def __init__(self,
resume_checkpoint='utilities/obman_train/release_models/obman/checkpoint.pth.tar',
mano_root='utilities/obman_train/misc/mano',
no_beta=True,cache_loc='cache/hand_mesh', image_extension='.jpg',
overwrite=False ):
self.overwrite = overwrite
self.extension_length = len(image_extension)
self.cache_loc = cache_loc
if not os.path.exists(self.cache_loc):
os.makedirs(self.cache_loc, exist_ok=True)
self.resume = resume_checkpoint
self.checkpoint = os.path.dirname(self.resume)
with open(os.path.join(self.checkpoint, 'opt.pkl'), 'rb') as opt_f:
self.opts = pickle.load(opt_f)
self.no_beta = no_beta
self.mano_root = mano_root
self.model = reload_model(self.resume, self.opts,
mano_root=self.mano_root, no_beta=self.no_beta)
self.model.eval()
"--image_path",
help="Path to image",
default="readme_assets/images/can.jpg",
)
parser.add_argument("--no_beta",
action="store_true",
help="Force shape to average")
args = parser.parse_args()
argutils.print_args(args)
checkpoint = os.path.dirname(args.resume)
with open(os.path.join(checkpoint, "opt.pkl"), "rb") as opt_f:
opts = pickle.load(opt_f)
# Initialize network
model = reload_model(args.resume, opts, no_beta=args.no_beta)
model.eval()
print("Input image is processed flipped and unflipped "
"(as left and right hand), both outputs are displayed")
# load faces of hand
with open("misc/mano/MANO_RIGHT.pkl", "rb") as p_f:
mano_right_data = pickle.load(p_f, encoding="latin1")
faces = mano_right_data["f"]
fig = plt.figure(figsize=(4, 4))
fig.clf()
frame = cv2.imread(args.image_path)
frame = preprocess_frame(frame)