yolo最新选择

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
@@ -322,6 +327,11 @@ 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)
 
@@ -380,10 +390,6 @@ 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}")
 
@@ -441,6 +447,13 @@ 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(