add_faces.py

import cv2
import numpy as np
import pickle as pkl
import os

video = cv2.VideoCapture(0)
facedetect = cv2.CascadeClassifier('./data/haarcascades/haarcascade_frontalface_default.xml')
faces_data = []
i = 0

name = input("Enter Your Name: ")

while True:
    ret, frame = video.read()
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = facedetect.detectMultiScale(gray, 1.3, 5)
    for (x,y,w,h) in faces:
        crop_img = frame[y:y+h, x:x+w, :]
        resized_img = cv2.resize(crop_img, (50,50))
        if len(faces_data) <= 100 and i%10 == 0:
            faces_data.append(resized_img)
        i = i+1
        cv2.putText(frame, str(len(faces_data)), (50,50), cv2.FONT_HERSHEY_COMPLEX, 1.5, (180,0,0), 3)
        cv2.rectangle(frame, (x,y), (x+w,y+h), (0,255,0), 1)
    cv2.imshow("Frame", frame)
    k = cv2.waitKey(1)
    if k == ord('a') or len(faces_data)==100:
        break
video.release()
cv2.destroyAllWindows()

faces_data = np.asarray(faces_data)
faces_data = faces_data.reshape(100, -1)

if 'names.pkl' not in os.listdir('data/'):
    names = [name]*100
    with open('data/names.pkl', 'wb') as f:
        pkl.dump(names, f)
else:
    with open('data/names.pkl', 'rb') as f:
        names = pkl.load(f)
    names = names + [name]*100
    with open('data/names.pkl', 'wb') as f:
        pkl.dump(names, f)


if 'faces_data.pkl' not in os.listdir('data/'):
    with open('data/faces_data.pkl', 'wb') as f:
        pkl.dump(faces_data, f)
else:
    with open('data/faces_data.pkl', 'rb') as f:
        faces = pkl.load(f)
    faces = np.append(faces, faces_data, axis = 0)
    with open('data/faces_data.pkl', 'wb') as f:
        pkl.dump(names, f)