添加计算滑块位置代码

utils/captcha.py

@@ -0,0 +1,46 @@
+import cv2
+import numpy as np
+import base64
+from io import BytesIO
+from PIL import Image
+
+def base64_to_cv2(base64_str: str):
+    """
+    将 base64 字符串解码为 OpenCV 图像
+    """
+    image_data = base64.b64decode(base64_str)
+    image = Image.open(BytesIO(image_data)).convert('RGB')
+    return cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+
+
+def get_slide_offset_from_base64(bg_base64: str, slider_base64: str, debug=False) -> int:
+    """
+    从 Base64 图像中计算滑动距离
+    """
+    # 解码 base64 为图像
+    bg_img = base64_to_cv2(bg_base64)
+    slider_img = base64_to_cv2(slider_base64)
+
+    # 转灰度图
+    bg_gray = cv2.cvtColor(bg_img, cv2.COLOR_BGR2GRAY)
+    slider_gray = cv2.cvtColor(slider_img, cv2.COLOR_BGR2GRAY)
+
+    # 边缘检测
+    bg_edge = cv2.Canny(bg_gray, 100, 200)
+    slider_edge = cv2.Canny(slider_gray, 100, 200)
+
+    # 模板匹配
+    result = cv2.matchTemplate(bg_edge, slider_edge, cv2.TM_CCOEFF_NORMED)
+    _, max_val, _, max_loc = cv2.minMaxLoc(result)
+
+    x, y = max_loc
+    if debug:
+        print(f"[DEBUG] 最大匹配值: {max_val:.4f} 位置: ({x}, {y})")
+        h, w = slider_gray.shape
+        vis = bg_img.copy()
+        cv2.rectangle(vis, (x, y), (x + w, y + h), (0, 255, 0), 2)
+        cv2.imshow("Match Result", vis)
+        cv2.waitKey(0)
+        cv2.destroyAllWindows()
+
+    return x