE_STATUS)
-                                    elif inner_cmd == 4:
-                                        voltage = get_bus_voltage()
-                                        battery_percent = voltage_to_percent(voltage)
-                                        battery_data = {"battery": battery_percent, "voltage": round(voltage, 3)}
-                                        safe_enqueue(battery_data, MSG_TYPE_STATUS)
-                                    elif inner_cmd == 5:
-                                        ssid = inner_data.get("ssid")
-                                        password = inner_data.get("password")
-                                        if not ssid or not password:
-                                            safe_enqueue({"result": "missing_ssid_or_password"}, MSG_TYPE_STATUS)
-                                        else:
-                                            # global update_thread_started
-                                            if not update_thread_started:
-                                                update_thread_started = True
-                                                _thread.start_new_thread(handle_wifi_and_update, (ssid, password))
-                                            else:
-                                                safe_enqueue({"result": "update_already_started"}, MSG_TYPE_STATUS)
-                                    elif inner_cmd == 6:
-                                        try:
-                                            ip = os.popen("ifconfig wlan0 2>/dev/null | grep 'inet ' | awk '{print $2}'").read().strip()
-                                            ip = ip if ip else "no_ip"
-                                        except:
-                                            ip = "error_getting_ip"
-                                        safe_enqueue({"result": "current_ip", "ip": ip}, MSG_TYPE_STATUS)
-
-                                    elif inner_cmd == 7:
-                                        # global update_thread_started
-                                        if update_thread_started:
-                                            safe_enqueue({"result": "update_already_started"}, MSG_TYPE_STATUS)
-                                            continue
-
-                                        # 实时检查是否有 IP
-                                        try:
-                                            ip = os.popen("ifconfig wlan0 2>/dev/null | grep 'inet ' | awk '{print $2}'").read().strip()
-                                        except:
-                                            ip = None
-
-                                        if not ip:
-                                            safe_enqueue({"result": "ota_rejected", "reason": "no_wifi_ip"}, MSG_TYPE_STATUS)
-                                        else:
-                                            # 启动纯下载线程
-                                            update_thread_started = True
-                                            _thread.start_new_thread(direct_ota_download, ())
-                            rx_buf = rx_buf[match.end():]
-                        else:
-                            break
-                    except Exception as e:
-                        print(f"[ERROR] 解析/处理数据包失败: {e}")
-                        rx_buf = b""
-                        break
-
-            # 发送队列处理
-            msg_type = None
-            if logged_in:
-                with send_queue_lock:
-                    if send_queue:
-                        msg_type, data_dict = send_queue.pop(0)
-                if msg_type is not None:
-                    pkt = make_packet(msg_type, data_dict)
-                    if not tcp_send_raw(pkt):
-                        print("💔 发送失败，断开重连")
-                        break
-
-            # 校准结果上报
-            if logged_in:
-                x = y = None
-                with laser_calibration_data_lock:
-                    if laser_calibration_result is not None:
-                        x, y = laser_calibration_result
-                        laser_calibration_result = None
-                if x is not None:
-                    safe_enqueue({"result": "ok", "x": x, "y": y}, MSG_TYPE_STATUS)
-
-            # 心跳机制
-            current_time = time.ticks_ms()
-            if logged_in and current_time - last_heartbeat_send_time > HEARTBEAT_INTERVAL * 1000:
-                if not tcp_send_raw(make_packet(MSG_TYPE_HEARTBEAT, {"t": int(time.time())})):
-                    print("💔 心跳发送失败")
-                    break
-                last_heartbeat_send_time = current_time
-
-            if logged_in and current_time - last_heartbeat_ack_time > 6000:
-                print("⏰ 6秒无心跳ACK，重连")
-                break
-
-            time.sleep_ms(50)
-
-        tcp_connected = False
-        time.sleep_ms(2000)
-
-
-def laser_calibration_worker():
-    """后台激光校准线程"""
-    global laser_calibration_active, laser_calibration_result
-    while True:
-        if laser_calibration_active:
-            result = calibrate_laser_position()
-            if result and len(result) == 2:
-                with laser_calibration_data_lock:
-                    laser_calibration_result = result
-                    laser_calibration_active = False
-                print(f"✅ 后台校准成功: {result}")
-            else:
-                time.sleep_ms(80)
-        else:
-            time.sleep_ms(50)
-
-
-# ==============================
-# 主程序入口
-# ==============================
-
-def cmd_str():
-    global DEVICE_ID, PASSWORD
-    DEVICE_ID = read_device_id()
-    PASSWORD = DEVICE_ID + "."
-
-    photo_dir = "/root/phot"
-    if photo_dir not in os.listdir("/root"):
-        try:
-            os.mkdir(photo_dir)
-        except:
-            pass
-
-    init_ina226()
-    load_laser_point()
-
-    disp = display.Display()
-    cam = camera.Camera(640, 480)
-
-    _thread.start_new_thread(tcp_main, ())
-    _thread.start_new_thread(laser_calibration_worker, ())
-
-    print("系统准备完成...")
-
-    while not app.need_exit():
-        if adc_obj.read() > ADC_TRIGGER_THRESHOLD:
-            time.sleep_ms(60)
-            frame = cam.read()
-
-            x, y = laser_point
-            frame.draw_line(int(x - length), int(y), int(x + length), int(y), color, thickness)
-            frame.draw_line(int(x), int(y - length), int(x), int(y + length), color, thickness)
-            frame.draw_circle(int(x), int(y), 1, color, thickness)
-
-            result_img, center, radius, method, _ = detect_circle(frame)
-            disp.show(result_img)
-
-            dx, dy = compute_laser_position(center, (x, y), radius, method)
-            distance_m = read_distance_from_laser_sensor()
-            voltage = get_bus_voltage()
-            battery_percent = voltage_to_percent(voltage)
-
-            try:
-                jpg_count = len([f for f in os.listdir(photo_dir) if f.endswith('.jpg')])
-                filename = f"{photo_dir}/{int(x)}_{int(y)}_{round((distance_m or 0.0) * 100)}_{method}_{jpg_count:04d}.jpg"
-                result_img.save(filename, quality=70)
-            except Exception as e:
-                print(f"❌ 保存照片失败: {e}")
-
-            inner_data = {
-                "x": float(dx) if dx is not None else 200.0,
-                "y": float(dy) if dy is not None else 200.0,
-                "r": 90.0,
-                "d": round((distance_m or 0.0) * 100),
-                "m": method
-            }
-            report_data = {"cmd": 1, "data": inner_data}
-            safe_enqueue(report_data, MSG_TYPE_STATUS)
-
-            time.sleep_ms(100)
-        else:
-            disp.show(cam.read())
-            time.sleep_ms(50)
-
-
-if __name__ == "__main__":
-    cmd_str()

logger_manager.py

@@ -0,0 +1,212 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+日志管理器模块
+提供异步日志功能（使用 QueueHandler + QueueListener）
+"""
+import logging
+from logging.handlers import QueueHandler, QueueListener, RotatingFileHandler
+import queue
+import os
+import config
+from version import VERSION
+
+
+class LoggerManager:
+    """日志管理器（单例）"""
+    _instance = None
+    
+    def __new__(cls):
+        if cls._instance is None:
+            cls._instance = super(LoggerManager, cls).__new__(cls)
+            cls._instance._initialized = False
+        return cls._instance
+    
+    def __init__(self):
+        if self._initialized:
+            return
+        
+        # 私有状态
+        self._log_queue = None
+        self._queue_listener = None
+        self._logger = None
+        
+        self._initialized = True
+    
+    # ==================== 状态访问（只读属性）====================
+    
+    @property
+    def logger(self):
+        """获取logger对象（只读）"""
+        return self._logger
+    
+    @property
+    def log_queue(self):
+        """获取日志队列（只读）"""
+        return self._log_queue
+    
+    # ==================== 业务方法 ====================
+    
+    def init_logging(self, log_level=logging.INFO, log_file=None, max_bytes=None, backup_count=None):
+        """
+        初始化异步日志系统（使用 QueueHandler + QueueListener）
+        
+        Args:
+            log_level: 日志级别，默认 INFO
+            log_file: 日志文件路径，默认使用 config.LOG_FILE
+            max_bytes: 单个日志文件最大大小（字节），默认使用 config.LOG_MAX_BYTES
+            backup_count: 保留的备份文件数量，默认使用 config.LOG_BACKUP_COUNT
+        """
+        if log_file is None:
+            log_file = config.LOG_FILE
+        if max_bytes is None:
+            max_bytes = config.LOG_MAX_BYTES
+        if backup_count is None:
+            backup_count = config.LOG_BACKUP_COUNT
+        
+        try:
+            # 创建日志队列（无界队列）
+            self._log_queue = queue.Queue(-1)
+            
+            # 确保日志文件所在的目录存在
+            log_dir = os.path.dirname(log_file)
+            if log_dir:  # 如果日志路径包含目录
+                try:
+                    os.makedirs(log_dir, exist_ok=True)
+                except Exception as e:
+                    print(f"[WARN] 无法创建日志目录 {log_dir}: {e}")
+            
+            # 尝试创建文件Handler（带日志轮转）
+            try:
+                file_handler = RotatingFileHandler(
+                    log_file,
+                    maxBytes=max_bytes,
+                    backupCount=backup_count,
+                    encoding='utf-8',
+                    mode='a'  # 追加模式，确保不覆盖
+                )
+            except Exception as e:
+                # 如果RotatingFileHandler不可用，降级为普通FileHandler
+                print(f"[WARN] RotatingFileHandler不可用，使用普通FileHandler: {e}")
+                try:
+                    file_handler = logging.FileHandler(log_file, encoding='utf-8', mode='a')
+                except Exception as e2:
+                    # 如果文件Handler创建失败，只使用控制台Handler
+                    print(f"[WARN] 无法创建文件Handler，仅使用控制台输出: {e2}")
+                    file_handler = None
+            
+            # 自定义Formatter，包含版本信息
+            class CustomFormatter(logging.Formatter):
+                """自定义日志格式，包含版本信息和行号"""
+                def format(self, record):
+                    record.version = VERSION
+                    return super().format(record)
+            
+            # 如果file_handler存在，设置格式和级别
+            if file_handler is not None:
+                file_handler.setFormatter(CustomFormatter(
+                    '%(asctime)s [v%(version)s] [%(levelname)s] %(filename)s:%(lineno)d - %(message)s',
+                    datefmt='%Y-%m-%d %H:%M:%S'
+                ))
+                file_handler.setLevel(log_level)
+            
+            # 创建控制台Handler（保留原有的print输出）
+            console_handler = logging.StreamHandler()
+            console_handler.setFormatter(CustomFormatter(
+                '[v%(version)s] [%(levelname)s] %(filename)s:%(lineno)d - %(message)s'
+            ))
+            console_handler.setLevel(log_level)
+            
+            # 创建QueueListener（后台线程处理日志写入）
+            # 如果file_handler为None，只使用console_handler
+            handlers = [console_handler]
+            if file_handler is not None:
+                handlers.append(file_handler)
+            
+            self._queue_listener = QueueListener(
+                self._log_queue, 
+                *handlers,
+                respect_handler_level=True
+            )
+            self._queue_listener.start()
+            
+            # 创建QueueHandler（用于记录日志）
+            queue_handler = QueueHandler(self._log_queue)
+            
+            # 配置根logger
+            self._logger = logging.getLogger()
+            self._logger.addHandler(queue_handler)
+            self._logger.setLevel(log_level)
+            
+            # 避免日志向上传播到其他logger
+            self._logger.propagate = False
+            
+            # 添加启动标记
+            self._logger.info("=" * 60)
+            self._logger.info("程序启动 - 日志系统初始化")
+            self._logger.info(f"版本: {VERSION}")
+            self._logger.info(f"日志文件: {log_file}")
+            self._logger.info("=" * 60)
+            
+            return True
+        except Exception as e:
+            # 如果日志初始化失败，至少保证程序能运行
+            print(f"[ERROR] 日志系统初始化失败: {e}")
+            import traceback
+            try:
+                traceback.print_exc()
+            except:
+                pass
+            return False
+    
+    def stop_logging(self):
+        """停止日志系统（程序退出时调用）"""
+        try:
+            if self._logger:
+                # 确保所有日志都写入
+                self._logger.info("程序退出，正在保存日志...")
+                import time as std_time
+                std_time.sleep(0.5)  # 给一点时间让日志写入
+            
+            if self._queue_listener:
+                self._queue_listener.stop()
+            
+            if self._logger:
+                # 等待队列中的日志处理完成
+                if self._log_queue:
+                    import time as std_time
+                    timeout = 5
+                    start = std_time.time()
+                    while not self._log_queue.empty() and (std_time.time() - start) < timeout:
+                        std_time.sleep(0.1)
+            print("[LOG] 日志系统已停止")
+        except Exception as e:
+            print(f"[ERROR] 停止日志系统失败: {e}")
+
+
+# 创建全局单例实例
+logger_manager = LoggerManager()
+
+# ==================== 向后兼容的函数接口 ====================
+
+def init_logging(log_level=logging.INFO, log_file=None, max_bytes=None, backup_count=None):
+    """初始化日志系统（向后兼容接口）"""
+    return logger_manager.init_logging(log_level, log_file, max_bytes, backup_count)
+
+def stop_logging():
+    """停止日志系统（向后兼容接口）"""
+    return logger_manager.stop_logging()
+
+def get_logger():
+    """
+    获取全局logger对象（向后兼容接口）
+    如果日志系统未初始化，返回None（此时可以使用print作为fallback）
+    """
+    return logger_manager.logger
+
+
+
+
+
+
+

model_270139.mud

@@ -0,0 +1,13 @@
+
+[basic]
+type = cvimodel
+model = model_270139.cvimodel
+
+[extra]
+model_type = yolov5
+input_type = rgb
+mean = 0, 0, 0
+scale = 0.00392156862745098, 0.00392156862745098, 0.00392156862745098
+anchors = 10, 13, 16, 30, 33, 23, 30, 61, 62, 45, 59, 119, 116, 90, 156, 198, 373, 326
+labels = 黑三角和圆环
+

model_270820.mud

@@ -0,0 +1,13 @@
+
+[basic]
+type = cvimodel
+model = model_270820.cvimodel
+
+[extra]
+model_type = yolov5
+input_type = rgb
+mean = 0, 0, 0
+scale = 0.00392156862745098, 0.00392156862745098, 0.00392156862745098
+anchors = 10, 13, 16, 30, 33, 23, 30, 61, 62, 45, 59, 119, 116, 90, 156, 198, 373, 326
+labels = triangle
+

package.py

@@ -0,0 +1,230 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+应用打包脚本
+根据 app.yaml 中列出的文件，打包成 zip 文件
+版本号从 version.py 中读取
+"""
+import argparse
+import os
+import yaml
+import zipfile
+from datetime import datetime
+import sys
+import secrets
+
+MAGIC = b"AROTAE1"  # 7 bytes: Archery OTA Encrypted v1
+GCM_NONCE_LEN = 12
+GCM_TAG_LEN = 16
+
+# 添加当前目录到路径，以便导入 version 模块
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+
+
+def load_app_yaml(yaml_path='app.yaml'):
+    """加载 app.yaml 文件"""
+    try:
+        with open(yaml_path, 'r', encoding='utf-8') as f:
+            return yaml.safe_load(f)
+    except Exception as e:
+        print(f"[ERROR] 读取 {yaml_path} 失败: {e}")
+        return None
+
+
+def check_files_exist(files, base_dir='.'):
+    """检查文件是否存在"""
+    missing_files = []
+    existing_files = []
+
+    for file_path in files:
+        full_path = os.path.join(base_dir, file_path)
+        if os.path.exists(full_path):
+            existing_files.append(file_path)
+        else:
+            missing_files.append(file_path)
+
+    return existing_files, missing_files
+
+
+def get_version_from_version_py():
+    """从 version.py 读取版本号"""
+    try:
+        from version import VERSION
+        return VERSION
+    except ImportError:
+        print("[WARNING] 无法导入 version.py，使用默认版本号 1.0.0")
+        return '1.0.0'
+    except Exception as e:
+        print(f"[WARNING] 读取 version.py 失败: {e}，使用默认版本号 1.0.0")
+        return '1.0.0'
+
+
+def create_zip_package(app_info, files, output_dir='.', base_dir='.'):
+    """创建 zip 打包文件"""
+    # 生成输出文件名：{name}_v{version}_{timestamp}.zip
+    # 版本号从 version.py 读取，而不是从 app.yaml
+    app_name = app_info.get('name', 'app')
+    version = get_version_from_version_py()  # 从 version.py 读取版本号
+    timestamp = datetime.now().strftime('%Y%m%d_%H%M%S')
+    zip_filename = f"{app_name}_v{version}_{timestamp}.zip"
+    zip_path = os.path.join(output_dir, zip_filename)
+
+    print(f"[INFO] 开始打包: {zip_filename}")
+    print(f"[INFO] 包含文件数: {len(files)}")
+
+    try:
+        with zipfile.ZipFile(zip_path, 'w', zipfile.ZIP_DEFLATED) as zipf:
+            for file_path in files:
+                full_path = os.path.join(base_dir, file_path)
+                # 使用相对路径作为 zip 内的路径
+                zipf.write(full_path, file_path)
+                print(f"  ✓ {file_path}")
+
+        # 获取文件大小
+        file_size = os.path.getsize(zip_path)
+        file_size_mb = file_size / (1024 * 1024)
+
+        print(f"\n[SUCCESS] 打包完成!")
+        print(f"  文件名: {zip_filename}")
+        print(f"  文件大小: {file_size_mb:.2f} MB ({file_size:,} 字节)")
+        print(f"  文件路径: {os.path.abspath(zip_path)}")
+
+        return zip_path
+    except Exception as e:
+        print(f"[ERROR] 打包失败: {e}")
+        import traceback
+        traceback.print_exc()
+        return None
+
+
+def _validate_key_hex(key_hex: str) -> bytes:
+    if not isinstance(key_hex, str):
+        raise ValueError("aead key must be hex string")
+    key_hex = key_hex.strip().lower()
+    if key_hex.startswith("0x"):
+        key_hex = key_hex[2:]
+    if len(key_hex) != 64:
+        raise ValueError("aead key must be 64 hex chars (32 bytes)")
+    try:
+        key = bytes.fromhex(key_hex)
+    except Exception as e:
+        raise ValueError(f"invalid hex key: {e}")
+    if len(key) != 32:
+        raise ValueError("aead key must be 32 bytes")
+    return key
+
+
+def encrypt_zip_aead(zip_path: str, key_hex: str, out_ext: str = ".enc") -> str:
+    """
+    Encrypt the whole zip file as one blob:
+    output format: MAGIC(7) | nonce(12) | ciphertext(N) | tag(16)
+    using AES-256-GCM (AEAD).
+    """
+    # Lazy import: packaging-only dependency
+    try:
+        from cryptography.hazmat.primitives.ciphers.aead import AESGCM
+    except Exception as e:
+        raise RuntimeError(
+            "Missing dependency: cryptography. Install with: pip install cryptography. "
+            f"Import error: {e}"
+        )
+
+    key = _validate_key_hex(key_hex)
+    with open(zip_path, "rb") as f:
+        plain = f.read()
+
+    nonce = secrets.token_bytes(GCM_NONCE_LEN)
+    aesgcm = AESGCM(key)
+    ct_and_tag = aesgcm.encrypt(nonce, plain, None)  # ciphertext || tag (16 bytes)
+
+    enc_path = zip_path + out_ext if out_ext else (zip_path + ".enc")
+    with open(enc_path, "wb") as f:
+        f.write(MAGIC)
+        f.write(nonce)
+        f.write(ct_and_tag)
+
+    return enc_path
+
+
+def main():
+    """主函数"""
+    parser = argparse.ArgumentParser(description="打包 app.yaml 文件列表到 zip，并可选进行 AES-256-GCM 加密输出 .enc")
+    parser.add_argument("--aead-key-hex", default=None, help="AES-256-GCM key (64 hex chars = 32 bytes). If set, output encrypted file.")
+    parser.add_argument("--keep-zip", action="store_true", help="Keep the plaintext zip when encryption is enabled.")
+    parser.add_argument("--out-ext", default=".enc", help="Encrypted output extension appended to zip path. Default: .enc (produces *.zip.enc)")
+    args = parser.parse_args()
+
+    print("=" * 60)
+    print("应用打包脚本")
+    print("=" * 60)
+
+    # 1. 加载 app.yaml
+    app_info = load_app_yaml('app.yaml')
+    if app_info is None:
+        return
+
+    # 从 version.py 读取版本号
+    version = get_version_from_version_py()
+    
+    print(f"\n[INFO] 应用信息:")
+    print(f"  ID: {app_info.get('id', 'N/A')}")
+    print(f"  名称: {app_info.get('name', 'N/A')}")
+    print(f"  版本: {version} (来自 version.py)")
+    print(f"  作者: {app_info.get('author', 'N/A')}")
+    if app_info.get('version') != version:
+        print(f"  [注意] app.yaml 中的版本 ({app_info.get('version', 'N/A')}) 与 version.py 不一致")
+
+    # 2. 获取文件列表
+    files = app_info.get('files', [])
+    if not files:
+        print("[ERROR] app.yaml 中没有找到 files 列表")
+        return
+
+    print(f"\n[INFO] 文件列表 ({len(files)} 个文件):")
+
+    # 3. 检查文件是否存在
+    existing_files, missing_files = check_files_exist(files)
+
+    if missing_files:
+        print(f"\n[WARNING] 以下文件不存在，将被跳过:")
+        for f in missing_files:
+            print(f"  ✗ {f}")
+
+    if not existing_files:
+        print("\n[ERROR] 没有找到任何有效文件，无法打包")
+        return
+
+    print(f"\n[INFO] 找到 {len(existing_files)} 个有效文件")
+
+    # 4. 创建 zip 包
+    zip_path = create_zip_package(app_info, existing_files)
+
+    if zip_path:
+        enc_path = None
+        if args.aead_key_hex:
+            try:
+                enc_path = encrypt_zip_aead(zip_path, args.aead_key_hex, out_ext=args.out_ext)
+                enc_size = os.path.getsize(enc_path)
+                print(f"\n[SUCCESS] AEAD加密完成: {os.path.basename(enc_path)} ({enc_size:,} bytes)")
+                print(f"  文件路径: {os.path.abspath(enc_path)}")
+                if not args.keep_zip:
+                    try:
+                        os.remove(zip_path)
+                        print(f"[INFO] 已删除明文zip: {os.path.basename(zip_path)}")
+                    except Exception as e:
+                        print(f"[WARNING] 删除明文zip失败（可忽略）: {e}")
+            except Exception as e:
+                print(f"\n[ERROR] AEAD加密失败: {e}")
+                print("[ERROR] 保留明文zip用于排查。")
+
+        print("\n" + "=" * 60)
+        print("打包成功完成!")
+        print("=" * 60)
+    else:
+        print("\n" + "=" * 60)
+        print("打包失败!")
+        print("=" * 60)
+
+
+if __name__ == "__main__":
+    main()

power.py

@@ -0,0 +1,254 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+电源管理模块（INA226）
+提供电压、电流监测和充电状态检测
+"""
+import config
+from logger_manager import logger_manager
+from maix import time as maix_time
+
+
+_INA226_PRESENT = None
+
+
+def _ina226_ready() -> bool:
+    """
+    是否允许访问 INA226。
+
+    重要：
+    - 这里刻意不做任何 I2C 探测/读写。
+    - 经验上，在 INA226 未供电/未响应时，I2C 的 readfrom_mem 可能直接触发底层崩溃（SIGSEGV），try/except 无法拦截。
+    - 因此只在开机 init_ina226() 成功后才允许后续读电压/电流。
+    """
+    return bool(getattr(config, "INA226_ENABLE", True)) and (_INA226_PRESENT is True)
+
+
+def write_register(reg, value):
+    """写入INA226寄存器"""
+    from hardware import hardware_manager
+    logger = logger_manager.logger
+    data = [(value >> 8) & 0xFF, value & 0xFF]
+    # 某些底层驱动在失败时只打印 “write failed” 并返回 -1，而不是抛异常；
+    # 为避免误判“初始化成功”导致后续 readfrom_mem SIGSEGV，这里把失败显式转成异常。
+    ret = hardware_manager.bus.writeto_mem(config.INA226_ADDR, reg, bytes(data))
+    if isinstance(ret, int) and ret < 0:
+        if logger:
+            logger.error(f"[INA226] writeto_mem 失败: addr=0x{config.INA226_ADDR:02X} reg=0x{reg:02X} ret={ret}")
+        raise OSError(ret)
+
+
+def read_register(reg):
+    """读取INA226寄存器"""
+    from hardware import hardware_manager
+    data = hardware_manager.bus.readfrom_mem(config.INA226_ADDR, reg, 2)
+    return (data[0] << 8) | data[1]
+
+
+def init_ina226():
+    """初始化 INA226 芯片：配置模式 + 校准值"""
+    global _INA226_PRESENT
+    logger = logger_manager.logger
+    if not getattr(config, "INA226_ENABLE", True):
+        if logger:
+            logger.info("[INA226] INA226_ENABLE=False，跳过初始化与 I2C 探测")
+        # 显式标记不可用，避免后续误读
+        _INA226_PRESENT = False
+        return False
+    try:
+        # 仅通过“写寄存器成功”来判定可用，避免额外的读操作触发底层崩溃
+        write_register(config.REG_CONFIGURATION, 0x4527)
+        write_register(config.REG_CALIBRATION, config.CALIBRATION_VALUE)
+        _INA226_PRESENT = True
+        return True
+    except Exception as e:
+        _INA226_PRESENT = False
+        if logger:
+            logger.error(f"[INA226] 初始化失败：{e}")
+        return False
+
+
+def get_bus_voltage():
+    """读取总线电压（单位：V）。未探测到 INA226 或读失败时返回 0.0（上报用，避免 null）。"""
+    logger = logger_manager.logger
+    if not _ina226_ready():
+        return 0.0
+    try:
+        raw = read_register(config.REG_BUS_VOLTAGE)
+        return raw * 1.25 / 1000
+    except Exception as e:
+        if logger:
+            logger.error(f"[INA226] 读取电压失败：{e}")
+        return 0.0
+
+
+def get_current():
+    """
+    读取电流（单位：mA）
+    正数表示充电，负数表示放电
+    
+    INA226 电流计算公式：
+    Current = (Current Register Value) × Current_LSB
+    Current_LSB = 0.001 × CALIBRATION_VALUE / 4096
+    """
+    try:
+        if not _ina226_ready():
+            return 0.0
+        raw = read_register(config.REG_CURRENT)
+        # INA226 电流寄存器是16位有符号整数
+        # 最高位是符号位：0=正（充电），1=负（放电）
+        # 计算 Current_LSB（根据 CALIBRATION_VALUE）
+        current_lsb = 0.001 * config.CALIBRATION_VALUE / 4096  # 单位：A
+        # 处理有符号数：如果最高位为1，转换为负数
+        if raw & 0x8000:  # 最高位为1，表示负数（放电）
+            signed_raw = raw - 0x10000  # 转换为有符号整数
+        else:  # 最高位为0，表示正数（充电）
+            signed_raw = raw
+        # 转换为毫安
+        current_ma = signed_raw * current_lsb * 1000
+        return current_ma
+    except Exception as e:
+        logger = logger_manager.logger
+        if logger:
+            logger.error(f"[INA226] 读取电流失败: {e}")
+        else:
+            print(f"[INA226] 读取电流失败: {e}")
+        return 0.0
+
+
+def is_charging(threshold_ma=10.0):
+    """
+    检测是否在充电（通过电流方向判断）
+    
+    Args:
+        threshold_ma: 电流阈值（毫安），超过此值认为在充电，默认10mA
+    
+    Returns:
+        True: 正在充电
+        False: 未充电或读取失败
+    """
+    try:
+        current = get_current()
+        is_charge = current > threshold_ma
+        return is_charge
+    except Exception as e:
+        logger = logger_manager.logger
+        if logger:
+            logger.error(f"[CHARGE] 检测充电状态失败: {e}")
+        else:
+            print(f"[CHARGE] 检测充电状态失败: {e}")
+        return False
+
+
+def voltage_to_percent(voltage):
+    """
+    根据电压估算电池百分比（高密度查表插值 + 滤波）。
+
+    - 电压先做 5 点移动平均（抑制瞬时抖动）
+    - SOC 再做一阶低通（抑制“跳电量”）
+
+    注意：
+    - 该方法仍是“开路电压→SOC”的近似；负载较大/瞬时大电流时电压会下沉，SOC 会偏低。
+    - 滤波会带来滞后：电量变化会更平滑，但更新更慢。
+    """
+    if voltage is None:
+        return 0
+    try:
+        v = float(voltage)
+    except Exception:
+        return 0
+    if v <= 0:
+        return 0
+    return int(int(_BATTERY_MONITOR.get_soc(v) * 10) / 10) # 截断而不是四舍五入
+
+
+class BatteryMonitor:
+    """
+    电压→SOC 估算器（查表 + 线性插值 + 双重滤波）。
+
+    说明：
+    - 表为单节锂电“静态电压”近似曲线；不同电池/温度/老化会有偏差。
+    - 这里不区分充电/放电曲线（滞后），主要用于“显示电量/粗略判断”。
+    """
+
+    def __init__(self, avg_window: int = 5, alpha: float = 0.2):
+        # 电压-SOC对照表（电压从高到低）
+        self.voltages = [
+            4.20, 4.15, 4.10, 4.05, 4.00,
+            3.95, 3.90, 3.88, 3.85, 3.82,
+            3.80, 3.78, 3.75, 3.72, 3.70,
+            3.65, 3.60, 3.55, 3.50, 3.45,
+            3.40, 3.35, 3.30, 3.20, 2.50,
+        ]
+        self.socs = [
+            100, 98, 95, 90, 85,
+            80, 75, 72, 68, 64,
+            60, 56, 52, 48, 44,
+            38, 32, 26, 20, 14,
+            10, 6, 3, 1, 0,
+        ]
+
+        self.avg_window = max(1, int(avg_window))
+        self.alpha = float(alpha) if alpha is not None else 0.2
+        if not (0.0 < self.alpha <= 1.0):
+            self.alpha = 0.2
+
+        self.voltage_history = []
+        self.last_soc = 50.0
+
+    def _voltage_to_soc_raw(self, voltage: float) -> float:
+        # 越界
+        if voltage >= self.voltages[0]:
+            return 100.0
+        if voltage <= self.voltages[-1]:
+            return 0.0
+
+        # 表是降序，二分查找
+        left, right = 0, len(self.voltages) - 1
+        while left <= right:
+            mid = (left + right) // 2
+            vm = self.voltages[mid]
+            if vm == voltage:
+                return float(self.socs[mid])
+            elif vm < voltage:
+                right = mid - 1
+            else:
+                left = mid + 1
+
+        # 线性插值：right 在高电压侧，left 在低电压侧（降序表）
+        # 例：voltages = [4.2,4.15,...]，则 v_high=voltages[right] >= voltage >= voltages[left]=v_low
+        v_high, v_low = float(self.voltages[right]), float(self.voltages[left])
+        soc_high, soc_low = float(self.socs[right]), float(self.socs[left])
+        if abs(v_high - v_low) < 1e-9:
+            return soc_low
+        soc = soc_low + (voltage - v_low) * (soc_high - soc_low) / (v_high - v_low)
+        return soc
+
+    def get_soc(self, raw_voltage: float) -> float:
+        # 1) 电压滤波（移动平均）
+        self.voltage_history.append(float(raw_voltage))
+        if len(self.voltage_history) > self.avg_window:
+            self.voltage_history.pop(0)
+        voltage = sum(self.voltage_history) / float(len(self.voltage_history))
+
+        # 2) 查表插值
+        raw_soc = self._voltage_to_soc_raw(voltage)
+
+        # 3) SOC 低通滤波
+        a = self.alpha
+        self.last_soc = a * raw_soc + (1.0 - a) * float(self.last_soc)
+
+        # clip
+        if self.last_soc < 0.0:
+            self.last_soc = 0.0
+        if self.last_soc > 100.0:
+            self.last_soc = 100.0
+        return float(self.last_soc)
+
+
+# 模块级单例：保留历史，实现平滑（进程重启会重置）
+_BATTERY_MONITOR = BatteryMonitor(
+    avg_window=int(getattr(config, "BATTERY_SOC_AVG_WINDOW", 5)),
+    alpha=float(getattr(config, "BATTERY_SOC_LPF_ALPHA", 0.2)),
+)
+

