自学教程：python通过opencv调用摄像头操作实例分析

#pip3 install opencv-pythonimport cv2from datetime import datetime FILENAME = 'myvideo.avi'WIDTH = 1280HEIGHT = 720FPS = 24.0 # 必须指定CAP_DSHOW(Direct Show)参数初始化摄像头,否则无法使用更高分辨率cap = cv2.VideoCapture(0, cv2.CAP_DSHOW)# 设置摄像头设备分辨率cap.set(cv2.CAP_PROP_FRAME_WIDTH, WIDTH)cap.set(cv2.CAP_PROP_FRAME_HEIGHT, HEIGHT)# 设置摄像头设备帧率,如不指定,默认600cap.set(cv2.CAP_PROP_FPS, 24)# 建议使用XVID编码,图像质量和文件大小比较都兼顾的方案fourcc = cv2.VideoWriter_fourcc(*'XVID') out = cv2.VideoWriter(FILENAME, fourcc, FPS, (WIDTH, HEIGHT)) start_time = datetime.now() while True:    ret, frame = cap.read()    if ret:        out.write(frame)        # 显示预览窗口        cv2.imshow('Preview_Window', frame)        # 录制5秒后停止        if (datetime.now()-start_time).seconds == 5:            cap.release()            break        # 监测到ESC按键也停止        if cv2.waitKey(3) & 0xff == 27:            cap.release()            break out.release()cv2.destroyAllWindows()

# 1. 打开摄像头import cv2import numpy as np  def video_demo():  capture = cv2.VideoCapture(0)#0为电脑内置摄像头  while(True):    ret, frame = capture.read()#摄像头读取,ret为是否成功打开摄像头,true,false。 frame为视频的每一帧图像    frame = cv2.flip(frame, 1)#摄像头是和人对立的，将图像左右调换回来正常显示。    cv2.imshow("video", frame)    c = cv2.waitKey(50)    if c == 27:      breakvideo_demo()cv2.destroyAllWindows()  #2. 打开摄像头并截图import cv2cap = cv2.VideoCapture(0, cv2.CAP_DSHOW) # 打开摄像头  while (1):  # get a frame  ret, frame = cap.read()  frame = cv2.flip(frame, 1) # 摄像头是和人对立的，将图像左右调换回来正常显示  # show a frame  cv2.imshow("capture", frame) # 生成摄像头窗口    if cv2.waitKey(1) & 0xFF == ord('q'): # 如果按下q 就截图保存并退出    cv2.imwrite("test.png", frame) # 保存路径    break  cap.release()cv2.destroyAllWindows()  #3. 打开摄像头并定时截图def video_demo():  print('开始')  cap = cv2.VideoCapture(0, cv2.CAP_DSHOW) # 电脑自身摄像头  i = 0#定时装置初始值  photoname = 1#文件名序号初始值    while True:    i = i + 1    reg, frame = cap.read()    frame = cv2.flip(frame, 1) # 图片左右调换    cv2.imshow('window', frame)      if i == 50: # 定时装置，定时截屏，可以修改。        filename = str(photoname) + '.png' # filename为图像名字，将photoname作为编号命名保存的截图      cv2.imwrite('C:/Users/Administrator/Desktop/m' + '//' + filename, frame) # 截图 前面为放在桌面的路径 frame为此时的图像      print(filename + '保存成功') # 打印保存成功      i = 0 # 清零        photoname = photoname + 1      if photoname >= 20: # 最多截图20张 然后退出（如果调用photoname = 1 不用break为不断覆盖图片）        # photoname = 1        break    if cv2.waitKey(1) & 0xff == ord('q'):      break  # 释放资源  cap.release()  video_demo()cv2.destroyAllWindows()

#-*- coding: utf-8 -*-# import 进openCV的库import cv2###调用电脑摄像头检测人脸并截图def CatchPICFromVideo(window_name, camera_idx, catch_pic_num, path_name): cv2.namedWindow(window_name) #视频来源，可以来自一段已存好的视频，也可以直接来自USB摄像头 cap = cv2.VideoCapture(camera_idx) #告诉OpenCV使用人脸识别分类器 classfier = cv2.CascadeClassifier("haarcascade_frontalface_alt.xml") #识别出人脸后要画的边框的颜色，RGB格式, color是一个不可增删的数组 color = (0, 255, 0) num = 0 while cap.isOpened(): ok, frame = cap.read() #读取一帧数据 if not ok:  break grey = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) #将当前桢图像转换成灰度图像 #人脸检测，1.2和2分别为图片缩放比例和需要检测的有效点数 faceRects = classfier.detectMultiScale(grey, scaleFactor = 1.2, minNeighbors = 3, minSize = (32, 32)) if len(faceRects) > 0:  #大于0则检测到人脸  for faceRect in faceRects: #单独框出每一张人脸  x, y, w, h = faceRect  #将当前帧保存为图片  img_name = "%s/%d.jpg" % (path_name, num)  #print(img_name)  image = frame[y - 10: y + h + 10, x - 10: x + w + 10]  cv2.imwrite(img_name, image,[int(cv2.IMWRITE_PNG_COMPRESSION), 9])  num += 1  if num > (catch_pic_num): #如果超过指定最大保存数量退出循环   break  #画出矩形框  cv2.rectangle(frame, (x - 10, y - 10), (x + w + 10, y + h + 10), color, 2)  #显示当前捕捉到了多少人脸图片了，这样站在那里被拍摄时心里有个数，不用两眼一抹黑傻等着  font = cv2.FONT_HERSHEY_SIMPLEX  cv2.putText(frame,'num:%d/100' % (num),(x + 30, y + 30), font, 1, (255,0,255),4)  #超过指定最大保存数量结束程序 if num > (catch_pic_num): break #显示图像 cv2.imshow(window_name, frame) c = cv2.waitKey(10) if c & 0xFF == ord('q'):  break  #释放摄像头并销毁所有窗口 cap.release() cv2.destroyAllWindows()if __name__ == '__main__': # 连续截100张图像，存进image文件夹中 CatchPICFromVideo("get face", 0, 99, "/image")