feat: 2.17.18

.gitattributes

@@ -1 +0,0 @@
-*.sh text eol=lf

.gitignore

@@ -1,4 +1,3 @@
 /cpp_ext/build/
 /.cursor/
 /dist/
-.idea

.idea/.gitignore

@@ -1,8 +0,0 @@
-# 默认忽略的文件
-/shelf/
-/workspace.xml
-# 基于编辑器的 HTTP 客户端请求
-/httpRequests/
-# Datasource local storage ignored files
-/dataSources/
-/dataSources.local.xml

.idea/archery.iml

@@ -1,12 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<module type="PYTHON_MODULE" version="4">
-  <component name="NewModuleRootManager">
-    <content url="file://$MODULE_DIR$" />
-    <orderEntry type="jdk" jdkName="yolov8" jdkType="Python SDK" />
-    <orderEntry type="sourceFolder" forTests="false" />
-  </component>
-  <component name="PyDocumentationSettings">
-    <option name="format" value="PLAIN" />
-    <option name="myDocStringFormat" value="Plain" />
-  </component>
-</module>

.idea/inspectionProfiles/profiles_settings.xml

@@ -1,6 +0,0 @@
-<component name="InspectionProjectProfileManager">
-  <settings>
-    <option name="USE_PROJECT_PROFILE" value="false" />
-    <version value="1.0" />
-  </settings>
-</component>

.idea/misc.xml

@@ -1,7 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="Black">
-    <option name="sdkName" value="yolov8" />
-  </component>
-  <component name="ProjectRootManager" version="2" project-jdk-name="yolov8" project-jdk-type="Python SDK" />
-</project>

.idea/modules.xml

@@ -1,8 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectModuleManager">
-    <modules>
-      <module fileurl="file://$PROJECT_DIR$/.idea/archery.iml" filepath="$PROJECT_DIR$/.idea/archery.iml" />
-    </modules>
-  </component>
-</project>

.idea/vcs.xml

@@ -1,6 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="VcsDirectoryMappings">
-    <mapping directory="" vcs="Git" />
-  </component>
-</project>

.vscode/settings.json

@@ -1,3 +1,3 @@
 {
-    "cmake.sourceDirectory": "E:/code/code/code/new/new/new/archery/cpp_ext"
+    "cmake.sourceDirectory": "E:/code/code/code/new/new/new/new/new/nw/2.17.0/archery/cpp_ext"
 }

app.yaml

@@ -1,6 +1,6 @@
 id: t11
 name: t11
-version: 2.15.31
+version: 2.17.18
 author: t11
 icon: ''
 desc: t11
@@ -12,13 +12,14 @@ files:
   - at_client.py
   - camera_manager.py
   - cameraParameters.xml
-  - charging_exit.sh
   - config.py
   - hardware.py
   - laser_detector.py
   - laser_manager.py
   - logger_manager.py
   - main.py
+  - model_317828.cvimodel
+  - model_317828.mud
   - network.py
   - ota_curl.sh
   - ota_manager.py

charging_exit.sh

@@ -1,47 +0,0 @@
-#!/bin/sh
-
-# The application supplies its own PID. Refuse broad or malformed targets.
-TARGET_PID="$1"
-LASER_DEVICE="${2:-/dev/ttyS1}"
-LASER_BAUD="${3:-9600}"
-
-turn_off_laser() {
-    if [ ! -c "$LASER_DEVICE" ]; then
-        echo "[CHARGE] laser serial device not found: $LASER_DEVICE" >&2
-        return 1
-    fi
-
-    stty -F "$LASER_DEVICE" "$LASER_BAUD" raw -echo 2>/dev/null || return 1
-    printf '\252\000\001\276\000\001\000\000\300' > "$LASER_DEVICE"
-}
-
-case "$TARGET_PID" in
-    ''|*[!0-9]*)
-        echo "[CHARGE] invalid application pid: $TARGET_PID" >&2
-        exit 2
-        ;;
-esac
-
-if [ "$TARGET_PID" -le 1 ]; then
-    echo "[CHARGE] refusing to terminate pid: $TARGET_PID" >&2
-    exit 2
-fi
-
-# First request laser-off while the application still owns the initialized UART.
-turn_off_laser || true
-
-kill -TERM "$TARGET_PID" 2>/dev/null || true
-
-# Wait up to two seconds for a graceful exit, then force termination.
-WAIT_COUNT=0
-while kill -0 "$TARGET_PID" 2>/dev/null && [ "$WAIT_COUNT" -lt 20 ]; do
-    sleep 0.1
-    WAIT_COUNT=$((WAIT_COUNT + 1))
-done
-if kill -0 "$TARGET_PID" 2>/dev/null; then
-    kill -KILL "$TARGET_PID" 2>/dev/null || true
-    sleep 0.1
-fi
-
-# Send laser-off again after the application releases the UART.
-turn_off_laser || true

config.py

@@ -234,10 +234,10 @@ TRIANGLE_BLACKHAT_KERNEL_FRAC = 0.018  # 核大小 ≈ min(h,w)*frac，取奇数
 # ── 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"
+TRIANGLE_YOLO_MODEL_PATH = APP_DIR + "/model_317211.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_CONF_TH = 0.9
 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。
@@ -262,6 +262,16 @@ TRIANGLE_SAMPLE_PATCH_HALF_PX = 2
 # 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 = False
 
+# YOLO target size classification: class 0=20cm, class 1=40cm.
+TARGET_CLASS_YOLO_ENABLE = True
+TARGET_CLASS_YOLO_MODEL_PATH = APP_DIR + "/model_317828.mud"
+TARGET_CLASS_YOLO_LABELS = (20, 40)
+TARGET_CLASS_YOLO_CONF_TH = 0.66
+TARGET_CLASS_YOLO_IOU_TH = 0.45
+TARGET_CLASS_YOLO_RETRY_ON_EMPTY = False
+TARGET_CLASS_YOLO_RETRY_CONF_TH = 0.25
+TARGET_CLASS_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）。
@@ -316,9 +326,13 @@ LOG_QUEUE_MAXSIZE = 10000       # 日志队列上限
 MAX_CMD_THREADS = 10            # 并发命令线程上限（防止服务器下发命令时无限创建线程）
 
 # ==================== 图像保存配置 ====================
-SAVE_IMAGE_ENABLED = False  # 是否保存图像（True=保存，False=不保存）
+SAVE_IMAGE_ENABLED = True  # 是否保存图像（True=保存，False=不保存）
+SAVE_IMAGE_ON_FAILURE = True  # 检测失败时是否强制保存图像（供调试测试用）
 PHOTO_DIR = "/root/phot"    # 照片存储目录
 MAX_IMAGES = 1000
+SAVE_RAW_IMAGE_ENABLED = False  # 额外保存完整原始帧（不画框、不画点、不裁剪）
+RAW_IMAGE_DIR = PHOTO_DIR + "/raw"
+RAW_IMAGE_MAX_IMAGES = MAX_IMAGES
 # 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
 
@@ -343,15 +357,6 @@ PIN_MAPPINGS = {
 # ==================== 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
 
-# 实机数据：正常放电约为正电流，插入充电线后约为负电流。
-CHARGING_SHUTDOWN_ENABLED = True  # True=充电时退出应用，False=关闭充电关机功能
-CHARGING_DIAGNOSTIC_LOG_ENABLED = False
-CHARGING_CHECK_INTERVAL_MS = 5000
-CHARGING_CURRENT_THRESHOLD_MA = 100.0
-CHARGING_CONFIRM_COUNT = 2
-CHARGING_NOTIFY_TIMEOUT_MS = 30000
-CHARGING_EXIT_SCRIPT = APP_DIR + "/charging_exit.sh"
-
 BATTERY_SOC_LPF_ALPHA = 0.5
 BATTERY_SOC_AVG_WINDOW = 5
 

main.py

@@ -22,7 +22,7 @@ from version import VERSION
 # from logger import init_logging, get_logger, stop_logging
 from logger_manager import logger_manager
 from time_sync import sync_system_time_from_4g
-from power import charging_shutdown_monitor, init_ina226
+from power import init_ina226
 from laser_manager import laser_manager
 from vision import start_save_shot_worker
 from network import network_manager
@@ -120,18 +120,11 @@ def cmd_str():
 
     # ==================== 第二阶段：软件初始化 ====================
 
-    # 1. 初始化日志系统
+    # 1. 初始化日志系统（WARNING级别，不打印/写入INFO和DEBUG日志，提高执行流畅度）
     import logging
     logger_manager.init_logging(log_level=logging.WARNING)
     logger = logger_manager.logger
 
-    # 充电关机独立读取 INA226，不依赖 TCP 连接或心跳流程。
-    try:
-        _thread.start_new_thread(charging_shutdown_monitor, ())
-    except Exception as e:
-        if logger:
-            logger.error(f"[CHARGE] 启动独立监测线程失败: {e}")
-
     # 补充：因为初始化的时候，激光会亮，先关了它
     # laser_manager.turn_off_laser()
 
@@ -139,6 +132,7 @@ def cmd_str():
     sync_system_time_from_4g()
 
