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faces_train.py
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faces_train.py
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import os
import cv2 as cv
import numpy as np
people = []
for i in os.listdir(r"D:\Photos\openCV"):
people.append(i)
DIR = r'D:\Photos\openCV'
haar_cascade = cv.CascadeClassifier('haar_face.xml')
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+h]
features.append(faces_roi)
labels.append(label)
create_train()
face_recognizer = cv.face.LBPHFaceRecognizer_create()
features = np.array(features, dtype = 'object')
labels = np.array(labels)
face_recognizer.train( features , labels)
face_recognizer.save('face_trained.yml')
np.save('features.npy', features)
np.save('labels.npy',labels)