Comments (5)
Can you try by disabling resizing?
Update: instead of [3,128,128]
, use [128,128]
. The reason behind this is that ITK reads multi-channel images as vector pixel types, and the vector dimension is not needed for processing (it is automatically handled via ITK's processing routines).
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Hey @orhunguley,
This is a great report, and allowed me to recreate the issue perfectly. I am hoping that I can solve it quickly and put in a PR.
Cheers!
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Can you try pulling from https://github.com/sarthakpati/GaNDLF/tree/100_rgb_fix to see if this fixes your problem?
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Hi Sarthak,
I got the following error with 100_rgb_fix branch:
Traceback (most recent call last):
File "gandlf_run", line 157, in <module>
main()
File "gandlf_run", line 143, in main
reset_prev=reset_prev,
File "/home/orhunguley/Git/GanDLF_forked/GaNDLF/GANDLF/training_manager.py", line 242, in TrainingManager
testing_data=testingData,
File "/home/orhunguley/Git/GanDLF_forked/GaNDLF/GANDLF/training_loop.py", line 654, in training_loop
training_data_for_torch = ImagesFromDataFrame(training_data, params, train=True)
File "/home/orhunguley/Git/GanDLF_forked/GaNDLF/GANDLF/data/ImagesFromDataFrame.py", line 271, in ImagesFromDataFrame
img_resized = apply_resize(img, preprocessing_params=preprocessing)
File "/home/orhunguley/Git/GanDLF_forked/GaNDLF/GANDLF/preprocessing.py", line 87, in apply_resize
resize_image_resolution(input, preprocessing_params["resize"]),
File "/home/orhunguley/Git/GanDLF_forked/GaNDLF/GANDLF/preprocessing.py", line 77, in resize_image_resolution
outputSpacing[i] = outputSpacing[i] * (inputSize[i] / output_size[i])
IndexError: index 2 is out of bounds for axis 0 with size 2
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Hi @sarthakpati,
Thanks, with setting [128, 128] the issue is solved now!
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Related Issues (20)
- Black configuration in pyproject.toml
- [FEATURE] Add the ability to split CSVs for training/validation/testing as a separate script HOT 1
- [FEATURE] Add the ability to generate training/validation/testing CSV with proportional splits HOT 1
- [FEATURE] Add tensorboard support HOT 2
- [FEATURE] speed up CI tests HOT 3
- [BUG] Moving from version `0.0.XX` to `0.Y.0` creates compatibility issues. HOT 2
- [FEATURE] Add a "migration guide" in documentation HOT 2
- [BUG] Trying to train a model for classification gives a weird warning HOT 1
- [FEATURE] Standardize the CLI option for output directory HOT 1
- [BUG] Loss signatures: CE Loss failure because of additional `params` argument HOT 2
- [FEATURE] Upgrade PyTorch to 2.2.1 HOT 2
- [BUG] Noise and Blur enhanced fail for certain images
- [BUG] final_preds_and_avg_probs.csv file is not generated after inference HOT 6
- [FEATURE] Include the output of `pip list` for debug info HOT 1
- [FEATURE] add the nadam optimizer
- [FEATURE] Update to new docker-py dependency once released HOT 3
- [FEATURE] Add Docker Compose HOT 4
- [BUG] dice_per_label metric fails HOT 1
- [FEATURE] Update PyTorch dependency HOT 9
- [FEATURE] add function to retrieve augmentations from config HOT 1
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