易盾增强版滑块识别/易盾识别/滑块识别/增强版滑块识别/易盾滑块本地识别

易盾增强版滑块识别

计算思路如下：

1. 滑动条拖动距离传入 restrict 算法处理得到 初次值 J

2. J * 率值0.309375 得到滑块偏移量。

3. 滑块的旋转角度=滑块偏移量*attrs

4. 所以滑块偏移量=滑块的旋转角度/attrs

5. 通过滑块偏移量 求出 滑动条拖动距离

 # 应用高斯模糊
        warped_image1 = cv2.GaussianBlur(warped_image1, ksize, sigmaX)
        warped_image2 = cv2.GaussianBlur(warped_image2, ksize, sigmaX)

        warped_image1 = cv2.adaptiveThreshold(warped_image1, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 11, 2)
        warped_image2 = cv2.adaptiveThreshold(warped_image2, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 11, 2)

        result = cv2.matchTemplate(warped_image2, warped_image1, cv2.TM_CCORR_NORMED)

        # 找到最佳匹配位置
        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)

        # max_val 是匹配差异，差异越小，俩个相似度越多
        similarity = max_val

        # 打印相似度
        # print(f"差异度: {similarity}")
        if similarity < mindif:
            mindif = similarity
            minpianyi = x_offset
        allpianyi[x_offset] = similarity