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Refactor: commented out ViT-related mentions in files #223

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merged 5 commits into from
Jul 30, 2024

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rizoudal
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This pull request addresses issue #220.

Changes made:

  • Commented out all ViT-related mentions in files.
  • Commented out ViT-related unittests.
  • Removed vit-keras dependency from requirements.txt.

Files modified:

  • README.md
  • aucmedi/neural_network/architectures/image/__init__.py
  • requirements.txt
  • setup.py
  • tests/test_architectures_image.py

Please review the changes and let me know if there are any questions or further adjustments needed.

@muellerdo muellerdo self-requested a review July 14, 2024 19:25
@muellerdo muellerdo self-assigned this Jul 14, 2024
@muellerdo
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Nice PR, thanks!

Two more things:

  1. Replace tensorflow addons with direct tensorflow imports
    -> F1 in AutoML scripts: from tensorflow_addons.metrics import F1Score
  2. There is a IndentationError in the unittesting for image architectures:
E     File "/home/runner/work/aucmedi/aucmedi/tests/test_architectures_image.py", line 749
E       def test_ConvNeXtBase(self):
E   IndentationError: unexpected indent

BR DM

README.md Outdated
@@ -14,7 +14,7 @@ The open-source software AUCMEDI allows fast setup of medical image classificati
- Wide range of 2D/3D data entry options with interfaces to the most common medical image formats such as DICOM, MetaImage, NifTI, PNG or TIF already supplied.
- Selection of pre-processing methods for preparing images, such as augmentation processes, color conversions, windowing, filtering, resizing and normalization.
- Use of deep neural networks for binary, multi-class as well as multi-label classification and efficient methods against class imbalances using modern loss functions such as focal loss.
- Library from modern architectures, like ResNet up to EfficientNet and Vision-Transformers (ViT)⁠.
- Library from modern architectures, like ResNet up to EfficientNet. <!-- and Vision-Transformers (ViT)⁠.-->
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ConvNeXt

- commented out ViT-related unittests to avoid IndentationError
- Updated README (from Architecture EfficientNet to Architecture ConvNeXt)
- Removed tensorflow-addons from requirements.txt and setup.py
- Changed import of F1Score in file aucmedi/automl/block_train.py
requirements.txt Outdated
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Here, the commented vit-keras is missing, but is fine and could be added later if vit-keras gets hopefully an update in the future.

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Changes looking good. Waiting for the CI action checks.

rizoudal added 2 commits July 17, 2024 12:26
…quirements.txt

- Removed num_classes parameter from F1Score in the AutoML training block to align with updated tf.keras
- Added and commented out vit-keras in requirements.txt
@muellerdo muellerdo merged commit 84902ee into frankkramer-lab:development Jul 30, 2024
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Nice! Requirements are running through :)
Merging to dev, great work! Thank you.

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2 participants