server.pem

@@ -0,0 +1,33 @@
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+nFBDkgzZxr4ZYlhVLzbSoab8D4A/z6riEMqv4S+oF5VkaJLhsN8vgHh9aPspCC3Q
+zhcosH8XmNmJmT/X64FhhRqxAqX65WanVQABtBS/vsC+FAQDGMb3RkZSbLEnIlgj
+bx/6bSkhHl+J2xIqA7tLvYhRSvM3H12X7VSVc+tkVzI5JoUSugZLxxRDGpYgkvRz
+SPFCqb9eTn5ES5gnQX6+E+f/E/WQTmadolSbEppdxNZW7AaIUdQo0aFxFwctwhA2
+YNUG9oW2TXAZjSECyTo28NFkFfwBhpHWigFCANNCd8Nrn0k0YMuJOkqW5e4w3/24
+/IxM/C9K7aAx4S1XZ16Nvh5pZQduEGKTSUYMJ/uV26Mf4ZGroUfGB9tBguK5rYbL
+UlRvtU9mkZPK04GbLsoo+8tZTDRtkuCiC19xk33XiitZrmavc24=
+-----END CERTIFICATE-----

set_autostart.py

@@ -47,6 +47,7 @@ def set_autostart_app(app_id):
 if __name__ == "__main__":
     new_autostart_app_id = "t11"   # change to app_id you want to set
     # new_autostart_app_id = None           # remove autostart
+    # new_autostart_app_id = "z1222"   # change to app_id you want to set
 
     list_apps()
     print("Before set autostart appid:", get_curr_autostart_app())

shoot_manager.py

@@ -0,0 +1,546 @@
+import os
+import threading
+import time as time_std
+
+import config
+from camera_manager import camera_manager
+from laser_manager import laser_manager
+from logger_manager import logger_manager
+from network import network_manager
+from triangle_target import load_camera_from_xml, load_triangle_positions, try_triangle_scoring
+from vision import estimate_distance, detect_circle_v3, enqueue_save_shot
+from maix import image, time
+
+# 缓存相机标定与三角形位置，避免每次射箭重复读磁盘
+_tri_calib_cache = None
+
+def _get_triangle_calib():
+    """返回 (K, dist, marker_positions)；首次调用时从磁盘加载并缓存。"""
+    global _tri_calib_cache
+    if _tri_calib_cache is not None:
+        return _tri_calib_cache
+    calib_path = getattr(config, "CAMERA_CALIB_XML", "")
+    tri_json = getattr(config, "TRIANGLE_POSITIONS_JSON", "")
+    if not (os.path.isfile(calib_path) and os.path.isfile(tri_json)):
+        _tri_calib_cache = (None, None, None)
+        return _tri_calib_cache
+    K, dist = load_camera_from_xml(calib_path)
+    pos = load_triangle_positions(tri_json)
+    _tri_calib_cache = (K, dist, pos)
+    return _tri_calib_cache
+
+
+def preload_triangle_calib():
+    """
+    启动阶段预加载三角形标定与坐标文件，避免首次射箭触发时的读盘/解析开销。
+    """
+    try:
+        _get_triangle_calib()
+    except Exception:
+        # 预加载失败不影响主流程；射箭时会再次按需尝试
+        pass
+
+
+def analyze_shot(frame, laser_point=None):
+    """
+    分析射箭结果（算法部分，可迁移到C++）
+    :param frame: 图像帧
+    :param laser_point: 激光点坐标 (x, y)
+    :return: 包含分析结果的字典
+
+    优先级：
+      1. 三角形单应性（USE_TRIANGLE_OFFSET=True 时）— 成功则直接返回，跳过圆形检测
+      2. 圆形检测（三角形不可用或识别失败时兜底）
+    """
+    logger = logger_manager.logger
+    from datetime import datetime
+
+    # ── Step 1: 确定激光点 ────────────────────────────────────────────────────
+    laser_point_method = None
+    distance_m_first = None
+
+    if config.HARDCODE_LASER_POINT:
+        laser_point = laser_manager.laser_point
+        laser_point_method = "hardcode"
+    elif laser_manager.has_calibrated_point():
+        laser_point = laser_manager.laser_point
+        laser_point_method = "calibrated"
+        if logger:
+            logger.info(f"[算法] 使用校准值: {laser_manager.laser_point}")
+    else:
+        # 动态模式：先做一次无激光点检测以估算距离，再推算激光点
+        _, _, _, _, best_radius1_temp, _ = detect_circle_v3(frame, None)
+        distance_m_first = estimate_distance(best_radius1_temp) if best_radius1_temp else None
+        if distance_m_first and distance_m_first > 0:
+            laser_point = laser_manager.calculate_laser_point_from_distance(distance_m_first)
+            laser_point_method = "dynamic"
+            if logger:
+                logger.info(f"[算法] 使用比例尺: {laser_point}")
+        else:
+            laser_point = laser_manager.laser_point
+            laser_point_method = "default"
+            if logger:
+                logger.info(f"[算法] 使用默认值: {laser_point}")
+
+    if laser_point is None:
+        return {"success": False, "reason": "laser_point_not_initialized"}
+
+    x, y = laser_point
+
+    # ── Step 2: 提前转换一次图像，两个检测线程共享（只读）────────────────────────
+    img_cv = image.image2cv(frame, False, False)
+
+    # ── Step 3: 检查三角形是否可用 ────────────────────────────────────────────────
+    use_tri = getattr(config, "USE_TRIANGLE_OFFSET", False)
+    K = dist_coef = pos = None
+    if use_tri:
+        K, dist_coef, pos = _get_triangle_calib()
+        use_tri = K is not None and dist_coef is not None and pos
+
+    def _build_circle_result(cdata, yolo_roi_xyxy=None):
+        """从圆形检测结果构建 analyze_shot 返回值。"""
+        r_img, center, radius, method, best_radius1, ellipse_params = cdata
+        dx, dy = None, None
+        d_m = distance_m_first
+        if center and radius:
+            dx, dy = laser_manager.compute_laser_position(center, (x, y), radius, method)
+            d_m = estimate_distance(best_radius1) if best_radius1 else distance_m_first
+        out = {
+            "success": True,
+            "result_img": r_img,
+            "center": center, "radius": radius, "method": method,
+            "best_radius1": best_radius1, "ellipse_params": ellipse_params,
+            "dx": dx, "dy": dy, "distance_m": d_m,
+            "laser_point": laser_point, "laser_point_method": laser_point_method,
+            "offset_method": "yellow_ellipse" if ellipse_params else "yellow_circle",
+            "distance_method": "yellow_radius",
+        }
+        if yolo_roi_xyxy is not None:
+            out["yolo_roi_xyxy"] = yolo_roi_xyxy
+        return out
+
+    if not use_tri:
+        # 三角形未配置，直接跑圆形检测
+        return _build_circle_result(
+            detect_circle_v3(frame, laser_point, img_cv=img_cv)
+        )
+
+    # ── Step 4: 先独占跑三角形，超时或失败后再跑圆形（不与圆心并行，避免抢 CPU）──
+    roi_xyxy = None
+    yolo_ring_ms = 0.0
+    yolo_black_ms = 0.0
+    if getattr(config, "TRIANGLE_YOLO_ROI_ENABLE", False):
+        _t_yolo_ring = time_std.perf_counter()
+        try:
+            from target_roi_yolo import try_get_triangle_roi_from_yolo
+            roi_xyxy = try_get_triangle_roi_from_yolo(
+                frame, img_cv.shape[1], img_cv.shape[0], logger
+            )
+        except Exception as e:
+            if logger:
+                logger.warning(f"[YOLO-ROI] {e}")
+        finally:
+            yolo_ring_ms = (time_std.perf_counter() - _t_yolo_ring) * 1000.0
+
+    _loc_mode = str(
+        getattr(config, "TRIANGLE_BLACK_TRIANGLE_LOCATE_MODE", "yolo")
+    ).lower().strip()
+    if _loc_mode not in ("yolo", "traditional"):
+        _loc_mode = "yolo"
+
+    black_boxes_work = None
+    _run_stage2_black_yolo = (
+        _loc_mode == "yolo"
+        and getattr(config, "TRIANGLE_BLACK_YOLO_ENABLE", False)
+        and roi_xyxy is not None
+    )
+    if _run_stage2_black_yolo:
+        _t_yolo_black = time_std.perf_counter()
+        try:
+            from target_roi_yolo import try_black_triangle_boxes_work
+
+            black_boxes_work = try_black_triangle_boxes_work(
+                img_cv, roi_xyxy, logger
+            )
+        except Exception as e:
+            if logger:
+                logger.warning(f"[YOLO-BLACK] {e}")
+        finally:
+            yolo_black_ms = (time_std.perf_counter() - _t_yolo_black) * 1000.0
+    elif (
+        logger
+        and _loc_mode == "traditional"
+        and roi_xyxy is not None
+        and getattr(config, "TRIANGLE_BLACK_YOLO_ENABLE", False)
+    ):
+        logger.info(
+            "[TRI] TRIANGLE_BLACK_TRIANGLE_LOCATE_MODE=traditional：跳过 Stage2 黑三角 YOLO，"
+            "仅在 Stage1 裁切内跑整幅传统三角检测"
+        )
+
+    tri_result = {}
+
+    def _run_triangle():
+        try:
+            logger.info(f"[TRI] begin {datetime.now()}")
+            logger.info(f"[TRI] K: {K}, dist: {dist_coef}, pos: {pos},  {datetime.now()}")
+            _t_wall_try = time_std.perf_counter()
+            tri = try_triangle_scoring(
+                img_cv, (x, y), pos, K, dist_coef,
+                size_range=getattr(config, "TRIANGLE_SIZE_RANGE", (8, 500)),
+                roi_xyxy=roi_xyxy,
+                black_yolo_boxes_work=black_boxes_work,
+                yolo_ring_ms=yolo_ring_ms,
+                yolo_black_ms=yolo_black_ms,
+            )
+            _wall_try_ms = (time_std.perf_counter() - _t_wall_try) * 1000.0
+            if logger and bool(getattr(config, "TRIANGLE_LOG_E2E_TIMING", True)):
+                _e2e = float(yolo_ring_ms) + float(yolo_black_ms) + float(_wall_try_ms)
+                logger.info(
+                    f"[TRI] timing_e2e_triangle_ms={_e2e:.1f} "
+                    f"(yolo_ring={float(yolo_ring_ms):.1f} yolo_black={float(yolo_black_ms):.1f} "
+                    f"try_triangle_wall={_wall_try_ms:.1f} locate_mode={_loc_mode})"
+                )
+            logger.info(f"[TRI] tri: {tri},  {datetime.now()}")
+            tri_result['data'] = tri
+        except Exception as e:
+            logger.error(f"[TRI] 三角形路径异常: {e}")
+            tri_result['data'] = {'ok': False}
+
+    t_tri = threading.Thread(target=_run_triangle, daemon=True)
+    t_tri.start()
+
+    tri_timeout_s = float(getattr(config, "TRIANGLE_TIMEOUT_MS", 2000)) / 1000.0
+
+    t_tri.join(timeout=tri_timeout_s)
+
+    def _tri_ok_validated(tri):
+        try:
+            import numpy as _np
+            ok = bool(tri.get('ok'))
+            if not ok:
+                return False
+
+            dxv = tri.get("dx_cm")
+            dyv = tri.get("dy_cm")
+            H = tri.get("homography")
+            if not _np.isfinite(dxv) or not _np.isfinite(dyv):
+                logger.warning("[TRI] dx/dy 非有限值，判定为误检")
+                return False
+            if H is not None and not _np.all(_np.isfinite(H)):
+                logger.warning("[TRI] 单应矩阵含非有限值，判定为误检")
+                return False
+
+            # ── 检查1：单应矩阵 x/y 缩放比（靶标是正方形，H[0,0]≈H[1,1]）──
+            if H is not None:
+                sx = abs(float(H[0, 0]))
+                sy = abs(float(H[1, 1]))
+                if sy > 1e-6:
+                    hxy_ratio = sx / sy
+                    # 正常拍摄比值在 0.6~1.7 之间；超出则四点严重变形，说明有误检
+                    if not (0.6 <= hxy_ratio <= 1.7):
+                        logger.warning(
+                            f"[TRI] 单应矩阵 sx/sy={hxy_ratio:.2f} 偏差过大，判定为误检，回退圆心"
+                        )
+                        return False
+
+            # ── 检查2：可选配置距离上下限（写 0 表示不启用）──────────────────
+            dist_m = tri.get("distance_m")
+            if dist_m is not None:
+                try:
+                    import config as _vc
+                    d_min = float(getattr(_vc, "TRIANGLE_DISTANCE_MIN_M", 0.0))
+                    d_max = float(getattr(_vc, "TRIANGLE_DISTANCE_MAX_M", 0.0))
+                except Exception:
+                    d_min, d_max = 0.0, 0.0
+                if d_min > 0 and d_max > d_min:
+                    if not (d_min <= dist_m <= d_max):
+                        logger.warning(
+                            f"[TRI] 距离 {dist_m:.2f}m 超出配置范围 [{d_min},{d_max}]，判定为误检，回退圆心"
+                        )
+                        return False
+
+            return True
+        except Exception:
+            return bool(tri.get('ok'))
+
+    def _build_tri_result(tri, yolo_roi_xyxy=None):
+        out = {
+            "success": True,
+            "result_img": frame,
+            "center": None, "radius": None,
+            "method": "triangle_homography",
+            "best_radius1": None, "ellipse_params": None,
+            "dx": tri["dx_cm"], "dy": tri["dy_cm"],
+            "distance_m": tri.get("distance_m") or distance_m_first,
+            "laser_point": laser_point, "laser_point_method": laser_point_method,
+            "offset_method": tri.get("offset_method") or "triangle_homography",
+            "distance_method": tri.get("distance_method") or "pnp_triangle",
+            "tri_markers": tri.get("markers", []),
+            "tri_markers_completed": tri.get("markers_completed", []),
+            "tri_homography": tri.get("homography"),
+        }
+        if yolo_roi_xyxy is not None:
+            out["yolo_roi_xyxy"] = yolo_roi_xyxy
+        return out
+
+    # 三角形在超时内完成
+    if not t_tri.is_alive():
+        tri = tri_result.get('data', {})
+        if _tri_ok_validated(tri):
+            logger.info(f"[TRI] end {datetime.now()} — 使用三角形结果(dx={tri['dx_cm']:.2f},dy={tri['dy_cm']:.2f}cm)")
+            return _build_tri_result(tri, roi_xyxy)
+        logger.info(f"[TRI] end(tri_failed, fallback circle) {datetime.now()}")
+    else:
+        logger.warning(f"[TRI] 超时 {tri_timeout_s:.2f}s 仍未结束，启动圆心算法（三角形仍在后台）")
+
+    # 三角形超时或失败 → 跑圆心；圆心跑完后再检查三角形是否已结束
+    try:
+        cdata = detect_circle_v3(frame, laser_point, img_cv=img_cv)
+    except Exception as e:
+        logger.error(f"[CIRCLE] 圆形检测异常: {e}")
+        cdata = (frame, None, None, None, None, None)
+
+    # 圆心跑完后，若三角形恰好已经结束且结果有效，优先用三角形
+    if not t_tri.is_alive():
+        tri = tri_result.get('data', {})
+        if _tri_ok_validated(tri):
+            logger.info(f"[TRI] 圆心跑完后三角形已就绪 — 优先使用三角形结果(dx={tri['dx_cm']:.2f},dy={tri['dy_cm']:.2f}cm)")
+            return _build_tri_result(tri, roi_xyxy)
+
+    return _build_circle_result(cdata, roi_xyxy)
+
+
+def process_shot(adc_val):
+    """
+    处理射箭事件（逻辑控制部分）
+    :param adc_val: ADC触发值
+    :return: None
+    """
+    logger = logger_manager.logger
+
+    try:
+        network_manager.safe_enqueue({"shoot_event": "start"}, msg_type=2, high=True)
+        frame = camera_manager.read_frame()
+
+        # 调用算法分析
+        analysis_result = analyze_shot(frame)
+
+        if not analysis_result.get("success"):
+            reason = analysis_result.get("reason", "unknown")
+            if logger:
+                logger.warning(f"[MAIN] 射箭分析失败: {reason}")
+            time.sleep_ms(100)
+            return
+
+        # 提取分析结果
+        result_img = analysis_result["result_img"]
+        center = analysis_result["center"]
+        radius = analysis_result["radius"]
+        method = analysis_result["method"]
+        ellipse_params = analysis_result["ellipse_params"]
+        dx = analysis_result["dx"]
+        dy = analysis_result["dy"]
+        distance_m = analysis_result["distance_m"]
+        laser_point = analysis_result["laser_point"]
+        laser_point_method = analysis_result["laser_point_method"]
+        offset_method = analysis_result.get("offset_method", "yellow_circle")
+        distance_method = analysis_result.get("distance_method", "yellow_radius")
+        tri_markers = analysis_result.get("tri_markers", [])
+        tri_markers_completed = analysis_result.get("tri_markers_completed", [])
+        tri_homography = analysis_result.get("tri_homography")
+        yolo_roi_xyxy = analysis_result.get("yolo_roi_xyxy")
+        draw_yolo_roi = (
+            yolo_roi_xyxy is not None
+            and getattr(config, "TRIANGLE_YOLO_DRAW_ROI_ON_SHOT", True)
+        )
+        x, y = laser_point
+
+        # 三角形路径成功时 center/radius 为空是正常的；此时用 triangle 方法名用于保存文件名与上报字段 m
+        if (not method) and tri_markers:
+            method = "triangle_homography"
+
+        if config.SHOW_CAMERA_PHOTO_WHILE_SHOOTING:
+            camera_manager.show(result_img)
+
+        if dx is None and dy is None and logger:
+            logger.warning("[MAIN] 未检测到偏移量（三角形与圆形均失败），但会保存图像")
+
+        # 生成射箭ID
+        from shot_id_generator import shot_id_generator
+        shot_id = shot_id_generator.generate_id()
+
+        if logger:
+            logger.info(f"[MAIN] 射箭ID: {shot_id}")
+
+        laser_distance_m = None
+        laser_signal_quality = 0
+
+        # x,y 单位：物理厘米（compute_laser_position 与三角形单应性均输出物理 cm）
+        # 未检测到靶心时 x/y 用 200.0（脱靶标志）
+        srv_x = round(float(dx), 4) if dx is not None else 200.0
+        srv_y = round(float(dy), 4) if dy is not None else 200.0
+
+        # 构造上报数据
+        inner_data = {
+            "shot_id": shot_id,
+            "x": srv_x,
+            "y": srv_y,
+            "r": 20.0,  # 保留字段（服务端当前忽略，物理外环半径 cm）
+            "d": round((distance_m or 0.0) * 100),
+            "d_laser": round((laser_distance_m or 0.0) * 100),
+            "d_laser_quality": laser_signal_quality,
+            "m": method if method else "no_target",
+            "adc": adc_val,
+            "laser_method": laser_point_method,
+            "target_x": float(x),
+            "target_y": float(y),
+            "offset_method": offset_method,
+            "distance_method": distance_method,
+        }
+
+        if ellipse_params:
+            (ell_center, (width, height), angle) = ellipse_params
+            inner_data["ellipse_major_axis"] = float(max(width, height))
+            inner_data["ellipse_minor_axis"] = float(min(width, height))
+            inner_data["ellipse_angle"] = float(angle)
+            inner_data["ellipse_center_x"] = float(ell_center[0])
+            inner_data["ellipse_center_y"] = float(ell_center[1])
+        else:
+            inner_data["ellipse_major_axis"] = None
+            inner_data["ellipse_minor_axis"] = None
+            inner_data["ellipse_angle"] = None
+            inner_data["ellipse_center_x"] = None
+            inner_data["ellipse_center_y"] = None
+
+        report_data = {"cmd": 1, "data": inner_data}
+        network_manager.safe_enqueue(report_data, msg_type=2, high=True)
+
+        # 数据上报后再画标注，不干扰检测阶段的原始画面
+        if result_img is not None:
+            # 1. 若有三角形标记，先用 cv2 画轮廓 / 顶点 / ID，再反推靶心位置
+            if tri_markers:
+                import cv2 as _cv2
+                import numpy as _np
+                _img_cv = image.image2cv(result_img, False, False)
+
+                # YOLO 靶环框在 vision.enqueue_save_shot 的 worker 里绘制，避免阻塞主流程
+
+                # 三角形轮廓 + 直角顶点 + ID
+                for _m in tri_markers:
+                    _corners = _np.array(_m["corners"], dtype=_np.int32)
+                    _cv2.polylines(_img_cv, [_corners], True, (0, 255, 0), 2)
+                    _cx, _cy = int(_m["center"][0]), int(_m["center"][1])
+                    _cv2.circle(_img_cv, (_cx, _cy), 4, (0, 0, 255), -1)
+                    _cv2.putText(_img_cv, f"T{_m['id']}",
+                                 (_cx - 18, _cy - 12),
+                                 _cv2.FONT_HERSHEY_SIMPLEX, 0.55, (0, 255, 0), 1)
+
+                # 3点补全的虚拟角点：只画中心点 + 文本，避免误认为真实检测到的三角形
+                try:
+                    if tri_markers_completed:
+                        for _m in tri_markers_completed:
+                            if not _m.get("is_virtual"):
+                                continue
+                            _cx, _cy = int(_m["center"][0]), int(_m["center"][1])
+                            _cv2.circle(_img_cv, (_cx, _cy), 6, (255, 0, 255), 2)  # 紫色空心圈
+                            _cv2.putText(
+                                _img_cv,
+                                f"VT{_m['id']}",
+                                (_cx - 22, _cy - 12),
+                                _cv2.FONT_HERSHEY_SIMPLEX,
+                                0.55,
+                                (255, 0, 255),
+                                1,
+                            )
+                except Exception:
+                    pass
+
+                # 靶心（H_inv @ [0,0]）：小红圆
+                _center_px = None
+                if tri_homography is not None:
+                    try:
+                        _H_inv = _np.linalg.inv(tri_homography)
+                        _c_img = _cv2.perspectiveTransform(
+                            _np.array([[[0.0, 0.0]]], dtype=_np.float32), _H_inv)[0][0]
+                        _ocx, _ocy = int(_c_img[0]), int(_c_img[1])
+                        _cv2.circle(_img_cv, (_ocx, _ocy), 5, (0, 0, 255), -1)   # 实心
+                        _cv2.circle(_img_cv, (_ocx, _ocy), 9, (0, 0, 255), 1)    # 外框
+                        _center_px = (_ocx, _ocy)
+                        logger.info(f"[算法] 靶心: {_center_px}")
+                    except Exception:
+                        pass
+
+                # 叠加信息：落点-圆心距离 / 相机-靶距离等
+                try:
+                    import math as _math
+                    _lines = []
+                    if dx is not None and dy is not None:
+                        _r_cm = _math.hypot(float(dx), float(dy))
+                        _lines.append(f"offset=({float(dx):.2f},{float(dy):.2f})cm  |r|={_r_cm:.2f}cm")
+                    if distance_m is not None:
+                        _lines.append(f"cam_dist={float(distance_m):.2f}m  ({distance_method})")
+                    if method:
+                        _lines.append(f"method={method}")
+                    if _lines:
+                        _y0 = 22
+                        for i, _t in enumerate(_lines):
+                            _cv2.putText(
+                                _img_cv,
+                                _t,
+                                (10, _y0 + i * 18),
+                                _cv2.FONT_HERSHEY_SIMPLEX,
+                                0.5,
+                                (0, 255, 0),
+                                1,
+                            )
+                except Exception:
+                    pass
+
+                result_img = image.cv2image(_img_cv, False, False)
+
+            elif draw_yolo_roi:
+                # 仅 YOLO 标注时也不在主线程画框，交给存图 worker
+                pass
+
+            # 2. 激光十字线
+            _lc = image.Color(config.LASER_COLOR[0], config.LASER_COLOR[1], config.LASER_COLOR[2])
+            result_img.draw_line(int(x - config.LASER_LENGTH), int(y),
+                                 int(x + config.LASER_LENGTH), int(y),
+                                 _lc, config.LASER_THICKNESS)
+            result_img.draw_line(int(x), int(y - config.LASER_LENGTH),
+                                 int(x), int(y + config.LASER_LENGTH),
+                                 _lc, config.LASER_THICKNESS)
+            result_img.draw_circle(int(x), int(y), 1, _lc, config.LASER_THICKNESS)
+
+        # 闪一下激光（射箭反馈）
+        if config.FLASH_LASER_WHILE_SHOOTING:
+            laser_manager.flash_laser(config.FLASH_LASER_DURATION_MS)
+
+        # 保存图像（异步队列，与 main.py 一致）
+        enqueue_save_shot(
+            result_img,
+            center,
+            radius,
+            method,
+            ellipse_params,
+            (x, y),
+            distance_m,
+            shot_id=shot_id,
+            photo_dir=config.PHOTO_DIR if config.SAVE_IMAGE_ENABLED else None,
+            yolo_roi_xyxy=yolo_roi_xyxy if draw_yolo_roi else None,
+        )
+
+        if logger:
+            if dx is not None and dy is not None:
+                logger.info(f"射箭事件已加入发送队列（偏移=({dx:.2f},{dy:.2f})cm），ID: {shot_id}")
+            else:
+                logger.info(f"射箭事件已加入发送队列（未检测到偏移，已保存图像），ID: {shot_id}")
+
+        time.sleep_ms(100)
+    except Exception as e:
+        if logger:
+            logger.error(f"[MAIN] 图像处理异常: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
+        time.sleep_ms(100)

shot_id_generator.py

@@ -0,0 +1,76 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+射箭ID生成器
+为每次射箭生成唯一ID，格式：{timestamp_ms}_{counter}
+"""
+from maix import time
+import threading
+
+
+class ShotIDGenerator:
+    """射箭ID生成器（单例）"""
+    _instance = None
+    _lock = threading.Lock()
+    
+    def __new__(cls):
+        if cls._instance is None:
+            with cls._lock:
+                if cls._instance is None:
+                    cls._instance = super(ShotIDGenerator, cls).__new__(cls)
+                    cls._instance._initialized = False
+        return cls._instance
+    
+    def __init__(self):
+        if self._initialized:
+            return
+        
+        self._counter = 0
+        self._last_timestamp_ms = 0
+        self._lock = threading.Lock()
+        
+        self._initialized = True
+    
+    def generate_id(self, device_id=None):
+        """
+        生成唯一的射箭ID
+        
+        Args:
+            device_id: 可选的设备ID，如果提供则包含在ID中（格式：{device_id}_{timestamp_ms}_{counter}）
+                       如果不提供，则使用简单格式（格式：{timestamp_ms}_{counter}）
+        
+        Returns:
+            str: 唯一的射箭ID
+        """
+        with self._lock:
+            current_timestamp_ms = time.ticks_ms()
+            
+            # 如果时间戳相同，增加计数器；否则重置计数器
+            if current_timestamp_ms == self._last_timestamp_ms:
+                self._counter += 1
+            else:
+                self._counter = 0
+                self._last_timestamp_ms = current_timestamp_ms
+            
+            # 生成ID
+            if device_id:
+                shot_id = f"{device_id}_{current_timestamp_ms}_{self._counter}"
+            else:
+                shot_id = f"{current_timestamp_ms}_{self._counter}"
+            
+            return shot_id
+    
+    def reset(self):
+        """重置计数器（通常不需要调用）"""
+        with self._lock:
+            self._counter = 0
+            self._last_timestamp_ms = 0
+
+
+# 创建全局单例实例
+shot_id_generator = ShotIDGenerator()
+
+
+
+
+

