import cv2
 
detector = cv2.CascadeClassifier('haarcascade_frontalface_alt.xml')
cap = cv2.VideoCapture(0)
sampleNum = 0
Id = input('enter your id: ')
 
while True:
 ret, img = cap.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)
 
 # incrementing sample number
 sampleNum = sampleNum + 1
 # saving the captured face in the dataset folder
 cv2.imwrite("dataSet/User." + str(Id) + '.' + str(sampleNum) + ".jpg", gray[y:y + h, x:x + w]) #
 
 cv2.imshow('frame', img)
 # wait for 100 miliseconds
 if cv2.waitKey(100) & 0xFF == ord('q'):
 break
 # break if the sample number is morethan 20
 elif sampleNum > 20:
 break
 
cap.release()
cv2.destroyAllWindows()

import cv2
import os
import numpy as np
from PIL import Image
 
# recognizer = cv2.createLBPHFaceRecognizer()
detector = cv2.CascadeClassifier("/Users/qiuchenglin/PycharmProjects/face_recognize/haarcascade_frontalface_alt.xml")
recognizer = cv2.face.LBPHFaceRecognizer_create()
 
 
def get_images_and_labels(path):
 image_paths = [os.path.join(path, f) for f in os.listdir(path)]
 face_samples = []
 ids = []
 
 for image_path in image_paths:
 image = Image.open(image_path).convert('L')
 image_np = np.array(image, 'uint8')
 if os.path.split(image_path)[-1].split(".")[-1] != 'jpg':
 continue
 image_id = int(os.path.split(image_path)[-1].split(".")[1])
 faces = detector.detectMultiScale(image_np)
 for (x, y, w, h) in faces:
 face_samples.append(image_np[y:y + h, x:x + w])
 ids.append(image_id)
 
 return face_samples, ids
 
 
Faces, Ids = get_images_and_labels('dataSet')
recognizer.train(Faces, np.array(Ids))
recognizer.save('trainner.yml')

import cv2
import numpy as np
 
recognizer = cv2.face.LBPHFaceRecognizer_create()
# recognizer = cv2.createLBPHFaceRecognizer() # in OpenCV 2
recognizer.read('/Users/qiuchenglin/PycharmProjects/face_recognize/trainner.yml')
# recognizer.load('trainner/trainner.yml') # in OpenCV 2
 
cascade_path = "/Users/qiuchenglin/PycharmProjects/face_recognize/haarcascade_frontalface_alt.xml"
face_cascade = cv2.CascadeClassifier(cascade_path)
cam = cv2.VideoCapture(0)
# font = cv2.cv.InitFont(cv2.cv.CV_FONT_HERSHEY_SIMPLEX, 1, 1, 0, 1, 1) # in OpenCV 2
font = cv2.FONT_HERSHEY_SIMPLEX
 
while True:
 ret, im = cam.read()
 gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
 faces = face_cascade.detectMultiScale(gray, 1.2, 5)
 for (x, y, w, h) in faces:
 cv2.rectangle(im, (x - 50, y - 50), (x + w + 50, y + h + 50), (225, 0, 0), 2)
 img_id, conf = recognizer.predict(gray[y:y + h, x:x + w])
 if conf > 50:
 if img_id == 1:
 img_id = 'liuzb'
 elif img_id == 2:
 img_id = 'linqc'
 elif img_id == 3:
 img_id = 'keaibao'
 else:
 img_id = "Unknown"
 # cv2.cv.PutText(cv2.cv.fromarray(im), str(Id), (x, y + h), font, 255)
 cv2.putText(im, str(img_id), (x, y), font, 1, (0, 255, 0), 1)
 cv2.imshow('im', im)
 if cv2.waitKey(10) & 0xFF == ord('q'):
 break
 
cam.release()
cv2.destroyAllWindows()