def display(cmd_args, in_que, log_que, log_level, kill_proc, kill_app):
logger = get_logger(log_que, log_level)
try:
logger.info('Display process starting')
while kill_app.value == 0 and kill_proc.value == 0:
try:
obj = in_que.get(block=True, timeout=1)
except Empty as emp:
logger.debug('Input que to display is empty.')
continue
if obj.get('done', False):
break
if not draw(obj, logger):
kill_proc.value = 1
kill_app.value = 1
break
except Exception as ex:
logger.error(traceback.format_exc())
kill_app.value = 1
finally:
logger.info('Exiting from Display process')
def video_writer(cmd_args, in_que, log_que, log_level, kill_proc, kill_app):
logger = get_logger(log_que, log_level)
video = cv2.VideoWriter(cmd_args.video_out,
cv2.VideoWriter_fourcc(*'mp4v'), cmd_args.fps,
(cmd_args.img_width, cmd_args.img_height))
try:
while kill_app.value == 0 and kill_proc.value == 0:
try:
obj = in_que.get(block=True, timeout=1)
except Empty as emp:
logger.debug('Input que to display is empty.')
continue
if obj.get('done', False):
break
frame = draw_on_frame(obj)
video.write(frame)
except Exception as ex:
logger.error(traceback.format_exc())
kill_app.value = 1
finally:
logger.info('Exiting from VideoWriter process')
def face_detector(cmd_args, in_que, out_que, log_que, log_level, kill_proc, kill_app):
logger = get_logger(log_que, log_level)
try:
logger.debug('FaceDetector process starting')
detection_threshold = cmd_args.detection_threshold
min_face_height = cmd_args.min_face_height
logger.info("Loading Face detector model...")
mtcnn = MTCNN()
while kill_proc.value == 0 and kill_app.value == 0:
try:
obj = in_que.get(block=True, timeout=1)
except Empty as emp:
logger.debug('Input que to face detector is empty.')
continue
if obj.get('done', False):
out_que.put(obj)
break
obj = detect_face(obj,mtcnn,detection_threshold,min_face_height, logger)
out_que.put(obj)
except Exception as ex:
logger.error(traceback.format_exc())
kill_proc.value = 1
kill_app.value = 1
finally:
logger.info('Exiting from Face Detector')
def __init__(self, cmd_args, in_que, log_que, log_level, kill_app, is_sub_proc=False):
self.is_sub_proc = is_sub_proc
self.logger = get_logger(log_que, log_level)
super(ImageWriter, self).__init__(None,
cmd_args=cmd_args,
in_que=in_que,
log_que=log_que,
log_level=log_level,
kill_app=kill_app)
def __init__(self,
cmd_args,
in_que,
log_que,
log_level,
kill_app,
is_sub_proc=False):
self.is_sub_proc = is_sub_proc
self.logger = get_logger(log_que, log_level)
super(Display, self).__init__(display,
cmd_args=cmd_args,
in_que=in_que,
log_que=log_que,
log_level=log_level,
kill_app=kill_app)
def __init__(self, cmd_args, in_que, out_que, log_que, log_level, kill_app, is_sub_proc=False):
self.is_sub_proc = is_sub_proc
if is_sub_proc is False:
self.logger = get_logger(log_que, log_level)
self.mtcnn = MTCNN()
self.graph = tf.get_default_graph()
self.session = tf.Session(graph=self.graph)
super(FaceDetector, self).__init__(face_detector,
cmd_args=cmd_args,
in_que=in_que,
out_que=out_que,
log_que=log_que,
log_level=log_level,
kill_app=kill_app)
def embedding_generator(cmd_args, in_que, log_que, log_level, kill_proc,
kill_app):
logger = get_logger(log_que, log_level)
try:
logger.info("Generating embeddings...")
face_group_manager = FaceGroupLocalManager(cmd_args)
face_group_manager.create_face_group(cmd_args.face_group or 'default')
while kill_proc.value == 0 and kill_app.value == 0:
try:
obj = in_que.get(block=True, timeout=1)
except Empty as emp:
logger.debug('Input que to face detector is empty.')