target_roi_yolo.py

@@ -0,0 +1,668 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+MaixCAM NPU YOLOv5：先检靶环/整靶区域并裁切 ROI；黑三角 Stage2 在裁切图上推理（与训练一致），
+再在各子框上跑传统直角点算法。
+
+- 相机全分辨率（如 640×480）与模型输入（如 320×320）不一致时，需把检测框从
+  「网络输入坐标系」映回全图，或直接使用 Maix 已映射到源图坐标的模式（见 config）。
+
+依赖：maix.nn.YOLOv5；靶环模型 config.TRIANGLE_YOLO_MODEL_PATH；黑三角模型
+config.TRIANGLE_BLACK_YOLO_MODEL_PATH（可多实例缓存，按路径区分）。
+
+224×224、320×320 等「网络输入尺寸」由导出的 .mud 决定，运行时打印为 net_in=，无需在业务 config 里写死。
+
+返回 (x0, y0, x1, y1) 为整幅 img_cv 上的轴对齐矩形，半开区间按三角形裁剪习惯：
+实际裁剪为 img[y0:y1, x0:x1]。
+"""
+
+from __future__ import annotations
+
+import os
+import threading
+
+import numpy as np
+
+
+def _stage2_roi_crop_save_worker(
+    slab_rgb,
+    out_local_boxes,
+    rx0,
+    ry0,
+    rw,
+    rh,
+    base_dir,
+    draw_boxes,
+    jpeg_quality,
+    roi_max_images,
+    logger_ref,
+):
+    """后台写 Stage2 裁切 JPEG，避免阻塞 NPU 后续流程。"""
+    try:
+        import time
+
+        import cv2
+
+        os.makedirs(base_dir, exist_ok=True)
+        fn = os.path.join(
+            base_dir,
+            f"stage2_roi_{rx0}_{ry0}_{rw}x{rh}_{int(time.time() * 1000)}.jpg",
+        )
+        bgr = cv2.cvtColor(slab_rgb, cv2.COLOR_RGB2BGR)
+        if draw_boxes and out_local_boxes:
+            for i, (bx0, by0, bx1, by1) in enumerate(out_local_boxes):
+                x0, y0 = int(bx0), int(by0)
+                x1, y1 = int(bx1) - 1, int(by1) - 1
+                x1 = max(x0, min(x1, rw - 1))
+                y1 = max(y0, min(y1, rh - 1))
+                cv2.rectangle(bgr, (x0, y0), (x1, y1), (0, 255, 0), 2)
+                cv2.putText(
+                    bgr,
+                    f"s2_{i}",
+                    (x0, max(0, y0 - 4)),
+                    cv2.FONT_HERSHEY_SIMPLEX,
+                    0.5,
+                    (0, 255, 0),
+                    1,
+                    cv2.LINE_AA,
+                )
+        cv2.imwrite(fn, bgr, [int(cv2.IMWRITE_JPEG_QUALITY), int(jpeg_quality)])
+        try:
+            from vision import prune_old_images_in_dir
+
+            prune_old_images_in_dir(
+                base_dir, roi_max_images, logger_ref, "[YOLO-BLACK]"
+            )
+        except Exception:
+            pass
+        if logger_ref:
+            extra = (
+                f"，已绘 Stage2 框×{len(out_local_boxes)}"
+                if (draw_boxes and out_local_boxes)
+                else ""
+            )
+            logger_ref.info(f"[YOLO-BLACK] 已保存 Stage1 裁切图(异步): {fn}{extra}")
+    except Exception as e:
+        if logger_ref:
+            logger_ref.warning(f"[YOLO-BLACK] 异步保存裁切图失败: {e}")
+
+_detector_by_path = {}
+
+
+def reset_yolo_detector_cache():
+    """切换模型路径时可调用（通常不必）。"""
+    global _detector_by_path
+    _detector_by_path.clear()
+
+
+def _get_detector(model_path: str):
+    global _detector_by_path
+    if not model_path or not os.path.isfile(model_path):
+        return None
+    if model_path in _detector_by_path:
+        return _detector_by_path[model_path]
+    try:
+        from maix import nn
+    except ImportError:
+        return None
+    _detector_by_path[model_path] = nn.YOLOv5(model=model_path, dual_buff=False)
+    return _detector_by_path[model_path]
+
+
+def preload_yolo_detector(logger=None):
+    """
+    启动阶段预加载 YOLO detector，避免第一次真实射箭承担模型加载开销。
+    detect 使用 dual_buff=False，不再需要用首帧 warmup 抵消双缓冲的一帧延迟。
+    """
+    try:
+        import config as cfg
+    except Exception as e:
+        if logger:
+            logger.warning(f"[YOLO-ROI] 预加载失败：无法读取 config: {e}")
+        return False
+
+    ok = False
+
+    if bool(getattr(cfg, "TRIANGLE_YOLO_ROI_ENABLE", False)):
+        model_path = getattr(cfg, "TRIANGLE_YOLO_MODEL_PATH", "") or ""
+        det = _get_detector(model_path)
+        if det is None:
+            if logger:
+                logger.warning(f"[YOLO-ROI] 预加载失败：无法加载模型 {model_path}")
+        else:
+            ok = True
+            try:
+                net_w = int(det.input_width())
+                net_h = int(det.input_height())
+            except Exception:
+                net_w = net_h = -1
+            if logger:
+                logger.info(
+                    f"[YOLO-ROI] 靶环模型已预加载: {model_path}, net_in={net_w}×{net_h}"
+                )
+
+    _loc_black = str(
+        getattr(cfg, "TRIANGLE_BLACK_TRIANGLE_LOCATE_MODE", "yolo")
+    ).lower().strip()
+    if _loc_black not in ("yolo", "traditional"):
+        _loc_black = "yolo"
+    _preload_black = (
+        bool(getattr(cfg, "TRIANGLE_BLACK_YOLO_ENABLE", False))
+        and _loc_black == "yolo"
+        and bool(getattr(cfg, "TRIANGLE_BLACK_YOLO_PRELOAD_ON_BOOT", True))
+    )
+    if _preload_black:
+        bp = getattr(cfg, "TRIANGLE_BLACK_YOLO_MODEL_PATH", "") or ""
+        d2 = _get_detector(bp)
+        if d2 is None:
+            if logger:
+                logger.warning(f"[YOLO-BLACK] 预加载失败：无法加载模型 {bp}")
+        else:
+            ok = True
+            try:
+                nw2 = int(d2.input_width())
+                nh2 = int(d2.input_height())
+            except Exception:
+                nw2 = nh2 = -1
+            if logger:
+                logger.info(
+                    f"[YOLO-BLACK] 黑三角模型已预加载: {bp}, net_in={nw2}×{nh2}"
+                )
+    elif logger and bool(getattr(cfg, "TRIANGLE_BLACK_YOLO_ENABLE", False)):
+        if _loc_black != "yolo":
+            logger.info(
+                "[YOLO-BLACK] TRIANGLE_BLACK_TRIANGLE_LOCATE_MODE=%s：跳过黑三角模型预加载"
+                % (_loc_black,)
+            )
+
+    return ok
+
+
+def _letterbox_net_to_src_xyxy(
+    x: float, y: float, w: float, h: float,
+    src_w: int, src_h: int, net_w: int, net_h: int,
+):
+    """
+    检测框在网络输入图上（含 letterbox 填充），映回到 src_w×src_h 原图。
+    x,y,w,h 为网络坐标系下的左上角与宽高。
+    """
+    scale = min(net_w / float(src_w), net_h / float(src_h))
+    nw = src_w * scale
+    nh = src_h * scale
+    pad_x = (net_w - nw) * 0.5
+    pad_y = (net_h - nh) * 0.5
+    x0 = (x - pad_x) / scale
+    y0 = (y - pad_y) / scale
+    x1 = (x + w - pad_x) / scale
+    y1 = (y + h - pad_y) / scale
+    return x0, y0, x1, y1
+
+
+def _det_obj_class_id(o):
+    """Maix / 不同版本可能用 class_id、cls、label 等字段。"""
+    for key in ("class_id", "cls", "label", "category", "cat_id", "id"):
+        if hasattr(o, key):
+            v = getattr(o, key)
+            if v is None:
+                continue
+            try:
+                return int(float(v))
+            except (TypeError, ValueError):
+                continue
+    return None
+
+
+def _det_obj_from_seq(t):
+    """若 detect 返回 list/tuple：[x,y,w,h,score,cls]（Maix 常用 xywh），包装成属性对象。"""
+    if not isinstance(t, (list, tuple)) or len(t) < 6:
+        return None
+
+    class _Box:
+        __slots__ = ("x", "y", "w", "h", "score", "class_id")
+
+    b = _Box()
+    b.x = float(t[0])
+    b.y = float(t[1])
+    b.w = float(t[2])
+    b.h = float(t[3])
+    b.score = float(t[4])
+    b.class_id = int(float(t[5]))
+    return b
+
+
+def _normalize_objs(objs):
+    out = []
+    for o in objs or []:
+        if isinstance(o, (list, tuple)):
+            m = _det_obj_from_seq(o)
+            if m is not None:
+                out.append(m)
+        else:
+            out.append(o)
+    return out
+
+
+def _det_to_src_xyxy(o, coord_mode: str, src_w: int, src_h: int, net_w: int, net_h: int):
+    """把单个检测框转为全图坐标系下的 xyxy（半开区间语义与后续 clip 一致）。"""
+    x, y, w, h = float(o.x), float(o.y), float(o.w), float(o.h)
+    if coord_mode in ("native", "source", "camera", "full"):
+        return x, y, x + w, y + h
+    return _letterbox_net_to_src_xyxy(x, y, w, h, src_w, src_h, net_w, net_h)
+
+
+def _merge_roi_xyxy(xy_list, merge_mode: str):
+    """
+    merge_mode:
+      union — 所有框的外接矩形（适合「整靶+多角标」同属一类、多框场景）
+      largest — 取面积最大的单个框（适合只有一个大框代表整靶）
+    """
+    if not xy_list:
+        return None
+    if merge_mode in ("union", "merge", "all"):
+        x0 = min(a[0] for a in xy_list)
+        y0 = min(a[1] for a in xy_list)
+        x1 = max(a[2] for a in xy_list)
+        y1 = max(a[3] for a in xy_list)
+        return x0, y0, x1, y1
+    # largest
+    def _area(t):
+        return max(0.0, t[2] - t[0]) * max(0.0, t[3] - t[1])
+
+    best = max(xy_list, key=_area)
+    return best[0], best[1], best[2], best[3]
+
+
+def _roi_aspect_sane(x0, y0, x1, y1, src_w: int, src_h: int) -> bool:
+    """过滤 letterbox 重复映射等导致的扁条/细条 ROI。"""
+    bw = x1 - x0
+    bh = y1 - y0
+    if bw < 8 or bh < 8:
+        return False
+    area_frac = (bw * bh) / float(max(1, src_w * src_h))
+    if area_frac < 0.015:  # 小于全图约 1.5% 认为不可信
+        return False
+    ar = bw / max(bh, 1e-6)
+    if ar > 5.5 or ar < 1.0 / 5.5:
+        return False
+    return True
+
+
+def _expand_xyxy(x0, y0, x1, y1, src_w, src_h, margin_frac: float):
+    bw = max(x1 - x0, 1e-6)
+    bh = max(y1 - y0, 1e-6)
+    mx = bw * margin_frac
+    my = bh * margin_frac
+    x0 -= mx
+    y0 -= my
+    x1 += mx
+    y1 += my
+    x0 = max(0, min(int(round(x0)), src_w - 1))
+    y0 = max(0, min(int(round(y0)), src_h - 1))
+    x1 = max(x0 + 1, min(int(round(x1)), src_w))
+    y1 = max(y0 + 1, min(int(round(y1)), src_h))
+    return x0, y0, x1, y1
+
+
+def try_get_triangle_roi_from_yolo(maix_frame, src_w: int, src_h: int, logger=None):
+    """
+    用 YOLO 在 maix_frame 上检测靶环类，返回整图上的裁剪框 (x0,y0,x1,y1)；失败返回 None。
+
+    :param maix_frame: camera.read() 返回的 Maix 图像（与 nn.YOLOv5.detect 一致）
+    :param src_w, src_h: 与 img_cv / 标定一致的分辨率（通常与 camera 一致）
+    """
+    try:
+        import config as cfg
+    except Exception:
+        return None
+
+    if not bool(getattr(cfg, "TRIANGLE_YOLO_ROI_ENABLE", False)):
+        return None
+
+    model_path = getattr(cfg, "TRIANGLE_YOLO_MODEL_PATH", "") or ""
+    if not os.path.isfile(model_path):
+        if logger:
+            logger.warning(f"[YOLO-ROI] 模型文件不存在: {model_path}")
+        return None
+
+    det = _get_detector(model_path)
+    if det is None:
+        if logger:
+            logger.warning("[YOLO-ROI] 无法加载 nn.YOLOv5（非 Maix 环境或导入失败）")
+        return None
+
+    conf_th = float(getattr(cfg, "TRIANGLE_YOLO_CONF_TH", 0.5))
+    iou_th = float(getattr(cfg, "TRIANGLE_YOLO_IOU_TH", 0.45))
+    class_ids = getattr(cfg, "TRIANGLE_YOLO_RING_CLASS_IDS", (0,))
+    if isinstance(class_ids, int):
+        class_ids = (class_ids,)
+    margin_frac = float(getattr(cfg, "TRIANGLE_YOLO_ROI_MARGIN_FRAC", 0.12))
+    coord_mode = str(getattr(cfg, "TRIANGLE_YOLO_COORD_MODE", "native")).lower()
+    merge_mode = str(getattr(cfg, "TRIANGLE_YOLO_ROI_MERGE_MODE", "union")).lower()
+    reject_bad = bool(getattr(cfg, "TRIANGLE_YOLO_REJECT_BAD_ROI", True))
+
+    try:
+        raw = det.detect(maix_frame, conf_th=conf_th, iou_th=iou_th)
+    except Exception as e:
+        if logger:
+            logger.warning(f"[YOLO-ROI] detect 异常: {e}")
+        return None
+
+    objs = _normalize_objs(raw if raw is not None else [])
+
+    candidates = []
+    for o in objs:
+        cid = _det_obj_class_id(o)
+        if cid is not None and cid in class_ids:
+            candidates.append(o)
+
+    if not candidates and bool(getattr(cfg, "TRIANGLE_YOLO_RETRY_ON_EMPTY", False)):
+        retry_conf = float(getattr(cfg, "TRIANGLE_YOLO_RETRY_CONF_TH", conf_th))
+        if retry_conf > 0 and retry_conf < conf_th:
+            try:
+                raw_retry = det.detect(maix_frame, conf_th=retry_conf, iou_th=iou_th)
+                objs_retry = _normalize_objs(raw_retry if raw_retry is not None else [])
+                candidates_retry = []
+                for o in objs_retry:
+                    cid = _det_obj_class_id(o)
+                    if cid is not None and cid in class_ids:
+                        candidates_retry.append(o)
+                if candidates_retry:
+                    if logger:
+                        logger.info(
+                            f"[YOLO-ROI] conf={conf_th} 下 0 候选，"
+                            f"用 retry_conf={retry_conf} 重试得到 {len(candidates_retry)} 个候选"
+                        )
+                    objs = objs_retry
+                    candidates = candidates_retry
+                    conf_th = retry_conf
+                elif logger:
+                    logger.info(
+                        f"[YOLO-ROI] conf={conf_th} 下 0 候选；"
+                        f"retry_conf={retry_conf} 仍为 0 候选"
+                    )
+            except Exception as e:
+                if logger:
+                    logger.warning(f"[YOLO-ROI] 低阈值重试异常: {e}")
+
+    if not candidates:
+        if logger:
+            n = len(objs)
+            if n == 0:
+                logger.info(
+                    f"[YOLO-ROI] detect 返回 0 个框（conf≥{conf_th}）。"
+                    f"可尝试 config 里降低 TRIANGLE_YOLO_CONF_TH（如 0.25~0.35），"
+                    f"或确认射箭帧与训练图光照/构图接近。"
+                )
+            else:
+                seen = []
+                for o in objs[:8]:
+                    cid = _det_obj_class_id(o)
+                    sc = getattr(o, "score", None)
+                    try:
+                        sc_f = float(sc) if sc is not None else None
+                    except Exception:
+                        sc_f = None
+                    seen.append(f"cls={cid},score={sc_f}")
+                logger.info(
+                    f"[YOLO-ROI] 有 {n} 个框但类别不在 {class_ids} 内；"
+                    f"前几条: {seen}。请核对 TRIANGLE_YOLO_RING_CLASS_IDS，"
+                    f"或查看 Maix 文档中检测结果的类别字段名。"
+                )
+        return None
+
+    net_w = int(det.input_width())
+    net_h = int(det.input_height())
+
+    min_side = float(getattr(cfg, "TRIANGLE_YOLO_MIN_BOX_SIDE_PX", 8.0))
+    xy_list = []
+    for o in candidates:
+        x0n, y0n, x1n, y1n = _det_to_src_xyxy(o, coord_mode, src_w, src_h, net_w, net_h)
+        bw, bh = x1n - x0n, y1n - y0n
+        if bw >= min_side and bh >= min_side:
+            xy_list.append((x0n, y0n, x1n, y1n))
+
+    if not xy_list:
+        if logger:
+            logger.info(
+                f"[YOLO-ROI] {len(candidates)} 个候选经 min_side={min_side} 过滤后为空，放弃 ROI"
+            )
+        return None
+
+    merged = _merge_roi_xyxy(xy_list, merge_mode)
+    if merged is None:
+        return None
+    x0, y0, x1, y1 = merged
+
+    # clip 到画布（合并前框可能略越界）
+    x0 = max(0, min(x0, src_w - 1))
+    y0 = max(0, min(y0, src_h - 1))
+    x1 = max(x0 + 1, min(x1, src_w))
+    y1 = max(y0 + 1, min(y1, src_h))
+
+    x0, y0, x1, y1 = _expand_xyxy(x0, y0, x1, y1, src_w, src_h, margin_frac)
+
+    if reject_bad and not _roi_aspect_sane(x0, y0, x1, y1, src_w, src_h):
+        if logger:
+            logger.warning(
+                f"[YOLO-ROI] 裁剪框异常（过小或过扁）mode={coord_mode} merge={merge_mode} "
+                f"→ [{x0},{y0},{x1},{y1}]，放弃 ROI、三角形改用整图。"
+                f"若持续出现可尝试 coord_mode=letterbox/native 切换。"
+            )
+        return None
+
+    if logger:
+        nbox = len(candidates)
+        logger.info(
+            f"[YOLO-ROI] boxes={nbox} merge={merge_mode} coord={coord_mode} "
+            f"net_in={net_w}×{net_h}(来自模型) → crop=[{x0},{y0},{x1},{y1}] "
+            f"({x1-x0}×{y1-y0}px)"
+        )
+
+    return (x0, y0, x1, y1)
+
+
+def _expand_xyxy_local(x0, y0, x1, y1, w_lim, h_lim, margin_frac: float):
+    """在宽 w_lim、高 h_lim 的局部坐标系内扩展框。"""
+    bw = max(x1 - x0, 1e-6)
+    bh = max(y1 - y0, 1e-6)
+    mx = bw * margin_frac
+    my = bh * margin_frac
+    x0 -= mx
+    y0 -= my
+    x1 += mx
+    y1 += my
+    x0 = max(0, min(int(round(x0)), w_lim - 1))
+    y0 = max(0, min(int(round(y0)), h_lim - 1))
+    x1 = max(x0 + 1, min(int(round(x1)), w_lim))
+    y1 = max(y0 + 1, min(int(round(y1)), h_lim))
+    return x0, y0, x1, y1
+
+
+def try_black_triangle_boxes_work(img_rgb, ring_roi_xyxy, logger=None):
+    """
+    Stage2：在 **Stage1 靶环 ROI 裁切图** 上跑黑三角 YOLO（与训练时 stage2 构图一致），
+    检测框坐标已落在 **靶环裁切图**（与 try_triangle_scoring 中 img_work）同一坐标系，
+    返回 (x0,y0,x1,y1) 整数元组列表。
+
+    img_rgb: 与 try_triangle_scoring 相同的全图 RGB（numpy，H×W×3）。
+    ring_roi_xyxy: 全图上的 (rx0, ry0, rx1, ry1)，与 try_get_triangle_roi_from_yolo 一致。
+    """
+    if ring_roi_xyxy is None:
+        return []
+    if img_rgb is None or getattr(img_rgb, "size", 0) == 0:
+        return []
+    try:
+        import config as cfg
+    except Exception:
+        return []
+
+    if not bool(getattr(cfg, "TRIANGLE_BLACK_YOLO_ENABLE", False)):
+        return []
+
+    model_path = getattr(cfg, "TRIANGLE_BLACK_YOLO_MODEL_PATH", "") or ""
+    if not os.path.isfile(model_path):
+        if logger:
+            logger.warning(f"[YOLO-BLACK] 模型文件不存在: {model_path}")
+        return []
+
+    det = _get_detector(model_path)
+    if det is None:
+        if logger:
+            logger.warning("[YOLO-BLACK] 无法加载 nn.YOLOv5")
+        return []
+
+    conf_th = float(getattr(cfg, "TRIANGLE_BLACK_YOLO_CONF_TH", 0.5))
+    iou_th = float(getattr(cfg, "TRIANGLE_BLACK_YOLO_IOU_TH", 0.45))
+    class_ids = getattr(cfg, "TRIANGLE_BLACK_YOLO_CLASS_IDS", (0,))
+    if isinstance(class_ids, int):
+        class_ids = (class_ids,)
+    coord_mode = str(getattr(cfg, "TRIANGLE_BLACK_YOLO_COORD_MODE", "native")).lower()
+    margin_frac = float(getattr(cfg, "TRIANGLE_BLACK_YOLO_BOX_MARGIN_FRAC", 0.08))
+    min_side = float(getattr(cfg, "TRIANGLE_BLACK_YOLO_MIN_BOX_SIDE_PX", 6.0))
+    crop_min = int(getattr(cfg, "TRIANGLE_CROP_ROI_MIN_SIDE_PX", 64))
+
+    h_full, w_full = int(img_rgb.shape[0]), int(img_rgb.shape[1])
+    rx0, ry0, rx1, ry1 = [int(round(float(v))) for v in ring_roi_xyxy]
+    rx0 = max(0, min(rx0, w_full - 1))
+    ry0 = max(0, min(ry0, h_full - 1))
+    rx1 = max(rx0 + 1, min(rx1, w_full))
+    ry1 = max(ry0 + 1, min(ry1, h_full))
+    rw, rh = rx1 - rx0, ry1 - ry0
+
+    if rw < crop_min or rh < crop_min:
+        if logger:
+            logger.warning(
+                f"[YOLO-BLACK] Stage1 ROI 过小 {rw}×{rh} < {crop_min}，跳过黑三角检测"
+            )
+        return []
+
+    # 必须与相机帧缓冲区脱钩：切片常为非连续视图，直接喂 cv2image/NPU 易 SIGSEGV
+    slab = np.ascontiguousarray(
+        img_rgb[ry0:ry1, rx0:rx1], dtype=np.uint8
+    ).copy()
+    if slab.size == 0:
+        return []
+
+    _save_roi = bool(getattr(cfg, "TRIANGLE_BLACK_YOLO_SAVE_ROI_CROP", False))
+
+    try:
+        from maix import image as maix_image
+
+        # copy=True：零拷贝时 detect 内 OpenCV 可能对底层 Mat release 触发 !fixedSize() 断言。
+        roi_maix = maix_image.cv2image(slab, False, True)
+    except Exception as e:
+        if logger:
+            logger.warning(f"[YOLO-BLACK] 裁切图转 Maix image 失败: {e}")
+        return []
+
+    try:
+        raw = det.detect(roi_maix, conf_th=conf_th, iou_th=iou_th)
+    except Exception as e:
+        if logger:
+            logger.warning(f"[YOLO-BLACK] detect 异常: {e}")
+        return []
+
+    objs = _normalize_objs(raw if raw is not None else [])
+    net_w = int(det.input_width())
+    net_h = int(det.input_height())
+
+    n_raw = len(objs)
+    n_cls_ok = 0
+    n_too_small = 0
+
+    out_local = []
+    for o in objs:
+        cid = _det_obj_class_id(o)
+        if cid is None or cid not in class_ids:
+            continue
+        n_cls_ok += 1
+        x0f, y0f, x1f, y1f = _det_to_src_xyxy(o, coord_mode, rw, rh, net_w, net_h)
+        lx0 = max(0, min(float(x0f), rw - 1))
+        ly0 = max(0, min(float(y0f), rh - 1))
+        lx1 = max(lx0 + 1, min(float(x1f), rw))
+        ly1 = max(ly0 + 1, min(float(y1f), rh))
+        lx0, ly0, lx1, ly1 = int(round(lx0)), int(round(ly0)), int(round(lx1)), int(round(ly1))
+        if (lx1 - lx0) < min_side or (ly1 - ly0) < min_side:
+            n_too_small += 1
+            continue
+        lx0, ly0, lx1, ly1 = _expand_xyxy_local(
+            lx0, ly0, lx1, ly1, rw, rh, margin_frac
+        )
+        out_local.append((lx0, ly0, lx1, ly1))
+
+    out_local.sort(key=lambda t: ((t[1] + t[3]) * 0.5, (t[0] + t[2]) * 0.5))
+
+    if logger and bool(
+        getattr(cfg, "TRIANGLE_BLACK_YOLO_LOG_EACH_SHOT", True)
+    ):
+        msg = (
+            f"[YOLO-BLACK] Stage1裁切{rw}×{rh}上推理: raw={n_raw} 类∈{class_ids}→{n_cls_ok} "
+            f"过小丢弃→{n_too_small} 最终子框={len(out_local)} "
+            f"(conf={conf_th}, coord={coord_mode}, net={net_w}×{net_h}, "
+            f"ring全图=[{rx0},{ry0},{rx1},{ry1}])"
+        )
+        logger.info(msg)
+        if n_raw > 0 and n_cls_ok == 0:
+            seen = []
+            for o in objs[:8]:
+                cid = _det_obj_class_id(o)
+                sc = getattr(o, "score", None)
+                try:
+                    sc_f = float(sc) if sc is not None else None
+                except Exception:
+                    sc_f = None
+                seen.append(f"cls={cid},score={sc_f}")
+            logger.info(
+                f"[YOLO-BLACK] 有框但类别不在 {class_ids} 内；前几条: {seen}。"
+                f"请核对 TRIANGLE_BLACK_YOLO_CLASS_IDS。"
+            )
+        elif n_cls_ok > 0 and len(out_local) == 0:
+            logger.info(
+                f"[YOLO-BLACK] {n_cls_ok} 个目标类框但边长均 < min_side={min_side}，已全部丢弃。"
+            )
+
+    if _save_roi:
+        try:
+            base = (getattr(cfg, "TRIANGLE_BLACK_YOLO_ROI_CROP_DIR", "") or "").strip()
+            if not base:
+                base = os.path.join(
+                    getattr(cfg, "PHOTO_DIR", "/tmp") or "/tmp", "stage2_roi"
+                )
+            _draw = bool(
+                getattr(cfg, "TRIANGLE_BLACK_YOLO_SAVE_ROI_DRAW_BOXES", True)
+            )
+            _roi_max_raw = getattr(
+                cfg, "TRIANGLE_BLACK_YOLO_STAGE2_ROI_MAX_IMAGES", None
+            )
+            try:
+                _roi_max = (
+                    int(_roi_max_raw)
+                    if _roi_max_raw is not None
+                    else int(getattr(cfg, "MAX_IMAGES", 1000))
+                )
+            except (TypeError, ValueError):
+                _roi_max = int(getattr(cfg, "MAX_IMAGES", 1000))
+            slab_copy = np.ascontiguousarray(slab, dtype=np.uint8).copy()
+            boxes_copy = [tuple(t) for t in out_local]
+            threading.Thread(
+                target=_stage2_roi_crop_save_worker,
+                args=(
+                    slab_copy,
+                    boxes_copy,
+                    rx0,
+                    ry0,
+                    rw,
+                    rh,
+                    base,
+                    _draw,
+                    92,
+                    _roi_max,
+                    logger,
+                ),
+                daemon=True,
+            ).start()
+        except Exception as e:
+            if logger:
+                logger.warning(f"[YOLO-BLACK] 提交异步保存裁切图失败: {e}")
+
+    return out_local

test/test_audio.py

@@ -0,0 +1,50 @@
+# test_audio.pyx
+from maix import audio, time, app, gpio
+
+def run_player_loop():
+    """
+    播放控制主循环函数
+    """
+    # 初始化音频播放器
+    p = audio.Player("/root/gun.wav")
+    p.volume(40)
+    
+    # 初始化 GPIO 引脚为输出
+    led = gpio.GPIO("A25", gpio.Mode.OUT)
+    # 设置低电平
+    led.value(0)
+    
+    # 主循环
+    while not app.need_exit():
+        led.value(1)           # 点亮 LED
+        time.sleep_ms(200)     # 保持 200ms
+        led.value(0)           # 熄灭 LED
+        p.play()               # 播放音频
+        time.sleep_ms(1000)    # 等待 1 秒
+    
+    print("play finish!")
+
+
+# 可选：添加一个简单的测试函数
+def hello():
+    return "Hello from test_audio!"
+
+
+# 可选：添加一个初始化函数
+def init_led():
+    """单独测试 GPIO"""
+    led = gpio.GPIO("A25", gpio.Mode.OUT)
+    led.value(0)
+    return "LED initialized"
+
+
+# 可选：添加一个播放测试函数
+def test_play():
+    """单独测试音频播放"""
+    p = audio.Player("/root/gun.wav")
+    p.volume(50)
+    p.play()
+    return "Playing..."
+
+
+run_player_loop()

test/test_button.py

@@ -0,0 +1,25 @@
+from maix import audio, time, app,gpio
+
+
+# button1 = gpio.GPIO("ADC", gpio.Mode.IN)
+button3 = gpio.GPIO("A26", gpio.Mode.IN) # 可用
+button2 = gpio.GPIO("A16", gpio.Mode.IN)
+#设置低电平
+from maix.peripheral import adc
+channel = 0
+res_bit = adc.RES_BIT_12
+_adc_obj = adc.ADC(channel, res_bit)
+
+
+while not app.need_exit():
+    # print(f"b1: {button1.value()}")
+
+    print(f"b2: {button2.value()}")
+
+    # print(_adc_obj.read_vol())
+    print(f"b3: {button3.value()}")
+    time.sleep_ms(50)
+
+    # time.sleep_ms(1000)
+
+

test/test_camera_rtsp.py

@@ -0,0 +1,36 @@
+# from maix import time, rtsp, camera, image
+
+# # 1. 初始化摄像头（注意：RTSP需要NV21格式）
+# # 分辨率可以根据需要调整，如 640x480 或 1280x720
+# cam = camera.Camera(640, 480, image.Format.FMT_YVU420SP)
+
+# # 2. 创建并启动RTSP服务器
+# server = rtsp.Rtsp()
+# server.bind_camera(cam)
+# server.start()
+
+# # 3. 打印出访问地址，例如： rtsp://192.168.xxx.xxx:8554/live
+# print("RTSP 流地址:", server.get_url())
+
+# # 4. 保持服务运行
+# while True:
+#     time.sleep(1)
+
+
+
+from maix import camera, time, app, http, image
+
+# 初始化相机，注意格式要用 FMT_RGB888（JPEG 编码需要 RGB 输入）
+cam = camera.Camera(640, 480, image.Format.FMT_RGB888)
+
+# 创建 JPEG 流服务器
+stream = http.JpegStreamer()
+stream.start()
+
+print("RTSP 替代方案 - HTTP JPEG 流地址: http://{}:{}".format(stream.host(), stream.port()))
+print("请在浏览器或 OpenCV 中访问: http://<MaixCAM_IP>:8000/stream")
+
+while not app.need_exit():
+    img = cam.read()
+    jpg = img.to_jpeg()      # 将 RGB 图像编码为 JPEG
+    stream.write(jpg)        # 推送到 HTTP 客户端

test/test_cammera.py

@@ -0,0 +1,20 @@
+# test_camera.py
+from maix import camera, display, time
+
+try:
+    print("Initializing camera...")
+    cam = camera.Camera(640,480)
+    # cam = camera.Camera(1280,720)
+    # cam.get_exposure_us()
+    # print("Camera exposure: ", cam.get_exposure_us())
+    print("Camera initialized successfully!")
+    
+    disp = display.Display()
+    
+    while True:
+        frame = cam.read()
+        disp.show(frame)
+        time.sleep_ms(50)
+        
+except Exception as e:
+    print(f"Error: {e}")

