model_dir = args.load_dir + "/" + args.net + "/" + args.dataset
if not os.path.exists(model_dir):
raise Exception(
'There is no input directory for loading network from ' +
model_dir)
output_dir = args.output_dir + "/" + args.net + "/" + args.dataset
if not os.path.exists(output_dir):
os.makedirs(output_dir)
load_name = os.path.join(
model_dir,
'tdcnn_{}_{}_{}.pth'.format(args.checksession, args.checkepoch,
args.checkpoint))
# initilize the network here.
if args.net == 'c3d':
tdcnn_demo = c3d_tdcnn(pretrained=False)
elif args.net == 'res18':
tdcnn_demo = resnet_tdcnn(depth=18, pretrained=False)
elif args.net == 'res34':
tdcnn_demo = resnet_tdcnn(depth=34, pretrained=False)
elif args.net == 'res50':
tdcnn_demo = resnet_tdcnn(depth=50, pretrained=False)
else:
print("network is not defined")
tdcnn_demo.create_architecture()
# save memory
for key, value in tdcnn_demo.named_parameters():
value.requires_grad = False
print(tdcnn_demo)
print('{:d} roidb entries'.format(num_videos))
input_dir = args.load_dir + "/" + args.net + "/" + args.dataset
if not os.path.exists(input_dir):
raise Exception(
'There is no input directory for loading network from ' +
input_dir)
load_name = os.path.join(
input_dir,
'tdcnn_{}_{}_{}.pth'.format(args.checksession, args.checkepoch,
args.checkpoint))
# initilize the network here.
if args.net == 'c3d':
tdcnn_demo = c3d_tdcnn(class_agnostic=cfg.AGNOSTIC, pretrained=False)
elif args.net == 'res34':
tdcnn_demo = resnet_tdcnn(depth=34,
class_agnostic=cfg.AGNOSTIC,
pretrained=False)
elif args.net == 'res50':
tdcnn_demo = resnet_tdcnn(depth=50,
class_agnostic=cfg.AGNOSTIC,
pretrained=False)
else:
print("network is not defined")
pdb.set_trace()
tdcnn_demo.create_architecture()
print("load checkpoint %s" % (load_name))
output_dir = args.save_dir + "/" + args.net + "/" + args.dataset
if not os.path.exists(output_dir):
os.makedirs(output_dir)
sampler_batch = sampler(train_size, args.batch_size)
dataset = roibatchLoader(roidb)
dataloader = torch.utils.data.DataLoader(dataset,
batch_size=args.batch_size,
sampler=sampler_batch,
num_workers=args.num_workers)
# initilize the network here.
if args.net == 'c3d':
tdcnn_demo = c3d_tdcnn(pretrained=True)
elif args.net == 'i3d':
tdcnn_demo = i3d_tdcnn(pretrained=True)
elif args.net == 'res34':
tdcnn_demo = resnet_tdcnn(depth=34, pretrained=True)
elif args.net == 'res50':
tdcnn_demo = resnet_tdcnn(depth=50, pretrained=True)
else:
print("network is not defined")
pdb.set_trace()
tdcnn_demo.create_architecture()
print(tdcnn_demo)
lr = args.lr
#tr_momentum = cfg.TRAIN.MOMENTUM