使用OpenCV调用摄像头检测人脸并截图-Python

桃扇骨 2022-05-29 05:45 353阅读 0赞

**注意：需要在python中安装OpenCV库，同时需要下载OpenCV人脸识别模型haarcascade\_frontalface\_alt.xml，模型可在[https://github.com/TimeIvyace/OpenCV-PCA-KNN-SVM\_face\_recognition.git][https_github.com_TimeIvyace_OpenCV-PCA-KNN-SVM_face_recognition.git]中下载。**

#### **使用OpenCV调用摄像头检测人脸并连续截图100张** ####

#-*- 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")

[https_github.com_TimeIvyace_OpenCV-PCA-KNN-SVM_face_recognition.git]: https://github.com/TimeIvyace/OpenCV-PCA-KNN-SVM_face_recognition.git