rgring / weedannotator Goto Github PK

$ 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