continue
if obj.get('done', False):
kill_app.value = 1
break
if len(obj.get('faces', [])) == 1:
face_group_manager.append_to_face_group(
cmd_args.face_group or 'default', obj['embeddings'][0],
obj['label'])
logger.info("Face {} added.".format(obj['label']))
else:
logger.error("0 or more than 1 face detected for {}".format(
obj['label']))
logger.info('Completed!')
except Exception as ex:
logger.error(traceback.format_exc())
kill_app.value = 1
finally:
logger.info('Exiting from Embedding Generator')
def face_recogniser(cmd_args, in_que, out_que, log_que, log_level, kill_proc,
kill_app):
logger = get_logger(log_que, log_level)
try:
logger.debug("Loading Face recognition model...")
fg_manager = FaceGroupLocalManager(cmd_args)
fg = fg_manager.get_face_group(cmd_args.face_group)
known_embeddings = fg.embeddings
known_labels = fg.labels
known_face_ids = fg.faceIds
while kill_proc.value == 0 and kill_app.value == 0:
try:
obj = in_que.get(block=True, timeout=1)
except Empty as emp:
logger.debug('Input que to face encoder is empty.')
continue
if obj.get('done', False):
out_que.put(obj)
break
obj = recognise(obj, known_embeddings, known_labels,
known_face_ids, cmd_args.recognition_threshold)
out_que.put(obj)
except Exception as ex:
logger.error(traceback.format_exc())
kill_app.value = 1
finally:
logger.info('Exiting from Face Recogniser')
def capture(cmd_args, out_queue, log_que, log_level, kill_proc, kill_app,
draw_frames):
logger = get_logger(log_que, log_level)
device = cmd_args.camera_url if cmd_args.camera_url != '' else cmd_args.camera_index
REQUIRED_FPS = cmd_args.fps
CAMERA_WAIT = cmd_args.camera_wait
img_dim = (cmd_args.img_width, cmd_args.img_height)
NUM_FRAME_TO_SKIP = 2
logger.info('Acquiring camera. Please wait...')
sleep(CAMERA_WAIT)
factor = cmd_args.img_red_factor
cap = cv2.VideoCapture(device)
logger.info('Camera acquired')
cap.set(cv2.CAP_PROP_FRAME_WIDTH, img_dim[0])
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, img_dim[1])
logger.info("Capturing Images with dimension: {}".format(img_dim))
def exit_gracefully(signum, frame):
kill_app.value = 1
logger.warning('Terminating camera process due to kill signal')
cap.release()
cv2.destroyAllWindows()
utils.clean_queue(out_queue)
signal.signal(signal.SIGINT, exit_gracefully)
signal.signal(signal.SIGTERM, exit_gracefully)
skip_count = 0
tik = time()
count = 0
if cap.isOpened():
logger.info('Camera opened')
else:
logger.error('Unable to open camera')
while cap.isOpened():
if kill_proc.value > 0 or kill_app.value > 0:
logger.warning('Breaking camera process loop')
break
ret, frame = cap.read()
tok = time()
count += 1
if (tok - tik) > 2.0:
tik = time()
camera_fps = math.ceil(count / 2)
NUM_FRAME_TO_SKIP = math.ceil(
(camera_fps - REQUIRED_FPS) / REQUIRED_FPS)
count = 0
if ret is True:
cv2.flip(frame, 1, frame)
if skip_count >= NUM_FRAME_TO_SKIP:
frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
red_frame_rgb = cv2.resize(frame_rgb, (int(
frame.shape[1] * factor), int(frame.shape[0] * factor)))
out_queue.put(
{
'cap_time': time(),
'raw_frame': frame,
'small_rgb_frame': red_frame_rgb,
'factor': factor
},
block=True,
timeout=5)
skip_count = 0
if draw_frames:
logger.info(
"Required frame size {}. Captured size {}".format(
img_dim, frame.shape))
cv2.imshow('CameraFeed', frame)
if cv2.waitKey(25) & 0xFF == ord('q'):
break
else:
skip_count += 1
else:
break
kill_app.value = 1
cap.release()
utils.clean_queue(out_queue)
cv2.destroyAllWindows()
logger.info('Exiting from Camera Process')