face_dataset.py

import subprocess
import cv2
import os

face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
cam = cv2.VideoCapture(0)
cam.set(3, 640)  # set video width
cam.set(4, 480)  # set video height

face_id = input('\n enter user id end press <return> ==>  ')
print("\n [INFO] Initializing face capture. Look the camera and wait ...")

count = 0
while(True):
    ret, img = cam.read()
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
    for (x, y, w, h) in faces:
        cv2.rectangle(img, (x, y), (x+w, y+h), (255, 0, 0), 2)
        count += 1
        cv2.imwrite(f"dataset/User.{face_id}.{count}.jpg", gray[y:y+h, x:x+w])
        cv2.imshow('image', img)
        print(f"ID: {face_id}: {count} saved.", end="\r")

    k = cv2.waitKey(100) & 0xff  # Press 'ESC' for exiting video
    if k == 27:
        break
    elif count >= 30:  # Take 30 face sample and stop video
        break

print("\n [INFO] Exiting Program and cleanup stuff")
cam.release()
cv2.destroyAllWindows()

datasets_path = os.path.join(os.getcwd(), "dataset")
subprocess.Popen(rf'explorer.exe "{datasets_path}"')