'commit'

Apps/TeLaiDian/TestCV.py

@@ -30,11 +30,25 @@ def test_cv_detection(image_path):
     for i, box in enumerate(bboxes):
         print(f"  卡片 {i+1}: {box}")
 
-    # 2. 生成 _vl.jpg (仅绿框)
+    # 1.5 检测红色价格块并打印
+    try:
+        price_blocks = Kit.detect_list_price_blocks_cv(image_path, top_ratio=SAFE_EXCLUDE_RATIO, bottom_ratio=BOTTOM_SAFE_EXCLUDE_RATIO)
+    except AttributeError:
+        price_blocks = []
+    print(f"检测到 {len(price_blocks)} 个红色价格块")
+    for i, pb in enumerate(price_blocks):
+        print(f"  价格块 {i+1}: {pb}")
+
+    # 2. 生成 _vl.jpg (绿框 + 蓝点标记红色价格行)
     vl_path = image_path.replace(".jpg", "_vl.jpg")
     img_vl = Kit.read_image(image_path)
     for box in bboxes:
         cv2.rectangle(img_vl, (box[0], box[1]), (box[2], box[3]), (0, 255, 0), 3)
+    for pb in price_blocks:
+        px1, py1, px2, py2 = pb
+        pcx = (px1 + px2) // 2
+        pcy = (py1 + py2) // 2
+        cv2.circle(img_vl, (pcx, pcy), 10, (255, 0, 0), -1)
     Kit.save_image(vl_path, img_vl)
     print(f"已生成 VLM 标注图: {vl_path}")
 
@@ -59,5 +73,5 @@ def test_cv_detection(image_path):
     print(f"已生成人工核对图: {flag_path}")
 
 if __name__ == "__main__":
-    target_image = r"d:\dsWork\aiData\Output\tld_list_1768347471.jpg"
+    target_image = r"d:\dsWork\aiData\Output\tld_list_1768359492.jpg"
     test_cv_detection(target_image)