import face_recognition
import cv2
from imutils.object_detection import non_max_suppression
from imutils import paths
import imutils
import time

video_capture = cv2.VideoCapture(0)

while True:
	start = time.time()
	print ("hello")
	# Grab a single frame of video
	ret, frame = video_capture.read()
	frame = imutils.resize(frame, width=720)

	# Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
	rgb_frame = frame[:, :, ::-1]

	# Find all the faces and face enqcodings in the frame of video
	face_locations = face_recognition.face_locations(rgb_frame, model = 'hog')
	#face_encodings = face_recognition.face_encodings(rgb_frame, face_locations)

	# Loop through each face in this frame of video
	for (top, right, bottom, left) in (face_locations):
		# See if the face is a match for the known face(s)
		#matches = face_recognition.compare_faces(known_face_encodings, face_encoding)

		name = "Desconocido"

		# If a match was found in known_face_encodings, just use the first one.
		#if True in matches:
		    #first_match_index = matches.index(True)
		    #name = known_face_names[first_match_index]

		# Draw a box around the face
		cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)

		# Draw a label with a name below the face
		cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
		font = cv2.FONT_HERSHEY_DUPLEX
		cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)

	# Display the resulting image
	#out.write(frame) #guarda video
	print (time.time() - start)
	cv2.imshow('Video', frame)

	# Hit 'q' on the keyboard to quit!
	if cv2.waitKey(1) & 0xFF == ord('q'):
		out.release()
		break

# Release handle to the webcam
video_capture.release()
cv2.destroyAllWindows()
