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When I run train.py or evaluate.py, the script always fails, probably because there is no pre-trained LayoutNet model for LayoutFID computation. Is it possible to share the weights?
Evaluating metrics...
Traceback (most recent call last):
File "train.py", line 313, in <module>
main() # pylint: disable=no-value-for-parameter
File "/home/jupyter/tmp/conda_envs/layoutdetr/lib/python3.8/site-packages/click/core.py", line 1128, in __call__
return self.main(*args, **kwargs)
File "/home/jupyter/tmp/conda_envs/layoutdetr/lib/python3.8/site-packages/click/core.py", line 1053, in main
rv = self.invoke(ctx)
File "/home/jupyter/tmp/conda_envs/layoutdetr/lib/python3.8/site-packages/click/core.py", line 1395, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/home/jupyter/tmp/conda_envs/layoutdetr/lib/python3.8/site-packages/click/core.py", line 754, in invoke
return __callback(*args, **kwargs)
File "train.py", line 308, in main
launch_training(c=c, desc=desc, outdir=opts.outdir, dry_run=opts.dry_run)
File "train.py", line 99, in launch_training
subprocess_fn(rank=0, c=c, temp_dir=temp_dir)
File "train.py", line 47, in subprocess_fn
training_loop.training_loop(rank=rank, **c)
File "/home/jupyter/pending/LayoutDETR/training/training_loop.py", line 419, in training_loop
result_dict = metric_main.calc_metric(metric=metric, run_dir=run_dir, G=snapshot_data['G_ema'],
File "/home/jupyter/pending/LayoutDETR/metrics/metric_main.py", line 53, in calc_metric
results = _metric_dict[metric](opts)
File "/home/jupyter/pending/LayoutDETR/metrics/metric_main.py", line 93, in layout_fid50k_train
layout_fid = layout_frechet_inception_distance.compute_layout_fid(opts, max_real=None, num_gen=50000)
File "/home/jupyter/pending/LayoutDETR/metrics/layout_frechet_inception_distance.py", line 25, in compute_layout_fid
mu_real, sigma_real = metric_utils_layout.compute_feature_stats_for_dataset(
File "/home/jupyter/pending/LayoutDETR/metrics/metric_utils_layout.py", line 230, in compute_feature_stats_for_dataset
detector_obj = get_feature_detector(pth=detector_pth, device=opts.device, num_gpus=opts.num_gpus, rank=opts.rank, verbose=progress.verbose)
File "/home/jupyter/pending/LayoutDETR/metrics/metric_utils_layout.py", line 53, in get_feature_detector
_feature_detector_cache[key] = LayoutFID(pth, device)
File "/home/jupyter/pending/LayoutDETR/metrics/metric_layoutnet.py", line 32, in __init__
state_dict = torch.load(pth, map_location=device)
File "/home/jupyter/tmp/conda_envs/layoutdetr/lib/python3.8/site-packages/torch/serialization.py", line 699, in load
with _open_file_like(f, 'rb') as opened_file:
File "/home/jupyter/tmp/conda_envs/layoutdetr/lib/python3.8/site-packages/torch/serialization.py", line 230, in _open_file_like
return _open_file(name_or_buffer, mode)
File "/home/jupyter/tmp/conda_envs/layoutdetr/lib/python3.8/site-packages/torch/serialization.py", line 211, in __init__
super(_open_file, self).__init__(open(name, mode))
FileNotFoundError: [Errno 2] No such file or directory: 'pretrained/layoutnet_ads_banner_dataset.pth.tar'
The text was updated successfully, but these errors were encountered:
When I run
train.py
orevaluate.py
, the script always fails, probably because there is no pre-trained LayoutNet model for LayoutFID computation. Is it possible to share the weights?The text was updated successfully, but these errors were encountered: