Facial_Recognition_Part3.py

import cv2
import numpy as np
from os import listdir
from os.path import isfile, join
import fagn

data_path = 'D:/A_naman/Documents/openCV/face_recognition_img/'
onlyfiles = [f for f in listdir(data_path) if isfile(join(data_path,f))]

Training_Data, Labels = [], []

for i, files in enumerate(onlyfiles):
    image_path = data_path + onlyfiles[i]
    images = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
    Training_Data.append(np.asarray(images, dtype=np.uint8))
    Labels.append(i)

Labels = np.asarray(Labels, dtype=np.int32)

model = cv2.face.LBPHFaceRecognizer_create()

model.train(np.asarray(Training_Data), np.asarray(Labels))

print("Model Training Complete!!!!!")





face_classifier = cv2.CascadeClassifier('D:/A_naman/Documents/openCV/haarcascade_frontalface_default.xml')

def face_detector(img, size = 0.5):
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    faces = face_classifier.detectMultiScale(gray,1.3,5)

    if faces is():
        return img,[]

    for(x,y,w,h) in faces:
        cv2.rectangle(img, (x,y),(x+w,y+h),(0,255,255),2)
        roi = img[y:y+h, x:x+w]
        roi = cv2.resize(roi, (200,200))

    return img,roi

cap = cv2.VideoCapture(1)

while True:
	
	ret, frame = cap.read()
	#pop=fagn.main(frame)
	image, face = face_detector(frame)

	try:
		face = cv2.cvtColor(face, cv2.COLOR_BGR2GRAY)
		result = model.predict(face)

		if result[1] < 500:
			confidence = int(100*(1-(result[1])/300))
			display_string = str(confidence)+'% Confidence it is user'
		cv2.putText(image,display_string,(100,120), cv2.FONT_HERSHEY_COMPLEX,1,(250,120,255),2)


		if confidence > 75:
			cv2.putText(image, "Unlocked", (250, 450), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 255, 0), 2)
			cv2.imshow('Face Cropper', image)

		else:
			cv2.putText(image, "Locked", (250, 450), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 255), 2)
			cv2.imshow('Face Cropper', image)


	except:
		cv2.putText(image, "Face Not Found", (250, 450), cv2.FONT_HERSHEY_COMPLEX, 1, (255, 0, 0), 2)
		cv2.imshow('Face Cropper', image)
		pass

	if cv2.waitKey(1)==13:
		break
		

		
cap.release()
cv2.destroyAllWindows()