rgring / weedannotator Goto Github PK
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License: BSD 3-Clause "New" or "Revised" License
The Segmentation training fails with the following output:
$ python3 -m weed_annotator.full_pipeline.run_full_pipeline
2023-04-13 15:03:05,730 Generating image compositions for training.
2023-04-13 15:03:24,496 Training semantic segmentation model on: sample_data/synthetic_imgs/10_no_leave_augmentations.
Downloading: "https://download.pytorch.org/models/resnet18-5c106cde.pth" to /home/dennis/.cache/torch/hub/checkpoints/resnet18-5c106cde.pth
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 44.7M/44.7M [00:03<00:00, 13.8MB/s]
Traceback (most recent call last):
File "~/anaconda3/envs/weedannotator/lib/python3.6/runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "~/anaconda3/envs/weedannotator/lib/python3.6/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "~/WeedAnnotator/weed_annotator/full_pipeline/run_full_pipeline.py", line 48, in <module>
train(train_config)
File "~/WeedAnnotator/weed_annotator/semantic_segmentation/train.py", line 73, in train
train_loader = DataLoader(train_dataset, batch_size=config["training"]["batch_size"], shuffle=True, num_workers=1)
File "~/anaconda3/envs/weedannotator/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 262, in __init__
sampler = RandomSampler(dataset, generator=generator) # type: ignore
File "~/anaconda3/envs/weedannotator/lib/python3.6/site-packages/torch/utils/data/sampler.py", line 104, in __init__
"value, but got num_samples={}".format(self.num_samples))
ValueError: num_samples should be a positive integer value, but got num_samples=0
We tried to run the sample (unchanged from this repository) in a docker container using python 3.6, a venv using python 3.6 as well as in a conda environment. Same Issue everytime. Possible Issue with the DataLoader?
It seems like the generated images are not forwarded to be reused in training. Are we supposed to make changes to the config?
Hi, your project WeedAnnotator(commit id: a56d6d4) requires "catalyst==20.10.1" in its dependency. After analyzing the source code, we found that the following versions of catalyst can also be suitable, i.e., catalyst 20.10, since all functions that you directly (2 APIs: catalyst.runners.runner.Runner.init, catalyst.metrics.iou.iou) or indirectly (propagate to 8 catalyst's internal APIs and 6 outsider APIs) used from the package have not been changed in these versions, thus not affecting your usage.
Therefore, we believe that it is quite safe to loose your dependency on catalyst from "catalyst==20.10.1" to "catalyst>=20.10,<=20.10.1". This will improve the applicability of WeedAnnotator and reduce the possibility of any further dependency conflict with other projects.
May I pull a request to further loosen the dependency on catalyst?
By the way, could you please tell us whether such an automatic tool for dependency analysis may be potentially helpful for maintaining dependencies easier during your development?
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