def main():
# Loading Parameters
parser = init_parameters()
args, _ = parser.parse_known_args()
# Updating Parameters (cmd > yaml > default)
args = update_parameters(parser, args)
# Setting save_dir
save_dir = get_save_dir(args)
U.set_logging(save_dir)
with open('{}/config.yaml'.format(save_dir), 'w') as f:
yaml.dump(vars(args), f)
# Processing
if args.generate_data or args.generate_label:
g = Generator(args)
g.start()
elif args.extract or args.visualization:
if args.extract:
p = Processor(args, save_dir)
p.extract()
if args.visualization:
v = Visualizer(args)
v.start()
else:
p = Processor(args, save_dir)
p.start()
def main():
parser = Init_parameters()
# Update parameters by yaml
args = parser.parse_args()
if os.path.exists('/home/aayadi/projet/RA-GCNv22/configs/' + args.config +
'.yaml'):
with open(
'/home/aayadi/projet/RA-GCNv22/configs/' + args.config +
'.yaml', 'r') as f:
yaml_arg = yaml.load(f, Loader=yaml.FullLoader)
default_arg = vars(args)
for k in yaml_arg.keys():
if k not in default_arg.keys():
raise ValueError('Do NOT exist the parameter {}'.format(k))
parser.set_defaults(**yaml_arg)
else:
raise ValueError('Do NOT exist this config: {}'.format(args.config))
# Update parameters by cmd
args = parser.parse_args()
# Show parameters
print('\n************************************************')
print('The running config is presented as follows:')
v = vars(args)
for i in v.keys():
print('{}: {}'.format(i, v[i]))
print('************************************************\n')
# Processing
os.environ['CUDA_VISIBLE_DEVICES'] = ','.join(list(map(str, args.gpus)))
if args.visualization:
if args.extract:
p = Processor(args)
p.extract()
print('Starting visualizing ...')
v = Visualizer(args)
v.show_wrong_sample()
v.show_important_joints()
v.show_heatmap()
v.show_skeleton()
print('Finish visualizing!')
else:
p = Processor(args)
p.start()
def main():
parser = Init_parameters()
# Update parameters by yaml
args = parser.parse_args()
if os.path.exists('./configs/' + args.config + '.yaml'):
with open('./configs/' + args.config + '.yaml', 'r') as f:
yaml_arg = yaml.load(f, Loader=yaml.FullLoader)
default_arg = vars(args)
for k in yaml_arg.keys():
if k not in default_arg.keys():
raise ValueError('Do NOT exist the parameter {}'.format(k))
parser.set_defaults(**yaml_arg)
else:
raise ValueError('Do NOT exist this config: {}'.format(args.config))
# Update parameters by cmd
args = parser.parse_args()
# Show parameters
print('\n************************************************')
#if type(args.gpus) == int:
# n = args.gpus
# if n == 4:
# args.gpus = [0, 1, 2, 3]
# else:
# args.gpus = [0]
print('The running config is presented as follows:')
print_default_keys = ['config', 'batch_size', 'pretrained', 'model_stream']
print_eval_keys = [
'occlusion_part', 'occlusion_time', 'occlusion_block',
'occlusion_rand', 'jittering_joint', 'jittering_frame', 'sigma'
]
v = vars(args)
if '-g' in sys.argv or '--gpus' in sys.argv:
aa = args.gpus
args.gpus = [int(x) for x in aa.split(',')]
else:
if node == 'obama':
args.gpus = [0, 1, 2, 3]
elif node == 'puma':
args.gpus = [0]
else:
args.gpus = [0]
for i in v.keys():
if i in print_default_keys:
print('{}: {}'.format(i, v[i]))
if args.evaluate:
for i in v.keys():
if i in print_eval_keys:
if v[i]:
print('{}: {}'.format(i, v[i]))
print('************************************************\n')
# Processing
os.environ['CUDA_VISIBLE_DEVICES'] = ','.join(list(map(str, args.gpus)))
if args.visualization:
if args.extract:
p = Processor(args)
p.extract()
print('Starting visualizing ...')
v = Visualizer(args)
v.show_wrong_sample()
v.show_important_joints()
v.show_heatmap()
v.show_skeleton()
print('Finish visualizing!')
else:
if args.baseline:
p = Processor_BS(args)
else:
p = Processor(args)
p.start()
