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


frame = cv2.imread('gente_metro4.jpg')

start = time.time()
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)

cv2.waitKey(0)                 # Espera una tecla
cv2.destroyAllWindows() 


