Python OpenCV对图像进行模糊处理详解流程

# -*-coding:utf-8-*-
"""
File Name: image_deeplearning.py
Program IDE: PyCharm
Date: 2021/10/17
Create File By Author: Hong
"""
import cv2 as cv


def image_blur(image_path: str):
    """
    图像卷积操作：设置卷积核大小，步距
    :param image_path:
    :return:
    """
    img = cv.imread(image_path, cv.IMREAD_COLOR)
    cv.imshow('input', img)
    # 模糊操作（类似卷积），第二个参数ksize是设置模糊内核大小
    result = cv.blur(img, (5, 5))
    cv.imshow('result', result)

    cv.waiTKEy(0)
    cv.destroyAllwindows()


if __name__ == '__main__':
    path = 'images/2.png'
    image_blur(path)

def image_conv(image_path: str):
    """
    高斯模糊
    :param image_path:
    :return:
    """
    img = cv.imread(image_path, cv.IMREAD_COLOR)
    cv.imshow('img', img)
    # 高斯卷积（高斯滤波）， 可以设置ksize，必须为奇数，不为0时，后面的步骤不起作用；也可以设置成（0，0），然后通过sigmaX和sigmaY计算标准偏差
    result = cv.GaussianBlur(img, (0, 0), 15)
    cv.imshow('result', result)

    cv.waitKey(0)
    cv.destroyAllWindows()


if __name__ == '__main__':
    path = 'images/2.png'
    image_conv(path)

# 边缘保留滤波器——高斯双边模糊
def image_bifilter(image_path: str):
    """
    高斯双边模糊
    :param image_path: 图片文件
    :return: 无返回值
    """
    img = cv.imread(image_path, cv.IMREAD_COLOR)
    cv.imshow('input', img)
    # 第三个参数是设置色彩、第四个参数是设置图像坐标
    result = cv.bilateralFilter(img, 0, 50, 10)
    cv.imshow('result', result)

    cv.waitKey(0)
    cv.destroyAllWindows()


if __name__ == '__main__':
    path = 'images/2.png'
    image_bifilter(path)