HackStar

First you should have pycharm and python 3.7 version then you need to install

pip install Django pip install sounddevice pip instal keyboard pip intall PyAutoGUI pip intall opencv-python3 pip install opencv-contrib-python pip install numpy

once you have done with your installation then write the following commands

also you need to create folder for storing pics which were captured for the face dectection and recognition and specify that path in the view.py file

def home2(request):

def active():
    face_classifier = cv2.CascadeClassifier(
        'C:/Users/pranalii/AppData/Local/Programs/Python/Python38-32/Lib/site-packages/cv2/data/haarcascade_frontalface_default.xml')

		# path where haarcascade_frontalface_default.xml is present 
		
    def face_extractor(img):
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        faces = face_classifier.detectMultiScale(gray, 1.3, 5)
        if faces is ():
            return None
        for (x, y, w, h) in faces:
            cropped_face = img[y:y + h, x:x + w]

        return cropped_face

    cap = cv2.VideoCapture(0)
    count = 0
    while True:
        ret, frame = cap.read()
        if face_extractor(frame) is not None:
            count += 1
            face = cv2.resize(face_extractor(frame), (200, 200))
            face = cv2.cvtColor(face, cv2.COLOR_BGR2GRAY)
            file_name_path = 'C:/Users/pranalii/PycharmProjects/photos/user' + str(count) + '.jpg'
			
			#path of the folder in which images will be stored and the name of the images will be like user1.jpg,user2.jpg....
            
			cv2.imwrite(file_name_path, face)
            cv2.putText(face, str(count), (50, 50), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 255, 0), 2)
            cv2.imshow('Face Cropper', face)
        else:
            print("Face not found")
            pass
        if cv2.waitKey(1) == 13 or count == 60:
            break
    cap.release()
    cv2.destroyAllWindows()
    print("Collecting Samples Complete")
active()
return render(request, 'home2.html')

data_path = 'C:/Users/pranalii/PycharmProjects/photos/'

#path of the folder in which images will be stored and the name of the images will be like user1.jpg,user2.jpg....

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 trained successfully") face_classifier = cv2.CascadeClassifier('C:/Users/pranalii/AppData/Local/Programs/Python/Python38-32/Lib/site-packages/cv2/data/haarcascade_frontalface_default.xml')

# path where haarcascade_frontalface_default.xml is present 

def face_detector(img): 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(0) while True: ret, frame = cap.read() image, face = face_detector(frame) try: face = cv2.cvtColor(face, cv2.COLOR_BGR2GRAY) results = model.predict(face) if results[1] < 500: confidence = int(100 * (1 - (results[1])/300)) display_string = str(confidence) + '% Confident it is User' cv2.putText(image, display_string, (100, 120), cv2.FONT_HERSHEY_COMPLEX, 1, (255, 120, 150), 2) if confidence > 75: cv2.putText(image, "Unlocked", (250, 450), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 255, 0), 2) cv2.imshow('Face Recognition', image) else: cv2.putText(image, "Locked", (250, 450), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 255), 2) cv2.imshow('Face Recognition', image) except Exception: cv2.putText(image, "No Face Found", (220, 120), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 255), 2) cv2.putText(image, "Locked", (250, 450), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 255), 2) cv2.imshow('Face Recognition', image) pass if cv2.waitKey(1) == 13: break cap.release() cv2.destroyAllWindows()

you are done with all this then you need to make migrations by using python manage.py makemigrations commands after this python manage.py migrate command then finally python manage.py runserver