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This repository has been archived by the owner on Mar 21, 2024. It is now read-only.
Traceback (most recent call last):
File "/home/fernando/git/RadiomicsNN/innereye-deeplearning/score.py", line 311, in <module>
main()
File "/home/fernando/git/RadiomicsNN/innereye-deeplearning/score.py", line 307, in main
score_image(ScorePipelineConfig.parse_args())
File "/home/fernando/git/RadiomicsNN/innereye-deeplearning/score.py", line 289, in score_image
segmentation = run_inference(images, inference_pipeline, config)
File "/home/fernando/git/RadiomicsNN/innereye-deeplearning/score.py", line 132, in run_inference
photo_norm_images = [photo_norm.transform(image_with_header.image) for image_with_header in images_with_header]
File "/home/fernando/git/RadiomicsNN/innereye-deeplearning/score.py", line 132, in <listcomp>
photo_norm_images = [photo_norm.transform(image_with_header.image) for image_with_header in images_with_header]
File "/home/fernando/git/RadiomicsNN/innereye-deeplearning/InnerEye/ML/photometric_normalization.py", line 99, in transformself.output_range, self.sharpen, self.tail, self.debug_mode
File "/home/fernando/git/RadiomicsNN/innereye-deeplearning/InnerEye/ML/photometric_normalization.py", line 300, in mri_windowmin(max_foreground, level + tail[ichannel] * std_i * sharpen))
IndexError: list index out of range
I'm not sure what an appropriate solution would be. Maybe just adding a channels dimension at the beginning of PhotometricNormalization.transform and removing it before returning?
I am trying to run inference locally, using the following command:
$ PYTHONPATH=/tmp/Hippocampus_ python \ ~/git/RadiomicsNN/innereye-deeplearning/score.py \ --data_folder /tmp/inputs \ --model_folder /tmp/Hippocampus_ \ --no-use_gpu
I got the following error:
In
photometric_normalization.py
:InnerEye-DeepLearning/InnerEye/ML/photometric_normalization.py
Line 276 in 95d8b72
Hence, this function expects a 4D image with the channels dimension being the first. However, images are loaded in
InnerEye-DeepLearning/InnerEye/ML/utils/io_util.py
Lines 186 to 201 in 95d8b72
which returns a 3D image.
I'm not sure what an appropriate solution would be. Maybe just adding a channels dimension at the beginning of
PhotometricNormalization.transform
and removing it before returning?AB#5331
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