'commit'

Apps/XinDianTu/Kit.py

@@ -137,43 +137,43 @@ def is_background_dimmed(image_path, threshold=80):
     return avg_brightness < threshold
 
 
-from Util.EasyOcrKit import get_easyocr_reader
+from Util.EasyOcrKit import get_easyocr_reader
-
+
-# 预加载 EasyOCR Reader (单例模式)
+# 预加载 EasyOCR Reader (单例模式)
-def get_ocr_reader():
+def get_ocr_reader():
-    return get_easyocr_reader(gpu=True)
+    return get_easyocr_reader(gpu=True)
-
+
-
+
-def detect_price_info_container_cv(image_path):
+def detect_price_info_container_cv(image_path):
-    """
+    """
-    使用 OCR 精准定位详情页中的价格入口文本（“全部时段”）。
+    使用 OCR 精准定位详情页中的价格入口文本（“全部时段”）。
-    返回: [x1, y1, x2, y2] 归一化坐标 (0-1000)，如果未找到则返回 None
+    返回: [x1, y1, x2, y2] 归一化坐标 (0-1000)，如果未找到则返回 None
-    """
+    """
-    img = read_image(image_path)
+    img = read_image(image_path)
-    if img is None:
+    if img is None:
-        return None
+        return None
-    h, w = img.shape[:2]
+    h, w = img.shape[:2]
-    
+    
-    keywords = ['全部时段']
+    keywords = ['全部时段']
-    
+    
-    try:
+    try:
-        reader = get_ocr_reader()
+        reader = get_ocr_reader()
-        # 获取所有识别结果
+        # 获取所有识别结果
-        results = reader.read_text(img)
+        results = reader.read_text(img)
-        
+        
-        for (quad, text, prob) in results:
+        for (quad, text, prob) in results:
-            # 检查是否包含关键字
+            # 检查是否包含关键字
-            if any(kw in text for kw in keywords) and prob >= 0.5:
+            if any(kw in text for kw in keywords) and prob >= 0.5:
-                # 使用封装后的方法计算归一化矩形
+                # 使用封装后的方法计算归一化矩形
-                res = reader.get_normalized_rect(quad, w, h)
+                res = reader.get_normalized_rect(quad, w, h)
-                logger.info(f"[OCR识别] 找到文本: '{text}', 置信度: {prob:.4f}, 归一化坐标: {res}")
+                logger.info(f"[OCR识别] 找到文本: '{text}', 置信度: {prob:.4f}, 归一化坐标: {res}")
-                return res
+                return res
-    except Exception as e:
+    except Exception as e:
-        logger.error(f"OCR 识别发生异常: {e}")
+        logger.error(f"OCR 识别发生异常: {e}")
-        
+        
-    return None
+    return None
-
+
-
+
 def detect_rabbit_ad_close(image_path, debug_dir=None):
     """
     通过图形学算法检测“新电兔AI”广告的关闭按钮
@@ -877,6 +877,18 @@ def crop_cards_from_image(img_path, output_dir=None, save_debug=True):
     # 准备 _vl.jpg (只画框，不画红点)
     vl_img = img.copy()
 
+    # 预先在整张图上标记“兔子广告潜在区域”的蓝色矩形，方便标定
+    try:
+        rabbit_x1 = int(w * 0.04)
+        rabbit_x2 = int(w * 0.96)
+        rabbit_y1 = int(h * 0.74)
+        rabbit_y2 = int(h * 0.86)
+        cv2.rectangle(debug_img, (rabbit_x1, rabbit_y1), (rabbit_x2, rabbit_y2), (255, 0, 0), 3)
+        cv2.rectangle(vl_img, (rabbit_x1, rabbit_y1), (rabbit_x2, rabbit_y2), (255, 0, 0), 3)
+        logger.info(f"  标记兔子广告蓝色区域: X={rabbit_x1}-{rabbit_x2}, Y={rabbit_y1}-{rabbit_y2}")
+    except Exception as e:
+        logger.warning(f"标记兔子广告蓝色区域失败: {e}")
+
     logger.info(f"  Step [2.1/VL] 准备在 VL 图片上绘制 {len(final_cards)} 个场站的绿色方框...")
 
     for idx, (y1, y2, x1, x2) in enumerate(final_cards):

Tools/T9_DebugRabbitBlueRect.py

@@ -0,0 +1,33 @@
+import os
+from PIL import Image, ImageDraw
+
+
+IMAGE_PATH = r"d:\dsWork\aiData\Output\Screenshot_20260117_073155.jpg"
+OUTPUT_PATH = r"d:\dsWork\aiData\Output\rabbit_blue_rect_20260117_073155.jpg"
+
+
+def draw_rabbit_blue_rect(image_path: str, output_path: str):
+    if not os.path.exists(image_path):
+        raise FileNotFoundError(image_path)
+
+    img = Image.open(image_path).convert("RGB")
+    w, h = img.size
+
+    # 水平方向收一点边：左右各预留 4% 宽度
+    x1 = int(w * 0.04)
+    x2 = int(w * 0.96)
+    # 垂直方向：稍微向上抬一点上边界，下边界大幅向上
+    y1 = int(h * 0.74)
+    y2 = int(h * 0.86)
+
+    draw = ImageDraw.Draw(img)
+    draw.rectangle((x1, y1, x2, y2), outline="blue", width=4)
+
+    os.makedirs(os.path.dirname(output_path), exist_ok=True)
+    img.save(output_path)
+    print(f"saved: {output_path}")
+
+
+if __name__ == "__main__":
+    draw_rabbit_blue_rect(IMAGE_PATH, OUTPUT_PATH)
+