The File for training the image :

[pandeydinesh]

For training the image we need to download the file "haarcascade_frontalface_default" from Opencv website.

[pandeydinesh]

import cv2,os import numpy as np from PIL import Image

recognizer = cv2.face.LBPHFaceRecognizer_create() detector= cv2.CascadeClassifier("haarcascade_frontalface_default.xml");

def getImagesAndLabels(path):

get the path of all the files in the folder

imagePaths=[os.path.join(path,f) for f in os.listdir(path)] 
#create empth face list
faceSamples=[]
#create empty ID list
Ids=[]
#now looping through all the image paths and loading the Ids and the images
for imagePath in imagePaths:
    #loading the image and converting it to gray scale
    pilImage=Image.open(imagePath).convert('L')
    #Now we are converting the PIL image into numpy array
    imageNp=np.array(pilImage,'uint8')
    #getting the Id from the image
    Id=int(os.path.split(imagePath)[-1].split(".")[1])
    # extract the face from the training image sample
    faces=detector.detectMultiScale(imageNp)
    #If a face is there then append that in the list as well as Id of it
    for (x,y,w,h) in faces:
        faceSamples.append(imageNp[y:y+h,x:x+w])
        Ids.append(Id)
return faceSamples,Ids

faces,Ids = getImagesAndLabels('dataSet') recognizer.train(faces, np.array(Ids)) recognizer.save('trainner/trainner.yml')