'commit'

Apps/YeLiTe/Kit.py

@@ -98,6 +98,96 @@ def save_image(path, img):
         logger.error(f"Error saving image {path}: {e}")
         return False
 
+def detect_cards_cv(image_path, top_ratio=0.15, bottom_ratio=0.1):
+    """
+    使用计算机图形学 (OpenCV) 检测列表中的场站卡片
+    方案：以 nav.jpg 为锚点，向上/下探测白色卡片边界
+    """
+    img = read_image(image_path)
+    if img is None:
+        return []
+        
+    h, w = img.shape[:2]
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    
+    # 1. 模板匹配查找锚点 (nav.jpg)
+    template_path = os.path.join(os.path.dirname(__file__), "Template", "nav.jpg")
+    anchors = []
+    if os.path.exists(template_path):
+        template = read_image(template_path)
+        if template is not None:
+            res = cv2.matchTemplate(img, template, cv2.TM_CCOEFF_NORMED)
+            threshold = 0.8
+            loc = np.where(res >= threshold)
+            
+            # 去重记录锚点中心
+            t_h, t_w = template.shape[:2]
+            matched_points = []
+            for pt in zip(*loc[::-1]): # (x, y)
+                is_duplicate = False
+                for mx, my in matched_points:
+                    if abs(mx - pt[0]) < 50 and abs(my - pt[1]) < 50:
+                        is_duplicate = True
+                        break
+                if not is_duplicate:
+                    matched_points.append(pt)
+                    anchors.append((pt[0] + t_w // 2, pt[1] + t_h // 2))
+                    
+    logger.info(f"通过模板匹配找到 {len(anchors)} 个锚点")
+
+    # 2. 基于锚点向上/下扩张探测边界
+    # 计算每一行的平均亮度，用于探测背景
+    row_means = np.mean(gray[:, int(w*0.2):int(w*0.8)], axis=1)
+    
+    cards = []
+    for ax, ay in anchors:
+        # 向上探测：直到亮度低于 245 (进入灰色背景)
+        y1 = ay
+        while y1 > h * top_ratio:
+            if row_means[int(y1)] < 245:
+                break
+            y1 -= 1
+        
+        # 向下探测：直到亮度低于 245
+        y2 = ay
+        while y2 < h * (1 - bottom_ratio):
+            if row_means[int(y2)] < 245:
+                break
+            y2 += 1
+            
+        # 验证卡片高度是否合理
+        if y2 - y1 > 150:
+            # 给 y 坐标增加一点 padding
+            cards.append([int(w * 0.05), int(y1 + 5), int(w * 0.95), int(y2 - 5)])
+
+    # 3. 兜底方案：如果模板匹配没找到，使用之前的投影法
+    if not cards:
+        logger.warning("模板匹配未找到卡片，尝试投影法兜底...")
+        _, binary = cv2.threshold(gray, 250, 255, cv2.THRESH_BINARY)
+        top = int(h * top_ratio)
+        bottom = int(h * (1 - bottom_ratio))
+        roi_binary = binary[:, int(w*0.2):int(w*0.8)]
+        row_white_counts = np.sum(roi_binary == 255, axis=1)
+        threshold_count = (int(w*0.8) - int(w*0.2)) * 0.9
+        is_card_row = row_white_counts > threshold_count
+        
+        start_y = None
+        for y in range(top, bottom):
+            if is_card_row[y]:
+                if start_y is None: start_y = y
+            else:
+                if start_y is not None:
+                    if y - start_y > 150:
+                        cards.append([int(w * 0.05), start_y + 10, int(w * 0.95), y - 10])
+                    start_y = None
+        if start_y is not None and bottom - start_y > 150:
+            cards.append([int(w * 0.05), start_y + 10, int(w * 0.95), bottom - 10])
+
+    # 4. 排序
+    cards.sort(key=lambda c: c[1])
+    logger.info(f"最终检测到 {len(cards)} 个场站卡片区域")
+    return cards
+
 def clear_temp_dir(save_dir=None):
     """清空临时目录中的所有文件"""
     if save_dir is None:
@@ -141,7 +231,7 @@ def draw_rectangles(image_path, points, output_path=None):
         if not DRAW_DEBUG_BOXES:
             return image_path
             
-        img = cv2.imread(image_path)
+        img = read_image(image_path)
         if img is None:
             return image_path
             
@@ -153,7 +243,7 @@ def draw_rectangles(image_path, points, output_path=None):
                 cv2.circle(img, center, 10, DEBUG_BOX_COLOR, -1)
                 
         save_path = output_path if output_path else image_path
-        cv2.imwrite(save_path, img)
+        save_image(save_path, img)
         return save_path
     except Exception as e:
         logger.error(f"绘制矩形框失败: {e}")