import cv2
import numpy as np




def find_line(image):
    if image is None:
        print("Error: Unable to load image.")
        exit()
    gray_frame = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    blurred_image = cv2.GaussianBlur(gray_frame, (9, 9), 0)
    ret, gray_frame = cv2.threshold(blurred_image, 50, 255, cv2.THRESH_BINARY)
    cv2.imshow("binary", gray_frame)
    # edges = cv2.Canny(blurred_image, 50, 150, apertureSize=3)
    # 应用边缘检测
    edges = cv2.Canny(gray_frame, 200, 400, apertureSize=3)

    # 使用标准霍夫变换检测直线
    # 使用标准霍夫变换检测直线
    lines = cv2.HoughLines(edges, rho=3, theta=np.pi / 180, threshold=200)

    # 绘制检测到的直线
    if lines is not None:
        for line in lines:
            rho, theta = line[0]
            a = np.cos(theta)
            b = np.sin(theta)
            x0 = a * rho
            y0 = b * rho
            x1 = int(x0 + 1000 * (-b))
            y1 = int(y0 + 1000 * (a))
            x2 = int(x0 - 1000 * (-b))
            y2 = int(y0 - 1000 * (a))
            cv2.line(image, (x1, y1), (x2, y2), (0, 0, 255), 2)



if __name__ == '__main__':
    # 读取图像
    img = cv2.imread("images/trans/subRawImg.jpg")

    find_line(img)
    # 显示结果
    cv2.imshow("Detected Lines", img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()