毕业设计 python opencv实现车牌识别 矩形矫正

主要代码参考https://blog.csdn.net/wzh191920/article/details/79589506

GitHub：https://github.com/yinghualuowu

答辩通过了，补完~

用的是仿射变换

def img_Transform(car_contours,oldimg,pic_width,pic_hight):
    car_imgs = []
    for car_rect in car_contours:
        if car_rect[2] > -1 and car_rect[2] < 1:
            angle = 1
            # 对于角度为-1 1之间时，默认为1
        else:
            angle = car_rect[2]
        car_rect = (car_rect[0], (car_rect[1][0] + 5, car_rect[1][1] + 5), angle)
        box = cv2.boxPoints(car_rect)

        heigth_point = right_point = [0, 0]
        left_point = low_point = [pic_width, pic_hight]
        for point in box:
            if left_point[0] > point[0]:
                left_point = point
            if low_point[1] > point[1]:
                low_point = point
            if heigth_point[1] < point[1]:
                heigth_point = point
            if right_point[0] < point[0]:
                right_point = point

        if left_point[1] <= right_point[1]:  # 正角度
            new_right_point = [right_point[0], heigth_point[1]]
            pts2 = np.float32([left_point, heigth_point, new_right_point])  # 字符只是高度需要改变
            pts1 = np.float32([left_point, heigth_point, right_point])
            M = cv2.getAffineTransform(pts1, pts2)
            dst = cv2.warpAffine(oldimg, M, (pic_width, pic_hight))
            point_limit(new_right_point)
            point_limit(heigth_point)
            point_limit(left_point)
            car_img = dst[int(left_point[1]):int(heigth_point[1]), int(left_point[0]):int(new_right_point[0])]
            car_imgs.append(car_img)

        elif left_point[1] > right_point[1]:  # 负角度
            new_left_point = [left_point[0], heigth_point[1]]
            pts2 = np.float32([new_left_point, heigth_point, right_point])  # 字符只是高度需要改变
            pts1 = np.float32([left_point, heigth_point, right_point])
            M = cv2.getAffineTransform(pts1, pts2)
            dst = cv2.warpAffine(oldimg, M, (pic_width, pic_hight))
            point_limit(right_point)
            point_limit(heigth_point)
            point_limit(new_left_point)
            car_img = dst[int(right_point[1]):int(heigth_point[1]), int(new_left_point[0]):int(right_point[0])]
            car_imgs.append(car_img)

    return car_imgs