<2> 滑块验证码距离识别

import io
import cv2
import numpy as np
from PIL import Image


class DetectDistanceXY:

    def detectDistanceX(self, imgSlider, imgBackground):
        """X坐标缺口检测"""

        # imgSlider = cv2.cvtColor(np.array(Image.open(io.BytesIO(imgSlider))), cv2.COLOR_BGR2GRAY)
        # imgBackground = cv2.cvtColor(np.array(Image.open(io.BytesIO(imgBackground))), cv2.COLOR_BGR2GRAY)

        imgSliderGray = cv2.cvtColor(np.array(Image.open(imgSlider)), cv2.COLOR_BGR2GRAY)
        imgBackgroundGray = cv2.cvtColor(np.array(Image.open(imgBackground)), cv2.COLOR_BGR2GRAY)
        # 寻找最佳匹配
        res = cv2.matchTemplate(self._tran_canny(imgSliderGray), self._tran_canny(imgBackgroundGray), cv2.TM_CCOEFF_NORMED)
        # 最小值，最大值，并得到最小值, 最大值的索引
        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)

        return max_loc[0]

    def detectDistanceY(self, imgSlider, imgBackground):
　
        #  传入二进制图片
        # target_gray = cv2.cvtColor(np.array(Image.open(io.BytesIO(imgSlider))), cv2.COLOR_BGR2GRAY)
        # template_gray = cv2.cvtColor(np.array(Image.open(io.BytesIO(imgBackground))), cv2.COLOR_BGR2GRAY)
        # 根据路径读取图片
        imgSliderGray = cv2.cvtColor(np.array(Image.open(imgSlider)), cv2.COLOR_BGR2GRAY)
        imgBackgroundGray = cv2.cvtColor(np.array(Image.open(imgBackground)), cv2.COLOR_BGR2GRAY)
        res = cv2.matchTemplate(imgSliderGray, imgBackgroundGray, cv2.TM_CCOEFF_NORMED)
        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
        return max_loc[0]

    def _tran_canny(self, image):
        """消除噪声"""

        image = cv2.GaussianBlur(image, (3, 3), 0)
        return cv2.Canny(image, 100, 200)


if __name__ == '__main__':
    detectdistancexy = DetectDistanceXY()

    targetFile = r'target.png'
    templateFile = r'template.png'
    print(detectdistancexy.detectDistanceX(targetFile, templateFile))
    print(detectdistancexy.detectDistanceY(targetFile, templateFile))