Face_data.py

import cv2
import numpy as np


cap = cv2.VideoCapture(0)
face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_alt.xml")


skip = 0
face_data = []
dataset_path = './data/'

file_name = input("Enter the name of the person :")

while True:
    ret,frame = cap.read()

    if ret==False:
        continue

    gray_frame = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)

#sorting based on area


    faces = face_cascade.detectMultiScale(frame,1.3,5)
    faces = sorted(faces,key=lambda f:f[2]*f[3])

#Pick the last face as it is the largest face acc to area

    for face in faces[-1:]:
        x,y,w,h = face
        cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,255),2)

    #extract (crop out the required face) 
        offset = 10
        face_section = frame[y-offset:y+h+offset,x-offset:x+w+offset]
        face_section = cv2.resize(face_section,(100,100))
    
    #store every 10th face
        skip+=1
        if skip%10==0:
            face_data.append(face_section)
            print(len(face_data))



    cv2.imshow("Frame",frame)
    #cv2.imshow("Face Section",face_section)



    


    key_pressed = cv2.waitKey(1) &0xFF
    if key_pressed == ord('q'):
        break


#convert face list into numpy array
face_data = np.asarray(face_data)
face_data = face_data.reshape((face_data.shape[0],-1))
print(face_data.shape)

#save this data into file system
np.save(dataset_path+file_name+'.npy',face_data)
print("data sucessfully save")


cap.release()
cv2.destroyAllWindows()