test/test_decect_circle.py

@@ -0,0 +1,620 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+离线测试脚本：直接复用 detect_circle 逻辑进行测试
+运行环境：MaixPy (Sipeed MAIX)
+"""
+import sys
+import os
+# import time
+from maix import image,time
+import cv2
+import numpy as np
+
+# ==================== 全局配置 (与 test_main.py 保持一致) ====================
+REAL_RADIUS_CM = 20  # 靶心实际半径（厘米）
+
+# ==================== 复制的核心算法 ====================
+# 注意：这里直接复制了 detect_circle 的逻辑，避免 import main 导致的冲突
+
+
+def detect_circle_v3(frame, laser_point=None):
+    """检测图像中的靶心（优先清晰轮廓，其次黄色区域）- 返回椭圆参数版本
+    增加红色圆圈检测，验证黄色圆圈是否为真正的靶心
+    如果提供 laser_point，会选择最接近激光点的目标
+    
+    Args:
+        frame: 图像帧
+        laser_point: 激光点坐标 (x, y)，用于多目标场景下的目标选择
+    
+    Returns:
+        (result_img, best_center, best_radius, method, best_radius1, ellipse_params)
+    """
+    img_cv = image.image2cv(frame, False, False)
+    
+    best_center = best_radius = best_radius1 = method = None
+    ellipse_params = None
+    
+    # HSV 黄色掩码检测（模糊靶心）
+    hsv = cv2.cvtColor(img_cv, cv2.COLOR_RGB2HSV)
+    h, s, v = cv2.split(hsv)
+
+    # 调整饱和度策略：稍微增强，不要过度
+    s = np.clip(s * 1.1, 0, 255).astype(np.uint8) 
+
+    hsv = cv2.merge((h, s, v))
+
+    # 放宽 HSV 阈值范围（针对模糊图像的关键调整）
+    lower_yellow = np.array([7, 80, 0])   # 饱和度下限降低，捕捉淡黄色
+    upper_yellow = np.array([32, 255, 255]) # 亮度上限拉满
+
+    mask_yellow = cv2.inRange(hsv, lower_yellow, upper_yellow)
+
+    # 调整形态学操作
+    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
+    mask_yellow = cv2.morphologyEx(mask_yellow, cv2.MORPH_CLOSE, kernel) 
+
+    contours_yellow, _ = cv2.findContours(mask_yellow, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+    # 存储所有有效的黄色-红色组合
+    valid_targets = []
+    
+    if contours_yellow:
+        for cnt_yellow in contours_yellow:
+            area = cv2.contourArea(cnt_yellow)
+            perimeter = cv2.arcLength(cnt_yellow, True)
+
+            # 计算圆度
+            if perimeter > 0:
+                circularity = (4 * np.pi * area) / (perimeter * perimeter)
+            else:
+                circularity = 0
+
+            logger = get_logger()
+            if area > 50 and circularity > 0.7:
+                if logger:
+                    logger.info(f"[target] -> 面积:{area}, 圆度:{circularity:.2f}")
+                # 尝试拟合椭圆
+                yellow_center = None
+                yellow_radius = None
+                yellow_ellipse = None
+                
+                if len(cnt_yellow) >= 5:
+                    (x, y), (width, height), angle = cv2.fitEllipse(cnt_yellow)
+                    yellow_ellipse = ((x, y), (width, height), angle)
+                    axes_minor = min(width, height)
+                    radius = axes_minor / 2
+                    yellow_center = (int(x), int(y))
+                    yellow_radius = int(radius)
+                else:
+                    (x, y), radius = cv2.minEnclosingCircle(cnt_yellow)
+                    yellow_center = (int(x), int(y))
+                    yellow_radius = int(radius)
+                    yellow_ellipse = None
+
+                # 如果检测到黄色圆圈，再检测红色圆圈进行验证
+                if yellow_center and yellow_radius:
+                    # HSV 红色掩码检测（红色在HSV中跨越0度，需要两个范围）
+                    # 红色范围1: 0-10度（接近0度的红色）
+                    lower_red1 = np.array([0, 80, 0])
+                    upper_red1 = np.array([10, 255, 255])
+                    mask_red1 = cv2.inRange(hsv, lower_red1, upper_red1)
+                    
+                    # 红色范围2: 170-180度（接近180度的红色）
+                    lower_red2 = np.array([170, 80, 0])
+                    upper_red2 = np.array([180, 255, 255])
+                    mask_red2 = cv2.inRange(hsv, lower_red2, upper_red2)
+                    
+                    # 合并两个红色掩码
+                    mask_red = cv2.bitwise_or(mask_red1, mask_red2)
+                    
+                    # 形态学操作
+                    kernel_red = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
+                    mask_red = cv2.morphologyEx(mask_red, cv2.MORPH_CLOSE, kernel_red)
+                    
+                    contours_red, _ = cv2.findContours(mask_red, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+                    
+                    found_valid_red = False
+                    
+                    if contours_red:
+                        # 找到所有符合条件的红色圆圈
+                        for cnt_red in contours_red:
+                            area_red = cv2.contourArea(cnt_red)
+                            perimeter_red = cv2.arcLength(cnt_red, True)
+                            
+                            if perimeter_red > 0:
+                                circularity_red = (4 * np.pi * area_red) / (perimeter_red * perimeter_red)
+                            else:
+                                circularity_red = 0
+                            
+                            # 红色圆圈也应该有一定的圆度
+                            if area_red > 50 and circularity_red > 0.6:
+                                # 计算红色圆圈的中心和半径
+                                if len(cnt_red) >= 5:
+                                    (x_red, y_red), (w_red, h_red), angle_red = cv2.fitEllipse(cnt_red)
+                                    radius_red = min(w_red, h_red) / 2
+                                    red_center = (int(x_red), int(y_red))
+                                    red_radius = int(radius_red)
+                                else:
+                                    (x_red, y_red), radius_red = cv2.minEnclosingCircle(cnt_red)
+                                    red_center = (int(x_red), int(y_red))
+                                    red_radius = int(radius_red)
+                                
+                                # 计算黄色和红色圆心的距离
+                                if red_center:
+                                    dx = yellow_center[0] - red_center[0]
+                                    dy = yellow_center[1] - red_center[1]
+                                    distance = np.sqrt(dx*dx + dy*dy)
+                                    
+                                    # 圆心距离阈值：应该小于黄色半径的某个倍数（比如1.5倍）
+                                    max_distance = yellow_radius * 1.5
+                                    
+                                    # 红色圆圈应该比黄色圆圈大（外圈）
+                                    if distance < max_distance and red_radius > yellow_radius * 0.8:
+                                        found_valid_red = True
+                                        logger = get_logger()
+                                        if logger:
+                                            logger.info(f"[target] -> 找到匹配的红圈: 黄心({yellow_center}), 红心({red_center}), 距离:{distance:.1f}, 黄半径:{yellow_radius}, 红半径:{red_radius}")
+                                        
+                                        # 记录这个有效目标
+                                        valid_targets.append({
+                                            'center': yellow_center,
+                                            'radius': yellow_radius,
+                                            'ellipse': yellow_ellipse,
+                                            'area': area
+                                        })
+                                        break
+                    
+                    if not found_valid_red:
+                        logger = get_logger()
+                        if logger:
+                            logger.debug("Debug -> 未找到匹配的红色圆圈，可能是误识别")
+    
+    # 从所有有效目标中选择最佳目标
+    if valid_targets:
+        if laser_point:
+            # 如果有激光点，选择最接近激光点的目标
+            best_target = None
+            min_distance = float('inf')
+            for target in valid_targets:
+                dx = target['center'][0] - laser_point[0]
+                dy = target['center'][1] - laser_point[1]
+                distance = np.sqrt(dx*dx + dy*dy)
+                if distance < min_distance:
+                    min_distance = distance
+                    best_target = target
+            if best_target:
+                best_center = best_target['center']
+                best_radius = best_target['radius']
+                ellipse_params = best_target['ellipse']
+                method = "v3_ellipse_red_validated_laser_selected"
+                best_radius1 = best_radius * 5
+        else:
+            # 如果没有激光点，选择面积最大的目标
+            best_target = max(valid_targets, key=lambda t: t['area'])
+            best_center = best_target['center']
+            best_radius = best_target['radius']
+            ellipse_params = best_target['ellipse']
+            method = "v3_ellipse_red_validated"
+            best_radius1 = best_radius * 5
+
+    result_img = image.cv2image(img_cv, False, False)
+    return result_img, best_center, best_radius, method, best_radius1, ellipse_params
+
+def detect_circle(frame):
+    """检测图像中的靶心（优先清晰轮廓，其次黄色区域）"""
+    img_cv = image.image2cv(frame, False, False)
+    # gray = cv2.cvtColor(img_cv, cv2.COLOR_RGB2GRAY)
+    # blurred = cv2.GaussianBlur(gray, (5, 5), 0)
+    # edged = cv2.Canny(blurred, 50, 150)
+    # kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
+    # ceroded = cv2.erode(cv2.dilate(edged, kernel), kernel)
+
+    # contours, _ = cv2.findContours(ceroded, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+    # best_center = best_radius = best_radius1 = method = None
+
+    # hsv = cv2.cvtColor(img_cv, cv2.COLOR_RGB2HSV)
+    # h, s, v = cv2.split(hsv)
+    # s = np.clip(s * 2, 0, 255).astype(np.uint8)
+    # hsv = cv2.merge((h, s, v))
+    # lower_yellow = np.array([7, 80, 0])
+    # upper_yellow = np.array([32, 255, 182])
+    # mask = cv2.inRange(hsv, lower_yellow, upper_yellow)
+    # kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
+    # mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
+    # mask = cv2.morphologyEx(mask, cv2.MORPH_DILATE, kernel)
+    # contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    # if contours:
+    #     largest = max(contours, key=cv2.contourArea)
+    #     if cv2.contourArea(largest) > 50:
+    #         (x, y), radius = cv2.minEnclosingCircle(largest)
+    #         best_center = (int(x), int(y))
+    #         best_radius = int(radius)
+    #         best_radius1 = radius * 5
+    #         method = "v2"
+
+    # auto
+    # R:31 M:v2 D:2.410110127692767
+    # hsv = cv2.cvtColor(img_cv, cv2.COLOR_RGB2HSV)
+    # h, s, v = cv2.split(hsv)
+
+    # # 1. 增强饱和度（模糊照片需要更强的增强）
+    # s = np.clip(s * 2.5, 0, 255).astype(np.uint8)  # 从2.0改为2.5
+
+    # # 2. 增强亮度（模糊照片可能偏暗）
+    # v = np.clip(v * 1.2, 0, 255).astype(np.uint8)  # 新增：提升亮度
+
+    # hsv = cv2.merge((h, s, v))
+
+    # # 3. 放宽HSV颜色范围（特别是模糊照片）
+    # # 降低饱和度下限，提高亮度上限
+    # lower_yellow = np.array([5, 50, 30])   # H:5-35, S:50-255, V:30-255
+    # upper_yellow = np.array([35, 255, 255])
+
+    # mask = cv2.inRange(hsv, lower_yellow, upper_yellow)
+
+    # # 4. 增强形态学操作（连接被分割的区域）
+    # kernel_small = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
+    # kernel_large = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (9, 9))  # 更大的核
+
+    # # 先开运算去除噪声
+    # mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel_small)
+    # # 多次膨胀连接区域（模糊照片需要更多膨胀）
+    # mask = cv2.dilate(mask, kernel_large, iterations=2)  # 增加迭代次数
+    # mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel_large)  # 闭运算填充空洞
+
+    # contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    # if contours:
+    #     largest = max(contours, key=cv2.contourArea)
+    #     area = cv2.contourArea(largest)
+    #     if area > 50:
+    #         # 5. 使用面积计算等效半径（更准确）
+    #         equivalent_radius = np.sqrt(area / np.pi)
+            
+    #         # 6. 同时使用minEnclosingCircle作为备选（取较大值）
+    #         (x, y), enclosing_radius = cv2.minEnclosingCircle(largest)
+            
+    #         # 取两者中的较大值，确保不遗漏
+    #         radius = max(equivalent_radius, enclosing_radius)
+            
+    #         best_center = (int(x), int(y))
+    #         best_radius = int(radius)
+    #         best_radius1 = radius * 5
+    #         method = "v2"
+
+    # codegee
+    # R:24 M:v2 D:3.061493895819174
+    # R:22 M:v2 D:3.3644971681267077  np.clip(s * 1.1, 0, 255)
+    hsv = cv2.cvtColor(img_cv, cv2.COLOR_RGB2HSV)
+    h, s, v = cv2.split(hsv)
+
+    # 2. 调整饱和度策略：
+    # 不要暴力翻倍，可以尝试稍微增强，或者使用 CLAHE 增强亮度/对比度
+    # 这里我们稍微增加一点饱和度，并确保不溢出
+    s = np.clip(s * 1.1, 0, 255).astype(np.uint8) 
+    # 对亮度通道 v 也可以做一点 CLAHE 处理来增强对比度（可选）
+    # clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))
+    # v = clahe.apply(v)
+
+    hsv = cv2.merge((h, s, v))
+
+    # 3. 放宽 HSV 阈值范围（针对模糊图像的关键调整）
+    # 降低 S 的下限 (80 -> 35)，提高 V 的上限 (182 -> 255)
+    lower_yellow = np.array([7, 80, 0])   # 饱和度下限降低，捕捉淡黄色
+    upper_yellow = np.array([32, 255, 255]) # 亮度上限拉满
+
+    mask = cv2.inRange(hsv, lower_yellow, upper_yellow)
+
+    # 4. 调整形态学操作
+    # 去掉 MORPH_OPEN，因为它会减小面积。
+    # 使用 MORPH_CLOSE (先膨胀后腐蚀) 来填充内部小黑洞，连接近邻区域
+    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
+    mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel) 
+    # 再进行一次膨胀，确保边缘被包含进来
+    # mask = cv2.dilate(mask, kernel, iterations=1) 
+
+    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+    if contours:
+        largest = max(contours, key=cv2.contourArea)
+        
+        # 这里可以适当降低面积阈值，或者保持不变
+        if cv2.contourArea(largest) > 50:
+            # (x, y), radius = cv2.minEnclosingCircle(largest)
+            # best_center = (int(x), int(y))
+            # best_radius = int(radius)
+            
+            # --- 核心修改开始 ---
+            # 1. 尝试拟合椭圆 (需要轮廓点至少为5个)
+            if len(largest) >= 5:
+                # 返回值: ((中心x, 中心y), (长轴, 短轴), 旋转角度)
+                (x, y), (axes_major, axes_minor), angle = cv2.fitEllipse(largest)
+
+                # 2. 计算半径
+                # 选项A：取长短轴的平均值 (比较稳健)
+                # radius = (axes_major + axes_minor) / 4
+
+                # 选项B：直接取短轴的一半 (抗模糊最强，推荐)
+                radius = axes_minor / 2
+
+                best_center = (int(x), int(y))
+                best_radius = int(radius)
+                method = "v2_ellipse"
+            else:
+                # 如果点太少无法拟合椭圆，降级回 minEnclosingCircle
+                (x, y), radius = cv2.minEnclosingCircle(largest)
+                best_center = (int(x), int(y))
+                best_radius = int(radius)
+                method = "v2"
+            # --- 核心修改结束 ---
+
+            # 你的后续逻辑
+            best_radius1 = radius * 5
+            
+
+    # operas 4.5
+    # R:25 M:v2 D:2.9554872521538527
+    # hsv = cv2.cvtColor(img_cv, cv2.COLOR_RGB2HSV)
+    # h, s, v = cv2.split(hsv)
+    
+    # # 1. 适度增强饱和度（不要过度，否则噪声也会增强）
+    # s = np.clip(s * 1.5, 0, 255).astype(np.uint8)
+    # hsv = cv2.merge((h, s, v))
+    
+    # # 2. 放宽 HSV 阈值范围（关键改动）
+    # # - 饱和度下限从 80 降到 40（捕捉淡黄色）
+    # # - 亮度上限从 182 提高到 255（允许更亮的黄色）
+    # lower_yellow = np.array([7, 40, 30])
+    # upper_yellow = np.array([35, 255, 255])
+    
+    # mask = cv2.inRange(hsv, lower_yellow, upper_yellow)
+    
+    # # 3. 调整形态学操作：用 CLOSE 替代 OPEN
+    # # CLOSE（先膨胀后腐蚀）：填充内部空洞，连接相邻区域
+    # # OPEN（先腐蚀后膨胀）：会缩小区域，不适合模糊图像
+    # kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (7, 7))  # 稍大的核
+    # mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)
+    # mask = cv2.dilate(mask, kernel, iterations=1)  # 额外膨胀，确保边缘被包含
+    
+    # contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    # if contours:
+    #     largest = max(contours, key=cv2.contourArea)
+    #     if cv2.contourArea(largest) > 50:
+    #         (x, y), radius = cv2.minEnclosingCircle(largest)
+    #         best_center = (int(x), int(y))
+    #         best_radius = int(radius)
+    #         best_radius1 = radius * 5
+    #         method = "v2"
+
+            # # --- 新增：将 Mask 叠加到原图上用于调试 ---
+            # # 创建一个彩色掩码（红色通道为255，其他为0）
+            # mask_overlay = np.zeros_like(img_cv)
+            # mask_overlay[:, :, 2] = mask  # 将掩码放在红色通道 (BGR中的R)
+            #
+            # cv2.addWeighted(img_cv, 0.6, mask_overlay, 0.4, 0, img_cv)
+
+    result_img = image.cv2image(img_cv, False, False)
+    return result_img, best_center, best_radius, method, best_radius1
+
+
+def detect_circle_v2(frame):
+    """检测图像中的靶心（优先清晰轮廓，其次黄色区域）- 返回椭圆参数版本"""
+    global REAL_RADIUS_CM
+    img_cv = image.image2cv(frame, False, False)
+    
+    best_center = best_radius = best_radius1 = method = None
+    ellipse_params = None  # 存储椭圆参数 ((x, y), (axes_major, axes_minor), angle)
+    
+    # HSV 黄色掩码检测（模糊靶心）
+    hsv = cv2.cvtColor(img_cv, cv2.COLOR_RGB2HSV)
+    h, s, v = cv2.split(hsv)
+
+    # 调整饱和度策略：稍微增强，不要过度
+    s = np.clip(s * 1.1, 0, 255).astype(np.uint8) 
+
+    hsv = cv2.merge((h, s, v))
+
+    # 放宽 HSV 阈值范围（针对模糊图像的关键调整）
+    lower_yellow = np.array([7, 80, 0])   # 饱和度下限降低，捕捉淡黄色
+    upper_yellow = np.array([32, 255, 255]) # 亮度上限拉满
+
+    mask = cv2.inRange(hsv, lower_yellow, upper_yellow)
+
+    # 调整形态学操作
+    # 使用 MORPH_CLOSE (先膨胀后腐蚀) 来填充内部小黑洞，连接近邻区域
+    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
+    mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel) 
+
+    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+    if contours:
+        largest = max(contours, key=cv2.contourArea)
+        
+        if cv2.contourArea(largest) > 50:
+            # 尝试拟合椭圆 (需要轮廓点至少为5个)
+            if len(largest) >= 5:
+                # 返回值: ((中心x, 中心y), (width, height), 旋转角度)
+                # 注意：width 和 height 是外接矩形的尺寸，不是长轴和短轴
+                (x, y), (width, height), angle = cv2.fitEllipse(largest)
+                
+                # 保存椭圆参数（保持原始顺序，用于绘制）
+                ellipse_params = ((x, y), (width, height), angle)
+                
+                # 计算半径：使用较小的尺寸作为短轴
+                axes_minor = min(width, height)
+                radius = axes_minor / 2
+
+                best_center = (int(x), int(y))
+                best_radius = int(radius)
+                method = "v2_ellipse"
+            else:
+                # 如果点太少无法拟合椭圆，降级回 minEnclosingCircle
+                (x, y), radius = cv2.minEnclosingCircle(largest)
+                best_center = (int(x), int(y))
+                best_radius = int(radius)
+                method = "v2"
+                ellipse_params = None  # 圆形，没有椭圆参数
+
+            best_radius1 = radius * 5
+
+    result_img = image.cv2image(img_cv, False, False)
+    return result_img, best_center, best_radius, method, best_radius1, ellipse_params
+
+# ==================== 测试逻辑 ====================
+
+def run_offline_test(image_path):
+    """读取图片，检测圆，绘制结果，保存图片"""
+    
+    # 1. 检查文件是否存在
+    if not os.path.exists(image_path):
+        print(f"[ERROR] 找不到图片文件: {image_path}")
+        return
+
+    # 2. 使用 maix.image 读取图片 (适配 MaixPy v4)
+    try:
+        # 使用 image.load 读取文件，返回 Image 对象
+        img = image.load(image_path)
+        print(f"[INFO] 成功读取图片: {image_path} (尺寸: {img.width()}x{img.height()})")
+    except Exception as e:
+        print(f"[ERROR] 读取图片失败: {e}")
+        print("提示：请确认 MaixPy 版本是否为 v4，且图片路径正确。")
+        return
+
+
+    # 3. 调用 detect_circle_v2 函数
+    print("[INFO] 正在调用 detect_circle_v2 进行检测...")
+    start_time = time.ticks_ms()
+    
+    result_img, center, radius, method, radius1, ellipse_params = detect_circle_v3(img)
+    
+    cost_time = time.ticks_ms() - start_time
+    print(f"[INFO] 检测完成，耗时: {cost_time}ms")
+    print(f"       结果 -> 圆心: {center}, 半径: {radius}, 方法: {method}")
+    if ellipse_params:
+        (ell_center, (width, height), angle) = ellipse_params
+        print(f"       椭圆 -> 中心: ({ell_center[0]:.1f}, {ell_center[1]:.1f}), 长轴: {max(width, height):.1f}, 短轴: {min(width, height):.1f}, 角度: {angle:.1f}°")
+
+    # 4. 绘制辅助线（可选，用于调试）
+    if center and radius:
+        # 为了绘制椭圆，需要转换回 cv2 图像
+        img_cv = image.image2cv(result_img, False, False)
+        
+        cx, cy = center
+        
+        # 如果有椭圆参数，绘制椭圆
+        if ellipse_params:
+            (ell_center, (width, height), angle) = ellipse_params
+            cx_ell, cy_ell = int(ell_center[0]), int(ell_center[1])
+            
+            # 确定长轴和短轴
+            if width >= height:
+                # width 是长轴，height 是短轴
+                axes_major = width
+                axes_minor = height
+                major_angle = angle  # 长轴角度就是 angle
+                minor_angle = angle + 90  # 短轴角度 = 长轴角度 + 90度
+            else:
+                # height 是长轴，width 是短轴
+                axes_major = height
+                axes_minor = width
+                major_angle = angle + 90  # 长轴角度 = width角度 + 90度
+                minor_angle = angle  # 短轴角度就是 angle
+            
+            # 使用 OpenCV 绘制椭圆（绿色，线宽2）
+            cv2.ellipse(img_cv, 
+                    (cx_ell, cy_ell),              # 中心点
+                    (int(width/2), int(height/2)), # 半宽、半高
+                    angle,                          # 旋转角度（OpenCV需要原始angle）
+                    0, 360,                         # 起始和结束角度
+                    (0, 255, 0),                    # 绿色 (RGB格式)
+                    2)                              # 线宽
+            
+            # 绘制椭圆中心点（红色）
+            cv2.circle(img_cv, (cx_ell, cy_ell), 3, (255, 0, 0), -1)
+            
+            import math            
+            # 绘制短轴（蓝色线条）
+            minor_length = axes_minor / 2
+            minor_angle_rad = math.radians(minor_angle)
+            dx_minor = minor_length * math.cos(minor_angle_rad)
+            dy_minor = minor_length * math.sin(minor_angle_rad)
+            pt1_minor = (int(cx_ell - dx_minor), int(cy_ell - dy_minor))
+            pt2_minor = (int(cx_ell + dx_minor), int(cy_ell + dy_minor))
+            cv2.line(img_cv, pt1_minor, pt2_minor, (0, 0, 255), 2)  # 蓝色 (RGB格式)
+        else:
+            # 如果没有椭圆参数，绘制圆形（红色）
+            cv2.circle(img_cv, (cx, cy), radius, (0, 0, 255), 2)
+            cv2.circle(img_cv, (cx, cy), 2, (0, 0, 255), -1)
+        
+        # 转换回 maix image
+        result_img = image.cv2image(img_cv, False, False)
+        
+        # 定义颜色对象用于文字
+        try:
+            color_black = image.Color.from_rgb(0,0,0)
+        except AttributeError:
+            color_black = image.Color(0,0,0)
+
+        # D. 添加文字信息
+        FOCAL_LENGTH_PIX = 1900
+        d = (REAL_RADIUS_CM * FOCAL_LENGTH_PIX) / radius1 / 100.0
+        info_str = f"R:{radius} M:{method} D:{d:.2f}" 
+        print(info_str)
+        
+        # 计算文字位置，防止超出图片边界
+        r_outer = int(radius * 11.0) if radius else 100
+        text_y = cy - r_outer - 20 if cy > r_outer + 20 else cy + r_outer + 20
+        
+        # 调用 draw_string
+        result_img.draw_string(0, 0, info_str, color=color_black, scale=1.0)
+
+
+    # 5. 保存结果图片
+    output_path = image_path.replace(".bmp", "_result.bmp")
+    output_path = image_path.replace(".jpg", "_result.jpg")
+    try:
+        result_img.save(output_path, quality=100)
+        print(f"[SUCCESS] 结果已保存至: {output_path}")
+    except Exception as e:
+        print(f"[ERROR] 保存图片失败: {e}")
+
+if __name__ == "__main__":
+    # ================= 配置区域 =================
+    
+    # 1. 设置要测试的图片路径
+    # 建议将图片放在与脚本同级目录，或者使用绝对路径
+    TARGET_IMAGE = "/root/phot/None_314_258_0_0041.bmp" 
+    
+    # TARGET_DIR = "/root/phot_test2"  # 修改为你想要读取的目录路径
+    
+    # 支持的图片格式
+    IMAGE_EXTENSIONS = ['.jpg', '.jpeg', '.png', '.bmp']
+    
+    # ================= 执行区域 =================
+    if 'TARGET_DIR' in locals():
+        # 读取目录下所有图片文件，过滤掉 _result.jpg 后缀的文件
+        image_files = []
+        if os.path.exists(TARGET_DIR) and os.path.isdir(TARGET_DIR):
+            for filename in os.listdir(TARGET_DIR):
+                # 检查文件扩展名
+                if any(filename.lower().endswith(ext) for ext in IMAGE_EXTENSIONS):
+                    # 过滤掉 _result.jpg 后缀的文件
+                    if not filename.endswith('_result.jpg'):
+                        filepath = os.path.join(TARGET_DIR, filename)
+                        if os.path.isfile(filepath):
+                            image_files.append(filepath)
+            
+            # 按文件名排序（可选）
+            image_files.sort()
+            
+            print(f"[INFO] 在目录 {TARGET_DIR} 中找到 {len(image_files)} 张图片")
+            
+            # 处理每张图片
+            for img_path in image_files:
+                print(f"\n{'='*10} 开始处理: {img_path} {'='*10}")
+                run_offline_test(img_path)
+        else:
+            print(f"[ERROR] 目录不存在或不是有效目录: {TARGET_DIR}")
+        
+    else:
+        run_offline_test(TARGET_IMAGE)

test/test_i2c.py

@@ -0,0 +1,61 @@
+#!/usr/bin/env python3
+# test_i2c_devices.py
+
+import os
+from maix import i2c
+
+def list_i2c_devices():
+    """List available I2C device nodes"""
+    print("Available I2C devices:")
+    
+    # Check /dev directory
+    try:
+        dev_files = os.listdir("/dev")
+        i2c_devices = [f for f in dev_files if "i2c" in f]
+        if i2c_devices:
+            for dev in sorted(i2c_devices):
+                print(f"  /dev/{dev}")
+        else:
+            print("  No /dev/i2c-* devices found!")
+    except Exception as e:
+        print(f"  Error listing /dev: {e}")
+
+def try_i2c_bus(bus_num):
+    """Try to initialize an I2C bus"""
+    try:
+        bus = i2c.I2C(bus_num, i2c.Mode.MASTER)
+        print(f"  I2C bus {bus_num}: OK")
+        return True
+    except RuntimeError as e:
+        print(f"  I2C bus {bus_num}: {e}")
+        return False
+    except Exception as e:
+        print(f"  I2C bus {bus_num}: Unexpected error: {e}")
+        return False
+
+def main():
+    print("=" * 60)
+    print("I2C Device Diagnostic")
+    print("=" * 60)
+    
+    # List kernel devices
+    list_i2c_devices()
+    
+    # Try common bus numbers
+    print("\nTesting I2C buses:")
+    working_buses = []
+    for bus_num in range(10):
+        if try_i2c_bus(bus_num):
+            working_buses.append(bus_num)
+    
+    print(f"\nWorking buses: {working_buses}")
+    
+    if not working_buses:
+        print("\nERROR: No I2C buses available!")
+        print("Possible causes:")
+        print("  1. I2C kernel driver not loaded")
+        print("  2. Device tree doesn't enable I2C")
+        print("  3. Different kernel version with different device naming")
+
+if __name__ == "__main__":
+    main()

