json.dump(label_dict, open(save_dir_label + '/' + str(step) + '.json', 'w'), sort_keys=True, indent=4)
return pck_dict
# ************************************ Build dataset ************************************
test_data = UCIHandPoseDataset(data_dir=test_data_dir, label_dir=test_label_dir)
print 'Test dataset total number of images sequence is ----' + str(len(test_data))
# Data Loader
test_dataset = DataLoader(test_data, batch_size=batch_size, shuffle=True)
# Build model
net = CPM(21)
if cuda:
net = net.cuda()
net = nn.DataParallel(net, device_ids=device_ids) # multi-Gpu
model_path = os.path.join('ckpt/model_epoch' + str(best_model)+'.pth')
state_dict = torch.load(model_path)
net.load_state_dict(state_dict)
# **************************************** test all images ****************************************
print '********* test data *********'
net.eval()
all_pcks = {} # {0005:[[], [],[]], 0011:[[], [],[]] }
for step, (image, label_map, center_map, imgs) in enumerate(test_dataset):
