Vectorized implementation of RandomColorDegeneration and Equalization preprocessing layers #2214
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divyashreepathihalli
requested changes
Dec 7, 2023
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There is also one failing test for ragged input - keras_cv/layers/preprocessing/ragged_image_test.py::RaggedImageTest::test_preserves_ragged_status_Equalization - ValueError: Exception encountered when calling layer 'equalization' (type Equalization). |
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I fixed the implementation to support RaggedTensors. The test should be ok now. New colab if needed: https://colab.research.google.com/drive/1uhuApsP8G6k0FYsN4Pw5wDx6X2aptTaN |
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/gcbrun |
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Thank you!! |
divyashreepathihalli
approved these changes
Dec 8, 2023
divyashreepathihalli
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that referenced
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Dec 11, 2023
* Adds Kokoro GPU Tests (#2224) * Adds Kokoro tests * Add Kokoro Tests * Update random_cutout.py to be a subclass of VectorizedBaseImageAugmentationLayer (#2123) * Update random_cutout.py Make RandomCutout a subclass of VectorizedBaseImageAugmentationLayer * Fix RandomCutout for ragged inputs * Fix typo and style * Vectorized implementation of RandomColorDegeneration and Equalization preprocessing layers (#2214) * Vectorize RandomColorDegeneration * Vectorize Equalization * Vectorize Equalization * Fix Equalization for ragged input --------- Co-authored-by: Ramesh Sampath <1437573+sampathweb@users.noreply.github.com> Co-authored-by: SUPERGIU <supergiu@outlook.com>
yuvraj-wale
pushed a commit
to yuvraj-wale/keras-cv
that referenced
this pull request
Feb 8, 2024
… preprocessing layers (keras-team#2214) * Vectorize RandomColorDegeneration * Vectorize Equalization * Vectorize Equalization * Fix Equalization for ragged input
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What does this PR do?
Fixes #2120 (issue)
As Keras_CV==0.7.1, RandomColorDegeneration and Equalization preprocessing layers are not subclasses of
VectorizedBaseImageAugmentationLayer, thus resulting in a slow forward pass.The vectorized implementation of
RandomColorDegenerationis quite straightforward, whileRandomColorDegenerationhas a potential bottleneck represented by tf.histogram_fixed_width.In this pull request I propose an implementation for both layers.
As requested in #2120, these are the demo outputs:
RandomColorDegeneration:
Equalization:
The output of the
Equalizationlayer is deterministic, so the two implementations (original vs vectorized) can be compared withnp.allclose(output_original, output_vectorized), which returnsTrue.Source: https://colab.research.google.com/drive/1t5b4a11ae3HWxUoyL-R50E2z8dkNSQYP
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