test/test_laser.py

@@ -0,0 +1,246 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+M01激光测距模块测试脚本 - 修正版
+基于文档中的完整命令示例
+"""
+
+from maix import uart, pinmap, time
+import binascii
+
+# ==================== 配置 ====================
+UART_PORT = "/dev/ttyS1"
+BAUDRATE = 9600
+
+# 初始化串口
+try:
+    pinmap.set_pin_function("A18", "UART1_RX")
+    pinmap.set_pin_function("A19", "UART1_TX")
+    laser_uart = uart.UART(UART_PORT, BAUDRATE)
+    print("✅ 硬件初始化完成")
+except Exception as e:
+    print(f"❌ 初始化失败: {e}")
+    exit(1)
+
+# ==================== 根据文档的完整命令集 ====================
+# 1. 激光开关（文档2.3.10，已验证可用）
+LASER_ON_CMD = bytes([0xAA, 0x00, 0x01, 0xBE, 0x00, 0x01, 0x00, 0x01, 0xC1])
+LASER_OFF_CMD = bytes([0xAA, 0x00, 0x01, 0xBE, 0x00, 0x01, 0x00, 0x00, 0xC0])
+
+# 2. 尝试不同的测距命令格式
+TEST_COMMANDS = [
+    # 格式1：文档2.3.12的单次测量（您测试失败的）
+    {
+        "name": "单次测量 (0x0020)",
+        "cmd": bytes([0xAA, 0x00, 0x00, 0x20, 0x00, 0x01, 0x00, 0x00, 0x21]),
+        "desc": "文档2.3.12 示例命令"
+    },
+    # 格式2：文档2.3.7的读取测量结果
+    {
+        "name": "读取测量结果 (0x0022)",
+        "cmd": bytes([0xAA, 0x80, 0x00, 0x22, 0xA2]),
+        "desc": "文档2.3.7 读取测量结果"
+    },
+    # 格式3：文档2.3.13的快速测量
+    {
+        "name": "快速测量 (0x0022带数据)",
+        "cmd": bytes([0xAA, 0x00, 0x00, 0x22, 0x00, 0x01, 0x00, 0x00, 0x23]),
+        "desc": "文档2.3.13 快速测量"
+    },
+    # 格式4：连续测量模式
+    {
+        "name": "连续测量模式 (0x0021)",
+        "cmd": bytes([0xAA, 0x00, 0x00, 0x21, 0x00, 0x01, 0x00, 0x00, 0x22]),
+        "desc": "文档2.3.14 连续测量"
+    }
+]
+
+def clear_buffer():
+    """清空串口缓冲区"""
+    try:
+        data = laser_uart.read(-1)
+        if data:
+            print(f"清空: {len(data)}字节")
+    except:
+        pass
+
+def send_and_wait(cmd, name, wait_time=2000):
+    """发送命令并等待响应"""
+    print(f"\n📤 发送: {name}")
+    print(f"   命令: {cmd.hex()}")
+    
+    clear_buffer()
+    
+    try:
+        laser_uart.write(cmd)
+        print(f"   已发送 {len(cmd)} 字节")
+    except Exception as e:
+        print(f"   ❌ 发送失败: {e}")
+        return None
+    
+    # 等待响应
+    start_time = time.ticks_ms()
+    response = b""
+    
+    while time.ticks_ms() - start_time < wait_time:
+        try:
+            chunk = laser_uart.read(1)
+            if chunk:
+                response += chunk
+                # 完整响应通常是9或13字节
+                if len(response) >= 9:
+                    # 检查是否完整帧
+                    if response[0] in [0xAA, 0xEE]:
+                        if len(response) >= 13:  # 测距完整响应
+                            break
+                        elif response[0] == 0xEE:  # 错误响应
+                            break
+        except:
+            break
+        
+        time.sleep_ms(10)
+    
+    if response:
+        print(f"   📥 响应: {response.hex()}")
+        print(f"   长度: {len(response)} 字节")
+        
+        # 解析错误码
+        if response[0] == 0xEE and len(response) >= 9:
+            err_code = (response[7] << 8) | response[8]
+            error_mapping = {
+                0x0000: "无错误",
+                0x0001: "硬件错误",
+                0x0002: "无输出数据", 
+                0x0003: "反射信号太弱",
+                0x0004: "反射信号太强",
+                0x0005: "温度太高(>40℃)",
+                0x0006: "温度太低(<-10℃)",
+                0x0007: "电源电压低(<2.5V)",
+                0x0008: "超出量程",
+                0x0009: "读通讯错误",
+                0x000A: "写通讯错误",
+                0x000B: "地址错误"
+            }
+            err_msg = error_mapping.get(err_code, f"未知错误: 0x{err_code:04X}")
+            print(f"   ❌ 模块错误: {err_msg}")
+    else:
+        print("   ⚠️ 无响应")
+    
+    return response
+
+def parse_distance_data(response):
+    """解析距离数据"""
+    if not response or len(response) < 13:
+        return None
+    
+    if response[0] != 0xAA or response[3] not in [0x20, 0x21, 0x22]:
+        return None
+    
+    # 解析4字节BCD码
+    bcd_bytes = response[6:10]
+    distance_int = 0
+    
+    for byte in bcd_bytes:
+        high = (byte >> 4) & 0x0F
+        low = byte & 0x0F
+        
+        if high > 9 or low > 9:
+            return None
+        
+        distance_int = distance_int * 100 + high * 10 + low
+    
+    distance_m = distance_int / 1000.0
+    
+    # 信号质量
+    signal = 0
+    if len(response) >= 12:
+        signal = (response[10] << 8) | response[11]
+    
+    return {
+        'meters': distance_m,
+        'millimeters': distance_m * 1000,
+        'signal': signal,
+        'raw': response.hex()
+    }
+
+# ==================== 主测试 ====================
+print("\n" + "="*50)
+print("M01激光测距模块详细测试")
+print("="*50)
+
+try:
+    # 1. 测试基本连接
+    print("\n1. 测试模块连接...")
+    version_cmd = bytes([0xAA, 0x80, 0x00, 0x0A, 0x8A])
+    resp = send_and_wait(version_cmd, "读取硬件版本")
+    
+    if resp and resp[0] == 0xAA and resp[3] == 0x0A:
+        print(f"✅ 模块正常，版本: {resp[6]:02X}{resp[7]:02X}")
+    else:
+        print("❌ 模块连接测试失败")
+        exit(1)
+    
+    # 2. 开启激光
+    print("\n2. 开启激光...")
+    resp = send_and_wait(LASER_ON_CMD, "开启激光", 1000)
+    if resp and resp.hex() == "aa0001be00010001c1":
+        print("✅ 激光已开启")
+    
+    print("   等待激光稳定...")
+    time.sleep(2)  # 重要等待时间
+    
+    # 3. 尝试不同的测距命令
+    print("\n3. 测试不同测距命令...")
+    
+    for i, test_cmd in enumerate(TEST_COMMANDS):
+        print(f"\n{'='*30}")
+        print(f"测试 {i+1}: {test_cmd['name']}")
+        print(f"{test_cmd['desc']}")
+        print(f"{'='*30}")
+        
+        resp = send_and_wait(test_cmd['cmd'], test_cmd['name'], 3000)
+        
+        if resp:
+            if resp[0] == 0xAA and len(resp) >= 13:
+                result = parse_distance_data(resp)
+                if result:
+                    print(f"✅ 测距成功!")
+                    print(f"   距离: {result['meters']:.3f} m")
+                    print(f"   距离: {result['millimeters']:.1f} mm")
+                    print(f"   信号质量: {result['signal']}")
+                    break
+                else:
+                    print("❌ 无法解析距离数据")
+            elif resp[0] == 0xEE:
+                print("❌ 命令执行错误")
+            else:
+                print("❌ 无效响应格式")
+        else:
+            print("❌ 无响应")
+        
+        time.sleep(1)  # 命令间间隔
+    
+    # 4. 关闭激光
+    print("\n4. 关闭激光...")
+    send_and_wait(LASER_OFF_CMD, "关闭激光", 1000)
+    
+    print("\n" + "="*50)
+    print("🏁 测试完成")
+    print("="*50)
+    
+    print("\n📋 测试总结：")
+    print("1. 模块通信: ✅ 正常")
+    print("2. 激光控制: ✅ 正常")
+    print("3. 测距功能: ❌ 有问题")
+    print("\n建议：")
+    print("1. 检查激光是否实际发光（在暗处观察红点）")
+    print("2. 确保测量目标在有效范围内（0.2-60米）")
+    print("3. 确保目标有足够反射率（白色平面最佳）")
+    print("4. 如果所有测距命令都返回ERR_ADDR，可能是固件版本问题")
+    
+except KeyboardInterrupt:
+    print("\n\n🛑 用户中断")
+    laser_uart.write(LASER_OFF_CMD)
+    print("✅ 已发送关闭指令")
+except Exception as e:
+    print(f"\n❌ 测试出错: {e}")

test/test_motor.py

@@ -0,0 +1,16 @@
+from maix import gpio, pinmap, time
+ 
+
+#设置引脚为输出
+led = gpio.GPIO("A25", gpio.Mode.OUT)
+#设置低电平
+led.value(0)
+ 
+while 1:
+    # time.sleep_ms(1000)
+    #对该引脚的电平进行取反（原高-》现低）
+    # led.toggle()
+    led.value(1)
+    #延时
+    time.sleep_ms(5000)
+    led.value(0)

test/test_power.py

@@ -0,0 +1,130 @@
+#!/usr/bin/env python3
+# test_power_with_init.py
+
+from maix import i2c, time
+import sys
+
+# INA226 register addresses
+INA226_ADDR = 0x40
+REG_CONFIGURATION = 0x00
+REG_BUS_VOLTAGE = 0x02
+REG_CURRENT = 0x04
+REG_CALIBRATION = 0x05
+
+# Configuration values
+CONFIG_VALUE = 0x4527      # Configuration: 16 averages, 1.1ms conversion time, continuous mode
+CALIBRATION_VALUE = 0x1400  # Calibration value
+
+def write_register(bus, reg, value):
+    """Write to INA226 register"""
+    data = [(value >> 8) & 0xFF, value & 0xFF]
+    bus.writeto_mem(INA226_ADDR, reg, bytes(data))
+
+def read_register(bus, reg):
+    """Read from INA226 register"""
+    data = bus.readfrom_mem(INA226_ADDR, reg, 2)
+    return (data[0] << 8) | data[1]
+
+def init_ina226(bus):
+    """Initialize INA226 chip"""
+    try:
+        # Write configuration register
+        write_register(bus, REG_CONFIGURATION, CONFIG_VALUE)
+        time.sleep_ms(10)
+        
+        # Write calibration register
+        write_register(bus, REG_CALIBRATION, CALIBRATION_VALUE)
+        time.sleep_ms(10)
+        
+        # Verify configuration by reading it back
+        config_read = read_register(bus, REG_CONFIGURATION)
+        if config_read != CONFIG_VALUE:
+            print(f"  Warning: Config readback mismatch: 0x{config_read:04X} != 0x{CONFIG_VALUE:04X}")
+        
+        return True
+    except Exception as e:
+        print(f"  Init failed: {e}")
+        return False
+
+def read_voltage(bus):
+    """Read bus voltage"""
+    raw = read_register(bus, REG_BUS_VOLTAGE)
+    voltage = raw * 1.25 / 1000
+    return voltage
+
+def read_current(bus):
+    """Read current"""
+    raw = read_register(bus, REG_CURRENT)
+    # Handle signed value
+    if raw & 0x8000:
+        raw = raw - 0x10000
+    current_lsb = 0.001 * CALIBRATION_VALUE / 4096
+    current = raw * current_lsb * 1000  # mA
+    return current
+
+def test_i2c_bus(bus_num):
+    """Test a single I2C bus with full initialization"""
+    print(f"\n{'='*60}")
+    print(f"Testing I2C Bus {bus_num}")
+    print(f"{'='*60}")
+    
+    try:
+        # Step 1: Initialize I2C bus
+        print(f"  1. Initializing I2C bus...")
+        bus = i2c.I2C(bus_num, i2c.Mode.MASTER)
+        print(f"     OK")
+        
+        # Step 2: Initialize INA226
+        print(f"  2. Initializing INA226...")
+        if not init_ina226(bus):
+            print(f"     FAILED")
+            return False
+        print(f"     OK")
+        
+        # Step 3: Read voltage multiple times
+        print(f"  3. Reading voltage...")
+        for i in range(5):
+            try:
+                voltage = read_voltage(bus)
+                current = read_current(bus)
+                print(f"     Read {i+1}: {voltage:.3f}V, {current:.1f}mA")
+                time.sleep_ms(100)
+            except Exception as e:
+                print(f"     Read {i+1} failed: {e}")
+        
+        print(f"  SUCCESS")
+        return True
+        
+    except Exception as e:
+        print(f"  FAILED: {e}")
+        import traceback
+        traceback.print_exc()
+        return False
+
+def main():
+    """Test all I2C buses"""
+    print("INA226 Test with Proper Initialization")
+    print("=" * 60)
+    
+    # Test buses in order of likelihood
+    test_order = [5, 1, 3, 4, 0, 2]
+    
+    success_buses = []
+    
+    for bus_num in test_order:
+        if test_i2c_bus(bus_num):
+            success_buses.append(bus_num)
+            # If we found a working bus, stop testing others
+            break
+    
+    print(f"\n{'='*60}")
+    print(f"Summary:")
+    print(f"  Working buses: {success_buses}")
+    if not success_buses:
+        print(f"  ERROR: No working I2C bus found!")
+        return 1
+    
+    return 0
+
+if __name__ == "__main__":
+    sys.exit(main())

time_sync.py

@@ -0,0 +1,186 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+时间同步模块
+从4G模块获取时间并同步到系统
+"""
+import re
+import os
+from datetime import datetime, timedelta
+import config
+# from logger_bak import get_logger
+from logger_manager import logger_manager
+
+
+def parse_4g_time(cclk_response, timezone_offset=8):
+    """
+    解析 AT+CCLK? 返回的时间字符串，并转换为本地时间
+    
+    Args:
+        cclk_response: AT+CCLK? 的响应字符串
+        timezone_offset: 时区偏移（小时），默认8（中国时区 UTC+8）
+    
+    Returns:
+        datetime 对象（已转换为本地时间），如果解析失败返回 None
+    """
+    try:
+        # 匹配格式: +CCLK: "YY/MM/DD,HH:MM:SS+TZ"
+        # 时区单位是四分之一小时（quarters of an hour）
+        match = re.search(r'\+CCLK:\s*"(\d{2})/(\d{2})/(\d{2}),(\d{2}):(\d{2}):(\d{2})([+-]\d{1,3})?"', cclk_response)
+        if not match:
+            return None
+        
+        yy, mm, dd, hh, MM, ss, tz_str = match.groups()
+        
+        # 年份处理：26 -> 2026
+        year = 2000 + int(yy)
+        month = int(mm)
+        day = int(dd)
+        hour = int(hh)
+        minute = int(MM)
+        second = int(ss)
+        
+        # 创建 UTC 时间的 datetime 对象
+        dt_utc = datetime(year, month, day, hour, minute, second)
+        
+        # 解析时区偏移（单位：四分之一小时）
+        if tz_str:
+            try:
+                # 时区偏移值（四分之一小时）
+                tz_quarters = int(tz_str)
+                
+                # 转换为小时（除以4）
+                tz_hours = tz_quarters / 4.0
+                
+                logger = logger_manager.logger
+                if logger:
+                    logger.info(f"[TIME] 时区偏移: {tz_str} (四分之一小时) = {tz_hours} 小时")
+                
+                # 转换为本地时间
+                dt_local = dt_utc + timedelta(hours=tz_hours)
+            except ValueError:
+                # 如果时区解析失败，使用默认值
+                logger = logger_manager.logger
+                if logger:
+                    logger.warning(f"[TIME] 时区解析失败: {tz_str}，使用默认 UTC+{timezone_offset}")
+                dt_local = dt_utc + timedelta(hours=timezone_offset)
+        else:
+            # 没有时区信息，使用默认值
+            logger = logger_manager.logger
+            if logger:
+                logger.info(f"[TIME] 未找到时区信息，使用默认 UTC+{timezone_offset}")
+            dt_local = dt_utc + timedelta(hours=timezone_offset)
+        
+        logger = logger_manager.logger
+        if logger:
+            logger.info(f"[TIME] UTC时间: {dt_utc.strftime('%Y-%m-%d %H:%M:%S')}")
+            logger.info(f"[TIME] 本地时间: {dt_local.strftime('%Y-%m-%d %H:%M:%S')}")
+        
+        return dt_local
+    except Exception as e:
+        logger = logger_manager.logger
+        if logger:
+            logger.error(f"[TIME] 解析时间失败: {e}, 响应: {cclk_response}")
+        else:
+            print(f"[TIME] 解析时间失败: {e}, 响应: {cclk_response}")
+        return None
+
+
+def get_time_from_4g(timezone_offset=8):
+    """
+    通过4G模块获取当前时间（已转换为本地时间）
+    
+    Args:
+        timezone_offset: 时区偏移（小时），默认8（中国时区）
+    
+    Returns:
+        datetime 对象（本地时间），如果获取失败返回 None
+    """
+    try:
+        # 发送 AT+CCLK? 命令（延迟导入避免循环依赖）
+        from hardware import hardware_manager
+        # 检查 at_client 是否已初始化
+        if hardware_manager.at_client is None:
+            logger = logger_manager.logger
+            if logger:
+                logger.warning("[TIME] ATClient 尚未初始化，无法获取4G时间")
+            else:
+                print("[TIME] ATClient 尚未初始化，无法获取4G时间")
+            return None
+        resp = hardware_manager.at_client.send("AT+CCLK?", "OK", 3000)
+        
+        if not resp or "+CCLK:" not in resp:
+            logger = logger_manager.logger
+            if logger:
+                logger.warning(f"[TIME] 未获取到时间响应: {resp}")
+            else:
+                print(f"[TIME] 未获取到时间响应: {resp}")
+            return None
+        
+        # 解析并转换时区
+        dt = parse_4g_time(resp, timezone_offset)
+        return dt
+    except Exception as e:
+        logger = logger_manager.logger
+        if logger:
+            logger.error(f"[TIME] 获取4G时间异常: {e}")
+        else:
+            print(f"[TIME] 获取4G时间异常: {e}")
+        return None
+
+
+def sync_system_time_from_4g(timezone_offset=8):
+    """
+    从4G模块同步时间到系统
+    
+    Args:
+        timezone_offset: 时区偏移（小时），默认8（中国时区）
+    
+    Returns:
+        bool: 是否成功
+    """
+    dt = get_time_from_4g(timezone_offset)
+    if not dt:
+        return False
+    
+    try:
+        # 转换为系统 date 命令需要的格式
+        time_str = dt.strftime('%Y-%m-%d %H:%M:%S')
+        
+        # 设置系统时间
+        cmd = f'date -s "{time_str}" 2>&1'
+        result = os.system(cmd)
+        
+        if result == 0:
+            logger = logger_manager.logger
+            if logger:
+                logger.info(f"[TIME] 系统时间已设置为: {time_str}")
+            else:
+                print(f"[TIME] 系统时间已设置为: {time_str}")
+            
+            # 可选：同步到硬件时钟
+            try:
+                os.system('hwclock -w 2>/dev/null')
+                logger = logger_manager.logger
+                if logger:
+                    logger.info("[TIME] 已同步到硬件时钟")
+            except:
+                pass
+            
+            return True
+        else:
+            logger = logger_manager.logger
+            if logger:
+                logger.error(f"[TIME] 设置系统时间失败，退出码: {result}")
+            else:
+                print(f"[TIME] 设置系统时间失败，退出码: {result}")
+            return False
+            
+    except Exception as e:
+        logger = logger_manager.logger
+        if logger:
+            logger.error(f"[TIME] 同步系统时间异常: {e}")
+        else:
+            print(f"[TIME] 同步系统时间异常: {e}")
+        return False
+

train_yolo/test_stage2_black_yolo_device.py

@@ -0,0 +1,343 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Stage2 黑三角 YOLO —— 在 Maix 设备上用本地图片测试（与线上 target_roi_yolo.try_black_triangle_boxes_work 完全一致）。
+
+不在 PC 上跑 NPU；需把脚本与 config / target_roi_yolo.py 同步到设备，并在设备上执行。
+
+典型用法
+--------
+  # 输入已是 Stage1 裁切（与你保存的 stage2_roi_*.jpg 一致）
+  python test/test_stage2_black_yolo_device.py /root/phot/stage2_roi_xxx.jpg
+
+  # 输入为整幅相机图，手动给出 Stage1 环靶 ROI（与线上日志 ring全图=[rx0,ry0,rx1,ry1] 一致）
+  python test/test_stage2_black_yolo_device.py /root/phot/full.jpg --roi 197,196,507,461
+
+  # 对比 native / letterbox 坐标映射（排查 contain 训练与推理对齐）
+  python test/test_stage2_black_yolo_device.py ./crop.jpg --compare-coord
+
+  # 覆盖置信度、模型路径（仍读其余项自 config）
+  python test/test_stage2_black_yolo_device.py ./crop.jpg --conf 0.25 -m /maixapp/apps/t11/model_270648.mud
+
+  # 只看 NPU 原始框（映射前）：判断坐标是 ~224 网络空间还是归一化 0~1
+  python test/test_stage2_black_yolo_device.py ./crop.jpg --conf 0.05 --dump-raw 15
+
+依赖：MaixPy（maix.nn）、OpenCV（cv2）、numpy；项目根须在 sys.path（本脚本已插入上级目录）。
+"""
+
+from __future__ import annotations
+
+import argparse
+import os
+import sys
+
+_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
+if _ROOT not in sys.path:
+    sys.path.insert(0, _ROOT)
+
+
+def _parse_roi(s: str) -> tuple[int, int, int, int]:
+    parts = [p.strip() for p in s.replace(" ", "").split(",")]
+    if len(parts) != 4:
+        raise ValueError("ROI 需要 4 个整数：x0,y0,x1,y1")
+    return tuple(int(x) for x in parts)  # type: ignore[return-value]
+
+
+def _load_rgb_numpy(path: str) -> "object":
+    import cv2
+    import numpy as np
+
+    bgr = cv2.imread(path, cv2.IMREAD_COLOR)
+    if bgr is None:
+        raise FileNotFoundError(f"cv2.imread 失败: {path}")
+    rgb = cv2.cvtColor(bgr, cv2.COLOR_BGR2RGB)
+    return np.ascontiguousarray(rgb, dtype=np.uint8)
+
+
+def _draw_boxes_on_crop(
+    slab_rgb,
+    boxes: list[tuple[int, int, int, int]],
+    labels: list[str] | None = None,
+):
+    """slab_rgb: H×W×3 RGB uint8；boxes 为扩 margin 后的 Stage2 子框（与线上绿框一致）。"""
+    import cv2
+
+    vis = slab_rgb.copy()
+    bgr = cv2.cvtColor(vis, cv2.COLOR_RGB2BGR)
+    rh, rw = bgr.shape[:2]
+    for i, (bx0, by0, bx1, by1) in enumerate(boxes):
+        x0, y0 = int(bx0), int(by0)
+        x1, y1 = int(bx1) - 1, int(by1) - 1
+        x1 = max(x0, min(x1, rw - 1))
+        y1 = max(y0, min(y1, rh - 1))
+        cv2.rectangle(bgr, (x0, y0), (x1, y1), (0, 255, 0), 2)
+        tag = labels[i] if labels and i < len(labels) else f"s2_{i}"
+        cv2.putText(
+            bgr,
+            tag,
+            (x0, max(0, y0 - 4)),
+            cv2.FONT_HERSHEY_SIMPLEX,
+            0.5,
+            (0, 255, 0),
+            1,
+            cv2.LINE_AA,
+        )
+    return bgr
+
+
+class _PrintLogger:
+    def info(self, msg):
+        print(msg)
+
+    def warning(self, msg):
+        print(msg)
+
+    def error(self, msg):
+        print(msg)
+
+
+def _run_once(yroi_mod, img_rgb, roi_xyxy, logger):
+    boxes = yroi_mod.try_black_triangle_boxes_work(img_rgb, roi_xyxy, logger)
+    rx0, ry0, rx1, ry1 = roi_xyxy
+    slab = img_rgb[ry0:ry1, rx0:rx1].copy()
+    return boxes, slab
+
+
+def _copy_dump_raw_rows(yroi_mod, objs):
+    """把 Maix detect 返回对象拷贝成基础类型，避免 native 对象跨下一次 detect 存活。"""
+    rows = []
+    for o in objs:
+        cid = yroi_mod._det_obj_class_id(o)
+        try:
+            sc = float(getattr(o, "score", 0.0))
+        except (TypeError, ValueError):
+            sc = 0.0
+        rows.append((cid, sc, float(o.x), float(o.y), float(o.w), float(o.h)))
+    return rows
+
+
+def _dump_raw_and_hard_exit(det, yroi_mod, slab_for_det, rw_s, rh_s, net_w, net_h, conf_th, iou_th, limit):
+    """
+    MaixPy 某些版本在 YOLO detect 返回对象正常析构时会 SIGSEGV/pure virtual。
+    raw dump 是诊断路径，打印完成后硬退出，绕过 Python/native 析构链。
+    """
+    from maix import image as maix_image
+
+    roi_maix = maix_image.cv2image(slab_for_det, False, False)
+    raw = det.detect(roi_maix, conf_th=conf_th, iou_th=iou_th)
+    objs = yroi_mod._normalize_objs(raw if raw is not None else [])
+    dump_rows = _copy_dump_raw_rows(yroi_mod, objs)
+    raw_count = len(dump_rows)
+    print(
+        f"[DUMP-RAW] slab={rw_s}×{rh_s} net={net_w}×{net_h} "
+        f"conf={conf_th} iou={iou_th} → NMS 后 raw 框数={raw_count}（与 coord_mode 无关）"
+    )
+    npr = min(int(limit), raw_count)
+    for i in range(npr):
+        cid, sc, x, y, ww, hh = dump_rows[i]
+        print(f"  #{i} cls={cid} score={sc:.4f} xywh=({x:.3f},{y:.3f},{ww:.3f},{hh:.3f})")
+    if dump_rows:
+        xs = [r[2] for r in dump_rows]
+        ws = [r[4] for r in dump_rows]
+        print(
+            f"[DUMP-RAW]  hint: x 范围≈[{min(xs):.2f},{max(xs):.2f}] "
+            f"w 范围≈[{min(ws):.2f},{max(ws):.2f}] — "
+            f"若整体在 0~{net_w} 量级多为网络画布坐标→应用 letterbox；"
+            f"若 x,w 多在 0~1→可能是归一化，需在代码里乘 net 尺寸"
+        )
+    print("[INFO] --dump-raw 已完成；为规避 MaixPy YOLO native 析构崩溃，测试进程将直接退出。")
+    sys.stdout.flush()
+    sys.stderr.flush()
+    os._exit(0)
+
+
+def main():
+    ap = argparse.ArgumentParser(
+        description="Stage2 黑三角 YOLO 设备本地图测试",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog=__doc__,
+    )
+    ap.add_argument("image", help="本地图片路径（设备上的路径）")
+    ap.add_argument(
+        "--roi",
+        default="",
+        metavar="x0,y0,x1,y1",
+        help="可选。若填写：image 为整幅图，在此图上取 Stage1 ROI 再跑 Stage2；"
+        "留空：image 本身就是 Stage1 裁切图（默认）",
+    )
+    ap.add_argument("-o", "--output", default="", help="输出可视化路径；默认 原名_stage2_vis.jpg")
+    ap.add_argument("-m", "--model", default="", help="覆盖 config.TRIANGLE_BLACK_YOLO_MODEL_PATH")
+    ap.add_argument("--conf", type=float, default=None, help="覆盖 TRIANGLE_BLACK_YOLO_CONF_TH")
+    ap.add_argument("--iou", type=float, default=None, help="覆盖 TRIANGLE_BLACK_YOLO_IOU_TH")
+    ap.add_argument(
+        "--coord",
+        choices=["native", "letterbox"],
+        default="",
+        help="覆盖 TRIANGLE_BLACK_YOLO_COORD_MODE；默认用 config",
+    )
+    ap.add_argument(
+        "--compare-coord",
+        action="store_true",
+        help="各跑一次 native 与 letterbox，输出两张图 *_stage2_native.jpg / *_stage2_letterbox.jpg",
+    )
+    ap.add_argument(
+        "--fresh-detector",
+        action="store_true",
+        help="清掉 YOLO 缓存再测（换模型或排查缓存时用）",
+    )
+    ap.add_argument(
+        "--allow-save-roi",
+        action="store_true",
+        help="不强制关闭 TRIANGLE_BLACK_YOLO_SAVE_ROI_CROP（默认测试时会关掉以免写满相册目录）",
+    )
+    ap.add_argument(
+        "--dump-raw",
+        type=int,
+        default=0,
+        metavar="N",
+        help="打印前 N 个 detect 原始框 x,y,w,h,score,cls（coord 映射前；native/letterbox 共用同一批 raw）",
+    )
+    args = ap.parse_args()
+
+    img_path = os.path.abspath(args.image)
+    if not os.path.isfile(img_path):
+        print(f"[ERR] 找不到图片: {img_path}")
+        sys.exit(1)
+
+    try:
+        import config as cfg
+        import target_roi_yolo as yroi
+    except ImportError as e:
+        print(f"[ERR] 无法导入 config / target_roi_yolo: {e}")
+        sys.exit(1)
+
+    if args.fresh_detector:
+        yroi.reset_yolo_detector_cache()
+
+    # 备份并临时覆盖 config（单进程顺序跑）
+    bak: dict[str, object] = {}
+
+    def _patch(key: str, val: object):
+        if key not in bak:
+            bak[key] = getattr(cfg, key, None)
+        setattr(cfg, key, val)
+
+    def _restore():
+        for k, v in bak.items():
+            setattr(cfg, k, v)
+
+    try:
+        _patch("TRIANGLE_BLACK_YOLO_ENABLE", True)
+        if not args.allow_save_roi:
+            _patch("TRIANGLE_BLACK_YOLO_SAVE_ROI_CROP", False)
+        if args.model.strip():
+            _patch("TRIANGLE_BLACK_YOLO_MODEL_PATH", args.model.strip())
+        if args.conf is not None:
+            _patch("TRIANGLE_BLACK_YOLO_CONF_TH", float(args.conf))
+        if args.iou is not None:
+            _patch("TRIANGLE_BLACK_YOLO_IOU_TH", float(args.iou))
+        if args.coord and not args.compare_coord:
+            _patch("TRIANGLE_BLACK_YOLO_COORD_MODE", args.coord)
+
+        mp = getattr(cfg, "TRIANGLE_BLACK_YOLO_MODEL_PATH", "") or ""
+        if not os.path.isfile(mp):
+            print(f"[ERR] 模型文件不存在: {mp}")
+            sys.exit(1)
+
+        img_rgb = _load_rgb_numpy(img_path)
+        h, w = int(img_rgb.shape[0]), int(img_rgb.shape[1])
+
+        if args.roi.strip():
+            roi_xyxy = _parse_roi(args.roi.strip())
+            rx0, ry0, rx1, ry1 = [int(round(float(v))) for v in roi_xyxy]
+            if rx1 <= rx0 or ry1 <= ry0:
+                print("[ERR] ROI 无效：需满足 x1>x0 且 y1>y0")
+                sys.exit(1)
+            # 与 target_roi_yolo.try_black_triangle_boxes_work 相同的 clip
+            rx0 = max(0, min(rx0, w - 1))
+            ry0 = max(0, min(ry0, h - 1))
+            rx1 = max(rx0 + 1, min(rx1, w))
+            ry1 = max(ry0 + 1, min(ry1, h))
+            ring_roi = (rx0, ry0, rx1, ry1)
+            print(f"[INFO] 模式=整图+ROI ring={ring_roi} image={w}×{h}")
+        else:
+            ring_roi = (0, 0, w, h)
+            print(f"[INFO] 模式=已是 Stage1 裁切 crop={w}×{h}")
+
+        logger = _PrintLogger()
+        det = yroi._get_detector(mp)
+        if det is None:
+            print("[ERR] 无法加载 nn.YOLOv5（检查模型路径与 Maix 环境）")
+            sys.exit(1)
+        net_w = int(det.input_width())
+        net_h = int(det.input_height())
+        print(f"[INFO] model={mp} net_in={net_w}×{net_h}")
+
+        rx0, ry0, rx1, ry1 = ring_roi
+        import numpy as np
+
+        slab_for_det = np.ascontiguousarray(img_rgb[ry0:ry1, rx0:rx1], dtype=np.uint8).copy()
+        rh_s, rw_s = int(slab_for_det.shape[0]), int(slab_for_det.shape[1])
+
+        modes = ["native", "letterbox"] if args.compare_coord else [
+            (args.coord or getattr(cfg, "TRIANGLE_BLACK_YOLO_COORD_MODE", "native"))
+        ]
+
+        base, ext = os.path.splitext(img_path)
+        ext = ext if ext else ".jpg"
+
+        for mode in modes:
+            _patch("TRIANGLE_BLACK_YOLO_COORD_MODE", mode)
+            cur_coord = getattr(cfg, "TRIANGLE_BLACK_YOLO_COORD_MODE", mode)
+            print(f"[INFO] --- TRIANGLE_BLACK_YOLO_COORD_MODE={cur_coord} ---")
+
+            boxes, slab = _run_once(yroi, img_rgb, ring_roi, logger)
+            print(
+                f"[INFO] 子框数量={len(boxes)} conf={getattr(cfg, 'TRIANGLE_BLACK_YOLO_CONF_TH', '?')} "
+                f"coord={cur_coord}"
+            )
+            for i, b in enumerate(boxes):
+                print(f"  s2_{i}: {b}")
+
+            if args.compare_coord:
+                out_path = f"{base}_stage2_{mode}{ext}"
+            elif args.output.strip():
+                out_path = args.output.strip()
+            else:
+                out_path = base + "_stage2_vis" + ext
+
+            import cv2
+
+            bgr = _draw_boxes_on_crop(slab, boxes)
+            cv2.imwrite(out_path, bgr, [int(cv2.IMWRITE_JPEG_QUALITY), 92])
+            print(f"[OK] saved: {out_path}")
+
+        if args.compare_coord:
+            print(
+                "[HINT] contain 训练时若 letterbox 对齐更好，请将 config 里 "
+                "TRIANGLE_BLACK_YOLO_COORD_MODE 设为 letterbox"
+            )
+
+        if args.dump_raw > 0:
+            conf_th = float(getattr(cfg, "TRIANGLE_BLACK_YOLO_CONF_TH", 0.5))
+            iou_th = float(getattr(cfg, "TRIANGLE_BLACK_YOLO_IOU_TH", 0.45))
+            print("\n[INFO] --dump-raw 放在最后执行，避免 raw native 对象影响 compare-coord 流程。")
+            _dump_raw_and_hard_exit(
+                det,
+                yroi,
+                slab_for_det,
+                rw_s,
+                rh_s,
+                net_w,
+                net_h,
+                conf_th,
+                iou_th,
+                args.dump_raw,
+            )
+
+    finally:
+        _restore()
+
+
+if __name__ == "__main__":
+    main()

