skip_frame = int(sys.argv[6])
# the foldername containing trained models
if layers[0] > 0:
cae_folder_name = sys.argv[7]
else:
cae_folder_name = None
train_flag = int(sys.argv[8])
print('layers:', layers)
print('layers_with_clusters:', layers_with_clusters)
print('direction:', direction)
print('cae_folder_name:', cae_folder_name)
print('train_flag:', train_flag)
params = ParamManager()
# experiment parameters
if train_flag == 0:
train_str = 'train'
elif train_flag == 1:
train_str = 'all1'
if skip_frame < 0:
if data_str in ['Avenue', 'Avenue_sz240x360fr1', 'UCSDped1']:
skip_frame = 2
else:
skip_frame = 1
print('skip_frame = %d\n' % skip_frame)
bshow = 1
bh5py = 1
if len(sys.argv) >= 6:
cae_folder_name = sys.argv[5]
else:
cae_folder_name = None
# the folder name of trained low-level GANs
if len(sys.argv) >= 7:
gan0_folder_name = sys.argv[6]
else:
gan0_folder_name = None
else:
raise ValueError("Please provide some arguments")
mode_explain = ['FtoM', 'MtoF']
params = ParamManager()
# experiment parameters
data_range = [-1.0, 1.0]
print('Mode: %d' % mode)
print('layers: ', layers)
print('layers_with_cluster', layers_with_cluster)
print('cae_folder_name', cae_folder_name)
print('gan0_folder_name', gan0_folder_name)
train_str = 'train'
test_str = 'test'
bshow = 1
bsave = 1
else:
mode = 0
data_str = 'UCSDped2'
batch_size = 100
encoder_dims = [32, 16, 8]
disp_freq = 10
save_freq = 10
num_epochs = 500
device = '/cpu:0'
print('mode = %d' % mode)
print('data_str = %s' % data_str)
print('batch_size = %d' % batch_size)
print('encoder_dims :', encoder_dims)
params = ParamManager()
train_str = 'train'
bshow = 1
bh5py = 1
frame_step = 5
params.add('mode', mode, 'hvad_cae')
params.add('data_str', data_str, 'hvad_cae')
params.add('train_str', train_str, 'hvad_cae')
params.add('bshow', bshow, 'hvad_cae')
params.add('bh5py', bh5py, 'hvad_cae')
params.add('frame_step', frame_step, 'hvad_cae')
params.add('batch_size', batch_size, 'hvad_cae')
params.add('encoder_dims', encoder_dims, 'hvad_cae')
# a file contains a list of testing videos
test_str = sys.argv[4]
else:
raise ValueError("Please provide the arguments")
gan_layer0_folder_name = 'hvad-gan-layer0-v5-brox'
layer_ids = [int(s) for s in layer_id_str.split('-')]
print('data_str=%s' % data_str)
print('layer_ids=',layer_ids)
print('cae_folder_name = %s' % cae_folder_name)
print('test_str = %s' % test_str)
print('use_gt = %d' % use_gt)
print('gan_layer0_folder_name = %s' % gan_layer0_folder_name)
params = ParamManager()
# experiment parameters
data_range = [-1.0, 1.0]
net_str = cae_folder_name.split(sep='-lrelu')
net_str = net_str[0]
net_str = net_str.replace('hvad-', '')
# layer = 0
layer_with_cluster = False
bh5py = 1
resz = [256, 256]
fr_rate_2obj = 0.1 # best for UCSDped1, UCSDped2 and Avenue
thresh = 0.8