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face_image_storer.py

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+import cv2 #pip install opencv-contrib-python
+cam = cv2.VideoCapture(0)
+detector=cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
+
+
+
+Id=input('enter your id')
+sampleNum=0
+while(True):
+    ret, img = cam.read()
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    faces = detector.detectMultiScale(gray, 1.3, 5)
+    for (x,y,w,h) in faces:
+        cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
+        
+        #saving the captured face in the dataset folder
+        cv2.imwrite("dataSet/User."+Id +'.'+ str(sampleNum) + ".jpg", gray[y:y+h,x:x+w])
+        sampleNum=sampleNum+1
+        cv2.imshow('frame',img)
+    # break if the sample number is morethan 20
+    if sampleNum>20:
+        break
+cam.release()
+cv2.destroyAllWindows()

face_trainer.py

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+import cv2
+import os
+import numpy as np
+from PIL import Image
+
+recognizer=cv2.face.LBPHFaceRecognizer_create()
+path='dataSet'
+def getImagesWithID(path):
+    imagePaths=[os.path.join(path,f) for f in os.listdir(path)]
+    faces=[]
+    IDs=[]
+
+    for imagepath in imagePaths:
+        faceImg=Image.open(imagepath).convert('L')
+        faceNp=np.array(faceImg,'uint8')
+        print(imagepath)
+        ID=int(os.path.split(imagepath)[-1].split(".")[1])
+        #dataset/User.1.3
+        faces.append(faceNp)
+        IDs.append(ID)
+        cv2.imshow("training",faceNp)
+        cv2.waitKey(10)
+    return np.array(IDs),faces
+
+Ids,faces=getImagesWithID(path)
+recognizer.train(faces,Ids)
+recognizer.save('trainingData.yml')
+cv2.destroyAllWindows()
+        
+