def main():
'''
Main loop that initializes camera and other
'''
args = parse_args()
config = Config()
#Start Camera async class
cam = Camera(args)
cam.start()
#Start io writing queue
write_queue = WriteQueue()
write_queue.start()
if config.Inference.mode == 'detect':
print('Running detection')
detector = OpenVinoDetectorAsync(config.Inference)
else:
detector = OpenVinoClassifierAsync(config.Inference)
while True:
_,frame = cam.read()
start_time = time.time()
infer_frame = deepcopy(frame)
detections = detector.run(infer_frame)
timestamp = datetime.now(tz=timezone.utc).strftime('%Y-%m-%d-%H-%M-%S-%f')
path = 'tmp/' + timestamp + '.jpg'
if detections:
'''
Need to fix the bounding box locations
for detection in detections:
xmin = detection.position.xmin
ymin = detection.position.ymin
xmax = detection.position.xmax
ymax = detection.position.ymax
cv2.rectangle(frame, (int(xmin), int(ymin)), (int(xmax), int(ymax)), detection.color, 2)
'''
cv2.putText(frame,'HUMAN',(10,400), cv2.FONT_HERSHEY_SIMPLEX, 4,(25,25,255),2,cv2.LINE_AA)
cv2.imshow('frame', frame)
cv2.imwrite(path, frame)
#This has to RTT
upload_frame(path, config)
else:
#add to upload queue
write_queue.enqueue(path, frame)
end_time = time.time()
print("[LOGS] ---PIPELINE TIME--- **{}**".format(end_time-start_time))
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cam.stop()
write_queue.stop()
cv2.destroyAllWindows()
class Main:
def __init__(self):
self.camera = Camera()
with timer.time(f'load'):
self.mtcnn = MTCNN()
self.mtcnn.init(480,640)
def main(self, manual_brake=None):
while not manual_brake:
frame = self.camera.read()
try:
with timer.time(f'inference'):
bboxes = self.mtcnn.findFace(frame) # [3,h,w]
for x1,y1,x2,y2 in bboxes:
cv2.rectangle(frame, (x1,y1), (x2,y2), (255,0,0), 2)
except Exception as e: # face not found
print(e)
continue
manual_brake = self.camera.show_frame(frame)
self.camera.clean()
timer.print_stats()
class Main:
def __init__(self, mrz_port="/dev/ttyACM0"):
with timer.time(f'load-total'):
self.card_reader = CardReader()
self.card_reader.set_mrz_port(mrz_port)
with timer.time(f'load-mtcnn'):
self.mtcnn = MTCNN()
self.mtcnn.init(480, 640)
with timer.time(f'load-facenet'):
self.face_embedder = FaceEmbedder()
self.camera = Camera()
#
self.camera_face = None
self.camera_emb = None
self.reader_face = None
self.reader_emb = None
def prep_im(self, im):
im = cv2.resize(im, (160, 160))
return torch.tensor(im).permute(2, 1, 0).to('cuda')
async def camera_loop(self):
while True:
with timer.time(f'camera-total'):
frame = self.camera.read()
print('[camera] frame:', frame.shape)
with timer.time(f'camera-mtcnn'):
bboxes = self.mtcnn.findFace(frame)
print('[camera] bboxes:', bboxes)
for x1, y1, x2, y2 in bboxes:
self.camera_face = frame[y1:y2, x1:x2]
print('[camera] face:', self.camera_face.shape)
with timer.time(f'camera-facenet'):
im = self.prep_im(self.camera_face)
self.camera_emb = self.face_embedder.face2embedding(im)
await asyncio.sleep(0)
async def reader_loop(self):
while True:
print('[reader] starting read...')
chip_img_future = self.card_reader.read_image_bytes_async()
t0 = time()
while not chip_img_future.isDone():
await asyncio.sleep(0)
byte_array = chip_img_future.get()
if len(byte_array) > 0:
print('[reader] byte arr len:', len(byte_array))
chip_img = self.card_reader.bytes2np(byte_array) # [h,w]
timer.D['reader-read'].append(time() - t0)
print('[reader] chip img:', chip_img.shape)
chip_img = np.concatenate(
[chip_img[:, :, None] for _ in range(3)],
axis=2) # [h,w,3]
with timer.time(f'reader-mtcnn'):
bboxes = self.mtcnn.findFace(chip_img)
print('[reader] bboxes:', bboxes)
for y1, x1, y2, x2 in bboxes:
self.reader_face = chip_img[y1:y2, x1:x2]
print('[reader] chip face:', self.reader_face.shape)
with timer.time(f'reader-facenet'):
im = self.prep_im(self.reader_face)
self.reader_emb = self.face_embedder.face2embedding(im)
timer.D['reader-total'].append(time() - t0)
self.compare_embeddings_and_exit()
def compare_embeddings_and_exit(self):
if self.reader_face is None:
print("[ERROR] Couldn't read face from reader...")
if self.camera_face is None:
print("[ERROR] Couldn't read face from camera...")
cv2.imwrite('reader_face.png', self.reader_face)
cv2.imwrite('camera_face.png', self.camera_face)
score = float((self.reader_emb - self.camera_emb).norm())
print('score:', score)
timer.print_stats()
sys.exit()
def main(self):
asyncio.gather(self.camera_loop(), self.reader_loop())
asyncio.get_event_loop().run_forever()