     # 2.1 WiFi 热点配网兜底：仅当 STA 与 4G 均不可用时起 AP + HTTP；提交后删 /boot/wifi.ap、建 wifi.sta 并 reboot
+    _ota_pending_path = f"{config.APP_DIR}/ota_pending.json"
     try:
         from wifi_config_httpd import maybe_start_wifi_ap_fallback
 
@@ -169,15 +163,21 @@ def cmd_str():
             and _loc_black == "yolo"
             and bool(getattr(config, "TRIANGLE_BLACK_YOLO_PRELOAD_ON_BOOT", True))
         )
-        _preload_yolo = _preload_yolo or _need_black_preload
-        if _preload_yolo:
+        _need_target_preload = (
+            bool(getattr(config, "TARGET_CLASS_YOLO_ENABLE", False))
+            and bool(getattr(config, "TARGET_CLASS_YOLO_PRELOAD_ON_BOOT", True))
+        )
+        _preload_yolo = _preload_yolo or _need_black_preload or _need_target_preload
+        if _preload_yolo and not os.path.exists(_ota_pending_path):
             preload_yolo_detector(logger)
+        elif _preload_yolo and logger:
+            logger.warning("[YOLO] ota_pending.json found; skip model preload until rollback check")
     except Exception as e:
         if logger:
             logger.warning(f"[YOLO-ROI] 启动预加载异常（不影响后续射箭）: {e}")
 
     # 3. 启动时检查：是否需要恢复备份
-    pending_path = f"{config.APP_DIR}/ota_pending.json"
+    pending_path = _ota_pending_path
     if os.path.exists(pending_path):
         try:
             with open(pending_path, 'r', encoding='utf-8') as f:
@@ -252,8 +252,12 @@ def cmd_str():
     # 4. 初始化设备ID（network_manager 内部会自动设置 device_id 和 password）
     network_manager.read_device_id()
 
-    # 5. 创建照片存储目录（如果启用图像保存）
-    if config.SAVE_IMAGE_ENABLED:
+    # 5. 创建照片存储目录（如果启用图像保存或检测失败时强制保存）
+    if (
+        config.SAVE_IMAGE_ENABLED
+        or getattr(config, "SAVE_IMAGE_ON_FAILURE", False)
+        or getattr(config, "SAVE_RAW_IMAGE_ENABLED", False)
+    ):
         photo_dir = config.PHOTO_DIR
         if photo_dir not in os.listdir("/root"):
             try:
@@ -285,6 +289,13 @@ def cmd_str():
         logger.info("系统准备完成...")
 
     last_adc_trigger = 0
+    trigger_adc_val = 0  # 触发时的气压值，气压需降回此值以下才能再次触发
+    # 读取一次ADC初始值，防止开机时传感器已有压力导致误触发
+    enable_check = True
+    try:
+        last_adc_val = hardware_manager.adc_obj.read()
+    except Exception:
+        last_adc_val = 0
     # 气压采样：减少日志频率（每 N 个点输出一条），避免 logger.debug 拖慢采样
     PRESSURE_BATCH_SIZE = 100
 
@@ -336,7 +347,6 @@ def cmd_str():
                 time.sleep_ms(250)
                 continue
 
-            # todo 去除或者不在这里检测
             # 不在 OTA 状态下，检测是否空闲足够长，自动关机
             # print(f"[MAIN] 空闲时间: {hardware_manager.get_idle_time_in_sec() }秒")
             # print(f"配置关机时间：{config.AUTO_POWER_OFF_IN_SECONDS} 秒")
@@ -375,16 +385,16 @@ def cmd_str():
                 pressure_max = adc_val
             if len(pressure_buf) >= PRESSURE_BATCH_SIZE:
                 _flush_pressure_buf("batch")
-            # if adc_val >= 2000:
-            # print(f"adc :{adc_val}")
-            if adc_val >= config.ADC_TRIGGER_THRESHOLD:
+            # 突变增量检测：压力增量大于400时触发
+            # 触发后需等气压降到触发值以下才重新检测增量
+            if adc_val < trigger_adc_val :
+                enable_check = True
+            if (adc_val - last_adc_val) > 200 and enable_check:
                 hardware_manager.start_idle_timer()  # 重新计时
-                diff_ms = current_time - last_adc_trigger
-                if diff_ms < 3000:
-                    logger.info(f"[MAIN] 扳机触发过于频繁, {diff_ms}ms")
-                    continue
                 last_adc_trigger = current_time
-                # 触发前先把缓存刷出来，避免波形被长耗时处理截断
+                trigger_adc_val = adc_val  # 记录触发时的气压值
+                last_adc_val = adc_val  # 更新基准值，防止连续增量误触发
+                enable_check = False
                 _flush_pressure_buf("before_trigger")
 
                 try:
@@ -402,10 +412,9 @@ def cmd_str():
                     try:
                         camera_manager.show(camera_manager.read_frame())
                     except Exception as e:
-                        logger = logger_manager.logger
-                        if logger:
-                            logger.error(f"[MAIN] 显示异常: {e}")
-                time.sleep_ms(5)
+                        pass
+                time.sleep_ms(1)
+            last_adc_val = adc_val
 
         except Exception as e:
             # 主循环的顶层异常捕获，防止程序静默退出

model_317189.mud

@@ -1,7 +1,7 @@
 
 [basic]
 type = cvimodel
-model = model_270139.cvimodel
+model = model_317189.cvimodel
 
 [extra]
 model_type = yolov5
@@ -9,5 +9,5 @@ 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
+labels = circle, triangle
 

model_317211.mud

@@ -0,0 +1,13 @@
+
+[basic]
+type = cvimodel
+model = model_317211.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 = circle, triangle
+

model_317423.mud

@@ -0,0 +1,13 @@
+
+[basic]
+type = cvimodel
+model = model_317423.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 = 20, 10, 40
+

model_317704.mud

@@ -0,0 +1,13 @@
+
+[basic]
+type = cvimodel
+model = model_317704.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 = 40, circle, triangle
+

model_317828.mud

@@ -1,7 +1,7 @@
 
 [basic]
 type = cvimodel
-model = model_270820.cvimodel
+model = model_317828.cvimodel
 
 [extra]
 model_type = yolov5
@@ -9,5 +9,5 @@ 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
+labels = 20, 40
 

network.py

@@ -18,7 +18,7 @@ import socket
 import config
 
 from hardware import hardware_manager
-from power import get_bus_voltage, voltage_to_percent
+from power import get_bus_voltage, voltage_to_percent, is_charging
 from logger_manager import logger_manager
 from wifi import wifi_manager
 import subprocess
@@ -669,6 +669,8 @@ class NetworkManager:
         self.logger.info(f"[conn wifi] cmd600 , data: {inner_data}")
         ssid = inner_data.get("ssid")
         password = inner_data.get("password")
+        # 停止旧的WiFi质量监测（无论当前是WiFi还是4G连接）
+        self._stop_wifi_quality_monitor()
         try:
             for _f in ("/etc/wpa_supplicant.conf", "/boot/wpa_supplicant.conf", "/boot/wifi.ssid", "/boot/wifi.pass"):
                 try:
@@ -709,12 +711,6 @@ class NetworkManager:
         """线程安全地将消息加入队列（公共方法）"""
         self._enqueue((msg_type, data_dict), high)
 
-    def safe_enqueue_and_wait(self, data_dict, msg_type=2, high=False, timeout_ms=30000):
-        """将消息加入队列，并等待网络线程确认已写入 TCP 连接。"""
-        sent_event = threading.Event()
-        self._enqueue((msg_type, data_dict, sent_event), high)
-        return bool(sent_event.wait(max(0, int(timeout_ms)) / 1000.0))
-
     def connect_server(self):
         """
         连接到服务器（自动选择WiFi或4G）
@@ -901,12 +897,6 @@ class NetworkManager:
         """检查WiFi TCP连接是否仍然有效"""
         if not wifi_manager.wifi_socket:
             return False
-        # TLS socket 无法可靠使用 MSG_PEEK，但物理 WiFi 链路仍可通过 STA 关联状态判断。
-        if not wifi_manager.is_sta_associated():
-            self.logger.warning("[WIFI-TCP] STA 已断开，关闭 WiFi TCP 并重新选网")
-            wifi_manager.disconnect_wifi()
-            self._tcp_connected = False
-            return False
         # TLS(ssl.wrap_socket/SSLContext.wrap_socket) 后的 socket 往往不支持 MSG_PEEK/MSG_DONTWAIT。
         # 这种情况下“主动探测”反而容易误报断线；让真正的 send/recv 去判定更稳。
         try:
@@ -1222,14 +1212,6 @@ class NetworkManager:
             # 这里保持 socket 为非阻塞模式（连接时已 setblocking(False)）。
             # 不要反复 settimeout()，否则会把 socket 切回"阻塞+超时"，并导致 conncheck 误报 timed out。
             data = wifi_manager.wifi_socket.recv(4096)  # 每次最多接收4KB（无数据会抛 BlockingIOError）
-            if data == b"":
-                self.logger.warning("[WIFI-TCP] 对端已关闭连接")
-                try:
-                    wifi_manager.wifi_socket.close()
-                except Exception:
-                    pass
-                wifi_manager.wifi_socket = None
-                self._tcp_connected = False
             return data
 
         except BlockingIOError:
@@ -1830,9 +1812,16 @@ class NetworkManager:
         self.logger.info("[NET] TCP主线程启动")
 