train_yolo/test_triangle_one_image.py

@@ -0,0 +1,242 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+单张图片快速测试：三角形四角标记识别 + 单应性落点 + PnP 估距
+
+用法（在板子上）：
+  python3 test/test_triangle_one_image.py --image /root/phot/xxx.jpg --out /root/phot/tri_out.jpg
+
+调参对比（不改代码，临时覆盖 config.TRIANGLE_*）：
+  python3 test/test_triangle_one_image.py --image /root/phot/xxx.jpg --preset shadow
+  python3 test/test_triangle_one_image.py --image /root/phot/xxx.jpg --max-interior-gray 160 --min-dark-ratio 0.20
+"""
+
+import argparse
+import json
+import os
+import time
+from typing import Any, Dict, Tuple
+
+import cv2
+import numpy as np
+
+import config
+import triangle_target as tri_mod
+from triangle_target import (
+    detect_triangle_markers,
+    load_camera_from_xml,
+    load_triangle_positions,
+    try_triangle_scoring,
+)
+
+
+def _apply_overrides(args) -> None:
+    # 预设：阴影/低对比度场景更宽松（尽量保持速度：不启 CLAHE）
+    if args.preset == "shadow":
+        setattr(config, "TRIANGLE_ENABLE_CLAHE_FALLBACK", False)
+        setattr(config, "TRIANGLE_MIN_CONTRAST_DIFF", 0)
+        setattr(config, "TRIANGLE_MAX_INTERIOR_GRAY", 160)
+        setattr(config, "TRIANGLE_DARK_PIXEL_GRAY", 160)
+        setattr(config, "TRIANGLE_MIN_DARK_RATIO", 0.20)
+        # adaptive 只在 Otsu 失败时尝试，保持尝试次数很少
+        setattr(config, "TRIANGLE_ADAPTIVE_BLOCK_SIZES", (21,))
+
+    # 手动覆盖（优先级高于 preset）
+    if args.max_interior_gray is not None:
+        setattr(config, "TRIANGLE_MAX_INTERIOR_GRAY", int(args.max_interior_gray))
+    if args.dark_pixel_gray is not None:
+        setattr(config, "TRIANGLE_DARK_PIXEL_GRAY", int(args.dark_pixel_gray))
+    if args.min_dark_ratio is not None:
+        setattr(config, "TRIANGLE_MIN_DARK_RATIO", float(args.min_dark_ratio))
+    if args.min_contrast_diff is not None:
+        setattr(config, "TRIANGLE_MIN_CONTRAST_DIFF", int(args.min_contrast_diff))
+    if args.detect_scale is not None:
+        setattr(config, "TRIANGLE_DETECT_SCALE", float(args.detect_scale))
+    if args.adaptive_blocks is not None:
+        bs = tuple(int(x) for x in args.adaptive_blocks.split(",") if x.strip())
+        setattr(config, "TRIANGLE_ADAPTIVE_BLOCK_SIZES", bs)
+
+
+def _dump_config() -> Dict[str, Any]:
+    keys = [
+        "TRIANGLE_DETECT_SCALE",
+        "TRIANGLE_SIZE_RANGE",
+        "TRIANGLE_MAX_INTERIOR_GRAY",
+        "TRIANGLE_DARK_PIXEL_GRAY",
+        "TRIANGLE_MIN_DARK_RATIO",
+        "TRIANGLE_MIN_CONTRAST_DIFF",
+        "TRIANGLE_ADAPTIVE_BLOCK_SIZES",
+        "TRIANGLE_MAX_FILTERED_FOR_COMBO",
+        "TRIANGLE_EARLY_EXIT_CANDIDATES",
+        "TRIANGLE_ENABLE_CLAHE_FALLBACK",
+    ]
+    out = {}
+    for k in keys:
+        out[k] = getattr(config, k, None)
+    return out
+
+
+def _draw_tri_debug(img_bgr: np.ndarray, tri: Dict[str, Any]) -> np.ndarray:
+    out = img_bgr.copy()
+    markers = tri.get("markers") or []
+
+    # 画三角形轮廓 + center + id
+    for m in markers:
+        corners = np.array(m.get("corners", []), dtype=np.int32)
+        if corners.size == 0:
+            continue
+        cv2.polylines(out, [corners], True, (0, 255, 0), 2)
+        c = m.get("center") or (corners[:, 0].mean(), corners[:, 1].mean())
+        cx, cy = int(c[0]), int(c[1])
+        cv2.circle(out, (cx, cy), 4, (0, 0, 255), -1)
+        mid = m.get("id", "?")
+        cv2.putText(out, f"T{mid}", (cx - 18, cy - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.55, (0, 255, 0), 1)
+
+    # 若有 homography，画靶心（把 (0,0) 反投影到图像）
+    H = tri.get("homography")
+    if H is not None:
+        try:
+            H = np.array(H, dtype=np.float64)
+            H_inv = np.linalg.inv(H)
+            c_img = cv2.perspectiveTransform(np.array([[[0.0, 0.0]]], dtype=np.float32), H_inv)[0][0]
+            ocx, ocy = int(c_img[0]), int(c_img[1])
+            cv2.circle(out, (ocx, ocy), 5, (0, 0, 255), -1)
+            cv2.circle(out, (ocx, ocy), 10, (0, 0, 255), 1)
+        except Exception:
+            pass
+
+    # 叠加结果信息
+    lines = []
+    if tri.get("ok"):
+        lines.append("tri_ok=True")
+        if tri.get("dx_cm") is not None and tri.get("dy_cm") is not None:
+            lines.append(f"dx,dy=({tri['dx_cm']:.2f},{tri['dy_cm']:.2f})cm")
+        if tri.get("distance_m") is not None:
+            lines.append(f"dist={float(tri['distance_m']):.2f}m")
+    else:
+        lines.append("tri_ok=False")
+
+    y0 = 22
+    for i, t in enumerate(lines):
+        cv2.putText(out, t, (10, y0 + i * 18), cv2.FONT_HERSHEY_SIMPLEX, 0.55, (0, 255, 0), 1)
+    return out
+
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--image", required=True, help="输入图片路径（jpg/png）")
+    ap.add_argument("--out", default="", help="输出标注图片路径（可选）")
+    ap.add_argument("--laser-x", type=int, default=-1, help="激光点 x（像素），默认用图像中心")
+    ap.add_argument("--laser-y", type=int, default=-1, help="激光点 y（像素），默认用图像中心")
+    ap.add_argument("--preset", choices=["", "shadow"], default="", help="调参预设（shadow=阴影更鲁棒，不启 CLAHE）")
+    ap.add_argument("--max-interior-gray", type=int, default=None)
+    ap.add_argument("--dark-pixel-gray", type=int, default=None)
+    ap.add_argument("--min-dark-ratio", type=float, default=None)
+    ap.add_argument("--min-contrast-diff", type=int, default=None)
+    ap.add_argument("--detect-scale", type=float, default=None)
+    ap.add_argument("--adaptive-blocks", default=None, help="例如: 11,21 ；为空表示不改")
+    ap.add_argument("--verbose", action="store_true", help="输出更多检测阶段信息")
+    args = ap.parse_args()
+
+    _apply_overrides(args)
+    # triangle_target.py 的日志默认写到 logger_manager；在离线脚本里 logger 可能未初始化。
+    # verbose 模式下把 _log 重定向为 print，方便直接看到诊断信息。
+    if args.verbose:
+        try:
+            tri_mod._log = lambda msg: print(str(msg))
+        except Exception:
+            pass
+
+    img_bgr = cv2.imread(args.image, cv2.IMREAD_COLOR)
+    if img_bgr is None:
+        raise SystemExit(f"读图失败：{args.image}")
+    # triangle_target.try_triangle_scoring 约定输入为 RGB；OpenCV imread 返回 BGR
+    img_rgb = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2RGB)
+
+    h, w = img_bgr.shape[:2]
+    if args.laser_x >= 0 and args.laser_y >= 0:
+        laser_point = (int(args.laser_x), int(args.laser_y))
+    else:
+        laser_point = (w // 2, h // 2)
+
+    K, dist = load_camera_from_xml(getattr(config, "CAMERA_CALIB_XML", ""))
+    pos = load_triangle_positions(getattr(config, "TRIANGLE_POSITIONS_JSON", ""))
+
+    print("[tri-test] image:", args.image, "shape:", (h, w))
+    print("[tri-test] laser_point:", laser_point)
+    print("[tri-test] calib_ok:", bool(K is not None and dist is not None), "pos_ok:", bool(pos))
+    print("[tri-test] config:", json.dumps(_dump_config(), ensure_ascii=False))
+
+    # 先单独跑一次三角形候选检测，便于区分“没找到候选” vs “找到候选但评分/单应性失败”
+    scale = float(getattr(config, "TRIANGLE_DETECT_SCALE", 0.5) or 0.5)
+    if not (0.05 <= scale <= 1.0):
+        scale = 0.5
+    long_side = max(h, w)
+    max_dim = max(64, int(long_side * scale))
+    if long_side > max_dim:
+        det_scale = max_dim / long_side
+        det_w = int(w * det_scale)
+        det_h = int(h * det_scale)
+        img_det = cv2.resize(img_bgr, (det_w, det_h), interpolation=cv2.INTER_LINEAR)
+        inv_scale = 1.0 / det_scale
+        size_range_det = (
+            max(4, int(getattr(config, "TRIANGLE_SIZE_RANGE", (8, 500))[0] * det_scale)),
+            max(8, int(getattr(config, "TRIANGLE_SIZE_RANGE", (8, 500))[1] * det_scale)),
+        )
+    else:
+        img_det = img_bgr
+        inv_scale = 1.0
+        size_range_det = getattr(config, "TRIANGLE_SIZE_RANGE", (8, 500))
+
+    gray = cv2.cvtColor(img_det, cv2.COLOR_BGR2GRAY)
+    markers_det = detect_triangle_markers(
+        gray,
+        orig_gray=gray,
+        size_range=size_range_det,
+        verbose=bool(args.verbose),
+    )
+    if inv_scale != 1.0 and markers_det:
+        for m in markers_det:
+            m["center"] = [m["center"][0] * inv_scale, m["center"][1] * inv_scale]
+            m["corners"] = [[c[0] * inv_scale, c[1] * inv_scale] for c in m["corners"]]
+
+    print("[tri-test] markers_found:", len(markers_det), "ids:", [m.get("id") for m in markers_det])
+
+    t0 = time.time()
+    tri = try_triangle_scoring(
+        img_rgb,  # try_triangle_scoring 期望 RGB
+        laser_point,
+        pos,
+        K,
+        dist,
+        size_range=getattr(config, "TRIANGLE_SIZE_RANGE", (8, 500)),
+    )
+    dt_ms = int(round((time.time() - t0) * 1000))
+
+    print("[tri-test] elapsed_ms:", dt_ms)
+    print(json.dumps(tri, ensure_ascii=False, indent=2))
+
+    if args.out:
+        out_path = args.out
+        # 允许传目录（如 ./），自动生成文件名；未带扩展名时默认 .jpg
+        if out_path.endswith("/") or out_path.endswith("\\") or os.path.isdir(out_path):
+            out_path = os.path.join(out_path, "tri_out.jpg")
+        root, ext = os.path.splitext(out_path)
+        if not ext:
+            out_path = root + ".jpg"
+
+        # 若 try_triangle_scoring 失败且没带回 markers，至少把候选 markers 画出来，方便肉眼判断
+        tri_for_draw = tri if isinstance(tri, dict) else {"ok": False}
+        if not tri_for_draw.get("markers") and markers_det:
+            tri_for_draw = dict(tri_for_draw)
+            tri_for_draw["markers"] = markers_det
+        out_img = _draw_tri_debug(img_bgr, tri_for_draw)
+        ok = cv2.imwrite(out_path, out_img)
+        if not ok:
+            raise SystemExit(f"写图失败（可能是不支持的扩展名）：{out_path}")
+        print("[tri-test] wrote:", out_path)
+
+
+if __name__ == "__main__":
+    main()
+

train_yolo/test_yolo_draw_boxes.py

@@ -0,0 +1,257 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+本地图片 → Maix YOLOv5 检测 → 画框保存（用于核对坐标 mode / 多框 union）。
+
+运行环境：MaixCAM / MaixPy（需 maix.image / maix.nn），在项目根或任意目录执行均可。
+
+示例：
+  python test/test_yolo_draw_boxes.py /root/phot/shot_xxx.jpg
+  python test/test_yolo_draw_boxes.py shot.jpg --loader cv2_rgb --conf 0.25
+  python test/test_yolo_draw_boxes.py shot.jpg --debug
+  python -h  # 查看 --loader / --debug / --union 等全部参数
+
+脚本版本（与设备同步用）：20260206-yolo-vis
+"""
+
+from __future__ import annotations
+
+import argparse
+import os
+import sys
+
+_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
+if _ROOT not in sys.path:
+    sys.path.insert(0, _ROOT)
+
+
+def _load_maix_image(path: str, image_mod):
+    """maix.image.load（部分 JPEG 解码后与 camera.read() 像素布局不一致，可能导致 NPU 全空）。"""
+    return image_mod.load(path)
+
+
+def _load_cv2_rgb_as_maix(path: str, image_mod):
+    """
+    OpenCV 读盘为 BGR → 转 RGB → 与 shoot_manager 里 image2cv 逆过程一致，供 YOLO input type: rgb。
+    """
+    import cv2
+
+    arr = cv2.imread(path, cv2.IMREAD_COLOR)
+    if arr is None:
+        raise FileNotFoundError(f"cv2.imread 失败: {path}")
+    arr = cv2.cvtColor(arr, cv2.COLOR_BGR2RGB)
+    return image_mod.cv2image(arr, False, False)
+
+
+def main():
+    ap = argparse.ArgumentParser(
+        description="YOLO 画框测试（Maix）",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog="若提示 unrecognized arguments: --debug，说明设备上脚本未更新，请同步仓库中的 test/test_yolo_draw_boxes.py",
+    )
+    ap.add_argument("image", help="输入图片路径")
+    ap.add_argument("-o", "--output", default="", help="输出图片路径；默认 原名_yolo_vis.jpg")
+    ap.add_argument("-m", "--model", default="", help="覆盖 config.TRIANGLE_YOLO_MODEL_PATH")
+    ap.add_argument("--conf", type=float, default=None, help="置信度阈值")
+    ap.add_argument("--iou", type=float, default=None, help="NMS IoU")
+    ap.add_argument(
+        "--coord",
+        choices=["native", "letterbox"],
+        default="",
+        help="坐标映射；默认读 config.TRIANGLE_YOLO_COORD_MODE",
+    )
+    ap.add_argument(
+        "--union",
+        action="store_true",
+        help="按 TRIANGLE_YOLO_RING_CLASS_IDS 过滤后画合并外接矩形（与线上 ROI merge=union 一致）",
+    )
+    ap.add_argument(
+        "--loader",
+        choices=["auto", "maix", "cv2_rgb"],
+        default="auto",
+        help="auto: 先 maix.load，0 框则改用 cv2 RGB（推荐排查「有图但始终 0 框」）",
+    )
+    ap.add_argument(
+        "--debug",
+        action="store_true",
+        help="打印 detect 原始返回类型与 repr（截断）",
+    )
+    args = ap.parse_args()
+
+    try:
+        from maix import image, nn
+    except ImportError:
+        print("[ERR] 需要 MaixPy（maix.image / maix.nn），请在 MaixCAM 上运行。")
+        sys.exit(1)
+
+    import config as cfg
+    import target_roi_yolo as yroi
+
+    img_path = os.path.abspath(args.image)
+    if not os.path.isfile(img_path):
+        print(f"[ERR] 找不到图片: {img_path}")
+        sys.exit(1)
+
+    model_path = (args.model or getattr(cfg, "TRIANGLE_YOLO_MODEL_PATH", "") or "").strip()
+    if not os.path.isfile(model_path):
+        print(f"[ERR] 模型文件不存在: {model_path}")
+        sys.exit(1)
+
+    conf_th = (
+        float(args.conf)
+        if args.conf is not None
+        else float(getattr(cfg, "TRIANGLE_YOLO_CONF_TH", 0.5))
+    )
+    iou_th = (
+        float(args.iou)
+        if args.iou is not None
+        else float(getattr(cfg, "TRIANGLE_YOLO_IOU_TH", 0.45))
+    )
+    coord_mode = (args.coord or getattr(cfg, "TRIANGLE_YOLO_COORD_MODE", "native")).lower()
+
+    out_path = args.output.strip()
+    if not out_path:
+        base, ext = os.path.splitext(img_path)
+        ext = ext if ext else ".jpg"
+        out_path = base + "_yolo_vis" + ext
+
+    det = nn.YOLOv5(model=model_path, dual_buff=False)
+    net_w = int(det.input_width())
+    net_h = int(det.input_height())
+
+    def _run_detect(maix_img, tag: str):
+        r = det.detect(maix_img, conf_th=conf_th, iou_th=iou_th)
+        if args.debug:
+            rlen = len(r) if r is not None and hasattr(r, "__len__") else "n/a"
+            rrepr = repr(r)
+            if len(rrepr) > 300:
+                rrepr = rrepr[:300] + "..."
+            print(f"[DEBUG] loader={tag} raw_type={type(r)} len={rlen} repr={rrepr}")
+        return yroi._normalize_objs(r if r is not None else []), maix_img, tag
+
+    img = None
+    load_tag = ""
+    objs = []
+
+    if args.loader == "cv2_rgb":
+        img = _load_cv2_rgb_as_maix(img_path, image)
+        load_tag = "cv2_rgb"
+        objs, img, load_tag = _run_detect(img, load_tag)
+    elif args.loader == "maix":
+        img = _load_maix_image(img_path, image)
+        load_tag = "maix_load"
+        objs, img, load_tag = _run_detect(img, load_tag)
+    else:
+        # auto
+        img = _load_maix_image(img_path, image)
+        load_tag = "maix_load"
+        objs, img, load_tag = _run_detect(img, load_tag)
+        if len(objs) == 0:
+            print(
+                "[WARN] maix.image.load 在 conf_th=%s 下仍为 0 框，改用 cv2 BGR→RGB→cv2image 重试（常见可恢复）"
+                % conf_th
+            )
+            img2 = _load_cv2_rgb_as_maix(img_path, image)
+            objs, img, load_tag = _run_detect(img2, "cv2_rgb_retry")
+
+    src_w, src_h = img.width(), img.height()
+
+    labels = getattr(det, "labels", None)
+
+    def _label(cid: int) -> str:
+        if labels is None:
+            return str(cid)
+        try:
+            return str(labels[int(cid)])
+        except Exception:
+            return str(cid)
+
+    print(
+        f"[INFO] loader={load_tag} image={src_w}×{src_h}, net_in={net_w}×{net_h}, "
+        f"coord={coord_mode}, conf_th={conf_th}, iou_th={iou_th}"
+    )
+    print(f"[INFO] NMS 后检测框数量={len(objs)} → {out_path}")
+    if len(objs) == 0:
+        print(
+            "[HINT] 仍为 0 框时常见原因：\n"
+            "  1) 强制 cv2 路径: --loader cv2_rgb\n"
+            "  2) NMS 过严: --iou 0.95\n"
+            "  3) 图与训练分布差太大 / 模型未见过该场景\n"
+            "  4) 用 camera.read() 一帧存盘再测，对比 file 与实时是否一致"
+        )
+
+    # 颜色：按类别轮换（仅有 COLOR_* 时常量时用）
+    color_cycle = []
+    for name in ("RED", "GREEN", "BLUE", "ORANGE", "YELLOW", "CYAN", "MAGENTA"):
+        c = getattr(image, f"COLOR_{name}", None)
+        if c is not None:
+            color_cycle.append(c)
+    if not color_cycle:
+        color_cycle = [getattr(image, "COLOR_RED", 0)]
+
+    for i, o in enumerate(objs):
+        cid = yroi._det_obj_class_id(o)
+        if cid is None:
+            cid = -1
+        try:
+            sc = float(o.score)
+        except Exception:
+            sc = 0.0
+        x0, y0, x1, y1 = yroi._det_to_src_xyxy(o, coord_mode, src_w, src_h, net_w, net_h)
+        ix = int(max(0, min(x0, src_w - 1)))
+        iy = int(max(0, min(y0, src_h - 1)))
+        iw = int(max(1, min(x1 - x0, src_w - ix)))
+        ih = int(max(1, min(y1 - y0, src_h - iy)))
+        col = color_cycle[cid % len(color_cycle)] if cid >= 0 else color_cycle[0]
+        img.draw_rect(ix, iy, iw, ih, color=col)
+        ty = max(0, iy - 14)
+        msg = f"{_label(cid)} {sc:.2f}"
+        img.draw_string(ix, ty, msg, color=col)
+        print(f"  #{i} cls={cid} {_label(cid)} score={sc:.3f} xywh=({ix},{iy},{iw},{ih})")
+
+    if args.union:
+        class_ids = getattr(cfg, "TRIANGLE_YOLO_RING_CLASS_IDS", (0,))
+        if isinstance(class_ids, int):
+            class_ids = (class_ids,)
+        cand = [o for o in objs if yroi._det_obj_class_id(o) in class_ids]
+        if cand:
+            xy_list = [
+                yroi._det_to_src_xyxy(o, coord_mode, src_w, src_h, net_w, net_h) for o in cand
+            ]
+            merged = yroi._merge_roi_xyxy(xy_list, "union")
+            if merged:
+                mx0, my0, mx1, my1 = merged
+                mx0 = max(0, min(mx0, src_w - 1))
+                my0 = max(0, min(my0, src_h - 1))
+                mx1 = max(mx0 + 1, min(mx1, src_w))
+                my1 = max(my0 + 1, min(my1, src_h))
+                uw, uh = int(mx1 - mx0), int(my1 - my0)
+                ucol = getattr(image, "COLOR_GREEN", color_cycle[0])
+                # 画粗一点的 union：描两遍错位矩形简易模拟加粗
+                for d in (0, 2):
+                    img.draw_rect(
+                        int(mx0) - d,
+                        int(my0) - d,
+                        uw + 2 * d,
+                        uh + 2 * d,
+                        color=ucol,
+                    )
+                img.draw_string(
+                    int(mx0),
+                    max(0, int(my0) - 28),
+                    f"UNION ({len(cand)} boxes)",
+                    color=ucol,
+                )
+                print(f"[INFO] UNION [{int(mx0)},{int(my0)},{int(mx1)},{int(my1)}] from {len(cand)} boxes")
+        else:
+            print("[WARN] --union 但 RING_CLASS_IDS 过滤后无框")
+
+    try:
+        img.save(out_path, quality=95)
+    except TypeError:
+        img.save(out_path)
+    print(f"[OK] saved: {out_path}")
+
+
+if __name__ == "__main__":
+    main()

