图像倾斜校正（霍夫变换）

import matplotlib.pyplot as plt
import cv2
import numpy as np
import matplotlib.pyplot as plt

# 完成灰度化，二值化
def Image_Binarization(img_raw):
    img_gray = cv2.cvtColor(img_raw, cv2.COLOR_BGR2GRAY)  # 灰度化
    ret, img_process = cv2.threshold(img_gray, 127, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)  # 二值化
    return img_process


# 旋转函数
def rotate(img_rotate_raw, angle):
    (h, w) = img_rotate_raw.shape[:2]
    (cx, cy) = (w // 2, h // 2)
    m = cv2.getRotationMatrix2D((cx, cy), angle, 1.0)  # 计算二维旋转的仿射变换矩阵
    return cv2.warpAffine(img_rotate_raw, m, (w, h), borderValue=(0, 0, 0))


# 霍夫直线检测
def get_angle(img_hou_raw):
    sum_theta = 0
    img_canny = cv2.Canny(img_hou_raw, 50, 200, 3)
    lines = cv2.HoughLines(img_canny, 1, np.pi / 180, 300, 0, 0)
    # lines 是三维的
    for i in range(lines.shape[0]):
        theta = lines[i][0][1]
        sum_theta += theta
    average = sum_theta / lines.shape[0]
    angle = average / np.pi * 180 - 90
    return angle


def correct(img_cor_raw):
    img_process = Image_Binarization(img_cor_raw)
    angle = get_angle(img_process)
    if angle == -1:
        print("No lines!!!")
        return 0
    return rotate(img_cor_raw, angle)


if __name__ == "__main__":
    img = cv2.imread('Pic_2020_10_11_161606_blockId#1527.bmp')

    img_rot2 = correct(img)
    cv2.imshow('dst',img_rot2)
    cv2.waitKey()