def buildModel(args): start = time.time() num_frames = args.seq_len cfg = ModelConfig((num_frames,) + pennaction_dataconf.input_shape, pa16j2d, num_actions=[15], num_pyramids=6, action_pyramids=[5, 6], num_levels=4, pose_replica=True, num_pose_features=160, num_visual_features=160) num_predictions = spnet.get_num_predictions( cfg.num_pyramids, cfg.num_levels) num_action_predictions = \ spnet.get_num_predictions(len(cfg.action_pyramids), cfg.num_levels) full_model = spnet.build(cfg) weights_file = 'weights/weights_mpii+penn_ar_028.hdf5' full_model.load_weights(weights_file, by_name=True) models = split_model(full_model, cfg, interlaced=False, model_names=['2DPose', '2DAction']) end = time.time() print("Time Taken to build model : ", end - start) return models[0], models[1]
logger.debug("NUM PREDICTIONS") logger.debug(num_action_predictions) """Load datasets""" # h36m = Human36M(datasetpath('Human3.6M'), dataconf=human36m_dataconf, # poselayout=pa17j3d, topology='frames') ntu_data_path = os.getcwd() + '/datasets/NTU' logger.debug(ntu_data_path) ntu = Ntu(ntu_data_path, ntu_dataconf, poselayout=pa17j3d, topology='sequences', use_gt_bbox=True, clip_size=num_frames, num_S=5) #logger.debug ('WARNING!! USING ONLY S1 FOR EVALUATION!') """Build the full model""" full_model = spnet.build(cfg) weights_file = os.getcwd() + '/weights/weights_3dp+ntu_ar_062.hdf5' logger.debug(weights_file) if os.path.isfile(weights_file) == False: logger.debug (f'Error: file {weights_file} not found!') logger.debug (f'\nPlease download it from https://drive.google.com/file/d/1I6GftXEkL5nohLA60Vi6faW0rvTZg6Kx/view?usp=sharing') sys.stdout.flush() sys.exit() """Load pre-trained weights from pose estimation and copy replica layers.""" full_model.load_weights(weights_file, #'output/ntu_spnet_trial_06_nopose_g_512a239/weights_3dp+ntu_ar_030.hdf5', by_name=True)