         send_hartbeat_fail_count = 0
+        last_charging_check = 0
+        CHARGING_CHECK_INTERVAL = 5000  # 5秒检查一次充电状态
 
         while True:
             try:
+                # 检查充电状态（每5秒检查一次）
+                current_time = time.ticks_ms()
+                if current_time - last_charging_check > CHARGING_CHECK_INTERVAL:
+                    last_charging_check = current_time
+
                 # OTA 期间不要 connect/登录/心跳/发送
                 try:
                     from ota_manager import ota_manager
@@ -2156,7 +2145,17 @@ class NetworkManager:
                                             "netType": self.network_type,
                                         }
                                         self.safe_enqueue(battery_data, 2)
-                                        self.logger.info(f"电量上报: {battery_percent}%")
+                                        self.logger.info(f"电量上报: {battery_percent}% 充电: {is_charging()}")
+                                        if is_charging():
+                                            self.safe_enqueue(
+                                                {
+                                                    "cmd": 700,
+                                                },
+                                                2,
+                                            )
+                                    elif inner_cmd == 700:
+                                        self.logger.warning("服务器下发关机！！！")
+                                        exit(-1)
                                     elif inner_cmd == 5:  # OTA 升级
                                         inner_data = data_obj.get("data", {}) if isinstance(data_obj, dict) else {}
                                         ssid = inner_data.get("ssid")
@@ -2310,8 +2309,7 @@ class NetworkManager:
                                 item_is_high = False
 
                         if item:
-                            msg_type, data_dict = item[:2]
-                            sent_event = item[2] if len(item) > 2 else None
+                            msg_type, data_dict = item
                             pkt = self._netcore.make_packet(msg_type, data_dict)
                             if not self.tcp_send_raw(pkt):
                                 # 发送失败：将消息放回队首（队列满则丢弃）
@@ -2328,8 +2326,6 @@ class NetworkManager:
                                 except:
                                     pass
                                 break
-                            if sent_event is not None:
-                                sent_event.set()
 
                     # 发送激光校准结果
                     if logged_in:

power.py

@@ -10,7 +10,6 @@ import subprocess
 from logger_manager import logger_manager
 from maix import time as maix_time
 
-
 _INA226_PRESENT = None
 
 
@@ -142,115 +141,6 @@ def is_charging(threshold_ma=10.0):
         return False
 
 
-def charging_shutdown_monitor():
-    """独立监测 INA226；连续确认充电后通知服务器并退出应用。"""
-    logger = logger_manager.logger
-    shutdown_enabled = bool(getattr(config, "CHARGING_SHUTDOWN_ENABLED", False))
-    diagnostic_enabled = bool(getattr(config, "CHARGING_DIAGNOSTIC_LOG_ENABLED", False))
-    if not shutdown_enabled and not diagnostic_enabled:
-        if logger:
-            logger.info("[CHARGE] 充电退出监测已禁用")
-        return
-
-    interval_ms = max(100, int(getattr(config, "CHARGING_CHECK_INTERVAL_MS", 5000)))
-    threshold_ma = float(getattr(config, "CHARGING_CURRENT_THRESHOLD_MA", 10.0))
-    confirm_required = max(1, int(getattr(config, "CHARGING_CONFIRM_COUNT", 2)))
-    confirm_count = 0
-
-    if logger:
-        logger.info(
-            f"[CHARGE] 独立监测线程启动: interval={interval_ms}ms, "
-            f"threshold={threshold_ma:.1f}mA, confirm={confirm_required}, "
-            f"shutdown={'on' if shutdown_enabled else 'off'}"
-        )
-
-    while True:
-        current_ma = get_current()
-        if diagnostic_enabled and logger:
-            voltage = get_bus_voltage()
-            logger.info(
-                f"[CHARGE-DIAG] INA226 voltage={voltage:.3f}V, "
-                f"current={current_ma:.1f}mA"
-            )
-
-        if not shutdown_enabled:
-            maix_time.sleep_ms(interval_ms)
-            continue
-
-        if current_ma < -abs(threshold_ma):
-            confirm_count += 1
-            if logger:
-                logger.info(
-                    f"[CHARGE] INA226 充电电流 {current_ma:.1f}mA "
-                    f"({confirm_count}/{confirm_required})"
-                )
-        else:
-            confirm_count = 0
-
-        if confirm_count >= confirm_required:
-            script_path = getattr(
-                config,
-                "CHARGING_EXIT_SCRIPT",
-                config.APP_DIR + "/charging_exit.sh",
-            )
-            if not os.path.isfile(script_path):
-                if logger:
-                    logger.error(f"[CHARGE] 退出脚本不存在: {script_path}")
-                confirm_count = 0
-            else:
-                if logger:
-                    logger.warning(
-                        f"[CHARGE] 已连续确认充电，通知服务器后退出应用: current={current_ma:.1f}mA"
-                    )
-                try:
-                    from network import network_manager
-
-                    notify_timeout_ms = max(
-                        0,
-                        int(getattr(config, "CHARGING_NOTIFY_TIMEOUT_MS", 30000)),
-                    )
-                    notification_sent = network_manager.safe_enqueue_and_wait(
-                        {"poweroff": "充电中"},
-                        2,
-                        high=True,
-                        timeout_ms=notify_timeout_ms,
-                    )
-                    if notification_sent:
-                        if logger:
-                            logger.info("[CHARGE] 充电状态已发送到服务器")
-                    elif logger:
-                        logger.warning(
-                            f"[CHARGE] 等待服务器发送超时({notify_timeout_ms}ms)，继续执行退出"
-                        )
-                except Exception as e:
-                    if logger:
-                        logger.error(f"[CHARGE] 充电状态上报失败，继续执行退出: {e}")
-                try:
-                    from laser_manager import laser_manager
-
-                    laser_manager.turn_off_laser()
-                    if logger:
-                        logger.info("[CHARGE] 激光关闭命令已发送")
-                except Exception as e:
-                    if logger:
-                        logger.error(f"[CHARGE] Python 关闭激光失败，交由退出脚本兜底: {e}")
-                try:
-                    subprocess.Popen([
-                        "/bin/sh",
-                        script_path,
-                        str(os.getpid()),
-                        str(getattr(config, "DISTANCE_SERIAL_DEVICE", "/dev/ttyS1")),
-                        str(getattr(config, "DISTANCE_SERIAL_BAUDRATE", 9600)),
-                    ])
-                    return
-                except Exception as e:
-                    if logger:
-                        logger.error(f"[CHARGE] 调用退出脚本失败: {e}")
-                    confirm_count = 0
-
-        maix_time.sleep_ms(interval_ms)
-
-
 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）。

shoot_manager.py

@@ -8,7 +8,12 @@ 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 vision import (
+    estimate_distance,
+    detect_circle_v3,
+    enqueue_save_shot,
+    enqueue_save_raw_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
@@ -54,6 +59,7 @@ def analyze_shot(frame, laser_point=None):
     """
     logger = logger_manager.logger
     from datetime import datetime
+    yellow_algorithm_ms = 0.0
 
     # ── Step 1: 确定激光点 ────────────────────────────────────────────────────
     laser_point_method = None
@@ -69,7 +75,11 @@ def analyze_shot(frame, laser_point=None):
             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
+        _t_yellow = time_std.perf_counter()
+        try:
             _, _, _, _, best_radius1_temp, _ = detect_circle_v3(frame, None)
+        finally:
+            yellow_algorithm_ms += (time_std.perf_counter() - _t_yellow) * 1000.0
         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)
@@ -114,6 +124,7 @@ def analyze_shot(frame, laser_point=None):
             "laser_point": laser_point, "laser_point_method": laser_point_method,
             "offset_method": "yellow_ellipse" if ellipse_params else "yellow_circle",
             "distance_method": "yellow_radius",
+            "yellow_algorithm_ms": float(yellow_algorithm_ms),
         }
         if yolo_roi_xyxy is not None:
             out["yolo_roi_xyxy"] = yolo_roi_xyxy
@@ -121,9 +132,12 @@ def analyze_shot(frame, laser_point=None):
 
     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)
-        )
+        _t_yellow = time_std.perf_counter()
+        try:
+            cdata = detect_circle_v3(frame, laser_point, img_cv=img_cv)
+        finally:
+            yellow_algorithm_ms += (time_std.perf_counter() - _t_yellow) * 1000.0
+        return _build_circle_result(cdata)
 
     # ── 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
@@ -276,6 +290,7 @@ def analyze_shot(frame, laser_point=None):
             "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",
+            "yellow_algorithm_ms": float(yellow_algorithm_ms),
             "tri_markers": tri.get("markers", []),
             "tri_markers_completed": tri.get("markers_completed", []),
             "tri_homography": tri.get("homography"),
@@ -295,8 +310,12 @@ def analyze_shot(frame, laser_point=None):
         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:
+        _t_yellow = time_std.perf_counter()
         try:
             cdata = detect_circle_v3(frame, laser_point, img_cv=img_cv)
+        finally:
+            yellow_algorithm_ms += (time_std.perf_counter() - _t_yellow) * 1000.0
     except Exception as e:
         logger.error(f"[CIRCLE] 圆形检测异常: {e}")
         cdata = (frame, None, None, None, None, None)
@@ -321,8 +340,32 @@ def process_shot(adc_val):
 
     try:
         frame = camera_manager.read_frame()
+
+        # Copy the untouched frame before any detection or drawing.
+        from shot_id_generator import shot_id_generator
+        shot_id = shot_id_generator.generate_id()
+        enqueue_save_raw_shot(frame, shot_id)
+
+        # 网络事件移到拍照之后，避免阻塞拍照
         network_manager.safe_enqueue({"shoot_event": "start"}, msg_type=2, high=True)
 
