OpenCV python 点与轮廓的距离

处理图片:[cs1.jpg]

import cv2


def point_contour_dist(img, hull, point, text, measure_dist=True):
    """点与轮廓hull的距离

    :param img: 绘制结果图片
    :param hull: 轮廓hull
    :param point: 计算的点
    :param text: 文本距离
    :param measure_dist: 计算结果方式
    :return: 距离
    """

    dist = cv2.pointPolygonTest(hull, point, measure_dist)

    font = cv2.FONT_HERSHEY_SIMPLEX
    cv2.putText(img, text, point, font, 1, (0, 255, 0), 3)
    print("dist%s=" % text, dist)

    return dist


def main():

    # 1.导入图片
    img_src = cv2.imread("cs1.jpg")

    # 2.灰度化,二值化
    img_gray = cv2.cvtColor(img_src, cv2.COLOR_BGR2GRAY)
    ret, img_bin = cv2.threshold(img_gray, 127, 255, cv2.THRESH_BINARY)

    # 3.连通域分析
    img_bin, contours, hierarchy = cv2.findContours(img_bin,
                                                    cv2.RETR_LIST,
                                                    cv2.CHAIN_APPROX_SIMPLE)

    # 4.计算hull并且显示
    hull = cv2.convexHull(contours[0])
    img_result = cv2.cvtColor(img_bin, cv2.COLOR_GRAY2BGR)
    cv2.polylines(img_result, [hull], True, (0, 255, 0), 2)

    # 5.计算点与轮廓hull之间的距离
    point_contour_dist(img_result, hull, (300, 150), "A")
    point_contour_dist(img_result, hull, (300, 250), "B")
    point_contour_dist(img_result, hull, (464, 122), "C")

    # 6.显示结果图片
    cv2.imshow("img_src", img_src)
    cv2.imshow("img_result", img_result)
    cv2.imwrite("img_result.jpg", img_result)

    cv2.waitKey()
    cv2.destroyAllWindows()


if __name__ == '__main__':
    main()

处理结果图片:[img_result.jpg]

处理结果:

来源：CSDN

作者：廷益--飞鸟

链接：https://blog.csdn.net/weixin_45875105/article/details/103934244