概述：文本对旋转验证码进行了突破及讲述了实现原理，代码使用纯算法 OpenCV，使用代价较小同时不用安装一大堆AI训练相关的模组，方便且能够快速上手
当前亲自验证了能够支持的网站：国内知名短视频平台、海外版 以及 某东等等使用了旋转验证码的网站
基本上是旋转验证码的网站都能过，测试成功率在 99% 以上
实现步骤：
一、下载图片
为了兼容，在这里可以支持自己传base64，或者自己传链接来下载图片
def request_image_content(image_url, proxies: Optional[dict] = None):"""图片下载:param image_url: :param proxies: :return: """import requests # type: ignoreheaders = {"user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 ""(KHTML, like Gecko) Chrome/108.0.0.0 Safari/537.36"}response = requests.get(image_url, headers=headers, proxies=proxies)return response.contentdef image_to_cv2(base_image: str, image_type: int, grayscale: bool, proxies=None):"""根据 图片类型来读取图片数据:param base_image: :param image_type: :param grayscale: :param proxies: :return: """assert image_type in [0, 1, 2]if image_type == 0:search_base64 = re.search("base64,(.*?)$", base_image)base64_image = search_base64.group(1) if search_base64 else base_imageimage_array = np.asarray(bytearray(base64.b64decode(base64_image)), dtype="uint8")image = cv2.imdecode(image_array, cv2.IMREAD_COLOR)elif image_type == 1:image_content = request_image_content(base_image, proxies)if not image_content:raise Exception("请求图片链接失败！")image_array = np.array(bytearray(image_content), dtype=np.uint8)image = cv2.imdecode(image_array, cv2.IMREAD_COLOR)else:image = cv2.imread(base_image)if grayscale:image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)return image二、识别图像像素相似度
核心原理：使用opencv对两张图片进行合并，同时从0度开始，一点点旋转，选择像素相似度最高的一个度数
步骤1：将外圈图与内圈图的边缘像素进行匹配，获取相似度
mat_rotate = cv2.getRotationMatrix2D((h * 0.5, w * 0.5), rtype * angle, 1)dst = cv2.warpAffine(inner_image, mat_rotate, (h, w))ret = cv2.matchTemplate(outer_image, dst, cv2.TM_CCOEFF_NORMED)similar_value = cv2.minMaxLoc(ret)[1]步骤2：将相似度最高的一个结果进行返回并输出
step作为步长，设置1则1度1度的旋转，会更加精准
step = 1rotate_info_list = [RotateData(0, 0, 1, 361, step)]for item in rotate_info_list:min_similar_rotate_info = itemfor angle in range(*item[2:]):mat_rotate = cv2.getRotationMatrix2D((h * 0.5, w * 0.5), rtype * angle, 1)dst = cv2.warpAffine(inner_image, mat_rotate, (h, w))ret = cv2.matchTemplate(outer_image, dst, cv2.TM_CCOEFF_NORMED)similar_value = cv2.minMaxLoc(ret)[1]if similar_value < min_similar_rotate_info.similar:continuerotate_info = RotateData(similar_value, angle, angle - step, angle + step, step)rotate_info_list.append(rotate_info)if len(rotate_info_list) > 5:rotate_info_list.remove(min_similar_rotate_info)min_similar_rotate_info = min(rotate_info_list)三、效果展示：
输入图片：
输出图片：
核心的步骤及思路提供了，剩下的交给大家了，如果需要源码的话欢迎私聊