+        # Classify only the current shot frame; never reuse a previous result.
+        target_class_result = None
+        yolo_target_ms = 0.0
+        try:
+            from target_roi_yolo import try_get_target_class_from_yolo
+
+            _t_yolo_target = time_std.perf_counter()
+            try:
+                target_class_result = try_get_target_class_from_yolo(frame, logger=logger)
+            finally:
+                yolo_target_ms = (time_std.perf_counter() - _t_yolo_target) * 1000.0
+            if logger:
+                logger.info(f"[YOLO-TARGET] 当前箭业务结果: {target_class_result}")
+        except Exception as exc:
+            if logger:
+                logger.warning(f"[YOLO-TARGET] 当前箭分类失败，按未知处理: {exc}")
+
         # 调用算法分析
         analysis_result = analyze_shot(frame)
 
@@ -346,6 +389,7 @@ def process_shot(adc_val):
         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")
+        yellow_algorithm_ms = float(analysis_result.get("yellow_algorithm_ms", 0.0) or 0.0)
         tri_markers = analysis_result.get("tri_markers", [])
         tri_markers_completed = analysis_result.get("tri_markers_completed", [])
         tri_homography = analysis_result.get("tri_homography")
@@ -366,10 +410,6 @@ def process_shot(adc_val):
         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}")
 
@@ -382,11 +422,27 @@ def process_shot(adc_val):
         srv_y = round(float(dy), 4) if dy is not None else 200.0
 
         # 构造上报数据
+        target_label = (
+            target_class_result.get("label")
+            if isinstance(target_class_result, dict)
+            else None
+        )
+        target_confidence = (
+            target_class_result.get("confidence")
+            if isinstance(target_class_result, dict)
+            else None
+        )
         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）
+            "target_class": target_label,
+            "target_class_confidence": (
+                round(float(target_confidence), 2)
+                if target_confidence is not None
+                else None
+            ),
             "d": round((distance_m or 0.0) * 100),
             "d_laser": round((laser_distance_m or 0.0) * 100),
             "d_laser_quality": laser_signal_quality,
@@ -397,6 +453,8 @@ def process_shot(adc_val):
             "target_y": float(y),
             "offset_method": offset_method,
             "distance_method": distance_method,
+            "yellow_algorithm_ms": round(yellow_algorithm_ms, 2),
+            "yolo_target_ms": round(float(yolo_target_ms), 2),
         }
 
         if ellipse_params:
@@ -413,7 +471,19 @@ def process_shot(adc_val):
             inner_data["ellipse_center_x"] = None
             inner_data["ellipse_center_y"] = None
 
+        # 记录这组 inner_data 即将进入上报队列的本地时间，精确到毫秒。
+        upload_time_ms = int(time_std.time() * 1000)
+        upload_time_sec, upload_time_millis = divmod(upload_time_ms, 1000)
+        inner_data["upload_time"] = (
+            time_std.strftime("%Y-%m-%d %H:%M:%S", time_std.localtime(upload_time_sec))
+            + f".{upload_time_millis:03d}"
+        )
         report_data = {"cmd": 1, "data": inner_data}
+        if logger:
+            logger.info(
+                f"[REPORT-TARGET] enqueue shot_id={shot_id}, "
+                f"target_class={target_label}, confidence={target_confidence}"
+            )
         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
@@ -518,6 +588,7 @@ def process_shot(adc_val):
             laser_manager.flash_laser(config.FLASH_LASER_DURATION_MS)
 
         # 保存图像（异步队列，与 main.py 一致）
+        _force_save = (dx is None and dy is None) and getattr(config, "SAVE_IMAGE_ON_FAILURE", False)
         enqueue_save_shot(
             result_img,
             center,
@@ -527,8 +598,9 @@ def process_shot(adc_val):
             (x, y),
             distance_m,
             shot_id=shot_id,
-            photo_dir=config.PHOTO_DIR if config.SAVE_IMAGE_ENABLED else None,
+            photo_dir=config.PHOTO_DIR if (config.SAVE_IMAGE_ENABLED or _force_save) else None,
             yolo_roi_xyxy=yolo_roi_xyxy if draw_yolo_roi else None,
+            force_save=_force_save,
         )
 
         if logger:

target_roi_yolo.py

@@ -89,6 +89,29 @@ def _stage2_roi_crop_save_worker(
 _detector_by_path = {}
 
 
+def _resolve_model_path(model_path: str):
+    """Resolve a model in either the installed app or MaixVision run directory."""
+    model_path = (model_path or "").strip()
+    if model_path and os.path.isfile(model_path):
+        return model_path
+    if not model_path:
+        return ""
+    name = os.path.basename(model_path)
+    module_dir = os.path.dirname(os.path.abspath(__file__))
+    candidates = (
+        os.path.join(module_dir, name),
+        os.path.join(module_dir, "test", name),
+        os.path.join("/tmp/maixpy_run", name),
+        os.path.join("/tmp/maixpy_run", "test", name),
+        os.path.join(os.getcwd(), name),
+        os.path.join(os.getcwd(), "test", name),
+    )
+    for candidate in candidates:
+        if os.path.isfile(candidate):
+            return candidate
+    return model_path
+
+
 def reset_yolo_detector_cache():
     """切换模型路径时可调用（通常不必）。"""
     global _detector_by_path
@@ -103,10 +126,19 @@ def _get_detector(model_path: str):
         return _detector_by_path[model_path]
     try:
         from maix import nn
-    except ImportError:
+    except Exception:
         return None
-    _detector_by_path[model_path] = nn.YOLOv5(model=model_path, dual_buff=False)
-    return _detector_by_path[model_path]
+    # YOLO is an optional capability. A broken/incompatible model must not
+    # abort boot (especially before the OTA rollback check).
+    try:
+        detector = nn.YOLOv5(model=model_path, dual_buff=False)
+    except Exception:
+        # Cache the failure to avoid retrying a broken native load every frame.
+        # reset_yolo_detector_cache() clears this after a model replacement.
+        _detector_by_path[model_path] = None
+        return None
+    _detector_by_path[model_path] = detector
+    return detector
 
 
 def preload_yolo_detector(logger=None):
@@ -175,6 +207,23 @@ def preload_yolo_detector(logger=None):
                 % (_loc_black,)
             )
 
+    if bool(getattr(cfg, "TARGET_CLASS_YOLO_ENABLE", False)) and bool(
+        getattr(cfg, "TARGET_CLASS_YOLO_PRELOAD_ON_BOOT", True)
+    ):
+        class_model_path = _resolve_model_path(
+            getattr(cfg, "TARGET_CLASS_YOLO_MODEL_PATH", "") or ""
+        )
+        class_detector = _get_detector(class_model_path)
+        if class_detector is None:
+            if logger:
+                logger.warning(
+                    f"[YOLO-TARGET] 预加载失败：无法加载模型 {class_model_path}"
+                )
+        else:
+            ok = True
+            if logger:
+                logger.info(f"[YOLO-TARGET] 靶规格模型已预加载: {class_model_path}")
+
     return ok
 
 
@@ -206,8 +255,10 @@ def _det_obj_class_id(o):
             if v is None:
                 continue
             try:
+                if callable(v):
+                    v = v()
                 return int(float(v))
-            except (TypeError, ValueError):
+            except (TypeError, ValueError, AttributeError):
                 continue
     return None
 
