collectdata.py

import cv2
import numpy as np

face_classifier = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

def face_extractor(img):

    faces = face_classifier.detectMultiScale(img, 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

# Collect 1000 samples of your face from webcam 
while True:

    ret, frame = cap.read()
    if face_extractor(frame) is not None:
        count += 1
        face = cv2.resize(face_extractor(frame), (224, 224))
        
        file_name_path = 'C://Users//Lenovo//Desktop//ashu//test//' + str(count) + '.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 == 100: 
        break
        
cap.release()
cv2.destroyAllWindows()      
print("Collecting Samples Complete")