def main():
args = DemoOptions().parse()
args.use_smplx = True
device = torch.device(
'cuda') if torch.cuda.is_available() else torch.device('cpu')
assert torch.cuda.is_available(), "Current version only supports GPU"
hand_bbox_detector = HandBboxDetector('third_view', device)
#Set Mocap regressor
body_mocap = BodyMocap(args.checkpoint_body_smplx,
args.smpl_dir,
device=device,
use_smplx=True)
hand_mocap = HandMocap(args.checkpoint_hand, args.smpl_dir, device=device)
# Set Visualizer
if args.renderer_type in ['pytorch3d', 'opendr']:
from renderer.screen_free_visualizer import Visualizer
else:
from renderer.visualizer import Visualizer
visualizer = Visualizer(args.renderer_type)
run_frank_mocap(args, hand_bbox_detector, body_mocap, hand_mocap,
visualizer)
def main():
args = DemoOptions().parse()
args.use_smplx = True
device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
assert torch.cuda.is_available(), "Current version only supports GPU"
hand_bbox_detector = HandBboxDetector('third_view', device)
#Set Mocap regressor
body_mocap = BodyMocap(args.checkpoint_body_smplx, args.smpl_dir, device = device, use_smplx= True)
hand_mocap = HandMocap(args.checkpoint_hand, args.smpl_dir, device = device)
run_frank_mocap(args, hand_bbox_detector, body_mocap, hand_mocap)
def main():
args = DemoOptions().parse()
args.use_smplx = True
device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
#Set Mocap regressor
if not torch.cuda.is_available():
hand_bbox_detector = HandBboxDetector_cpu("third_view", device)
body_mocap = BodyMocap_cpu(args.checkpoint_body_smplx, args.smpl_dir, device = device, use_smplx= True)
hand_mocap = HandMocap_cpu(args.checkpoint_hand, args.smpl_dir, device = device)
# Set Visualizer
if args.renderer_type in ['pytorch3d', 'opendr']:
from renderer.screen_free_visualizer import Visualizer
else:
from renderer.visualizer import Visualizer
visualizer = Visualizer(args.renderer_type)
run_frank_mocap_cpu(args, hand_bbox_detector, body_mocap, hand_mocap,visualizer)
else:
print("This is the CPU beta version")
args.out_dir = os.path.join(args.out_dir, f"hand_bboxes_{args.th_hands}")
if not os.path.exists(args.out_dir):
os.makedirs(args.out_dir)
elif not args.replace and os.path.exists(os.path.join(args.out_dir, f"finished.marker")):
print(f"[{i}/{len(lines)-1}] Already processed video -> '{args.out_dir}'")
continue
print(f"[{i}/{len(lines)-1}] Processing video '{args.input_path}' -> '{args.out_dir}'")
run_hand_mocap(args, bbox_detector)
print(f"[FINISHED] Time: {time.time() - t0} s")
if __name__ == '__main__':
args = DemoOptions().parse()
args.use_smplx = True
device = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
assert torch.cuda.is_available(), "Current version only supports GPU"
#Set Bbox detector
bbox_detector = HandBboxDetector(args.view_type, device, th=args.th_hands)
if args.list:
run_from_list(args, bbox_detector)
else:
root = "/data/sessions_processed/final_dataset/"
args.out_dir = os.path.join(args.out_dir, args.input_path.replace(root, "").split(".")[0], f"hand_bboxes_{args.th_hands}")
if not os.path.exists(args.out_dir):
os.makedirs(args.out_dir)
run_hand_mocap(args, bbox_detector)