python通过opencv调用摄像头操作实例分析

#pip3 install opencv-python
import cv2
from datetime import datetime
 
FILENAME = 'myvideo.avi'
WIDTH = 1280
HEIGHT = 720
FPS = 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600
cap.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 cv2
import 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:
      break
video_demo()
cv2.destroyAllWindows()
 
 
#2. 打开摄像头并截图
import cv2
cap = 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")