Python OpenCV实时人脸检测裁剪保存

Question

我对此做了大量的研究，我认为我的逻辑已经过时了，几乎在那里，但似乎无法理解为什么在cv2.imshow()窗口中没有显示任何东西，只是一个灰色的盒子，然而好消息是我能够检测到一张脸并裁剪那张脸，然后将其保存在文件夹中。

你能告诉我哪里出错了吗?

#Author: Waheed Rafiq
#Research Student Birmingham City University
#Date: 03/11/2016
#Description :detect and Save capture face in a folder.
#Import library required for Capture face.
import cv2

#import the cascade for face detection
FaceClassifier =cv2.CascadeClassifier
('haarcascade_frontalface_default.xml')
# access the webcam (every webcam has 
capture = cv2.VideoCapture(0)
   while(True):
     # Capture frame-by-frame
    ret, frame = capture.read()
    if not capture:
    print "Error opening webcam device"
    sys.exit(1)

    # to detect faces in video
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = FaceClassifier.detectMultiScale(gray, 1.3, 5)
    # Resize Image 
    minisize = (frame.shape[1],frame.shape[0])
    miniframe = cv2.resize(frame, minisize)
    # Store detected frames in variable name faces
   faces =  FaceClassifier.detectMultiScale(miniframe)
   # Draw rectangle 
   for f in faces:
    x, y, w, h = [ v for v in f ]
    cv2.rectangle(frame, (x,y), (x+w,y+h), (255,255,255))
    #Save just the rectangle faces in SubRecFaces
    sub_face = frame[y:y+h, x:x+w]
    FaceFileName = "unknowfaces/face_" + str(y) + ".jpg"
    cv2.imwrite(FaceFileName, sub_face)
    #Display the image 
    cv2.imshow('Result',frame)

    break
    # When everything done, release the capture
    img.release()
    cv2.waitKey(20)
    cv2.destroyAllWindows()

非常感谢您的支持

Answer 1

我不得不修改我的代码，并再次重新思考逻辑:对于那些希望知道如何使用Opencv从网络摄像头或树莓派检测人脸，然后裁剪检测到的人脸的人来说，这是如何在python 2.7中使用Opencv 2.4.12完成的

# croppfacedetection.py
#Author: Waheed Rafiq
#Research Student Birmingham City University
#Date: 03/11/2016
#Description : Save capture face in a folder.
#Import library required for Capture face.
# Should you wish to use this code for 
#education purpose in your assignment or dissertation
# please use the correct citation and give credit where required. 

import cv2
size = 4
webcam = cv2.VideoCapture(0) #Use camera 0
# We load the xml file
classifier = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
#  Above line normalTest
#classifier = cv2.CascadeClassifier('haarcascade_frontalface_alt.xml') 
#Above line test with different calulation
#classifier = cv2.CascadeClassifier('haarcascade_frontalface_alt_tree.xml')
#classifier = cv2.CascadeClassifier('lbpcascade_frontalface.xml')

while True:
    (rval, im) = webcam.read()
    im=cv2.flip(im,1,0) #Flip to act as a mirror
    # Resize the image to speed up detection
    mini = cv2.resize(im, (im.shape[1] / size, im.shape[0] / size))
    # detect MultiScale / faces 
    faces = classifier.detectMultiScale(mini)
    # Draw rectangles around each face
    for f in faces:
        (x, y, w, h) = [v * size for v in f] #Scale the shapesize backup
        cv2.rectangle(im, (x, y), (x + w, y + h),(0,255,0),thickness=4)
        #Save just the rectangle faces in SubRecFaces
        sub_face = im[y:y+h, x:x+w]
        FaceFileName = "unknowfaces/face_" + str(y) + ".jpg"
        cv2.imwrite(FaceFileName, sub_face)
    # Show the image
    cv2.imshow('BCU Research by Waheed Rafiq (c)',   im)
    key = cv2.waitKey(10)
    # if Esc key is press then break out of the loop 
    if key == 27: #The Esc key
    break

请记住，您需要创建一个文件夹，并在该区域内需要一个名为unknownfaces的文件夹，从该文件夹的根目录运行脚本，它应该将检测到的任何faces保存到unknowfaces文件夹中。关于此代码的更多信息将很快在我的网站上提供
waheedrafiq.net

Answer 2

这是Python 3.6 OpenCV 4+的"工作"版本。你不需要参考任何人，自由地使用它。

import cv2
import os
classifier = cv2.CascadeClassifier(cv2.data.haarcascades+"haarcascade_frontalface_default.xml")
dirFace = 'cropped_face'
# Create if there is no cropped face directory
if not os.path.exists(dirFace):
    os.mkdir(dirFace)
    print("Directory " , dirFace ,  " Created ")
else:    
    print("Directory " , dirFace ,  " has found.")
webcam = cv2.VideoCapture(0) # Camera 0 according to USB port
# video = cv2.VideoCapture(r"use full windows path") # video path
while (True):
    (f, im) = webcam.read() # f returns only True, False according to video access
    # (f, im) = video.read() # video 
    if f != True:
       break
    # im=cv2.flip(im,1,0) #if you would like to give mirror effect
    # detectfaces 
    faces = classifier.detectMultiScale(
        im, # stream 
        scaleFactor=1.10, # change these parameters to improve your video processing performance
        minNeighbors=20, 
        minSize=(30, 30) # min image detection size
        ) 
    # Draw rectangles around each face
    for (x, y, w, h) in faces:
        cv2.rectangle(im, (x, y), (x + w, y + h),(0,0,255),thickness=2)
        # saving faces according to detected coordinates 
        sub_face = im[y:y+h, x:x+w]
        FaceFileName = "cropped_face/face_" + str(y+x) + ".jpg" # folder path and random name image
        cv2.imwrite(FaceFileName, sub_face)
    # Video Window
    cv2.imshow('Video Stream',im)
    key = cv2.waitKey(1) & 0xFF
    # q for exit
    if key == ord('q'): 
        break
webcam.release()

Answer 3

看起来您的代码没有到达cv2.waitKey(20)。您应该将它移到break语句之前。

在OpenCV中，cv2.waitKey完成图像显示任务。