def register():
try:
if app.unused_port:
port = app.unused_port.pop()
else:
return register_response(
status=afy_flask_register_status.QUOTA_EXCEEDED,
error="Quota Exceeded")
in_addr = app.base_address + ":" + str(port)
out_addr = app.base_address + ":" + str(port + 1)
sps = shlex.split(
f'./run.sh --is-worker --in-port {port} --out-port {port+1} --no-vcam'
)
ps = Popen(sps)
time.sleep(2)
try:
predictor_args = {
'config_path': app.opt.config,
'checkpoint_path': app.opt.checkpoint,
'relative': app.opt.relative,
'adapt_movement_scale': app.opt.adapt_scale,
'enc_downscale': app.opt.enc_downscale
}
predictor = predictor_remote.PredictorRemote(in_addr=in_addr,
out_addr=out_addr,
**predictor_args)
except ConnectionError as err:
if app.verbose:
traceback.print_exc()
return register_response(
status=afy_flask_register_status.CONNECTION_ERROR,
error=str(err))
while True:
token = generate_token()
if token not in app.processes:
break
app.processes[token] = {}
app.processes[token]['port'] = port
app.processes[token]['ps'] = ps
app.processes[token]['predictor'] = predictor
return register_response(status=afy_flask_register_status.SUCCESS,
token=token)
except Exception as e:
if app.verbose:
traceback.print_exc()
return register_response(error=str(e))
predictor_args = {
'config_path': opt.config,
'checkpoint_path': opt.checkpoint,
'relative': opt.relative,
'adapt_movement_scale': opt.adapt_scale,
'enc_downscale': opt.enc_downscale
}
if opt.is_worker:
from afy import predictor_worker
predictor_worker.run_worker(opt.in_port, opt.out_port)
sys.exit(0)
elif opt.is_client:
from afy import predictor_remote
try:
predictor = predictor_remote.PredictorRemote(in_addr=opt.in_addr,
out_addr=opt.out_addr,
**predictor_args)
except ConnectionError as err:
log(err)
sys.exit(1)
predictor.start()
else:
from afy import predictor_local
predictor = predictor_local.PredictorLocal(**predictor_args)
cam_id = select_camera(config)
if cam_id is None:
exit(1)
cap = VideoCaptureAsync(cam_id)
log('Loading Predictor')
predictor_args = {
'config_path': opt.config,
'checkpoint_path': opt.checkpoint,
'relative': opt.relative,
'adapt_movement_scale': opt.adapt_scale,
'enc_downscale': opt.enc_downscale
}
if opt.is_worker:
from afy import predictor_worker
predictor_worker.run_worker(opt.worker_port)
sys.exit(0)
elif opt.worker_host:
from afy import predictor_remote
predictor = predictor_remote.PredictorRemote(
worker_host=opt.worker_host,
worker_port=opt.worker_port,
**predictor_args)
else:
from afy import predictor_local
predictor = predictor_local.PredictorLocal(**predictor_args)
avatars = []
images_list = sorted(glob.glob(f'{opt.avatars}/*'))
for i, f in enumerate(images_list):
if f.endswith('.jpg') or f.endswith('.jpeg') or f.endswith('.png'):
key = len(avatars) + 1
log(f'Key {key}: {f}')
img = cv2.imread(f)
if img.ndim == 2:
img = np.tile(img[..., None], [1, 1, 3])
img = img[..., :3][..., ::-1]