face_detector.py

#!/Users/albertolanaro/venv3/bin/python3
import os
import cv2
import numpy as np
import sys
import datetime

if len(sys.argv) != 3:
	print("usage: ./face_detector.py <user_name> <save_face flag>")
	sys.exit(1)

# -----PARAMS---------
USER = sys.argv[1]
SAVE_FACE = int(sys.argv[2])
FACES_FOLDER = 'Faces' # folder where to store the detected faces
# --------------------

if SAVE_FACE and not os.path.exists(FACES_FOLDER + '/' + USER):
	os.makedirs(FACES_FOLDER + '/' + USER)

print('Detecting faces for user named', USER)

def process_frame(frame, face_classifier):
	gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
	faces = face_classifier.detectMultiScale(gray, 1.6, 8)

	return faces

def display_result(img, faces, save_results):
	for (x,y,w,h) in faces:
		cv2.rectangle(img, (x,y), (x+w,y+h), (255,0,0), 2)
		# if detected save face in .png
		if save_results and len(faces)==1:
			t_index = datetime.datetime.now()
			t_index = "%s_%s_%s_%s" % (t_index.hour, t_index.minute, t_index.second, str(t_index.microsecond)[:2])
			mask = img[y:y+h,x:x+w,:]
			cv2.imwrite(FACES_FOLDER + '/' + USER + '/' + USER + '_' + t_index + '.png', mask)
	# display results
	cv2.imshow('Face detector', img)
	cv2.waitKey(1)

if __name__=='__main__':
	face_cascade = cv2.CascadeClassifier('/Users/albertolanaro/opencv/data/haarcascades/haarcascade_frontalface_default.xml')
	# webcam
	cap = cv2.VideoCapture(0)
	n_img = 0
	while True:
		grabbed, frame = cap.read()	
		if grabbed:
			#face + eye detection
			faces = process_frame(frame, face_cascade)
			if len(faces) != 0:
				if SAVE_FACE:
					n_img+=1
					print('# saved imgs:', n_img)
				else:
					print('Face detected!')
			display_result(frame, faces, SAVE_FACE)