train_yolo/train_black_triangle_pos.py

@@ -0,0 +1,506 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+YOLO11 关键点检测训练脚本（靶纸四角）。
+
+设备优先级（--device auto）：Intel XPU > NVIDIA CUDA > CPU。
+默认 imgsz=960；批大小默认 4（大图显存紧张时可再降）。
+
+关于「业务像素误差」：
+  Ultralytics 没有在 yaml 里设定「像素阈值」的选项；反向传播仍由 pose/kobj/box 等内部 loss 驱动。
+  - 监控：--pixel-metrics-every N（每 N 个 epoch 打印 mean/p95，并合并进 runs/.../results.csv，见 pose_pixel_metrics.py）。
+  - 选 best.pt / early stopping：加 --best-by-pixel，用验证集 mean 像素误差（与 pose_pixel_metrics
+    同一口径）代替 mAP 合成 fitness（fitness = -mean_px，越小越好）。
+    多卡 DDP（world_size>1）时会自动退回默认 mAP fitness。
+
+  XPU：Ultralytics BaseTrainer._get_memory / _clear_memory 把非 MPS、非 CPU 一律当 CUDA，
+  会在验证前调用 torch.cuda 而报错；本脚本在选用 XPU 时自动打补丁（见 _patch_ultralytics_trainer_for_xpu）。
+
+  务必使用 pose 任务：YOLO(...) 与 model.train(...) 均指定 task='pose'。若误用默认 detect，
+  会把 17 列 Pose 标注当成检测/分割解析，校验时出现「coordinates > 1」或 [2.] 等假象。
+"""
+
+from __future__ import annotations
+
+import argparse
+import csv
+import gc
+import glob
+import os
+import tempfile
+from copy import deepcopy
+from pathlib import Path
+
+import torch
+from ultralytics import YOLO
+
+from pose_pixel_metrics import eval_val_pixel_error
+import warnings
+warnings.filterwarnings('ignore', 
+    message=".*scatter_add_kernel does not have a deterministic implementation.*")
+
+
+def _clear_ultralytics_label_caches(data_yaml_path: str) -> int:
+    """删除 data.yaml 的 path 下 labels/*.cache。
+
+    Ultralytics 的校验缓存 hash 仅依赖「标签/图片路径字符串 + 各文件 size 之和」，不含文件内容；
+    修正 *.txt 后若总和巧合不变，可能继续加载旧 cache 并重播旧的 corrupt 日志，训练前应删掉。"""
+    from ultralytics.utils import YAML
+
+    try:
+        cfg = YAML.load(data_yaml_path)
+    except Exception:
+        return 0
+    root = cfg.get("path")
+    if not root:
+        return 0
+    root = os.path.abspath(os.path.expanduser(str(root)))
+    pattern = os.path.join(root, "labels", "*.cache")
+    n = 0
+    for p in glob.glob(pattern):
+        try:
+            os.unlink(p)
+            n += 1
+        except OSError:
+            pass
+    return n
+
+
+def _pick_device(explicit: str | None):
+    """返回 ultralytics train/predict 可用的 device。"""
+    if explicit and explicit != "auto":
+        e = explicit.lower()
+        if e == "xpu":
+            if getattr(torch, "xpu", None) is None or not torch.xpu.is_available():
+                raise RuntimeError("指定了 --device xpu 但当前环境不可用")
+            return torch.device("xpu")
+        if e in ("0", "cuda", "gpu"):
+            if not torch.cuda.is_available():
+                raise RuntimeError("指定了 CUDA 但不可用")
+            return 0
+        if e == "cpu":
+            return "cpu"
+        return explicit
+    if getattr(torch, "xpu", None) is not None and torch.xpu.is_available():
+        return torch.device("xpu")
+    if torch.cuda.is_available():
+        return 0
+    return "cpu"
+
+
+def _default_amp(device) -> bool:
+    if isinstance(device, torch.device) and device.type == "xpu":
+        return False
+    if device == "cpu":
+        return False
+    return True
+
+
+def _patch_ultralytics_for_xpu():
+    """为 Ultralytics 打补丁，使其能在 XPU 环境下正常训练和验证。"""
+    import ultralytics.engine.trainer as ut_trainer
+    import ultralytics.engine.validator as ut_validator
+    from ultralytics.utils.torch_utils import select_device as _original_select_device
+
+    # 1. 覆盖 select_device：Trainer 初始化传入 torch.device("xpu") 会走原版早返回；
+    #    初始化后 args.device 会变成字符串 "xpu"，中期 val 用 trainer.device，不调用 select_device；
+    #    训练结束 final_eval 里 Validator 会 select_device("xpu")，且 validator 在 import 时已绑定原函数，
+    #    只改 torch_utils 无效，必须同时修补 trainer/validator 模块内的引用。
+    def _patched_select_device(device="", *args, **kwargs):
+        # Ultralytics 8.4.x: select_device(device="", newline=False, verbose=True)
+        # Older forks sometimes passed extra positional args; forward everything.
+        if isinstance(device, str):
+            d = device.strip().lower()
+            if d == "xpu" or d.startswith("xpu:"):
+                return torch.device(device.strip())
+        return _original_select_device(device, *args, **kwargs)
+
+    import ultralytics.utils.torch_utils
+
+    ultralytics.utils.torch_utils.select_device = _patched_select_device
+    ut_trainer.select_device = _patched_select_device
+    ut_validator.select_device = _patched_select_device
+
+    # 2. 修补 Trainer 的内存函数
+    BT = ut_trainer.BaseTrainer
+    if not getattr(BT, "_archery_xpu_memory_patched", False):
+        _orig_get_memory = BT._get_memory
+        _orig_clear_memory = BT._clear_memory
+
+        def _get_memory(self, fraction=False):
+            if self.device.type != "xpu":
+                return _orig_get_memory(self, fraction)
+            # ... (原有的 XPU 内存获取逻辑保持不变) ...
+            memory, total = 0, 0
+            try:
+                idx = self.device.index
+                if idx is None:
+                    idx = torch.xpu.current_device()
+                memory = int(torch.xpu.memory_allocated(idx))
+                if fraction:
+                    total = int(torch.xpu.get_device_properties(idx).total_memory)
+            except Exception:
+                pass
+            return (memory / total) if fraction and total > 0 else (memory / 2**30)
+
+        def _clear_memory(self, threshold=None):
+            if self.device.type != "xpu":
+                return _orig_clear_memory(self, threshold)
+            if threshold is not None:
+                assert 0 <= threshold <= 1, "Threshold must be between 0 and 1."
+                if self._get_memory(fraction=True) <= threshold:
+                    return
+            gc.collect()
+            if hasattr(torch.xpu, "empty_cache"):
+                torch.xpu.empty_cache()
+
+        BT._get_memory = _get_memory
+        BT._clear_memory = _clear_memory
+        BT._archery_xpu_memory_patched = True
+
+    # 3. 修补 Validator 的内存函数 (关键是添加这部分)
+    BV = ut_validator.BaseValidator
+    if not getattr(BV, "_archery_xpu_memory_patched", False):
+        # 为 Validator 添加同样的内存处理方法
+        BV._get_memory = _get_memory
+        BV._clear_memory = _clear_memory
+        BV._archery_xpu_memory_patched = True
+
+
+def _install_best_by_pixel_validate(data_yaml: str, imgsz: int, conf: float) -> None:
+    """用验证集关键点像素 mean 替代 mAP fitness，驱动 best.pt 与 patience early stopping。"""
+    import ultralytics.engine.trainer as ut
+    from ultralytics.utils import RANK
+
+    BT = ut.BaseTrainer
+    if getattr(BT, "_archery_best_by_pixel_installed", False):
+        return
+
+    _orig_validate = BT.validate
+
+    def validate(self):
+        import torch.distributed as dist
+
+        if self.ema and self.world_size > 1:
+            for buffer in self.ema.ema.buffers():
+                dist.broadcast(buffer, src=0)
+        metrics = self.validator(self)
+        if metrics is None:
+            return None, None
+        orig_fitness = metrics.pop("fitness", -self.loss.detach().cpu().numpy())
+
+        use_pixel = self.world_size <= 1 and RANK in {-1, 0}
+        mean_px: float | None = None
+        if use_pixel:
+            tmp_path: str | None = None
+            try:
+                fd, tmp_path = tempfile.mkstemp(suffix=".pt", prefix="archery_pxfit_")
+                os.close(fd)
+                from ultralytics.utils.torch_utils import unwrap_model
+
+                core = unwrap_model(self.ema.ema if self.ema else self.model)
+                torch.save({"ema": deepcopy(core).half(), "train_args": vars(self.args)}, tmp_path)
+                probe = YOLO(tmp_path)
+                stats = eval_val_pixel_error(
+                    probe,
+                    data_yaml,
+                    device=self.device,
+                    imgsz=imgsz,
+                    conf=conf,
+                )
+                mean_px = stats.get("mean_px")
+                if mean_px is None:
+                    raise RuntimeError("无有效 mean_px（检查 val 标签与检测是否为空）")
+            except Exception as exc:
+                print(f"\n⚠️ [best-by-pixel] 像素探针失败，本 epoch 仍用 mAP fitness: {exc}\n")
+                mean_px = None
+            finally:
+                if tmp_path:
+                    try:
+                        os.unlink(tmp_path)
+                    except OSError:
+                        pass
+
+        if mean_px is not None:
+            fitness = -float(mean_px)
+            metrics["metrics/mean_px(val)"] = float(mean_px)
+        else:
+            fitness = float(orig_fitness)
+
+        if not self.best_fitness or self.best_fitness < fitness:
+            self.best_fitness = fitness
+        return metrics, fitness
+
+    BT.validate = validate
+    BT._archery_best_by_pixel_installed = True
+
+
+def _fmt_csv_metric(v: float | int | None) -> str:
+    if v is None:
+        return ""
+    if isinstance(v, float):
+        return f"{v:.6g}"
+    return str(v)
+
+
+# 写入 results.csv 的列名（与 --best-by-pixel 的 metrics/mean_px(val) 区分，避免被 last.pt 回调覆盖 EMA 行）
+_PIXEL_METRIC_COLUMNS: tuple[tuple[str, str], ...] = (
+    ("pixel_error/mean_px", "mean_px"),
+    ("pixel_error/median_px", "median_px"),
+    ("pixel_error/p95_px", "p95_px"),
+    ("pixel_error/max_px", "max_px"),
+    ("pixel_error/n_points", "n_points"),
+    ("pixel_error/n_images", "n_images"),
+    ("pixel_error/skip_no_det", "skip_no_det"),
+    ("pixel_error/skip_no_gt", "skip_no_gt"),
+    ("pixel_error/skip_kpt_mismatch", "skip_kpt_mismatch"),
+)
+
+
+def _merge_pixel_metrics_into_results_csv(save_dir: str | Path, epoch_1based: int, stats: dict) -> None:
+    """在 Ultralytics 写完本 epoch 行之后，把像素指标列合并进 results.csv（扩展表头、补空列）。"""
+    csv_path = Path(save_dir) / "results.csv"
+    if not csv_path.is_file():
+        return
+    try:
+        with open(csv_path, newline="", encoding="utf-8") as f:
+            rows = list(csv.reader(f))
+    except OSError:
+        return
+    if len(rows) < 2:
+        return
+    header = list(rows[0])
+    for col_name, _ in _PIXEL_METRIC_COLUMNS:
+        if col_name not in header:
+            header.append(col_name)
+            for ri in range(1, len(rows)):
+                rows[ri].append("")
+    col_ix = {name: i for i, name in enumerate(header)}
+    rows[0] = header
+    target_ri: int | None = None
+    for ri in range(1, len(rows)):
+        row = rows[ri]
+        while len(row) < len(header):
+            row.append("")
+        try:
+            if int(float(row[0].strip())) == int(epoch_1based):
+                target_ri = ri
+        except (ValueError, IndexError):
+            continue
+    if target_ri is None:
+        return
+    row = rows[target_ri]
+    while len(row) < len(header):
+        row.append("")
+    for col_name, sk in _PIXEL_METRIC_COLUMNS:
+        row[col_ix[col_name]] = _fmt_csv_metric(stats.get(sk))
+    try:
+        with open(csv_path, "w", newline="", encoding="utf-8") as f:
+            w = csv.writer(f)
+            w.writerows(rows)
+    except OSError:
+        pass
+
+
+def _make_pixel_metrics_callback(data_yaml: str, every: int, imgsz: int, conf: float = 0.25):
+    def on_fit_epoch_end(trainer):
+        from ultralytics.utils import RANK
+
+        if RANK not in {-1, 0}:
+            return
+        if every <= 0:
+            return
+        ep = int(getattr(trainer, "epoch", -1))
+        if (ep + 1) % every != 0:
+            return
+        w = Path(trainer.save_dir) / "weights" / "last.pt"
+        if not w.is_file():
+            return
+        m = YOLO(str(w))
+        stats = eval_val_pixel_error(
+            m,
+            data_yaml,
+            device=trainer.device,
+            imgsz=imgsz,
+            conf=conf,
+        )
+        mean_px = stats.get("mean_px")
+        p95_px = stats.get("p95_px")
+        mean_s = f"{mean_px:.3f}" if mean_px is not None else "n/a"
+        p95_s = f"{p95_px:.3f}" if p95_px is not None else "n/a"
+        print(
+            f"\n[pixel-metrics] epoch {ep + 1}: mean_px={mean_s} p95_px={p95_s} "
+            f"n_points={stats.get('n_points', 0)} "
+            f"skip(det/gt/k)={stats['skip_no_det']}/{stats['skip_no_gt']}/{stats['skip_kpt_mismatch']}\n"
+        )
+        _merge_pixel_metrics_into_results_csv(trainer.save_dir, ep + 1, stats)
+
+    return on_fit_epoch_end
+
+
+def main():
+    ap = argparse.ArgumentParser(description="YOLO Pose 训练（XPU/CUDA/CPU）")
+    ap.add_argument("--data", default="datasets/dataset_pose.yaml", help="data.yaml")
+    ap.add_argument("--model", default="yolo11x-pose.pt", help="预训练权重")
+    ap.add_argument("--epochs", type=int, default=100)
+    ap.add_argument("--imgsz", type=int, default=960, help="训练输入边长（默认 960）")
+    ap.add_argument("--batch", type=int, default=4, help="批大小；OOM 时减小")
+    ap.add_argument(
+        "--device",
+        default="auto",
+        help="auto | xpu | 0 | cuda | cpu（auto：XPU 优先）",
+    )
+    ap.add_argument(
+        "--no-amp",
+        action="store_true",
+        help="关闭混合精度（默认：CUDA 开启，XPU/CPU 关闭）",
+    )
+    ap.add_argument("--project", default="runs/pose")
+    ap.add_argument("--name", default="target_pose_train")
+    ap.add_argument("--workers", type=int, default=4)
+    ap.add_argument(
+        "--pixel-metrics-every",
+        type=int,
+        default=0,
+        help="每 N 个 epoch 在 val 上打印像素误差并写入 results.csv 对应 epoch 行（0=关闭）；需 labels 与 data.yaml 布局一致",
+    )
+    ap.add_argument(
+        "--pixel-metrics-conf",
+        type=float,
+        default=0.25,
+        help="--pixel-metrics-every 时 predict 置信度阈值（默认 0.25）",
+    )
+    ap.add_argument(
+        "--best-by-pixel",
+        action="store_true",
+        help="best.pt 与 early stopping 按验证集 mean 像素误差（同 pose_pixel_metrics），fitness=-mean_px；单卡有效，DDP 自动退回 mAP",
+    )
+    ap.add_argument(
+        "--pixel-fitness-conf",
+        type=float,
+        default=0.25,
+        help="--best-by-pixel 时 predict 置信度阈值（默认与 pixel-metrics 一致）",
+    )
+    ap.add_argument(
+        "--export-onnx",
+        action="store_true",
+        help="训练结束后导出 ONNX（需再设 --onnx-imgsz）",
+    )
+    ap.add_argument(
+        "--onnx-imgsz",
+        type=int,
+        nargs=2,
+        metavar=("H", "W"),
+        default=[224, 320],
+        help="导出 ONNX 的 [高, 宽]，默认 224 320（Maix 常用）",
+    )
+    ap.add_argument(
+        "--clear-label-cache",
+        action="store_true",
+        help="启动训练前删除 data.yaml 中 path 下的 labels/*.cache（修正标注后仍报 corrupt 时用）",
+    )
+    args = ap.parse_args()
+
+    device = _pick_device(None if args.device == "auto" else args.device)
+    use_amp = False if args.no_amp else _default_amp(device)
+
+    if isinstance(device, torch.device) and device.type == "xpu":
+        print(f"✅ 使用 Intel XPU: {device}")
+    elif device == 0 or device == "0":
+        print(f"✅ 使用 CUDA: {torch.cuda.get_device_name(0)}")
+    else:
+        print("⚠️ 使用 CPU，训练会较慢")
+
+    if isinstance(device, torch.device) and device.type == "xpu":
+        _patch_ultralytics_for_xpu()
+
+    data_yaml = args.data
+    if not os.path.isabs(data_yaml):
+        data_yaml = os.path.join(os.path.dirname(os.path.abspath(__file__)), data_yaml)
+    if not os.path.exists(data_yaml):
+        print(f"❌ 数据集配置不存在: {data_yaml}")
+        return
+
+    if args.clear_label_cache:
+        n_rm = _clear_ultralytics_label_caches(data_yaml)
+        print(f"🗑️ 已删除标签目录缓存 {n_rm} 个（labels/*.cache），将强制重新扫描标注。")
+
+    print(f"📦 加载模型: {args.model}（固定 task=pose）")
+    model = YOLO(args.model, task="pose")
+
+    if args.best_by_pixel:
+        _install_best_by_pixel_validate(data_yaml, args.imgsz, args.pixel_fitness_conf)
+        print(
+            "📌 已启用 --best-by-pixel：best.pt / patience 按验证集 mean 像素误差（fitness=-mean_px）；"
+            "反向传播仍为 Ultralytics 默认 pose/box loss。"
+        )
+
+    if args.pixel_metrics_every > 0:
+        model.add_callback(
+            "on_fit_epoch_end",
+            _make_pixel_metrics_callback(
+                data_yaml, args.pixel_metrics_every, args.imgsz, conf=args.pixel_metrics_conf
+            ),
+        )
+
+    model.train(
+        task="pose",
+        data=data_yaml,
+        epochs=args.epochs,
+        imgsz=args.imgsz,
+        batch=args.batch,
+        name=args.name,
+        project=args.project,
+        exist_ok=True,
+        save=True,
+        save_period=5,
+        device=device,
+        workers=args.workers,
+        lr0=0.0001,
+        lrf=0.01,
+        optimizer="AdamW",
+        momentum=0.937,
+        weight_decay=0.001,
+        warmup_epochs=0,
+        warmup_momentum=0.8,
+        warmup_bias_lr=0.1,
+        hsv_h=0.015,
+        hsv_s=0.7,
+        hsv_v=0.4,
+        degrees=5.0,
+        translate=0.0,
+        scale=0.2,
+        shear=0.0,
+        perspective=0.0000,
+        flipud=0.0,
+        fliplr=0.5,
+        mosaic=0.0,
+        mixup=0.0,
+        copy_paste=0.0,
+        box=6,
+        cls=0.5,
+        dfl=1.5,
+        pose=18.0,
+        kobj=0.5,
+        freeze=0,
+        seed=42,
+        verbose=True,
+        amp=use_amp,
+        patience=100,
+        cos_lr=True,
+    )
+
+    print("\n✅ 训练完成！")
+    print(f"📁 best: {args.project}/{args.name}/weights/best.pt")
+    print(f"📁 last: {args.project}/{args.name}/weights/last.pt")
+    print("📊 仅看像素误差可运行: python pose_pixel_metrics.py --model <best.pt> --data <yaml> --imgsz", args.imgsz)
+
+    if args.export_onnx:
+        h, w = args.onnx_imgsz
+        print(f"📦 导出 ONNX imgsz=[{h}, {w}] ...")
+        model.export(format="onnx", imgsz=[h, w], simplify=True, opset=17, dynamic=False)
+        print("✅ ONNX 完成")
+
+
+if __name__ == "__main__":
+    main()

triangle_positions.json

@@ -0,0 +1,6 @@
+{
+    "0": [-20.0, -20.0, 0.0],
+    "1": [-20.0,  20.0, 0.0],
+    "2": [ 20.0,  20.0, 0.0],
+    "3": [ 20.0, -20.0, 0.0]
+}

version.py

@@ -0,0 +1,30 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+应用版本号
+每次 OTA 更新时，只需要更新这个文件中的版本号
+"""
+VERSION = '1.2.12'
+
+# 1.2.0 开始使用C++编译成.so，替换部分代码
+# 1.2.1 ota使用加密包
+# 1.2.2 支持wifi ota，并且设定时区，并使用单独线程保存图片
+# 1.2.3 修改ADC_TRIGGER_THRESHOLD 为2300，支持上传日志到服务器
+# 1.2.4 修改ADC_TRIGGER_THRESHOLD 为3000，并默认关闭摄像头的显示，并把ADC的采样间隔从50ms降低到10ms
+# 1.2.5 支持空气传感器采样，并默认关闭日志。优化断网时的发送队列丢消息问题，解决 WiFi 断线检测不可靠问题。
+# 1.2.6 在链接 wifi 前先判断 wifi 的可用性，假如不可用，则不落盘。增加日志批量压缩上传功能
+# 1.2.7 修复OTA失败的bug, 空气压力传感器的阈值是2500
+# 1.2.8 （1） 加快 wifi 下数据传输的速度。（2） 调整射箭时处理的逻辑，优先上报数据，再存照片之类的操作。（3）假如是用户打开激光的，射箭触发后不再关闭激光，因为是调瞄阶段
+# 1.2.9 增加电源板的控制和自动关机的功能
+# 1.2.10 config formal
+# 1.2.11 增加三角形的单应性算法，适配对应的靶纸
+# 1.2.110 关掉了黑色三角形算法，只用于测试
+
+
+
+
+
+
+
+
+

wifi.py

@@ -0,0 +1,685 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+WiFi管理模块
+提供WiFi连接、网络检测、质量监测等功能
+"""
+import os
+import re
+import socket
+import threading
+import time as std_time
+from maix import time
+
+import config
+from logger_manager import logger_manager
+from wpa_supplicant_conf import build_sta_conf_open, build_sta_conf_psk
+
+
+class WiFiManager:
+    """WiFi管理器（单例）"""
+    _instance = None
+    
+    def __new__(cls):
+        if cls._instance is None:
+            cls._instance = super(WiFiManager, cls).__new__(cls)
+            cls._instance._initialized = False
+        return cls._instance
+    
+    def __init__(self):
+        if self._initialized:
+            return
+        
+        # WiFi 相关状态
+        self._wifi_connected = False
+        self._wifi_ip = None
+        self._wifi_socket = None
+        self._wifi_socket_lock = threading.Lock()
+        self._prefer_wifi = True  # 是否优先使用 WiFi
+        self._recv_buffer = b""  # TCP 接收缓冲区
+        
+        # WiFi 质量监测（后台线程）
+        self._wifi_quality_monitor_thread = None
+        self._wifi_quality_stop_event = threading.Event()
+        self._last_wifi_rtt_ms = None  # 最近一次测量的 RTT
+        self._last_wifi_rssi_dbm = None  # 最近一次测量的 RSSI
+        
+        # 服务器相关（用于网络检测）
+        try:
+            import archery_netcore as _netcore
+            self._server_ip = _netcore.get_config().get("SERVER_IP")
+            self._server_port = _netcore.get_config().get("SERVER_PORT")
+        except Exception:
+            self._server_ip = getattr(config, "SERVER_IP", None)
+            self._server_port = getattr(config, "SERVER_PORT", None)
+        
+        self._initialized = True
+    
+    @property
+    def logger(self):
+        """获取 logger 对象"""
+        return logger_manager.logger
+    
+    @property
+    def wifi_connected(self):
+        """WiFi是否已连接"""
+        return self._wifi_connected
+    
+    @property
+    def wifi_ip(self):
+        """WiFi IP地址"""
+        return self._wifi_ip
+    
+    @property
+    def wifi_socket(self):
+        """WiFi socket对象"""
+        return self._wifi_socket
+    
+    @wifi_socket.setter
+    def wifi_socket(self, value):
+        """设置WiFi socket对象"""
+        self._wifi_socket = value
+    
+    @property
+    def wifi_socket_lock(self):
+        """获取WiFi socket锁"""
+        return self._wifi_socket_lock
+    
+    @property
+    def prefer_wifi(self):
+        """是否优先使用WiFi"""
+        return self._prefer_wifi
+    
+    @prefer_wifi.setter
+    def prefer_wifi(self, value):
+        """设置是否优先使用WiFi"""
+        self._prefer_wifi = value
+    
+    @property
+    def last_wifi_rtt_ms(self):
+        """最近一次测量的RTT"""
+        return self._last_wifi_rtt_ms
+    
+    @property
+    def last_wifi_rssi_dbm(self):
+        """最近一次测量的RSSI"""
+        return self._last_wifi_rssi_dbm
+    
+    @property
+    def recv_buffer(self):
+        """TCP接收缓冲区"""
+        return self._recv_buffer
+    
+    @recv_buffer.setter
+    def recv_buffer(self, value):
+        """设置TCP接收缓冲区"""
+        self._recv_buffer = value
+    
+    # ==================== WiFi 连接方法 ====================
+    
+    def is_sta_associated(self):
+        """
+        是否作为 STA 已关联到上游 AP（用于与 AP 模式区分：AP 模式下 wlan0 可能有 IP 但 iw link 为 Not connected）。
+        """
+        try:
+            out = os.popen("iw dev wlan0 link 2>/dev/null").read()
+            if not out.strip():
+                return False
+            if "Not connected" in out:
+                return False
+            return "Connected to" in out
+        except Exception:
+            return False
+
+    def is_wifi_connected(self):
+        """检查WiFi是否已连接"""
+        # AP 模式下 wlan0 也可能有 IP（如 192.168.66.1），但这不代表已作为 STA 连上路由器。
+        # 业务侧（选网/TCP）只应在 STA 已关联到上游 AP 时认为 WiFi 可用。
+        if not self.is_sta_associated():
+            self._wifi_connected = False
+            return False
+
+        # 优先用 MaixPy network（如果可用）
+        try:
+            from maix import network
+            wifi = network.wifi.Wifi()
+            if wifi.is_connected():
+                self._wifi_connected = True
+                # MaixPy 的 is_connected 可能不会同步填充 IP，这里用系统命令补齐一次
+                try:
+                    ip = os.popen("ifconfig wlan0 2>/dev/null | grep 'inet ' | awk '{print $2}'").read().strip()
+                    if ip:
+                        self._wifi_ip = ip
+                except Exception:
+                    pass
+                return True
+        except:
+            self.logger.warning("Failed to check WiFi connection using MaixPy network", exc_info=True)
+        
+        # 兜底：看系统 wlan0 有没有 IP
+        try:
+            ip = os.popen("ifconfig wlan0 2>/dev/null | grep 'inet ' | awk '{print $2}'").read().strip()
+            if ip:
+                self._wifi_connected = True
+                self._wifi_ip = ip
+                return True
+        except:
+            self.logger.warning("Failed to check WiFi connection using system command", exc_info=True)
+        
+        self._wifi_connected = False
+        return False
+    
+    def connect_wifi(self, ssid, password, verify_callback=None, persist=True, timeout_s=20):
+        """
+        连接 Wi-Fi（唯一实现：写 wpa_supplicant + /boot 凭证，MaixPy Wifi.connect，再等 IP 与可选校验）。
+
+        ``NetworkManager.connect_wifi`` 仅封装本方法（通过 ``verify_callback`` 传入 host/port 校验）。
+
+        重要：``/boot/wpa_supplicant.conf`` 存在时 S30wifi 会优先 cp，避免 shell 传中文 SSID。
+
+        Args:
+            ssid: WiFi SSID
+            password: WiFi密码
+            verify_callback: 可选；``(ip) -> (success: bool, error: str)``，在拿到 IP 后调用
+            persist: 是否持久化保存凭证（False 时成功后回滚 /boot 与 /etc 中的本次写入）
+            timeout_s: 等待 DHCP / 轮询 IP 的超时基数（秒）；Maix 连接超时亦据此推导
+
+        Returns:
+            (ip, error): IP地址和错误信息（成功时 error 为 None）
+        """
+        # 配置文件路径定义
+        conf_path = "/etc/wpa_supplicant.conf"
+        boot_wpa_path = "/boot/wpa_supplicant.conf"
+        ssid_file = "/boot/wifi.ssid"
+        pass_file = "/boot/wifi.pass"
+
+        def _read_text(path: str):
+            try:
+                if os.path.exists(path):
+                    with open(path, "r", encoding="utf-8") as f:
+                        return f.read()
+            except Exception:
+                return None
+            return None
+
+        def _write_text(path: str, content: str):
+            with open(path, "w", encoding="utf-8") as f:
+                f.write(content)
+
+        def _restore_boot(old_ssid: str | None, old_pass: str | None):
+            # 还原 /boot 凭证：原来没有就删除，原来有就写回
+            try:
+                if old_ssid is None:
+                    if os.path.exists(ssid_file):
+                        os.remove(ssid_file)
+                else:
+                    _write_text(ssid_file, old_ssid)
+            except Exception:
+                pass
+            try:
+                if old_pass is None:
+                    if os.path.exists(pass_file):
+                        os.remove(pass_file)
+                else:
+                    _write_text(pass_file, old_pass)
+            except Exception:
+                pass
+
+        def _restore_boot_wpa(old_wpa: str | None):
+            try:
+                if old_wpa is None:
+                    if os.path.exists(boot_wpa_path):
+                        os.remove(boot_wpa_path)
+                else:
+                    _write_text(boot_wpa_path, old_wpa)
+            except Exception:
+                pass
+
+        old_conf = _read_text(conf_path)
+        old_boot_ssid = _read_text(ssid_file)
+        old_boot_pass = _read_text(pass_file)
+        old_boot_wpa = _read_text(boot_wpa_path) if os.path.exists(boot_wpa_path) else None
+
+        try:
+            try:
+                full_conf = build_sta_conf_psk(ssid.strip(), password.strip())
+            except ValueError as ve:
+                raise RuntimeError(str(ve)) from ve
+
+            try:
+                _write_text(conf_path, full_conf)
+            except Exception:
+                pass
+            _write_text(boot_wpa_path, full_conf)
+
+            # 仍写入 ssid/pass，便于其它脚本/人工查看；S30wifi 优先使用 wpa_supplicant.conf
+            _write_text(ssid_file, ssid.strip())
+            _write_text(pass_file, password.strip())
+
+            from maix import err as maix_err
+            from maix import network as maix_net
+
+            self.logger.info(f"[WIFI] Maix connect start ssid={ssid!r}")
+            w = maix_net.wifi.Wifi()
+            connect_timeout_s = int(timeout_s) if timeout_s and timeout_s > 0 else 60
+            connect_timeout_s = max(10, min(connect_timeout_s, 120))
+            e = w.connect(ssid, password, wait=True, timeout=connect_timeout_s)
+            maix_err.check_raise(e, "connect wifi failed")
+            try:
+                maix_ip = w.get_ip()
+            except Exception:
+                maix_ip = None
+            self.logger.info(f"[WIFI] Maix connect ok ip={maix_ip!r}")
+
+            # 等待获取 IP
+            wait_s = int(timeout_s) if timeout_s and timeout_s > 0 else 20
+            wait_s = min(max(wait_s, 5), 60)
+            for _ in range(wait_s):
+                ip = os.popen("ifconfig wlan0 2>/dev/null | grep 'inet ' | awk '{print $2}'").read().strip()
+                if ip:
+                    # 拿到 IP 不代表可上网/可访问目标；继续做可达性验证
+                    self._wifi_connected = True
+                    self._wifi_ip = ip
+                    self.logger.info(f"[WIFI] 已连接，IP: {ip}，开始验证网络可用性...")
+
+                    # 验证能访问指定目标（通过回调函数）
+                    if verify_callback:
+                        success, error = verify_callback(ip)
+                        if not success:
+                            raise RuntimeError(error or "Verification failed")
+
+                    # ====== 验证通过 ======
+                    if not persist:
+                        # 不持久化：把 /boot 恢复成旧值（不重启，当前连接保持不变）
+                        _restore_boot(old_boot_ssid, old_boot_pass)
+                        _restore_boot_wpa(old_boot_wpa)
+                        self.logger.info("[WIFI] 网络验证通过，但按 persist=False 回滚 /boot 凭证（不重启）")
+                    else:
+                        self.logger.info("[WIFI] 网络验证通过，/boot 凭证已保留（持久化）")
+
+                    return ip, None
+
+                std_time.sleep(1)
+
+            raise RuntimeError("Timeout: No IP obtained")
+
+        except Exception as e:
+            # 失败：回滚 /boot 和 /etc，重启 WiFi 恢复旧网络
+            _restore_boot(old_boot_ssid, old_boot_pass)
+            _restore_boot_wpa(old_boot_wpa)
+            try:
+                if old_conf is not None:
+                    _write_text(conf_path, old_conf)
+            except Exception:
+                pass
+            try:
+                os.system("/etc/init.d/S30wifi restart")
+            except Exception:
+                pass
+
+            self._wifi_connected = False
+            self._wifi_ip = None
+            self.logger.error(f"[WIFI] 连接/验证失败，已回滚: {e}")
+            return None, str(e)
+
+    def persist_sta_credentials(self, ssid: str, password: str, restart_service: bool = True):
+        """
+        仅写入 STA 凭证（/etc/wpa_supplicant.conf、/boot/wpa_supplicant.conf、/boot/wifi.ssid|pass），
+        可选是否立即 /etc/init.d/S30wifi restart。
+        不做可达性验证。用于热点配网页提交后切换到连接指定路由器。
+        password 为空时按开放网络（key_mgmt=NONE）写入。
+        Returns:
+            (ok: bool, err_msg: str)
+        """
+        ssid = (ssid or "").strip()
+        password = (password or "").strip()
+        if not ssid:
+            return False, "SSID 为空"
+
+        conf_path = "/etc/wpa_supplicant.conf"
+        boot_wpa_path = "/boot/wpa_supplicant.conf"
+        ssid_file = "/boot/wifi.ssid"
+        pass_file = "/boot/wifi.pass"
+
+        def _write_text(path: str, content: str):
+            with open(path, "w", encoding="utf-8") as f:
+                f.write(content)
+
+        try:
+            if password:
+                full_conf = build_sta_conf_psk(ssid, password)
+            else:
+                full_conf = build_sta_conf_open(ssid)
+            _write_text(conf_path, full_conf)
+            _write_text(boot_wpa_path, full_conf)
+        except ValueError as e:
+            return False, str(e)
+        except Exception as e:
+            return False, str(e)
+
+        try:
+            _write_text(ssid_file, ssid)
+            _write_text(pass_file, password)
+        except Exception as e:
+            return False, str(e)
+
+        if restart_service:
+            try:
+                os.system("/etc/init.d/S30wifi restart")
+            except Exception as e:
+                return False, str(e)
+            self.logger.info(f"[WIFI] persist_sta_credentials: 已写入并重启 S30wifi, ssid={ssid!r}")
+        else:
+            self.logger.info(f"[WIFI] persist_sta_credentials: 已写入凭证（未重启 S30wifi）, ssid={ssid!r}")
+        return True, ""
+
+    def disconnect_wifi(self):
+        """断开WiFi连接并清理资源"""
+        if self._wifi_socket:
+            try:
+                self._wifi_socket.close()
+            except Exception:
+                pass
+            finally:
+                self._wifi_socket = None
+        self._wifi_connected = False
+        self._wifi_ip = None
+    
+    # ==================== WiFi 质量监测 ====================
+    
+    def _get_wifi_rssi_dbm(self):
+        """
+        获取 WiFi 信号强度（dBm，越大越好；比如 -40 比 -80 好）
+        由于不同固件实现差异，这里做多策略兜底，失败返回 None
+        """
+        # 1) 优先使用：iw dev wlan0 link
+        #    你提供的输出示例包含：signal: -58 dBm
+        try:
+            out = os.popen("iw dev wlan0 link 2>/dev/null").read()
+            if out:
+                m = re.search(r"signal:\s*(-?\d+(?:\.\d+)?)\s*dBm", out, re.IGNORECASE)
+                if m:
+                    v = float(m.group(1))
+                    # 合理范围兜底
+                    if -120.0 <= v <= 0.0:
+                        return v
+                m2 = re.search(r"signal:\s*(-?\d+(?:\.\d+)?)", out, re.IGNORECASE)
+                if m2:
+                    v = float(m2.group(1))
+                    if -120.0 <= v <= 0.0:
+                        return v
+        except Exception:
+            pass
+
+        # 2) 兜底：iwconfig
+        try:
+            out = os.popen("iwconfig wlan0 2>/dev/null").read()
+            m = re.search(r"Signal level[=:]\s*(-?\d+(?:\.\d+)?)\s*dBm", out, re.IGNORECASE)
+            if m:
+                v = float(m.group(1))
+                if -120.0 <= v <= 0.0:
+                    return v
+            m2 = re.search(r"Signal level[=:]\s*(-?\d+(?:\.\d+)?)", out, re.IGNORECASE)
+            if m2:
+                v = float(m2.group(1))
+                if -120.0 <= v <= 0.0:
+                    return v
+        except Exception:
+            pass
+
+        return None
+    
+    def _measure_wifi_tcp_rtt_ms(self, host, port, samples=3, per_sample_timeout_ms=900):
+        """
+        测量：在当前 WiFi 下，TCP 建连耗时（RTT 的近似）
+        
+        Args:
+            host: 目标主机
+            port: 目标端口
+            samples: 采样次数
+            per_sample_timeout_ms: 每次采样超时时间（毫秒）
+        
+        Returns:
+            (median_rtt_ms, reachable_bool)
+        """
+        rtts = []
+        reachable = False
+        addr = None
+
+        # 先解析一次地址，避免每次样本都做 DNS
+        try:
+            addr_info = socket.getaddrinfo(host, port)[0]
+            addr = (addr_info[0], addr_info[1], addr_info[2], addr_info[-1])
+        except Exception:
+            return float("inf"), False
+
+        for _ in range(max(1, int(samples or 1))):
+            s = None
+            try:
+                s = socket.socket(addr[0], addr[1], addr[2])
+                s.settimeout(max(0.1, float(per_sample_timeout_ms) / 1000.0))
+                t0 = time.ticks_ms()
+                s.connect(addr[-1])
+                elapsed_ms = abs(time.ticks_diff(time.ticks_ms(), t0))
+                rtts.append(float(elapsed_ms))
+                reachable = True
+            except Exception:
+                # 单个样本失败不影响整体，只要有成功样本就继续
+                pass
+            finally:
+                try:
+                    if s:
+                        s.close()
+                except Exception:
+                    pass
+
+            # 小间隔，避免过度占用
+            try:
+                time.sleep_ms(100)
+            except Exception:
+                pass
+
+        if not rtts:
+            return float("inf"), False
+
+        rtts_sorted = sorted(rtts)
+        mid = len(rtts_sorted) // 2
+        if len(rtts_sorted) % 2 == 1:
+            median = rtts_sorted[mid]
+        else:
+            median = (rtts_sorted[mid - 1] + rtts_sorted[mid]) / 2.0
+        return median, reachable
+    
+    def _is_wifi_quality_bad(self, wifi_rtt_ms, wifi_rssi_dbm):
+        """
+        综合判断 WiFi 质量是否差：
+        - RTT中位数超过阈值 -> bad
+        - 若启用 RSSI：信号弱(RSSI更差于阈值) 且 RTT 也偏高 -> bad
+        """
+        if wifi_rtt_ms >= config.WIFI_QUALITY_RTT_BAD_MS:
+            return True
+
+        if not getattr(config, "WIFI_QUALITY_USE_RSSI", False):
+            return False
+
+        if wifi_rssi_dbm is None:
+            return False
+
+        # "rtt_warn + rssi_bad" 联合条件
+        if wifi_rtt_ms >= config.WIFI_QUALITY_RTT_WARN_MS and wifi_rssi_dbm <= config.WIFI_QUALITY_RSSI_BAD_DBM:
+            return True
+
+        return False
+    
+    def get_wifi_quality_status(self):
+        """
+        获取当前 WiFi 质量状态（用于调试或显示）
+        
+        Returns:
+            dict: {"rtt_ms": float, "rssi_dbm": float, "is_bad": bool}
+        """
+        rtt = self._last_wifi_rtt_ms
+        rssi = self._last_wifi_rssi_dbm
+        is_bad = False
+        
+        if rtt is not None and rtt != float("inf"):
+            is_bad = self._is_wifi_quality_bad(rtt, rssi)
+        
+        return {
+            "rtt_ms": rtt if rtt is not None and rtt != float("inf") else None,
+            "rssi_dbm": rssi,
+            "is_bad": is_bad
+        }
+    
+    # ==================== 后台质量监测线程 ====================
+    
+    def start_quality_monitor(self, network_type_callback, on_poor_quality_callback):
+        """
+        启动 WiFi 质量后台监测线程（每 5 秒测量一次 RTT 和 RSSI）
+        只在 WiFi 连接时运行，不影响业务发送性能
+        
+        Args:
+            network_type_callback: 获取当前网络类型的回调函数
+            on_poor_quality_callback: WiFi质量差时的回调函数
+        """
+        if self._wifi_quality_monitor_thread is not None:
+            self.logger.warning("[WiFi Monitor] 监测线程已在运行")
+            return
+        
+        self._network_type_callback = network_type_callback
+        self._on_poor_quality_callback = on_poor_quality_callback
+        self._wifi_quality_stop_event.clear()
+        self._wifi_quality_monitor_thread = threading.Thread(
+            target=self._quality_monitor_loop,
+            daemon=True,
+            name="wifi_quality_monitor"
+        )
+        self._wifi_quality_monitor_thread.start()
+        self.logger.info("[WiFi Monitor] 已启动后台监测线程")
+    
+    def stop_quality_monitor(self):
+        """停止 WiFi 质量监测线程"""
+        if self._wifi_quality_monitor_thread is None:
+            return
+        
+        self._wifi_quality_stop_event.set()
+        try:
+            self._wifi_quality_monitor_thread.join(timeout=2.0)
+        except Exception as e:
+            self.logger.error(f"[WiFi Monitor] 停止线程失败：{e}")
+        finally:
+            self._wifi_quality_monitor_thread = None
+            self.logger.info("[WiFi Monitor] 已停止后台监测线程")
+    
+    def _quality_monitor_loop(self):
+        """
+        WiFi 质量监测循环（后台线程）
+        每 5 秒测量一次 RTT 和 RSSI，发现质量差则触发切换
+        """
+        while not self._wifi_quality_stop_event.is_set():
+            try:
+                # 只在 WiFi 连接时才测量
+                network_type = self._network_type_callback()
+                if network_type == "wifi" and self._wifi_socket:
+                    # # 测量 RTT（1 个样本，快速测量）
+                    # rtt_ms, reachable = self._measure_wifi_tcp_rtt_ms(
+                    #     self._server_ip, self._server_port,
+                    #     samples=1, per_sample_timeout_ms=600
+                    # )
+                    
+                    # 获取 RSSI
+                    rssi_dbm = self._get_wifi_rssi_dbm()
+                    
+                    # 更新缓存
+                    # 不使用 RTT 测量
+                    rtt_ms = 0
+                    reachable = True
+                    self._last_wifi_rtt_ms = rtt_ms if reachable else None
+                    self._last_wifi_rssi_dbm = rssi_dbm
+                    _rssi_s = f"{rssi_dbm:.0f}" if rssi_dbm is not None else "n/a"
+                    self.logger.debug(f"[WiFi Monitor] - RTT={rtt_ms:.0f}ms, RSSI={_rssi_s}dBm")
+                    
+                    # 判断质量是否差（切换前做 2 次快速复测，防止瞬时抖动）
+                    def _is_bad_now(_reachable, _rtt, _rssi):
+                        if (not _reachable) or (_rtt is None) or (_rtt == float("inf")):
+                            return True
+                        return self._is_wifi_quality_bad(_rtt, _rssi)
+
+                    bad = _is_bad_now(reachable, rtt_ms, rssi_dbm)
+                    if bad:
+                        self.logger.warning("[WiFi Monitor] 质量差,切换前快速重试 2 次（每次间隔1秒）")
+
+                        for retry_idx in range(2):
+                            time.sleep_ms(1000)
+                            # 不使用 RTT 测量
+                            rtt2 = 0
+                            reachable2 = True
+                            # rtt2, reachable2 = self._measure_wifi_tcp_rtt_ms(
+                            #     self._server_ip, self._server_port,
+                            #     samples=1, per_sample_timeout_ms=600
+                            # )
+                            rssi2 = self._get_wifi_rssi_dbm()
+
+                            # 更新缓存，便于外部查看最新状态
+                            self._last_wifi_rtt_ms = rtt2 if reachable2 else None
+                            self._last_wifi_rssi_dbm = rssi2
+
+                            bad2 = _is_bad_now(reachable2, rtt2, rssi2)
+                            try:
+                                _rtt_disp = (
+                                    rtt2
+                                    if rtt2 is not None and rtt2 != float("inf")
+                                    else -1
+                                )
+                                self.logger.info(
+                                    f"[WiFi Monitor] 复测{retry_idx+1}/2: reachable={reachable2}, "
+                                    f"rtt={_rtt_disp:.0f}ms, rssi={rssi2}, bad={bad2}"
+                                )
+                            except Exception:
+                                pass
+
+                            if not bad2:
+                                self.logger.info("[WiFi Monitor] 复测恢复正常，继续保留 WiFi（不切换）")
+                                bad = False
+                                break
+
+                        if bad:
+                            self.logger.warning("[WiFi Monitor] 复测仍差/不通，尝试切换到 4G")
+                            self._on_poor_quality_callback()
+                
+                # 休眠 5 秒
+                time.sleep(5)
+                
+            except Exception as e:
+                self.logger.error(f"[WiFi Monitor] 监测异常：{e}")
+                # 异常后继续循环，避免线程退出
+                continue
+
+
+# 全局 WiFi 管理器实例
+wifi_manager = WiFiManager()
+
+
+# ==================== 兼容旧接口的函数 ====================
+
+def is_wifi_connected():
+    """尽量判断当前是否有 Wi-Fi（有则走 Wi-Fi OTA，否则走 4G OTA）"""
+    return wifi_manager.is_wifi_connected()
+
+
+def connect_wifi(ssid, password, verify_callback=None, persist=True, timeout_s=20):
+    """
+    连接 Wi-Fi 并将凭证持久化保存到 /boot/ 目录，
+    以便设备重启后自动连接。
+    
+    Args:
+        ssid: WiFi SSID
+        password: WiFi密码
+        verify_callback: 验证回调函数，接收 (ip) 参数，返回 (success: bool, error: str)
+        persist: 是否持久化保存
+        timeout_s: 超时时间（秒）
+    
+    Returns:
+        (ip, error): IP地址和错误信息（成功时error为None）
+    """
+    return wifi_manager.connect_wifi(ssid, password, verify_callback, persist, timeout_s)

