recognize.py

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



data_path = 'C:/Users/abhin\Desktop/abhinav/projects/Facial Recognition Based Attendance System/user data/'
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('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, 0),  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)
        result = model.predict(face)

        if result[1] < 500:
            confidence = int(100*(1-(result[1])/300))
            display_string = str(confidence) + '% FACE MATCHED '
        cv2.putText(image, display_string, (100,120),cv2.FONT_HERSHEY_SIMPLEX,1,(255,0,0),2)

        if confidence > 75:
            cv2.putText(image, 'ATTENDANCE MARKED', (0, 450), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
            cv2.imshow('Face Cropper',image)

        else:
            cv2.putText(image, 'FACE NOT MATCHED', (0, 450), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
            cv2.imshow('Face Cropper', image)

    except:
        cv2.putText(image, 'FACE NOT FOUND IN DATABASE', (0, 450), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
        cv2.imshow('Face Cropper', image)
        pass

    if cv2.waitKey(1) == 27:
        break


cap.release()
cv2.destroyAllWindows()
import login