@@ -242,6 +293,106 @@ def _normalize_objs(objs):
     return out
 
 
+def _det_obj_score(o):
+    """Return confidence across supported Maix YOLO result formats."""
+    for key in ("score", "confidence", "conf", "prob"):
+        if hasattr(o, key):
+            try:
+                value = getattr(o, key)
+                if callable(value):
+                    value = value()
+                value = float(value)
+                if value == value:
+                    return value
+            except (TypeError, ValueError, AttributeError):
+                pass
+    return 0.0
+
+
+def try_get_target_class_from_yolo(maix_frame, logger=None):
+    """Classify the current target as 20cm or 40cm; return None if unknown."""
+    try:
+        import config as cfg
+    except Exception:
+        return None
+
+    if not bool(getattr(cfg, "TARGET_CLASS_YOLO_ENABLE", False)):
+        return None
+    model_path = _resolve_model_path(
+        getattr(cfg, "TARGET_CLASS_YOLO_MODEL_PATH", "") or ""
+    )
+    if not os.path.isfile(model_path):
+        if logger:
+            logger.warning(f"[YOLO-TARGET] 模型文件不存在: {model_path}")
+        return None
+    detector = _get_detector(model_path)
+    if detector is None:
+        if logger:
+            logger.warning("[YOLO-TARGET] 无法加载 nn.YOLOv5")
+        return None
+
+    conf_th = float(getattr(cfg, "TARGET_CLASS_YOLO_CONF_TH", 0.5))
+    iou_th = float(getattr(cfg, "TARGET_CLASS_YOLO_IOU_TH", 0.45))
+    labels = getattr(cfg, "TARGET_CLASS_YOLO_LABELS", (20, 40))
+    if isinstance(labels, str):
+        labels = tuple(x.strip() for x in labels.split(",") if x.strip())
+    labels = tuple(labels)
+
+    def _detect(threshold):
+        try:
+            raw = detector.detect(maix_frame, conf_th=threshold, iou_th=iou_th)
+        except Exception as exc:
+            if logger:
+                logger.warning(f"[YOLO-TARGET] detect 异常: {exc}")
+            return []
+        return _normalize_objs(raw if raw is not None else [])
+
+    def _candidates(objs):
+        found = []
+        for obj in objs:
+            class_id = _det_obj_class_id(obj)
+            if class_id is None or class_id < 0 or class_id >= len(labels):
+                continue
+            try:
+                label = int(float(labels[class_id]))
+            except (TypeError, ValueError):
+                continue
+            if label in (20, 40):
+                found.append((label, class_id, _det_obj_score(obj)))
+        return found
+
+    objects = _detect(conf_th)
+    candidates = _candidates(objects)
+    if logger and objects:
+        logger.info(
+            "[YOLO-TARGET] 原始框=%d, 解析类别=%s"
+            % (
+                len(objects),
+                [(_det_obj_class_id(o), _det_obj_score(o)) for o in objects[:8]],
+            )
+        )
+    if not candidates and bool(
+        getattr(cfg, "TARGET_CLASS_YOLO_RETRY_ON_EMPTY", False)
+    ):
+        retry_th = float(getattr(cfg, "TARGET_CLASS_YOLO_RETRY_CONF_TH", conf_th))
+        if 0 < retry_th < conf_th:
+            candidates = _candidates(_detect(retry_th))
+
+    if not candidates:
+        if logger:
+            logger.warning("[YOLO-TARGET] 当前帧未识别到 20/40，按未知处理")
+        return None
+
+    label, class_id, confidence = max(candidates, key=lambda item: item[2])
+    result = {"label": label, "class_id": class_id, "confidence": confidence}
+    if logger:
+        logger.info(
+            f"[YOLO-TARGET] 当前帧分类={label}, class_id={class_id}, "
+            f"conf={confidence:.3f}"
+        )
+    return result
+
+
 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)

test/test_charging_shutdown.py

@@ -1,144 +0,0 @@
-import importlib.util
-from pathlib import Path
-import sys
-import types
-import unittest
-from unittest import mock
-
-
-class _StopMonitor(Exception):
-    pass
-
-
-class _FakeTime:
-    now_ms = 0
-    stop_at_ms = None
-
-    @classmethod
-    def reset(cls, stop_at_ms=None):
-        cls.now_ms = 0
-        cls.stop_at_ms = stop_at_ms
-
-    @classmethod
-    def ticks_ms(cls):
-        return cls.now_ms
-
-    @classmethod
-    def sleep_ms(cls, milliseconds):
-        cls.now_ms += milliseconds
-        if cls.stop_at_ms is not None and cls.now_ms >= cls.stop_at_ms:
-            raise _StopMonitor()
-
-
-def _load_power_module():
-    module_path = Path(__file__).resolve().parents[1] / "power.py"
-    module_name = "power_charging_shutdown_test"
-    maix_module = types.ModuleType("maix")
-    maix_module.time = _FakeTime
-
-    previous_maix = sys.modules.get("maix")
-    sys.modules["maix"] = maix_module
-    try:
-        spec = importlib.util.spec_from_file_location(module_name, module_path)
-        module = importlib.util.module_from_spec(spec)
-        spec.loader.exec_module(module)
-        return module
-    finally:
-        if previous_maix is None:
-            sys.modules.pop("maix", None)
-        else:
-            sys.modules["maix"] = previous_maix
-
-
-power = _load_power_module()
-
-
-class ChargingShutdownTests(unittest.TestCase):
-    def setUp(self):
-        self.config_patch = mock.patch.multiple(
-            power.config,
-            CHARGING_SHUTDOWN_ENABLED=True,
-            CHARGING_DIAGNOSTIC_LOG_ENABLED=False,
-            CHARGING_CHECK_INTERVAL_MS=5000,
-            CHARGING_CURRENT_THRESHOLD_MA=100.0,
-            CHARGING_CONFIRM_COUNT=2,
-            CHARGING_NOTIFY_TIMEOUT_MS=30000,
-            CHARGING_EXIT_SCRIPT="/tmp/charging_exit.sh",
-        )
-        self.config_patch.start()
-        self.network_manager = mock.Mock()
-        self.network_manager.safe_enqueue_and_wait.return_value = True
-        network_module = types.ModuleType("network")
-        network_module.network_manager = self.network_manager
-        self.network_module_patch = mock.patch.dict(
-            sys.modules,
-            {"network": network_module},
-        )
-        self.network_module_patch.start()
-        _FakeTime.reset()
-
-    def tearDown(self):
-        self.network_module_patch.stop()
-        self.config_patch.stop()
-
-    def test_two_charging_samples_notify_server_and_exit(self):
-        popen_calls = []
-        with (
-            mock.patch.object(power, "get_current", return_value=-200.0),
-            mock.patch.object(power.os.path, "isfile", return_value=True),
-            mock.patch.object(
-                power.subprocess,
-                "Popen",
-                side_effect=lambda args: popen_calls.append(args),
-            ),
-        ):
-            power.charging_shutdown_monitor()
-
-        self.assertEqual(_FakeTime.now_ms, 5000)
-        self.assertEqual(len(popen_calls), 1)
-        self.network_manager.safe_enqueue_and_wait.assert_called_once_with(
-            {"poweroff": "充电中"}, 2, high=True, timeout_ms=30000
-        )
-
-    def test_discharging_does_not_notify_or_exit(self):
-        _FakeTime.reset(stop_at_ms=10000)
-        popen_calls = []
-
-        with (
-            mock.patch.object(power, "get_current", return_value=200.0),
-            mock.patch.object(power.os.path, "isfile", return_value=True),
-            mock.patch.object(
-                power.subprocess,
-                "Popen",
-                side_effect=lambda args: popen_calls.append(args),
-            ),
-            self.assertRaises(_StopMonitor),
-        ):
-            power.charging_shutdown_monitor()
-
-        self.assertEqual(popen_calls, [])
-        self.network_manager.safe_enqueue_and_wait.assert_not_called()
-
-    def test_failed_sample_resets_confirmation_count(self):
-        popen_calls = []
-        currents = iter((-200.0, 0.0, -200.0, -200.0))
-        with (
-            mock.patch.object(power, "get_current", side_effect=lambda: next(currents)),
-            mock.patch.object(power.os.path, "isfile", return_value=True),
-            mock.patch.object(
-                power.subprocess,
-                "Popen",
-                side_effect=lambda args: popen_calls.append(args),
-            ),
-        ):
-            power.charging_shutdown_monitor()
-
-        self.assertEqual(_FakeTime.now_ms, 15000)
-        self.assertEqual(len(popen_calls), 1)
-        self.network_manager.safe_enqueue_and_wait.assert_called_once_with(
-            {"poweroff": "充电中"}, 2, high=True, timeout_ms=30000
-        )
-
-
-if __name__ == "__main__":
-    unittest.main()

test/test_decect_circle_v4.py

@@ -154,11 +154,11 @@ def detect_circle_v3(frame, laser_point=None):
                                     max_r = max(red_radius, yellow_radius)
                                     size_ratio = min_r / max_r if max_r > 0 else 0
                                     print(f"Debug -> 圆心距={distance:.1f}(阈值={max_distance:.1f}), "
-                                          f"大小比={size_ratio:.2f}(阈值=0.5), "
-                                          f"距离OK={distance < max_distance}, 大小OK={size_ratio > 0.5}")
+                                          f"大小比={size_ratio:.2f}(阈值=0.4), "
+                                          f"距离OK={distance < max_distance}, 大小OK={size_ratio >= 0.4}")
 
                                     # 允许红圈在黄圈外侧或内侧，只要大小相近（较小/较大 >= 0.5）
-                                    if distance < max_distance and size_ratio > 0.5:
+                                    if distance < max_distance and size_ratio >= 0.4:
                                         found_valid_red = True
                                         print(
                                             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}")
@@ -598,7 +598,7 @@ if __name__ == "__main__":
 
