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]
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)
"""Split model to simplify evaluation."""
models = split_model(full_model, cfg, interlaced=False,
model_names=['3DPose', '3DAction'])
"""Human3.6H validation samples."""
# h36m_val = BatchLoader(h36m, ['frame'],
# ['pose_w', 'pose_uvd', 'afmat', 'camera', 'action'], VALID_MODE,
# batch_size=h36m.get_length(VALID_MODE), shuffle=False)
# printcn(OKBLUE, 'Preloading Human3.6M validation samples...')
# [h36m_x_val], [h36m_pw_val, h36m_puvd_val, h36m_afmat_val, h36m_scam_val, \
# h36m_action] = h36m_val[0]
"""NTU subset of testing samples"""
#ntu_te = BatchLoader(ntu, ['frame'], ['ntuaction'], TEST_MODE, batch_size=1,
# shuffle=False)
"""Evaluate on Human3.6M using 3D poses."""
