face_train.py

import os
import cv2 as cv
import numpy as np

haar_cascade = cv.CascadeClassifier('haar_face.xml')
people = ['Tung_Duong', 'Ha_Anh_Tuan']
DIR = r'/home/vudangitwork/Documents/code/Train'
features = []
labels = []
def create_train():
    for person in people:
        path = os.path.join(DIR,person)
        label = people.index(person)
        
        for img in os.listdir(path):
            img_path = os.path.join(path, img)

            img_array = cv.imread(img_path) 
            gray = cv.cvtColor(img_array, cv.COLOR_BGR2GRAY)
            
            faces_rect = haar_cascade.detectMultiScale(gray, scaleFactor = 1.1, minNeighbors=9)
            for (x, y, w, h) in faces_rect:
                faces_roi = gray[y:y+h, x:x+w]
                features.append(faces_roi)
                labels.append(label)
create_train()
print('Training done ----------------------------------')
features = np.array(features, dtype='object')
labels = np.array(labels)
face_recognizer = cv.face.LBPHFaceRecognizer_create()
# Train the recognizer on the features list and the labels list
face_recognizer.train(features,labels)
face_recognizer.save('face_trained.yml')

np.save('features.npy', features)
np.save('labels.npy', labels)