     # 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_IMAGE = "/root/phot/shot_1830921_0_no_target.jpg"
 
     TARGET_DIR = "/root/phot"  # 修改为你想要读取的目录路径
 

test/test_p21_voltage.py

@@ -1,59 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""Read the digital voltage level on the MaixCAM P21 pin.
-
-P21 is a digital GPIO pin, not the MaixCAM analog ADC input. Therefore this
-script can only distinguish LOW and HIGH. For a continuous voltage value,
-connect the signal to the board's B3/ADC pin and use ADC channel 0 instead.
-
-Do not apply more than 3.3 V to P21. Always connect the signal ground to the
-MaixCAM ground.
-"""
-
-from maix import app, gpio, pinmap, time
-
-
-PIN = "P21"
-IO_HIGH_VOLTAGE = 3.3
-SAMPLE_INTERVAL_MS = 200
-
-
-def find_gpio_function(pin):
-    """Return the GPIO function supported by the requested physical pin."""
-    functions = pinmap.get_pin_functions(pin)
-    gpio_functions = [name for name in functions if name.startswith("GPIO")]
-
-    print(f"{pin} supported functions: {', '.join(functions)}")
-    if not gpio_functions:
-        raise RuntimeError(f"{pin} does not provide a GPIO input function")
-
-    return gpio_functions[0]
-
-
-def main():
-    gpio_function = find_gpio_function(PIN)
-    pinmap.set_pin_function(PIN, gpio_function)
-    voltage_input = gpio.GPIO(gpio_function, gpio.Mode.IN)
-
-    print(f"Reading {PIN} through {gpio_function}")
-    print("P21 only reports LOW/HIGH; displayed voltage is an estimate.")
-    print("Press the MaixCAM exit key to stop.")
-
-    while not app.need_exit():
-        level = voltage_input.value()
-        estimated_voltage = IO_HIGH_VOLTAGE if level else 0.0
-        state = "HIGH" if level else "LOW"
-        print(
-            f"{PIN}: level={level}, state={state}, "
-            f"estimated_voltage={estimated_voltage:.1f} V"
-        )
-        time.sleep_ms(SAMPLE_INTERVAL_MS)
-
-
-if __name__ == "__main__":
-    try:
-        main()
-    except Exception as error:
-        print(f"P21 voltage detection failed: {error}")
-        print("Check that this MaixCAM model exposes P21 as a GPIO pin.")
-        raise

test/test_target_yolo_maixvision.py

@@ -0,0 +1,108 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""Run from MaixVision on PC to inspect the box's live 20/40 YOLO output."""
+
+import os
+
+from maix import app, camera, display, image, nn, time
+
+
+# This file is sent to /tmp/maixpy_run by MaixVision. Keep the model path
+# absolute so the script uses the model already installed on the box.
+MODEL_PATH = "/maixapp/apps/t11/model_317181.mud"
+CAMERA_WIDTH = 640
+CAMERA_HEIGHT = 480
+CONF_TH = 0.65
+IOU_TH = 0.45
+
+
+def _flatten_objects(raw):
+    if raw is None:
+        return []
+    if isinstance(raw, (list, tuple)):
+        result = []
+        for item in raw:
+            if isinstance(item, (list, tuple)):
+                result.extend(_flatten_objects(item))
+            else:
+                result.append(item)
+        return result
+    return [raw]
+
+
+def main():
+    if not os.path.isfile(MODEL_PATH):
+        raise FileNotFoundError("model not found on box: " + MODEL_PATH)
+
+    detector = nn.YOLOv5(model=MODEL_PATH, dual_buff=False)
+    cam = camera.Camera(CAMERA_WIDTH, CAMERA_HEIGHT)
+    disp = display.Display()
+
+    labels = tuple(str(label) for label in detector.labels)
+    print("[YOLO] model:", MODEL_PATH)
+    print("[YOLO] labels:", labels)
+    print("[YOLO] conf=%.2f iou=%.2f" % (CONF_TH, IOU_TH))
+
+    fps = 0.0
+    frame_count = 0
+    last_log_ms = time.ticks_ms()
+
+    while not app.need_exit():
+        loop_start_ms = time.ticks_ms()
+        img = cam.read()
+
+        detect_start_ms = time.ticks_ms()
+        raw = detector.detect(img, conf_th=CONF_TH, iou_th=IOU_TH)
+        detect_ms = max(0, time.ticks_diff(time.ticks_ms(), detect_start_ms))
+        objects = _flatten_objects(raw)
+
+        candidates = []
+        for obj in objects:
+            class_id = int(obj.class_id)
+            score = float(obj.score)
+            label = labels[class_id] if 0 <= class_id < len(labels) else "unknown"
+            color = image.COLOR_GREEN if label in ("20", "40") else image.COLOR_RED
+
+            img.draw_rect(obj.x, obj.y, obj.w, obj.h, color=color)
+            img.draw_string(
+                obj.x,
+                max(0, obj.y - 16),
+                "%scm %.2f" % (label, score),
+                color=color,
+            )
+            if label in ("20", "40"):
+                candidates.append((score, label))
+
+        loop_ms = max(1, time.ticks_diff(time.ticks_ms(), loop_start_ms))
+        instant_fps = 1000.0 / float(loop_ms)
+        fps = instant_fps if frame_count == 0 else fps * 0.9 + instant_fps * 0.1
+
+        if candidates:
+            best_score, best_label = max(candidates, key=lambda item: item[0])
+            status = "TARGET %scm %.2f" % (best_label, best_score)
+            status_color = image.COLOR_GREEN
+        else:
+            status = "TARGET UNKNOWN"
+            status_color = image.COLOR_RED
+
+        img.draw_string(5, 5, status, color=status_color)
+        img.draw_string(
+            5,
+            25,
+            "infer=%dms fps=%.1f boxes=%d" % (detect_ms, fps, len(objects)),
+            color=image.COLOR_YELLOW,
+        )
+        disp.show(img)
+
+        frame_count += 1
+        now_ms = time.ticks_ms()
+        if time.ticks_diff(now_ms, last_log_ms) >= 1000:
+            print(
+                "[YOLO] %s infer=%dms fps=%.1f boxes=%d"
+                % (status, detect_ms, fps, len(objects))
+            )
+            last_log_ms = now_ms
+
+
+if __name__ == "__main__":
+    main()

test/test_wifi_failover.py

@@ -1,139 +0,0 @@
-import json
-import sys
-import types
-import unittest
-
-
-class _FakeTime:
-    @staticmethod
-    def sleep(_seconds):
-        pass
-
-    @staticmethod
-    def sleep_ms(_milliseconds):
-        pass
-
-    @staticmethod
-    def ticks_ms():
-        return 0
-
-    @staticmethod
-    def ticks_diff(left, right):
-        return left - right
-
-
-class _FakeLogger:
-    def debug(self, *_args, **_kwargs):
-        pass
-
-    def info(self, *_args, **_kwargs):
-        pass
-
-    def warning(self, *_args, **_kwargs):
-        pass
-
-    def error(self, *_args, **_kwargs):
-        pass
-
-
-class _FakeSocket:
-    def __init__(self, recv_data=b""):
-        self.recv_data = recv_data
-        self.closed = False
-
-    def close(self):
-        self.closed = True
-
-    def recv(self, _size, *_flags):
-        return self.recv_data
-
-
-class _StopAfterCallback:
-    def __init__(self):
-        self.stopped = False
-
-    def is_set(self):
-        return self.stopped
-
-
-maix_module = types.ModuleType("maix")
-maix_module.time = _FakeTime
-maix_module.network = types.SimpleNamespace()
-maix_module.err = types.SimpleNamespace()
-sys.modules.setdefault("maix", maix_module)
-sys.modules.setdefault("ujson", json)
-
-netcore_module = types.ModuleType("archery_netcore")
-netcore_module.get_config = lambda: {"SERVER_IP": "127.0.0.1", "SERVER_PORT": 1234}
-netcore_module.parse_packet = lambda _packet: (0, {})
-netcore_module.make_packet = lambda *_args, **_kwargs: b""
-netcore_module.actions_for_inner_cmd = lambda *_args, **_kwargs: []
-sys.modules["archery_netcore"] = netcore_module
-
-hardware_module = types.ModuleType("hardware")
-hardware_module.hardware_manager = types.SimpleNamespace()
-sys.modules["hardware"] = hardware_module
-
-power_module = types.ModuleType("power")
-power_module.get_bus_voltage = lambda: 0
-power_module.voltage_to_percent = lambda _voltage: 0
-sys.modules["power"] = power_module
-
-import logger_manager
-import wifi
-import network
-
-
-class WiFiFailoverTests(unittest.TestCase):
-    def setUp(self):
-        logger_manager.logger_manager._logger = _FakeLogger()
-
-    def test_monitor_switches_when_sta_association_is_lost(self):
-        manager = wifi.wifi_manager
-        stop_event = _StopAfterCallback()
-        callbacks = []
-
-        manager._wifi_socket = _FakeSocket()
-        manager._wifi_quality_stop_event = stop_event
-        manager._network_type_callback = lambda: "wifi"
-        manager.is_sta_associated = lambda: False
-        manager._get_wifi_rssi_dbm = lambda: None
-
-        def on_poor_quality():
-            callbacks.append(True)
-            stop_event.stopped = True
-
-        manager._on_poor_quality_callback = on_poor_quality
-        manager._quality_monitor_loop()
-
-        self.assertEqual(callbacks, [True])
-        self.assertIsNone(manager.last_wifi_rtt_ms)
-
-    def test_tls_connection_check_rejects_lost_sta_association(self):
-        manager = network.network_manager
-        sock = _FakeSocket()
-        wifi.wifi_manager._wifi_socket = sock
-        wifi.wifi_manager._wifi_connected = True
-        wifi.wifi_manager._wifi_ip = "192.168.1.2"
-        wifi.wifi_manager.is_sta_associated = lambda: False
-        manager._tcp_connected = True
-
-        self.assertFalse(manager._check_wifi_connection())
-        self.assertTrue(sock.closed)
-        self.assertIsNone(wifi.wifi_manager.wifi_socket)
-        self.assertFalse(manager.tcp_connected)
-
-    def test_receive_eof_marks_wifi_tcp_disconnected(self):
-        manager = network.network_manager
-        sock = _FakeSocket(recv_data=b"")
-        wifi.wifi_manager._wifi_socket = sock
-        manager._tcp_connected = True
-
-        self.assertEqual(manager.receive_tcp_data_via_wifi(), b"")
-        self.assertTrue(sock.closed)
-        self.assertIsNone(wifi.wifi_manager.wifi_socket)
-        self.assertFalse(manager.tcp_connected)
-
-
-if __name__ == "__main__":
-    unittest.main()

