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build_face.py
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build_face.py
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# import the necessary packages
from imutils.video import VideoStream
from imutils import face_utils
import argparse
import imutils
import time
import dlib
import cv2
from load_face import Loadface
class Build_face:
def run_cam(self,vs):
#construct the argument parser and parse the arguments
#ap = argparse.ArgumentParser()
#ap.add_argument("-p", "--shape-predictor", required=True,
# help="path to facial landmark predictor")
#args = vars(ap.parse_args())
# initialize dlib's face detector (HOG-based) and then create the
# facial landmark predictor
print("[INFO] loading facial landmark predictor...")
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor('face_landmarks_5points.dat')
#user insert name
name = input('Please insert your name:')
while True:
# grab the frame from the threaded video stream, resize it to
# have a maximum width of 400 pixels, and convert it to
# grayscale
frame = vs.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# detect faces in the grayscale frame
rects = detector(gray, 0)
# check to see if a face was detected, and if so, draw the total
# number of faces on the frame
if len(rects) > 0:
text = "{} face(s) found".format(len(rects))
cv2.putText(frame, text, (10, 20), cv2.FONT_HERSHEY_SIMPLEX,
0.5, (0, 0, 255), 2)
if len(rects)>1:
text = 'Please keep one face inside the frame'
cv2.putText(frame, text, (10, 50), cv2.FONT_HERSHEY_SIMPLEX,
0.5, (0, 0, 255), 2)
# loop over the face detections
for rect in rects:
# compute the bounding box of the face and draw it on the
# frame
(bX, bY, bW, bH) = face_utils.rect_to_bb(rect)
cv2.rectangle(frame, (bX, bY), (bX + bW, bY + bH),
(0, 255, 0), 1)
# determine the facial landmarks for the face region, then
# convert the facial landmark (x, y)-coordinates to a NumPy
# array
shape = predictor(gray, rect)
shape = face_utils.shape_to_np(shape)
# loop over the (x, y)-coordinates for the facial landmarks
# and draw each of them
for (i, (x, y)) in enumerate(shape):
cv2.circle(frame, (x, y), 1, (0, 0, 255), -1)
cv2.putText(frame, str(i + 1), (x - 10, y - 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1)
# show the frame
cv2.imshow("Video", frame)
key = cv2.waitKey(1) & 0xFF
#if found only 1 face, and type in q
if (len(rects) == 1) and (key == ord('p')):
cv2.imwrite('/home/angel/Desktop/donkey_custom/angel_facerec/face_photo/{}.jpg'.format(name),frame)
print('face in and crop:{}'.format(name))
cv2.rectangle(frame,(50,50),(300,110),(0,0,0),-1)
text = 'Cropped'
cv2.putText(frame, text,(50,100), cv2.FONT_HERSHEY_SIMPLEX,2,(255,0,0),3)
cv2.imshow('Video',frame)
key = cv2.waitKey(1) & 0xFF
load = Loadface()
load.load_json()
load.update(name)
load.to_json()
time.sleep(3)
break
# if the `q` key was pressed, break from the loop
elif key == ord("q"):
break
# do a bit of cleanup
cv2.destroyAllWindows()
vs.stop()
if __name__ =='__main__':
build = Build_face()
build.run_cam()