fix: rm yolo

app.yaml

@@ -1,6 +1,6 @@
 id: t11
 name: t11
-version: 2.15.6
+version: 2.15.8
 author: t11
 icon: ''
 desc: t11

config.py

@@ -260,7 +260,7 @@ TRIANGLE_SAMPLE_RADIUS_CM = 15.0
 TRIANGLE_SAMPLE_ANGLES_DEG = (0, 90, 180, 270)
 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 = True
+TRIANGLE_YOLO_PRELOAD_ON_BOOT = False
 
 # ── 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）：

test/test_decect.py

@@ -71,8 +71,8 @@ def detect_circle_v3(frame, laser_point=None, img_cv=None):
 
     # -- 3. 红色掩码：在循环外只算一次
     mask_red = cv2.bitwise_or(
-        cv2.inRange(hsv, np.array([0, 80, 0]), np.array([10, 255, 255])),
+        cv2.inRange(hsv, np.array([0, 50, 40]), np.array([10, 255, 255])),
-        cv2.inRange(hsv, np.array([170, 80, 0]), np.array([180, 255, 255])),
+        cv2.inRange(hsv, np.array([170, 50, 40]), np.array([180, 255, 255])),
     )
     kernel_red = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
     mask_red = cv2.morphologyEx(mask_red, cv2.MORPH_CLOSE, kernel_red)
@@ -81,10 +81,10 @@ def detect_circle_v3(frame, laser_point=None, img_cv=None):
     red_candidates = []
     for cnt_r in contours_red:
         ar = cv2.contourArea(cnt_r)
-        if ar <= 50:
+        if ar <= 30:
             continue
         pr = cv2.arcLength(cnt_r, True)
-        if pr <= 0 or (4 * np.pi * ar) / (pr * pr) <= 0.6:
+        if pr <= 0 or (4 * np.pi * ar) / (pr * pr) <= 0.4:
             continue
         if len(cnt_r) >= 5:
             (xr, yr), (wr, hr), _ = cv2.fitEllipse(cnt_r)
@@ -125,7 +125,7 @@ def detect_circle_v3(frame, laser_point=None, img_cv=None):
             ddx = yellow_center[0] - rc["center"][0]
             ddy = yellow_center[1] - rc["center"][1]
             dist_centers = math.hypot(ddx, ddy)
-            if dist_centers < yellow_radius * 1.5 and rc["radius"] > yellow_radius * 0.8:
+            if dist_centers < yellow_radius * 1.5 and rc["radius"] > yellow_radius * 0.7:
                 print(f"[target] -> 找到匹配的红圈: 黄心({yellow_center}), "
                                 f"红心({rc['center']}), 距离:{dist_centers:.1f}, "
                                 f"黄半径:{yellow_radius}, 红半径:{rc['radius']}")
@@ -279,8 +279,8 @@ def run_offline_test(image_path):
         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")
+    base, ext = os.path.splitext(image_path)
-    output_path = image_path.replace(".jpg", "_result.jpg")
+    output_path = f"{base}_result{ext}"
     try:
         result_img.save(output_path, quality=100)
         print(f"[SUCCESS] 结果已保存至: {output_path}")

version.md

@@ -17,3 +17,5 @@
 # 2.15.4 更新版本号
 # 2.15.5 打印ota进度
 # 2.15.6 更新版本号
+# 2.15.7 更新版本号
+# 2.15.8 启动不加载预加载yolo

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 = '2.15.6'
+VERSION = '2.15.7'
 
 

vision.py

@@ -570,8 +570,8 @@ def detect_circle_v3(frame, laser_point=None, img_cv=None):
 
     # -- 3. 红色掩码：在循环外只算一次
     mask_red = cv2.bitwise_or(
-        cv2.inRange(hsv, np.array([0, 80, 0]),   np.array([10,  255, 255])),
+        cv2.inRange(hsv, np.array([0, 50, 40]),   np.array([10,  255, 255])),
-        cv2.inRange(hsv, np.array([170, 80, 0]), np.array([180, 255, 255])),
+        cv2.inRange(hsv, np.array([170, 50, 40]), np.array([180, 255, 255])),
     )
     kernel_red = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
     mask_red = cv2.morphologyEx(mask_red, cv2.MORPH_CLOSE, kernel_red)
@@ -580,10 +580,10 @@ def detect_circle_v3(frame, laser_point=None, img_cv=None):
     red_candidates = []
     for cnt_r in contours_red:
         ar = cv2.contourArea(cnt_r)
-        if ar <= 50:
+        if ar <= 30:
             continue
         pr = cv2.arcLength(cnt_r, True)
-        if pr <= 0 or (4 * np.pi * ar) / (pr * pr) <= 0.6:
+        if pr <= 0 or (4 * np.pi * ar) / (pr * pr) <= 0.4:
             continue
         if len(cnt_r) >= 5:
             (xr, yr), (wr, hr), _ = cv2.fitEllipse(cnt_r)
@@ -625,7 +625,7 @@ def detect_circle_v3(frame, laser_point=None, img_cv=None):
             ddx = yellow_center[0] - rc["center"][0]
             ddy = yellow_center[1] - rc["center"][1]
             dist_centers = math.hypot(ddx, ddy)
-            if dist_centers < yellow_radius * 1.5 and rc["radius"] > yellow_radius * 0.8:
+            if dist_centers < yellow_radius * 1.5 and rc["radius"] > yellow_radius * 0.7:
                 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}, "