test_traditional_target.py

@@ -0,0 +1,184 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""Offline baseline for traditional target-paper detection.
+
+Dataset format: sibling .txt files use YOLO boxes and classes.txt maps ids
+(the supplied dataset uses 0=40, 1=20, 2=10).  This intentionally simple
+baseline uses grayscale segmentation and contour geometry; it is useful as a
+reference before adding more specialized black-triangle grouping.
+"""
+from __future__ import annotations
+
+import argparse
+import csv
+import glob
+import itertools
+import os
+
+import cv2
+import numpy as np
+
+
+def detect_white_papers(image: np.ndarray) -> list[tuple[int, int, int, int]]:
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    h, w = gray.shape[:2]
+    mask = cv2.inRange(gray, 120, 255)
+    mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, np.ones((9, 9), np.uint8))
+    mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, np.ones((5, 5), np.uint8))
+    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    out = []
+    for contour in contours:
+        x, y, bw, bh = cv2.boundingRect(contour)
+        area = float(bw * bh)
+        if area < 0.05 * w * h or min(bw, bh) < 80:
+            continue
+        fill = cv2.contourArea(contour) / max(area, 1.0)
+        aspect = bw / max(float(bh), 1.0)
+        if fill >= 0.45 and 0.4 <= aspect <= 2.5:
+            out.append((x, y, x + bw, y + bh))
+    return out
+
+
+def detect_black_triangle_papers(image: np.ndarray):
+    """Infer paper boxes from the four small black corner marks."""
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    mask = cv2.inRange(gray, 0, 100)
+    mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, np.ones((2, 2), np.uint8))
+    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    points = []
+    for contour in contours:
+        x, y, bw, bh = cv2.boundingRect(contour)
+        area = cv2.contourArea(contour)
+        vertices = cv2.approxPolyDP(contour, 0.08 * cv2.arcLength(contour, True), True)
+        if 60 <= area <= 400 and 8 <= bw <= 24 and 8 <= bh <= 24:
+            if 3 <= len(vertices) <= 5 and 0.5 <= bw / max(bh, 1) <= 2.0:
+                points.append((x + bw / 2.0, y + bh / 2.0))
+    candidates = []
+    for group in itertools.combinations(points, 4):
+        xs = sorted(p[0] for p in group)
+        ys = sorted(p[1] for p in group)
+        span_x, span_y = xs[-1] - xs[0], ys[-1] - ys[0]
+        if span_x < 50 or span_y < 50 or not 0.45 < span_x / span_y < 1.5:
+            continue
+        corners = ((xs[0], ys[0]), (xs[-1], ys[0]),
+                   (xs[0], ys[-1]), (xs[-1], ys[-1]))
+        error = max(min(np.hypot(p[0] - c[0], p[1] - c[1]) for c in corners)
+                    for p in group) / max(span_x, span_y)
+        if error > 0.22:
+            continue
+        ex, ey = 0.12 * span_x, 0.12 * span_y
+        candidates.append((xs[0] - ex, ys[0] - ey,
+                           xs[-1] + ex, ys[-1] + ey, error))
+    # A colored target ring supplies an independent center check. Hough is
+    # deliberately low-cost here because it runs only on the already small
+    # candidate list's source frame.
+    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
+    color = cv2.inRange(hsv, (0, 70, 45), (179, 255, 255))
+    color = cv2.morphologyEx(color, cv2.MORPH_OPEN, np.ones((5, 5), np.uint8))
+    ring_centers = []
+    for contour in cv2.findContours(color, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[0]:
+        area = cv2.contourArea(contour)
+        if area < 150:
+            continue
+        moments = cv2.moments(contour)
+        if moments["m00"]:
+            ring_centers.append((moments["m10"] / moments["m00"], moments["m01"] / moments["m00"]))
+    checked = []
+    for box in candidates:
+        if not ring_centers:
+            checked.append(box)
+            continue
+        x0, y0, x1, y1, err = box
+        inside = any(x0 - .15 * (x1 - x0) <= cx <= x1 + .15 * (x1 - x0)
+                     and y0 - .15 * (y1 - y0) <= cy <= y1 + .15 * (y1 - y0)
+                     for cx, cy in ring_centers)
+        if inside:
+            checked.append(box)
+    return sorted(checked, key=lambda x: x[-1])
+
+
+def iou(a, b):
+    x0, y0 = max(a[0], b[0]), max(a[1], b[1])
+    x1, y1 = min(a[2], b[2]), min(a[3], b[3])
+    inter = max(0, x1 - x0) * max(0, y1 - y0)
+    aa = max(0, a[2] - a[0]) * max(0, a[3] - a[1])
+    bb = max(0, b[2] - b[0]) * max(0, b[3] - b[1])
+    return inter / max(aa + bb - inter, 1)
+
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("dataset", help="directory containing jpg and YOLO txt files")
+    ap.add_argument("--iou", type=float, default=0.5)
+    ap.add_argument("--out", default="traditional_eval_results.csv",
+                    help="CSV output path; relative paths are next to the dataset")
+    ap.add_argument("--vis-dir", default="traditional_eval_images",
+                    help="directory for annotated result images; empty disables")
+    args = ap.parse_args()
+    stats = {0: [0, 0], 1: [0, 0]}
+    rows = []
+    # OpenCV on some Windows builds cannot decode non-ASCII filenames. Work
+    # relative to the dataset directory so the supplied Chinese path is safe.
+    dataset = os.path.abspath(args.dataset)
+    os.chdir(dataset)
+    # cwd is now the dataset, so a relative output avoids Windows console
+    # encoding issues with the Chinese parent path.
+    vis_dir = args.vis_dir if args.vis_dir else ""
+    if vis_dir:
+        os.makedirs(vis_dir, exist_ok=True)
+    files = glob.glob(os.path.join("**", "*.jpg"), recursive=True)
+    for image_path in files:
+        label_path = os.path.splitext(image_path)[0] + ".txt"
+        if not os.path.isfile(label_path):
+            continue
+        image = cv2.imread(image_path)
+        if image is None:
+            continue
+        h, w = image.shape[:2]
+        predictions = detect_black_triangle_papers(image)
+        vis = image.copy()
+        for p in predictions:
+            cv2.rectangle(vis, (int(p[0]), int(p[1])), (int(p[2]), int(p[3])), (0, 255, 255), 2)
+        for line in open(label_path, encoding="utf-8", errors="ignore"):
+            z = line.split()
+            if len(z) < 5 or int(float(z[0])) not in stats:
+                continue
+            cls, cx, cy, bw, bh = int(float(z[0])), *map(float, z[1:5])
+            truth = (int((cx - bw / 2) * w), int((cy - bh / 2) * h),
+                     int((cx + bw / 2) * w), int((cy + bh / 2) * h))
+            best = max((iou(truth, p) for p in predictions), default=0.0)
+            best_box = max(predictions, key=lambda p: iou(truth, p), default=())
+            stats[cls][0] += 1
+            stats[cls][1] += int(best >= args.iou)
+            rows.append({
+                "image": image_path,
+                "class_id": cls,
+                "truth_xyxy": ",".join(map(str, truth[:4])),
+                "pred_xyxy": ",".join(map(str, best_box[:4])) if best_box else "",
+                "iou": f"{best:.4f}",
+                "pass": int(best >= args.iou),
+            })
+            color = (0, 255, 0) if best >= args.iou else (0, 0, 255)
+            cv2.rectangle(vis, truth[:2], truth[2:4], color, 2)
+            cv2.putText(vis, f"GT {cls} IoU {best:.2f}",
+                        (truth[0], max(16, truth[1] - 4)),
+                        cv2.FONT_HERSHEY_SIMPLEX, 0.45, color, 1, cv2.LINE_AA)
+        if vis_dir:
+            name = os.path.splitext(os.path.basename(image_path))[0] + "_result.jpg"
+            cv2.imwrite(os.path.join(vis_dir, name), vis)
+    total = sum(v[0] for v in stats.values())
+    good = sum(v[1] for v in stats.values())
+    print(f"paper objects: {good}/{total} = {good / max(total, 1):.2%} (IoU >= {args.iou})")
+    for cls, (n, ok) in stats.items():
+        print(f"class {cls}: {ok}/{n} = {ok / max(n, 1):.2%}")
+    out_path = args.out if os.path.isabs(args.out) else os.path.join(dataset, args.out)
+    with open(out_path, "w", newline="", encoding="utf-8-sig") as fp:
+        writer = csv.DictWriter(fp, fieldnames=("image", "class_id", "truth_xyxy",
+                                                "pred_xyxy", "iou", "pass"))
+        writer.writeheader()
+        writer.writerows(rows)
+    print(f"details csv: {out_path}")
+
+
+if __name__ == "__main__":
+    main()

version.md

@@ -29,10 +29,12 @@
 # 2.15.16 修复wifi连接问题
 # 2.15.17 修复wifi连接问题
 # 2.15.18 wifi连接成功重新登录
-# 2.15.20 加了充电关机，激光也同时关闭
-# 2.15.21 测试4g 扩大了缓存池和改了心跳时间
-# 2.15.22 修复了4g网络和wifi切换问题
-# 2.15.23 合并充电关机与稳定版网络修复
-# 2.15.24 空改测试
-# 2.15.25 修复整合后关机失败和ota格式更新问题
-# 2.15.26 
+# 2.16.4  优化射箭延迟
+# 2.17.0  yolo标靶类别识别
+# 2.17.1  26-08-19 17：39 压力传感修改 增量方式 
+
+# 2.17.2 26-08-24 17：56 靶纸识别模型更替
+
+# 2.17.3 26-08-25 9：57 原图拍摄开关
+
+# 2.17.4 26-08-25 14：57 模型修改

version.py

@@ -4,6 +4,6 @@
 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 = '2.15.31'
+VERSION = '2.17.18'
 
