python3调用oepncv检测人脸

python3调用oepncv检测人脸，检测结果发送后台服务器，可使用多线程

 

# -*- coding: utf-8 -*-

import cv2

 

import time

import multiprocessing as mp

import numpy as np

import os

import requests

 

respNum = 1

# showVideo = True

showVideo = False

camera_ips = [

"saveImg",

"xxx",

]

 

path = './opencvImg'

 

# 获取画面

def image_put(q, ip):

    cap = cv2.VideoCapture(ip)

    while True:

        q.put(cap.read()[1])

        q.get() if q.qsize() > 1 else time.sleep(0.01)

 

# 检测并显示画面

def image_get(q, window_name,lock,outImgList,showVideo):

    FONT = cv2.FONT_HERSHEY_PLAIN

    frame_id = 0

    time_start = time.time()

 

    frame_jum = 5

    frame_now = 0

    #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 = (0, 255, 0)

    while True:

        frame = q.get()

        frame_now+=1

        if(frame_now>=frame_jum):

            frame_now = 0

        else:

            continue

        frame_id += frame_jum

 

        #将当前帧转换成灰度图像

        grey = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)                 

        

        #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

                names = str(time.time()).replace('.','')+'.jpg'

                path_img = os.path.join(path, names)

                outImg = frame[y:y+h,x:x+w]

                if(outImg is None):

                    continue

                cv2.imwrite(path_img,outImg)

                print('imwrite')        

                lock.acquire()

                outImgList.append(path_img)

                lock.release()

        if showVideo:

            cv2.namedWindow(window_name, flags=cv2.WINDOW_FREERATIO)

            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        

                    cv2.rectangle(frame, (x - 10, y - 10), (x + w + 10, y + h + 10), color, 2)

                    

            elapsed_time = time.time() - time_start

            fps = frame_id/elapsed_time

            cv2.putText(frame, "FPS: " + str(round(fps, 2)), (8, 30), FONT, 2, (0, 0, 0), 2)

            cv2.imshow(window_name, frame)

        cv2.waitKey(10)

 

# 保存检测出的人物

def saveImg(q,lock,outImgList,http):

    while True:

        lock.acquire()

        if outImgList:

            try:

                path_img=outImgList.pop()

                lock.release()

                imgs = open(path_img, 'rb')

                files = {'img': ('img.jpg', imgs)}

                r = requests.post(http, files=files)

                imgs.close()

                os.remove(path_img)

            except EOFError:

                print(EOFError)

                continue

        else:

            lock.release()

        time.sleep(0.5)

 

def run_multi_camera():

    h=''

    video=''

    with open("http.txt","r",encoding='utf-8') as f:

        h=f.readline()

    with open("video.txt","r",encoding='utf-8') as f:

        video=f.readline()

    camera_ip_l = camera_ips[0:respNum+1]

    mp.set_start_method(method='spawn')  # init

    queues = [mp.Queue(maxsize=4) for _ in camera_ip_l]

 

    processes = []

    lock = mp.Lock()

    outImgList=mp.Manager().list()

    for queue, camera_ip in zip(queues, camera_ip_l):

        if camera_ip=='saveImg':

            processes.append(mp.Process(target=saveImg, args=(queue,lock,outImgList,h)))

        else:

            processes.append(mp.Process(target=image_put, args=(queue, video)))

            processes.append(mp.Process(target=image_get, args=(queue, video,lock,outImgList,showVideo)))

 

    for process in processes:

        process.daemon = True

        process.start()

    for process in processes:

        process.join()

 

if __name__ == '__main__':

    # mp.freeze_support()

    run_multi_camera()