python通過opencv調(diào)用攝像頭操作實例分析

#pip3 install opencv-python
import cv2
from datetime import datetime
 
FILENAME = 'myvideo.avi'
WIDTH = 1280
HEIGHT = 720
FPS = 24.0
 
# 必須指定CAP_DSHOW(Direct Show)參數(shù)初始化攝像頭,否則無法使用更高分辨率
cap = cv2.VideoCapture(0, cv2.CAP_DSHOW)
# 設(shè)置攝像頭設(shè)備分辨率
cap.set(cv2.CAP_PROP_FRAME_WIDTH, WIDTH)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, HEIGHT)
# 設(shè)置攝像頭設(shè)備幀率,如不指定,默認(rèn)600
cap.set(cv2.CAP_PROP_FPS, 24)
# 建議使用XVID編碼,圖像質(zhì)量和文件大小比較都兼顧的方案
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)
        # 顯示預(yù)覽窗口
        cv2.imshow('Preview_Window', frame)
        # 錄制5秒后停止
        if (datetime.now()-start_time).seconds == 5:
            cap.release()
            break
        # 監(jiān)測到ESC按鍵也停止
        if cv2.waitKey(3)  0xff == 27:
            cap.release()
            break
 
out.release()
cv2.destroyAllWindows()

# 1. 打開攝像頭
import cv2
import numpy as np
  
def video_demo():
  capture = cv2.VideoCapture(0)#0為電腦內(nèi)置攝像頭
  while(True):
    ret, frame = capture.read()#攝像頭讀取,ret為是否成功打開攝像頭,true,false。 frame為視頻的每一幀圖像
    frame = cv2.flip(frame, 1)#攝像頭是和人對立的，將圖像左右調(diào)換回來正常顯示。
    cv2.imshow("video", frame)
    c = cv2.waitKey(50)
    if c == 27:
      break
video_demo()
cv2.destroyAllWindows()
 
 
#2. 打開攝像頭并截圖
import cv2
cap = cv2.VideoCapture(0, cv2.CAP_DSHOW) # 打開攝像頭
  
while (1):
  # get a frame
  ret, frame = cap.read()
  frame = cv2.flip(frame, 1) # 攝像頭是和人對立的，將圖像左右調(diào)換回來正常顯示
  # show a frame
  cv2.imshow("capture", frame) # 生成攝像頭窗口
  
  if cv2.waitKey(1)  0xFF == ord('q'): # 如果按下q 就截圖保存并退出
    cv2.imwrite("test.png", frame) # 保存路徑
    break
  
cap.release()
cv2.destroyAllWindows()
 
 
#3. 打開攝像頭并定時截圖
def video_demo():
  print('開始')
  cap = cv2.VideoCapture(0, cv2.CAP_DSHOW) # 電腦自身攝像頭
  i = 0#定時裝置初始值
  photoname = 1#文件名序號初始值
  
  while True:
    i = i + 1
    reg, frame = cap.read()
    frame = cv2.flip(frame, 1) # 圖片左右調(diào)換
    cv2.imshow('window', frame)
  
    if i == 50: # 定時裝置，定時截屏，可以修改。
  
      filename = str(photoname) + '.png' # filename為圖像名字，將photoname作為編號命名保存的截圖
      cv2.imwrite('C:/Users/Administrator/Desktop/m' + '\\' + filename, frame) # 截圖 前面為放在桌面的路徑 frame為此時的圖像
      print(filename + '保存成功') # 打印保存成功
      i = 0 # 清零
  
      photoname = photoname + 1
      if photoname >= 20: # 最多截圖20張 然后退出（如果調(diào)用photoname = 1 不用break為不斷覆蓋圖片）
        # photoname = 1
        break
    if cv2.waitKey(1)  0xff == ord('q'):
      break
  # 釋放資源
  cap.release()
  
video_demo()
cv2.destroyAllWindows()

#-*- coding: utf-8 -*-
# import 進openCV的庫
import cv2

###調(diào)用電腦攝像頭檢測人臉并截圖

def CatchPICFromVideo(window_name, camera_idx, catch_pic_num, path_name):
 cv2.namedWindow(window_name)

 #視頻來源，可以來自一段已存好的視頻，也可以直接來自USB攝像頭
 cap = cv2.VideoCapture(camera_idx)

 #告訴OpenCV使用人臉識別分類器
 classfier = cv2.CascadeClassifier("haarcascade_frontalface_alt.xml")

 #識別出人臉后要畫的邊框的顏色，RGB格式, color是一個不可增刪的數(shù)組
 color = (0, 255, 0)

 num = 0
 while cap.isOpened():
 ok, frame = cap.read() #讀取一幀數(shù)據(jù)
 if not ok:
  break

 grey = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) #將當(dāng)前楨圖像轉(zhuǎn)換成灰度圖像

 #人臉檢測，1.2和2分別為圖片縮放比例和需要檢測的有效點數(shù)
 faceRects = classfier.detectMultiScale(grey, scaleFactor = 1.2, minNeighbors = 3, minSize = (32, 32))
 if len(faceRects) > 0:  #大于0則檢測到人臉
  for faceRect in faceRects: #單獨框出每一張人臉
  x, y, w, h = faceRect

  #將當(dāng)前幀保存為圖片
  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): #如果超過指定最大保存數(shù)量退出循環(huán)
   break

  #畫出矩形框
  cv2.rectangle(frame, (x - 10, y - 10), (x + w + 10, y + h + 10), color, 2)

  #顯示當(dāng)前捕捉到了多少人臉圖片了，這樣站在那里被拍攝時心里有個數(shù)，不用兩眼一抹黑傻等著
  font = cv2.FONT_HERSHEY_SIMPLEX
  cv2.putText(frame,'num:%d/100' % (num),(x + 30, y + 30), font, 1, (255,0,255),4)

  #超過指定最大保存數(shù)量結(jié)束程序
 if num > (catch_pic_num): break

 #顯示圖像
 cv2.imshow(window_name, frame)
 c = cv2.waitKey(10)
 if c  0xFF == ord('q'):
  break

  #釋放攝像頭并銷毀所有窗口
 cap.release()
 cv2.destroyAllWindows()

if __name__ == '__main__':
 # 連續(xù)截100張圖像，存進image文件夾中
 CatchPICFromVideo("get face", 0, 99, "/image")