 

vision.py

@@ -631,7 +631,7 @@ def detect_circle_v3(frame, laser_point=None, img_cv=None):
             min_r = min(rc["radius"], yellow_radius)
             max_r = max(rc["radius"], yellow_radius)
             size_ratio = min_r / max_r if max_r > 0 else 0
-            if dist_centers < max_dist and size_ratio >= 0.3:
+            if dist_centers < max_dist and size_ratio >= 0.4:
                 if logger:
                     logger.info(f"[target] -> 找到匹配的红圈: 黄心({yellow_center}), "
                                 f"红心({rc['center']}), 距离:{dist_centers:.1f}, "
@@ -797,12 +797,12 @@ def estimate_pixel(physical_distance_cm, target_distance_m):
 
 def _save_shot_image_impl(img_cv, center, radius, method, ellipse_params,
                           laser_point, distance_m, shot_id=None, photo_dir=None,
-                          yolo_roi_xyxy=None):
+                          yolo_roi_xyxy=None, force_save=False):
     """
     内部实现：在 img_cv (numpy HWC RGB) 上绘制标注并保存。
     由 save_shot_image（同步）和存图 worker（异步）调用。
     """
-    if not config.SAVE_IMAGE_ENABLED:
+    if not config.SAVE_IMAGE_ENABLED and not force_save:
         return None
     if photo_dir is None:
         photo_dir = config.PHOTO_DIR
@@ -908,6 +908,11 @@ def _save_worker_loop():
             item = _save_queue.get()
             if item is None:
                 break
+            if isinstance(item, dict) and item.get("kind") == "raw":
+                _save_raw_image_impl(
+                    item["img_cv"], item["shot_id"], item["photo_dir"]
+                )
+            else:
                 _save_shot_image_impl(*item)
         except Exception as e:
             logger = logger_manager.logger
@@ -936,13 +941,64 @@ def start_save_shot_worker():
         logger.info("[VISION] 存图 worker 线程已启动")
 
 
+def _save_raw_image_impl(img_cv, shot_id, photo_dir):
+    """保存相机完整原始帧，不添加任何检测标注。"""
+    logger = logger_manager.logger
+    try:
+        os.makedirs(photo_dir, exist_ok=True)
+        filename = os.path.join(photo_dir, f"shot_{shot_id}_raw.jpg")
+        image.cv2image(img_cv, False, False).save(filename)
+        prune_old_images_in_dir(
+            photo_dir,
+            getattr(config, "RAW_IMAGE_MAX_IMAGES", config.MAX_IMAGES),
+            logger,
+            "[VISION-RAW]",
+        )
+        if logger:
+            logger.info(f"[VISION-RAW] 已保存纯原图: {filename}")
+        return filename
+    except Exception as e:
+        if logger:
+            logger.error(f"[VISION-RAW] 保存纯原图失败: {e}")
+        return None
+
+
+def enqueue_save_raw_shot(frame, shot_id, photo_dir=None):
+    """立即复制相机帧并异步保存，避免后续识别和绘图修改原图。"""
+    if not getattr(config, "SAVE_RAW_IMAGE_ENABLED", False):
+        return
+    if photo_dir is None:
+        photo_dir = getattr(
+            config, "RAW_IMAGE_DIR", os.path.join(config.PHOTO_DIR, "raw")
+        )
+    try:
+        img_copy = np.copy(image.image2cv(frame, False, False))
+        _save_queue.put_nowait(
+            {
+                "kind": "raw",
+                "img_cv": img_copy,
+                "shot_id": shot_id,
+                "photo_dir": photo_dir,
+            }
+        )
+    except queue.Full:
+        logger = logger_manager.logger
+        if logger:
+            logger.warning("[VISION-RAW] 存图队列已满，跳过本次纯原图保存")
+    except Exception as e:
+        logger = logger_manager.logger
+        if logger:
+            logger.error(f"[VISION-RAW] 复制纯原图失败: {e}")
+
+
 def enqueue_save_shot(result_img, center, radius, method, ellipse_params,
                       laser_point, distance_m, shot_id=None, photo_dir=None,
-                      yolo_roi_xyxy=None):
+                      yolo_roi_xyxy=None, force_save=False):
     """
     将存图任务放入队列，由 worker 异步保存。主线程传入 result_img 的复制，不阻塞。
+    force_save=True 时，忽略 SAVE_IMAGE_ENABLED 配置强制保存（用于检测失败时的调试图像）。
     """
-    if not config.SAVE_IMAGE_ENABLED:
+    if not config.SAVE_IMAGE_ENABLED and not force_save:
         return
     if photo_dir is None:
         photo_dir = config.PHOTO_DIR
@@ -965,6 +1021,7 @@ def enqueue_save_shot(result_img, center, radius, method, ellipse_params,
         shot_id,
         photo_dir,
         yolo_roi_xyxy,
+        force_save,
     )
     try:
         _save_queue.put_nowait(task)
@@ -976,12 +1033,12 @@ def enqueue_save_shot(result_img, center, radius, method, ellipse_params,
 
 def save_shot_image(result_img, center, radius, method, ellipse_params,
                     laser_point, distance_m, shot_id=None, photo_dir=None,
-                    yolo_roi_xyxy=None):
+                    yolo_roi_xyxy=None, force_save=False):
     """
     保存射击图像（带标注）。同步调用，会阻塞。
     主流程建议使用 enqueue_save_shot；此处保留供校准、测试等场景使用。
     """
-    if not config.SAVE_IMAGE_ENABLED:
+    if not config.SAVE_IMAGE_ENABLED and not force_save:
         return None
     if photo_dir is None:
         photo_dir = config.PHOTO_DIR
@@ -998,6 +1055,7 @@ def save_shot_image(result_img, center, radius, method, ellipse_params,
             shot_id,
             photo_dir,
             yolo_roi_xyxy,
+            force_save,
         )
     except Exception as e:
         logger = logger_manager.logger

wifi.py

@@ -541,7 +541,7 @@ class WiFiManager:
     
     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 秒检查 STA 关联状态和 RSSI）
+        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:
@@ -591,38 +591,34 @@ class WiFiManager:
     def _quality_monitor_loop(self):
         """
         WiFi 质量监测循环（后台线程）
-        每 5 秒检查 STA 关联状态和 RSSI，发现断链或质量差则触发切换
+        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:
-                    # RTT 测量当前禁用；STA 关联状态用于判断物理 WiFi 链路是否仍存在。
-                    # 不能把禁用的 RTT 伪装成 0ms，否则关闭热点后会一直被判为正常。
-                    reachable = self.is_sta_associated()
-                    rtt_ms = None
+                    # # 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
-                    self._last_wifi_rtt_ms = rtt_ms
+                    # 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
-                    _rtt_s = f"{rtt_ms:.0f}ms" if rtt_ms is not None else "n/a"
                     _rssi_s = f"{rssi_dbm:.0f}" if rssi_dbm is not None else "n/a"
-                    self.logger.debug(
-                        f"[WiFi Monitor] - associated={reachable}, RTT={_rtt_s}, RSSI={_rssi_s}dBm"
-                    )
+                    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:
-                            return True
-                        # RTT 未启用时不参与质量判断；链路状态仍由 STA 关联保证。
-                        if _rtt is None:
-                            return False
-                        if _rtt == float("inf"):
+                        if (not _reachable) or (_rtt is None) or (_rtt == float("inf")):
                             return True
                         return self._is_wifi_quality_bad(_rtt, _rssi)
 
@@ -632,8 +628,13 @@ class WiFiManager:
 
                         for retry_idx in range(2):
                             time.sleep_ms(1000)
-                            reachable2 = self.is_sta_associated()
-                            rtt2 = None
+                            # 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
@@ -642,10 +643,14 @@ class WiFiManager:
 
                             bad2 = _is_bad_now(reachable2, rtt2, rssi2)
                             try:
-                                _rtt_disp = f"{rtt2:.0f}ms" if rtt2 is not None else "n/a"
+                                _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}, rssi={rssi2}, bad={bad2}"
+                                    f"rtt={_rtt_disp:.0f}ms, rssi={rssi2}, bad={bad2}"
                                 )
                             except Exception:
                                 pass