wifi_config_httpd.py

@@ -0,0 +1,521 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+WiFi 热点配网：迷你 HTTP 服务器（仅 GET/POST，标准库 socket），独立线程运行。
+
+策略（与 /etc/init.d/S30wifi 一致）：
+- 仅当 STA 未连上 WiFi 且 4G 也不可用时，写入 /boot/wifi.ap、去掉 /boot/wifi.sta，
+  并重启 S30wifi 由系统起热点；再在本进程起 HTTP。
+- 用户 POST 提交路由器 SSID/密码后：仅写凭证、stop S30wifi、删 /boot/wifi.ap、建 /boot/wifi.sta、sync、reboot。
+"""
+import html
+import os
+import socket
+import threading
+import time as std_time
+from urllib.parse import parse_qs
+
+import config
+from logger_manager import logger_manager
+from wifi import wifi_manager
+
+
+_http_thread = None
+_http_stop = threading.Event()
+
+
+def _http_response(status, body_bytes, content_type="text/html; charset=utf-8"):
+    head = (
+        f"HTTP/1.1 {status}\r\n"
+        f"Content-Type: {content_type}\r\n"
+        f"Content-Length: {len(body_bytes)}\r\n"
+        f"Connection: close\r\n"
+        f"\r\n"
+    ).encode("utf-8")
+    return head + body_bytes
+
+
+def _read_http_request(conn, max_total=65536):
+    """返回 (method, path, headers_str, body_bytes) 或 None。"""
+    buf = b""
+    while b"\r\n\r\n" not in buf and len(buf) < max_total:
+        chunk = conn.recv(4096)
+        if not chunk:
+            break
+        buf += chunk
+    if b"\r\n\r\n" not in buf:
+        return None
+    idx = buf.index(b"\r\n\r\n")
+    header_bytes = buf[:idx]
+    rest = buf[idx + 4 :]
+    try:
+        headers_str = header_bytes.decode("utf-8", errors="replace")
+    except Exception:
+        headers_str = ""
+    lines = headers_str.split("\r\n")
+    if not lines:
+        return None
+    parts = lines[0].split()
+    method = parts[0] if parts else "GET"
+    path = parts[1] if len(parts) > 1 else "/"
+
+    content_length = 0
+    for line in lines[1:]:
+        if line.lower().startswith("content-length:"):
+            try:
+                content_length = int(line.split(":", 1)[1].strip())
+            except Exception:
+                content_length = 0
+            break
+
+    body = rest
+    while content_length > 0 and len(body) < content_length and len(body) < max_total:
+        chunk = conn.recv(4096)
+        if not chunk:
+            break
+        body += chunk
+    body = body[:content_length]
+    return method, path, headers_str, body
+
+
+def _page_form(msg_html=""):
+    # 页面展示的热点名：以 /boot/wifi.ssid 为准（与实际 AP 保持一致）
+    try:
+        if os.path.exists("/boot/wifi.ssid"):
+            with open("/boot/wifi.ssid", "r", encoding="utf-8") as f:
+                _ssid = f.read().strip()
+        else:
+            _ssid = ""
+    except Exception:
+        _ssid = ""
+    ap_ssid = html.escape(_ssid or getattr(config, "WIFI_CONFIG_AP_SSID", "ArcherySetup"))
+    port = int(getattr(config, "WIFI_CONFIG_HTTP_PORT", 8080))
+    ap_ip = html.escape(getattr(config, "WIFI_CONFIG_AP_IP", "192.168.66.1"))
+    body = f"""<!DOCTYPE html>
+<html><head><meta charset="utf-8"/><meta name="viewport" content="width=device-width,initial-scale=1"/>
+<title>WiFi 配网</title></head><body>
+<h1>WiFi 配网</h1>
+<p>热点：<b>{ap_ssid}</b> · 端口 <b>{port}</b></p>
+<p>请填写要连接的<b>路由器</b> SSID 与密码（用于 STA 上网，不是热点密码）。提交后将关闭热点、保存并<b>重启设备</b>。</p>
+{msg_html}
+<form method="POST" action="/" accept-charset="utf-8">
+<p>SSID<br/><input name="ssid" type="text" style="width:100%;max-width:320px" required/></p>
+<p>密码（开放网络可留空）<br/><input name="password" type="password" style="width:100%;max-width:320px"/></p>
+<p><button type="submit">保存并重启</button></p>
+</form>
+<p style="color:#666;font-size:12px">提示：提交后设备会重启；请手机改连路由器 WiFi。</p>
+</body></html>"""
+    return body.encode("utf-8")
+
+
+def _apply_sta_and_reboot(router_ssid: str, router_password: str):
+    """
+    写路由器 STA 凭证 -> 停 WiFi 服务 -> 删 /boot/wifi.ap -> 建 /boot/wifi.sta -> sync -> reboot
+    """
+    logger = logger_manager.logger
+    ok, err = wifi_manager.persist_sta_credentials(router_ssid, router_password, restart_service=False)
+    if not ok:
+        return False, err
+
+    try:
+        os.system("/etc/init.d/S30wifi stop")
+    except Exception as e:
+        logger.warning(f"[WIFI-AP] S30wifi stop: {e}")
+
+    ap_flag = "/boot/wifi.ap"
+    sta_flag = "/boot/wifi.sta"
+    try:
+        if os.path.exists(ap_flag):
+            os.remove(ap_flag)
+    except Exception as e:
+        return False, f"删除 {ap_flag} 失败: {e}"
+
+    try:
+        with open(sta_flag, "w", encoding="utf-8") as f:
+            f.write("")
+    except Exception as e:
+        return False, f"创建 {sta_flag} 失败: {e}"
+
+    try:
+        os.system("sync")
+    except Exception:
+        pass
+
+    logger.info("[WIFI-AP] 已切换为 STA 标志并准备 reboot")
+    try:
+        os.system("reboot")
+    except Exception as e:
+        return False, f"reboot 调用失败: {e}"
+    return True, ""
+
+
+def _handle_client(conn, addr):
+    logger = logger_manager.logger
+    try:
+        conn.settimeout(30.0)
+        req = _read_http_request(conn)
+        if not req:
+            conn.sendall(_http_response("400 Bad Request", b"Bad Request"))
+            return
+        method, path, _headers, body = req
+        path = path.split("?", 1)[0]
+
+        if method == "GET" and path in ("/", "/index.html"):
+            conn.sendall(_http_response("200 OK", _page_form()))
+            return
+
+        if method == "POST" and path in ("/", "/index.html"):
+            try:
+                qs = body.decode("utf-8", errors="replace")
+            except Exception:
+                qs = ""
+            fields = parse_qs(qs, keep_blank_values=True)
+            ssid = (fields.get("ssid") or [""])[0].strip()
+            password = (fields.get("password") or [""])[0]
+            ok, err = _apply_sta_and_reboot(ssid, password)
+            if ok:
+                msg = '<p style="color:green"><b>已保存，设备正在重启…</b></p>'
+            else:
+                msg = f'<p style="color:red"><b>失败：</b>{html.escape(err)}</p>'
+            conn.sendall(_http_response("200 OK", _page_form(msg)))
+            return
+
+        if method == "GET" and path == "/favicon.ico":
+            conn.sendall(_http_response("204 No Content", b""))
+            return
+
+        conn.sendall(_http_response("404 Not Found", b"Not Found"))
+    except Exception as e:
+        try:
+            logger.error(f"[WIFI-HTTP] 处理请求异常 {addr}: {e}")
+        except Exception:
+            pass
+    finally:
+        try:
+            conn.close()
+        except Exception:
+            pass
+
+
+def _serve_loop(host, port):
+    logger = logger_manager.logger
+    srv = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+    try:
+        srv.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
+        srv.bind((host, port))
+        srv.listen(5)
+        srv.settimeout(1.0)
+        logger.info(f"[WIFI-HTTP] 监听 {host}:{port}")
+    except Exception as e:
+        logger.error(f"[WIFI-HTTP] bind 失败: {e}")
+        try:
+            srv.close()
+        except Exception:
+            pass
+        return
+
+    while not _http_stop.is_set():
+        try:
+            conn, addr = srv.accept()
+        except socket.timeout:
+            continue
+        except Exception as e:
+            if _http_stop.is_set():
+                break
+            logger.warning(f"[WIFI-HTTP] accept: {e}")
+            continue
+        t = threading.Thread(target=_handle_client, args=(conn, addr), daemon=True)
+        t.start()
+
+    try:
+        srv.close()
+    except Exception:
+        pass
+    logger.info("[WIFI-HTTP] 服务已停止")
+
+
+def _ensure_hostapd_ssid(ssid: str, logger=None) -> bool:
+    """
+    某些固件会把 SSID 写到 /etc/hostapd.conf 或 /boot/hostapd.conf。
+    为避免只改 /boot/wifi.ssid 不生效，这里同步更新已存在的 hostapd.conf。
+    Returns:
+        bool: 任一文件被修改则 True
+    """
+    if logger is None:
+        logger = logger_manager.logger
+    if not ssid:
+        return False
+
+    changed_any = False
+    for conf_path in ("/etc/hostapd.conf", "/boot/hostapd.conf"):
+        try:
+            if not os.path.exists(conf_path):
+                continue
+            with open(conf_path, "r", encoding="utf-8") as f:
+                lines = f.read().splitlines()
+        except Exception:
+            continue
+
+        changed = False
+        out = []
+        seen = False
+        for ln in lines:
+            s = ln.strip()
+            if s.lower().startswith("ssid="):
+                seen = True
+                cur = s.split("=", 1)[1].strip()
+                if cur != ssid:
+                    out.append(f"ssid={ssid}")
+                    changed = True
+                else:
+                    out.append(ln)
+            else:
+                out.append(ln)
+        if not seen:
+            out.append(f"ssid={ssid}")
+            changed = True
+
+        if changed:
+            try:
+                with open(conf_path, "w", encoding="utf-8") as f:
+                    f.write("\n".join(out).rstrip() + "\n")
+                changed_any = True
+            except Exception as e:
+                if logger:
+                    logger.warning(f"[WIFI-AP] 写入 {conf_path} 失败: {e}")
+
+    if changed_any and logger:
+        logger.info(f"[WIFI-AP] 已同步热点 SSID 到 hostapd.conf: {ssid}")
+    return changed_any
+
+
+def _write_boot_ap_credentials_for_s30wifi():
+    """供 S30wifi AP 分支 gen_hostapd 使用的热点 SSID/密码。"""
+    base = (getattr(config, "WIFI_CONFIG_AP_SSID", "ArcherySetup") or "ArcherySetup").strip()
+    # 追加设备码，便于区分多台设备（读取 /device_key，失败则不加后缀）
+    suffix = ""
+    try:
+        with open("/device_key", "r", encoding="utf-8") as f:
+            dev = (f.read() or "").strip()
+        if dev:
+            s = dev
+            # 只保留字母数字，避免 SSID 出现不可见字符
+            s = "".join([c for c in s if c.isalnum()])
+            if s:
+                suffix = s
+    except Exception:
+        suffix = ""
+    ssid = f"{base}_{suffix}" if suffix else base
+    pwd = getattr(config, "WIFI_CONFIG_AP_PASSWORD", "12345678")
+    with open("/boot/wifi.ssid", "w", encoding="utf-8") as f:
+        f.write(ssid.strip())
+    with open("/boot/wifi.pass", "w", encoding="utf-8") as f:
+        f.write(pwd.strip())
+    try:
+        _ensure_hostapd_ssid(ssid.strip())
+    except Exception:
+        pass
+
+def _ensure_hostapd_modern_security(logger=None) -> bool:
+    """
+    确保 AP 使用较新的安全标准（至少 WPA2-PSK + CCMP）。
+    你现场验证需要的两行：
+      - wpa_key_mgmt=WPA-PSK
+      - rsn_pairwise=CCMP
+    Returns:
+        bool: 若文件被修改返回 True，否则 False
+    """
+    if logger is None:
+        logger = logger_manager.logger
+
+    conf_path = "/etc/hostapd.conf"
+    try:
+        if not os.path.exists(conf_path):
+            return False
+        with open(conf_path, "r", encoding="utf-8") as f:
+            lines = f.read().splitlines()
+    except Exception as e:
+        logger.warning(f"[WIFI-AP] 读取 hostapd.conf 失败: {e}")
+        return False
+
+    wanted = {
+        "wpa_key_mgmt": "WPA-PSK",
+        "rsn_pairwise": "CCMP",
+    }
+
+    changed = False
+    seen = set()
+    new_lines = []
+    for ln in lines:
+        s = ln.strip()
+        if not s or s.startswith("#") or "=" not in s:
+            new_lines.append(ln)
+            continue
+        k, v = s.split("=", 1)
+        k = k.strip()
+        if k in wanted:
+            seen.add(k)
+            new_v = wanted[k]
+            if v.strip() != new_v:
+                new_lines.append(f"{k}={new_v}")
+                changed = True
+            else:
+                new_lines.append(ln)
+            continue
+        new_lines.append(ln)
+
+    # 缺的补到末尾
+    for k, v in wanted.items():
+        if k not in seen:
+            new_lines.append(f"{k}={v}")
+            changed = True
+
+    if not changed:
+        return False
+
+    try:
+        with open(conf_path, "w", encoding="utf-8") as f:
+            f.write("\n".join(new_lines).rstrip() + "\n")
+        logger.info("[WIFI-AP] 已更新 /etc/hostapd.conf 安全参数（WPA-PSK + CCMP）")
+        return True
+    except Exception as e:
+        logger.warning(f"[WIFI-AP] 写入 hostapd.conf 失败: {e}")
+        return False
+
+
+def _cleanup_ap_flag_if_needed(logger):
+    """若 /boot/wifi.ap 残留，删除它并恢复 /boot/wifi.sta，避免 main.py 误判为 AP 配网模式。"""
+    ap_flag = "/boot/wifi.ap"
+    sta_flag = "/boot/wifi.sta"
+    if not os.path.exists(ap_flag):
+        return
+    try:
+        os.remove(ap_flag)
+        logger.info(f"[WIFI-AP] 已清理残留标记 {ap_flag}")
+    except Exception as e:
+        logger.warning(f"[WIFI-AP] 清理 {ap_flag} 失败: {e}")
+        return
+    if not os.path.exists(sta_flag):
+        try:
+            with open(sta_flag, "w", encoding="utf-8") as f:
+                f.write("")
+            logger.info(f"[WIFI-AP] 已恢复 {sta_flag}")
+        except Exception as e:
+            logger.warning(f"[WIFI-AP] 恢复 {sta_flag} 失败: {e}")
+
+
+def _switch_boot_to_ap_mode(logger):
+    """
+    去掉 STA 标志、建立 AP 标志，由 S30wifi 起 hostapd（与 Maix start_ap 二选一，以系统脚本为准）。
+    """
+    try:
+        sta = "/boot/wifi.sta"
+        ap = "/boot/wifi.ap"
+        if os.path.exists(sta):
+            os.remove(sta)
+        with open(ap, "w", encoding="utf-8") as f:
+            f.write("")
+        os.system("/etc/init.d/S30wifi restart")
+        # 某些固件生成的 hostapd.conf 缺少新安全参数，导致 Windows 提示“较旧的安全标准”。
+        # 若本次修改了 hostapd.conf，则再重启一次让 hostapd 重新加载配置。
+        try:
+            if _ensure_hostapd_modern_security(logger):
+                os.system("/etc/init.d/S30wifi restart")
+        except Exception:
+            pass
+        return True
+    except Exception as e:
+        logger.error(f"[WIFI-AP] 切换 /boot 为 AP 模式失败: {e}")
+        return False
+
+
+def start_http_server_thread():
+    """仅启动 HTTP 线程（假定 AP 已由 S30wifi 拉起）。"""
+    global _http_thread
+    logger = logger_manager.logger
+
+    if _http_thread is not None and _http_thread.is_alive():
+        logger.warning("[WIFI-HTTP] 配网线程已在运行")
+        return
+
+    _http_stop.clear()
+    host = getattr(config, "WIFI_CONFIG_HTTP_HOST", "0.0.0.0")
+    port = int(getattr(config, "WIFI_CONFIG_HTTP_PORT", 8080))
+
+    _http_thread = threading.Thread(
+        target=_serve_loop,
+        args=(host, port),
+        daemon=True,
+        name="wifi_config_httpd",
+    )
+    _http_thread.start()
+
+
+def maybe_start_wifi_ap_fallback(logger=None):
+    """
+    若启用 WIFI_CONFIG_AP_FALLBACK：等待若干秒后检测 STA WiFi 与 4G，
+    仅当二者均不可用时，写热点用的 /boot/wifi.ssid|pass、切到 /boot/wifi.ap 并 restart S30wifi，再启动 HTTP。
+    """
+    if logger is None:
+        logger = logger_manager.logger
+
+    if not getattr(config, "WIFI_CONFIG_AP_FALLBACK", False):
+        return
+
+    from network import network_manager
+
+    # 先快速检测一次：若 STA 或 4G 已可用，直接返回，避免不必要的等待
+    wifi_ok = wifi_manager.is_sta_associated()
+    g4_ok = network_manager.is_4g_available()
+    logger.info(f"[WIFI-AP] 兜底检测(quick)：sta关联={wifi_ok}, 4g={g4_ok}")
+    if wifi_ok or g4_ok:
+        logger.info("[WIFI-AP] STA 或 4G 可用，不启动热点配网")
+        # 清理上次开机可能残留的 /boot/wifi.ap 标记，避免 main.py 误判为 AP 配网模式
+        _cleanup_ap_flag_if_needed(logger)
+        return
+
+    # 两者均不可用：再按配置等待一段时间后复检，避免开机瞬态误判
+    wait_sec = int(getattr(config, "WIFI_AP_FALLBACK_WAIT_SEC", 10))
+    wait_sec = max(0, min(wait_sec, 120))
+    if wait_sec > 0:
+        logger.info(f"[WIFI-AP] 兜底配网：等待 {wait_sec}s 后再检测 STA/4G…")
+        std_time.sleep(wait_sec)
+
+    # 必须用 STA 关联判断；is_wifi_connected() 在 AP 模式会因 192.168.66.1 误判为已连接
+    wifi_ok = wifi_manager.is_sta_associated()
+    g4_ok = network_manager.is_4g_available()
+
+    logger.info(f"[WIFI-AP] 兜底检测：sta关联={wifi_ok}, 4g={g4_ok}")
+
+    if wifi_ok or g4_ok:
+        logger.info("[WIFI-AP] STA 或 4G 可用，不启动热点配网")
+        _cleanup_ap_flag_if_needed(logger)
+        return
+
+    logger.warning("[WIFI-AP] STA 与 4G 均不可用，启动热点配网（/boot/wifi.ap + HTTP）")
+
+    try:
+        _write_boot_ap_credentials_for_s30wifi()
+    except Exception as e:
+        logger.error(f"[WIFI-AP] 写热点 /boot 凭证失败: {e}")
+        return
+
+    if not _switch_boot_to_ap_mode(logger):
+        return
+
+    std_time.sleep(3)
+    start_http_server_thread()
+
+    p = int(getattr(config, "WIFI_CONFIG_HTTP_PORT", 8080))
+    ip = getattr(config, "WIFI_CONFIG_AP_IP", "192.168.66.1")
+    logger.info(f"[WIFI-AP] 请连接热点后访问 http://{ip}:{p}/ （若 IP 以 S30wifi 为准）")
+
+
+def stop_wifi_config_http():
+    """请求停止 HTTP 线程（下次 accept 超时后退出）。"""
+    _http_stop.set()
+
+
+# 兼容旧名：不再使用「强制开 AP」逻辑，统一走 maybe_start_wifi_ap_fallback
+def start_wifi_config_ap_thread():
+    maybe_start_wifi_ap_fallback()

wpa_supplicant_conf.py

@@ -0,0 +1,53 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+生成 wpa_supplicant STA 配置（不经过 shell / wpa_passphrase），避免中文 SSID 在 /bin/sh 传参时被破坏。
+
+与 wpa_passphrase 一致：PMK = PBKDF2-SHA1(password_utf8, ssid_utf8, 4096, 32)，
+ssid 行使用 UTF-8 字节的十六进制（无引号），与 wpa_supplicant 文档一致。
+"""
+from __future__ import annotations
+
+import hashlib
+
+_CTRL_HEADER = (
+    "ctrl_interface=/var/run/wpa_supplicant\n"
+    "update_config=1\n\n"
+)
+
+
+def _ssid_utf8_bytes(ssid: str) -> bytes:
+    b = (ssid or "").encode("utf-8")
+    if not b:
+        raise ValueError("SSID 为空")
+    if len(b) > 32:
+        raise ValueError("SSID UTF-8 超过 32 字节")
+    return b
+
+
+def build_sta_conf_psk(ssid: str, password: str) -> str:
+    """WPA2-PSK STA：完整 wpa_supplicant.conf 文本。"""
+    ssid_b = _ssid_utf8_bytes(ssid)
+    pw = (password or "").encode("utf-8")
+    if len(pw) < 8 or len(pw) > 63:
+        raise ValueError("WPA2-PSK 密码长度应为 8–63 字节（UTF-8）")
+    pmk = hashlib.pbkdf2_hmac("sha1", pw, ssid_b, 4096, 32)
+    net = (
+        "network={\n"
+        f"\tssid={ssid_b.hex()}\n"
+        f"\tpsk={pmk.hex()}\n"
+        "}\n"
+    )
+    return _CTRL_HEADER + net
+
+
+def build_sta_conf_open(ssid: str) -> str:
+    """开放网络 STA：完整 wpa_supplicant.conf 文本。"""
+    ssid_b = _ssid_utf8_bytes(ssid)
+    net = (
+        "network={\n"
+        f"\tssid={ssid_b.hex()}\n"
+        "\tkey_mgmt=NONE\n"
+        "}\n"
+    )
+    return _CTRL_HEADER + net