feat: 2.17.18

app.yaml

@@ -1,6 +1,6 @@
 id: t11
 name: t11
-version: 2.17.15
+version: 2.17.18
 author: t11
 icon: ''
 desc: t11

camera_manager.py

@@ -8,15 +8,6 @@ import threading
 import config
 from logger_manager import logger_manager
 
-_USE_CV = False
-try:
-    import cv2
-    import numpy as np
-    from maix import image as _maix_image
-    _USE_CV = True
-except ImportError:
-    pass
-
 
 class CameraManager:
     """相机管理器（单例）"""
@@ -110,23 +101,7 @@ class CameraManager:
         with self._camera_lock:
             if self._camera is None:
                 self.init_camera()
-            frame = self._camera.read()
+            return self._camera.read()
-            if frame is not None and _USE_CV:
-                try:
-                    v_flip = getattr(config, 'CAMERA_V_FLIP', False)
-                    h_mirror = getattr(config, 'CAMERA_H_MIRROR', False)
-                    if v_flip or h_mirror:
-                        img_cv = _maix_image.image2cv(frame, False, False)
-                        if v_flip and h_mirror:
-                            img_cv = cv2.flip(img_cv, -1)
-                        elif v_flip:
-                            img_cv = cv2.flip(img_cv, 0)
-                        elif h_mirror:
-                            img_cv = cv2.flip(img_cv, 1)
-                        frame = _maix_image.cv2image(img_cv, False, False)
-                except Exception:
-                    pass
-            return frame
     
     def show(self, image):
         """

config.py

@@ -15,8 +15,6 @@ LOCAL_FILENAME = APP_DIR + "/main_tmp.py"
 # 相机初始化分辨率（CameraManager / main.py 使用）
 CAMERA_WIDTH = 640
 CAMERA_HEIGHT = 480
-CAMERA_V_FLIP = True   # 摄像头垂直翻转（上下颠倒时设为 True）
-CAMERA_H_MIRROR = True  # 摄像头水平镜像（左右反了时设为 True）
 
 # 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
@@ -329,16 +327,16 @@ MAX_CMD_THREADS = 10            # 并发命令线程上限（防止服务器下
 
 # ==================== 图像保存配置 ====================
 SAVE_IMAGE_ENABLED = True  # 是否保存图像（True=保存，False=不保存）
-SAVE_IMAGE_ON_FAILURE = False  # 检测失败时是否强制保存图像（供调试测试用）
+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 = True  # 额外保存完整原始帧（不画框、不画点、不裁剪）
+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
 
-SHOW_CAMERA_PHOTO_WHILE_SHOOTING = True  # 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
+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

main.py

@@ -385,11 +385,11 @@ def cmd_str():
                 pressure_max = adc_val
             if len(pressure_buf) >= PRESSURE_BATCH_SIZE:
                 _flush_pressure_buf("batch")
-            # 突变增量检测：压力增量大于300时触发
+            # 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) > 500 and enable_check:
+            if (adc_val - last_adc_val) > 200 and enable_check:
                 hardware_manager.start_idle_timer()  # 重新计时
                 last_adc_trigger = current_time
                 trigger_adc_val = adc_val  # 记录触发时的气压值

shoot_manager.py

@@ -59,6 +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
@@ -74,7 +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)
@@ -119,6 +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
@@ -126,9 +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(
+        _t_yellow = time_std.perf_counter()
-            detect_circle_v3(frame, laser_point, img_cv=img_cv)
+        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
@@ -281,6 +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"),
@@ -300,8 +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)
@@ -337,10 +351,15 @@ def process_shot(adc_val):
 
         # 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:
@@ -370,6 +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")
@@ -419,7 +439,9 @@ def process_shot(adc_val):
             "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": (
-                float(target_confidence) if target_confidence is not None else None
+                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),
@@ -431,6 +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:

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 = '2.17.15'
+VERSION = '2.17.18'