Remove scikit image

[ternaus]

Summary by Sourcery

Remove the dependency on scikit-image by implementing custom functions for histogram matching and superpixel segmentation using OpenCV and NumPy. Update related tests to validate the new implementations.

New Features:

• Introduce a custom implementation of histogram matching using OpenCV and NumPy, replacing the previous dependency on scikit-image.

Enhancements:

• Replace the scikit-image SLIC superpixel segmentation with a custom implementation using OpenCV and NumPy.
• Add a custom label function for connected region labeling, mimicking scikit-image's label function using OpenCV.

Tests:

• Add tests for the new histogram matching function to ensure it produces results comparable to the scikit-image implementation.

[sourcery-ai]

Reviewer's Guide by Sourcery

This pull request removes the dependency on scikit-image by implementing custom functions for histogram matching and connected component labeling using OpenCV and NumPy. The changes primarily affect the domain adaptation and superpixel functionality in the Albumentations library.

No diagrams generated as the changes look simple and do not need a visual representation.

File-Level Changes

Change	Details	Files
Replaced scikit-image's histogram matching with a custom implementation	Implemented a custom match_histograms function using OpenCV and NumPy Updated the apply_histogram function to use the new custom implementation Added a helper function _match_cumulative_cdf for histogram matching Updated tests to compare the custom implementation with scikit-image's version	albumentations/augmentations/domain_adaptation/functional.py tests/test_domain_adaptation.py
Replaced scikit-image's SLIC superpixel implementation with a custom one	Implemented a custom slic function using OpenCV and NumPy Updated the superpixels function to use the new custom implementation Removed references to scikit-image in the Superpixels class documentation	albumentations/augmentations/functional.py albumentations/augmentations/transforms.py
Implemented a custom connected component labeling function	Added a new label function in the dropout functional module Updated the MaskDropout transform to use the new custom labeling function	albumentations/augmentations/dropout/functional.py albumentations/augmentations/dropout/mask_dropout.py
Updated imports and removed unused imports	Removed import of match_histograms from skimage.exposure Removed import of NUM_MULTI_CHANNEL_DIMENSIONS Added import of uint8_io from albucore	albumentations/augmentations/domain_adaptation/functional.py

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[sourcery-ai]

Hey @ternaus - I've reviewed your changes and they look great!

Here's what I looked at during the review

• 🟡 General issues: 2 issues found
• 🟢 Security: all looks good
• 🟡 Testing: 3 issues found
• 🟢 Complexity: all looks good
• 🟢 Documentation: all looks good

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