'commit'

Apps/TeLaiDian/Config/Setting.py

@@ -15,5 +15,6 @@ WAIT_BACK_TO_LIST = 1.0
 WAIT_AFTER_SCROLL = 2.5
 
 # 坐标计算与安全防护
-SAFE_EXCLUDE_RATIO = 0.15
-BOTTOM_SAFE_EXCLUDE_RATIO = 0.10
+SAFE_EXCLUDE_RATIO = 0.35  # 调整顶部排除比例，避开搜索、活动 Banner、快捷入口和广告位
+BOTTOM_SAFE_EXCLUDE_RATIO = 0.12 # 略微增加底部排除比例，避开底部导航栏
+MIN_CARD_HEIGHT = 150 # 场站卡片最小高度，防止识别不完整的卡片

Apps/TeLaiDian/Kit.py

@@ -93,56 +93,72 @@ 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):
+def detect_cards_cv(image_path, top_ratio=0.40, bottom_ratio=0.12):
     """
-    使用计算机图形学 (OpenCV) 检测列表中的场站卡片
+    使用计算机图形学 (OpenCV) 检测列表中的场站卡片。
     """
+    from Apps.TeLaiDian.Config.Setting import MIN_CARD_HEIGHT
+    
     img = read_image(image_path)
     if img is None:
         return []
         
     h, w = img.shape[:2]
     
+    # 转换为灰度图
     gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-    blurred = cv2.GaussianBlur(gray, (5, 5), 0)
-    edges = cv2.Canny(blurred, 10, 50)
     
-    contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-    
-    cards = []
-    min_card_width = int(w * 0.8) 
-    min_card_height = 150         
+    # 限制检测范围
     top_limit = int(h * top_ratio)
     bottom_limit = int(h * (1 - bottom_ratio))
     
-    valid_contours = []
+    # 使用自适应阈值
+    thresh = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV, 11, 2)
     
+    # 闭运算：连接断开的边缘
+    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (w // 2, 1))
+    closed = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)
+    
+    # 寻找轮廓
+    contours, _ = cv2.findContours(closed, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    
+    cards = []
+    min_card_width = int(w * 0.7)
+    
+    temp_boxes = []
     for cnt in contours:
         x, y, cw, ch = cv2.boundingRect(cnt)
+        
+        # 增加最小高度验证 MIN_CARD_HEIGHT
         if (cw > min_card_width and 
-            ch > min_card_height and 
+            ch > MIN_CARD_HEIGHT and
             y > top_limit and 
             y + ch < bottom_limit):
             
-            center_y = y + ch // 2
-            is_duplicate = False
-            for vx, vy, vcw, vch in valid_contours:
-                v_center_y = vy + vch // 2
-                if abs(center_y - v_center_y) < 50:
-                    is_duplicate = True
-                    break
+            temp_boxes.append((x, y, cw, ch))
             
-            if not is_duplicate:
-                valid_contours.append((x, y, cw, ch))
-                padding = 5
-                cards.append([
-                    max(0, x + padding), 
-                    max(0, y + padding), 
-                    max(0, x + cw - padding), 
-                    max(0, y + ch - padding)
-                ])
+    # 按 Y 轴排序
+    temp_boxes.sort(key=lambda b: b[1])
     
-    cards.sort(key=lambda c: c[1])
+    # 再次过滤和去重
+    for i, box in enumerate(temp_boxes):
+        x, y, cw, ch = box
+        
+        # 检查是否与已有的框重叠
+        is_duplicate = False
+        for v in cards:
+            if abs(y - v[1]) < 100: # 增加去重间距
+                is_duplicate = True
+                break
+        if not is_duplicate:
+            padding = 2
+            cards.append([
+                max(0, x + padding), 
+                max(top_limit, y + padding), 
+                min(w, x + cw - padding), 
+                min(bottom_limit, y + ch - padding)
+            ])
+            
     return cards
 
 def draw_rectangles(image_path, points, output_path=None):

Apps/TeLaiDian/TestCV.py

@@ -0,0 +1,63 @@
+# coding=utf-8
+import os
+import sys
+import cv2
+import numpy as np
+
+# 确保项目根目录在 sys.path 中
+project_root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+if project_root not in sys.path:
+    sys.path.append(project_root)
+
+from Apps.TeLaiDian import Kit
+from Apps.TeLaiDian.Config.Setting import SAFE_EXCLUDE_RATIO, BOTTOM_SAFE_EXCLUDE_RATIO
+
+def test_cv_detection(image_path):
+    print(f"开始测试 CV 检测: {image_path}")
+    
+    if not os.path.exists(image_path):
+        print(f"错误: 文件不存在 {image_path}")
+        return
+
+    img = Kit.read_image(image_path)
+    h, w = img.shape[:2]
+    print(f"图片尺寸: {w}x{h}")
+    print(f"当前过滤阈值: top_limit={int(h*SAFE_EXCLUDE_RATIO)}, bottom_limit={int(h*(1-BOTTOM_SAFE_EXCLUDE_RATIO))}")
+
+    # 1. 检测卡片
+    bboxes = Kit.detect_cards_cv(image_path, top_ratio=SAFE_EXCLUDE_RATIO, bottom_ratio=BOTTOM_SAFE_EXCLUDE_RATIO)
+    print(f"检测到 {len(bboxes)} 个卡片区域")
+    for i, box in enumerate(bboxes):
+        print(f"  卡片 {i+1}: {box}")
+
+    # 2. 生成 _vl.jpg (仅绿框)
+    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)
+    Kit.save_image(vl_path, img_vl)
+    print(f"已生成 VLM 标注图: {vl_path}")
+
+    # 3. 生成 _flag.jpg (绿框 + 点击点)
+    flag_path = image_path.replace(".jpg", "_flag.jpg")
+    img_flag = img_vl.copy()
+    for box in bboxes:
+        # 计算点击点：卡片中心
+        center_x = (box[0] + box[2]) // 2
+        center_y = (box[1] + box[3]) // 2
+        
+        # 绘制红色点击点 (实心圆 + 十字)
+        cv2.circle(img_flag, (center_x, center_y), 15, (0, 0, 255), -1)
+        cv2.line(img_flag, (center_x - 30, center_y), (center_x + 30, center_y), (255, 255, 255), 3)
+        cv2.line(img_flag, (center_x, center_y - 30), (center_x, center_y + 30), (255, 255, 255), 3)
+        
+        # 标注序号
+        idx = bboxes.index(box) + 1
+        cv2.putText(img_flag, str(idx), (box[0] + 10, box[1] + 40), cv2.FONT_HERSHEY_SIMPLEX, 1.5, (0, 0, 255), 3)
+
+    Kit.save_image(flag_path, img_flag)
+    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"
+    test_cv_detection(target_image)

Python运行环境.txt

@@ -1 +0,0 @@
-D:\anaconda3\envs\py310\python.exe