[人工智能]opencv+python实现调用摄像头进行拍照保存，并对图像进行置灰处理

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


def photo_save():
    capture = cv.VideoCapture(0, cv.CAP_DSHOW)
    while True:
        ret, frame = capture.read()              #ret=return,frame是视频的每一帧
        frame = cv.flip(frame, 1)                #镜像倒转    1是正像-1是反像
        if ret:
            cv.imshow("video", frame)  # 显示图像的每一帧
            if cv.waitKey(1) & 0xFF == ord('q'):
                cv.imwrite("D:/summer/test.png", frame)
                file_name = "xieyang.jpg"
                cv.imwrite(file_name, frame)
                break


def binary(image):                              #对图像进行二值化处理
    gray = cv.cvtColor(image, cv.COLOR_RGB2GRAY)
    ret, binary = cv.threshold(gray, 0, 255, cv.THRESH_BINARY_INV | cv.THRESH_OTSU)  # 进行图像二值化
    cv.imshow("binary", binary)


def image_hist(image):                     #展示图像的直方图和灰度图
    image = cv.imread("C:/Users/ZMZ/Desktop/aidu.jpg")
    gray = cv.cvtColor(image, cv.COLOR_RGB2GRAY)

    plt.subplots(311), plt.imshow(gray, "gray")  
    plt.title("input image"), plt.xticks([]), plt.yticks([])
    ret1, th1 = cv.threshold(gray, 0, 255, cv.THRESH_OTSU)
    plt.subplot(312), plt.hist(gray.ravel(), 256)
    plt.axvline(x=ret1, color='red', label='otsu')
    plt.legend(loc='upper right')
    plt.title('Histogram'), plt.xticks([]), plt.yticks([])
    plt.subplot(313),plt.imshow(th1, "gray")
    plt.title("output image"), plt.xticks([]), plt.yticks([])
    plt.show()


def dilate(image):                 #对图像进行膨胀化处理
    print(image.shape)
    gray = cv.cvtColor(image, cv.COLOR_RGB2GRAY)
    ret, binary = cv.threshold(gray, 0, 255, cv.THRESH_BINARY_INV | cv.THRESH_OTSU)     #进行图像二值化
    cv.imshow("binary", binary)
    kernel = cv.getStructuringElement(cv.MORPH_RECT, (3, 3))    #图像的结构元素
    dst = cv.dilate(binary, kernel)     #图像膨胀
    cv.imshow("erode_demo", dst)


photo_save()
src = cv.imread("D:/summer/test.png")
cv.namedWindow('input_image', cv.WINDOW_AUTOSIZE)
cv.imshow('input_image', src)
dilate(src)
cv.waitKey(0)
cv.destroyAllWindows()