Update sharpen

[ternaus]

Addresses: #2110

Summary by Sourcery

Enhance the Sharpen transform by adding support for a Gaussian interpolation method alongside the existing kernel-based method. Update the transform's parameters to accommodate the new method, including options for kernel size and sigma. Implement a new function, sharpen_gaussian, to apply the Gaussian sharpening technique.

New Features:

• Introduce a new sharpening method using Gaussian interpolation in the Sharpen transform.

Enhancements:

• Refactor the Sharpen transform to support multiple sharpening methods, including kernel-based and Gaussian interpolation.

[sourcery-ai]

Reviewer's Guide by Sourcery

This PR enhances the Sharpen transform by introducing two different sharpening methods: a traditional kernel-based approach using Laplacian operator and a new Gaussian interpolation method. The implementation includes updated parameters, improved documentation, and a new functional method for Gaussian sharpening.

Updated class diagram for Sharpen transform

classDiagram
    class Sharpen {
        +tuple[float, float] alpha
        +tuple[float, float] lightness
        +Literal["kernel", "gaussian"] method
        +int kernel_size
        +float sigma
        +get_params() dict[str, Any]
        +apply(np.ndarray img, float alpha, np.ndarray|None sharpening_matrix, **params) np.ndarray
        +get_transform_init_args_names() tuple[str, ...]
    }
    note for Sharpen "Added method, kernel_size, and sigma attributes. Updated apply and get_params methods."

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File-Level Changes

Change	Details	Files
Added a new Gaussian interpolation sharpening method alongside the existing kernel-based approach	Added 'method' parameter to select between 'kernel' and 'gaussian' approaches Introduced new parameters 'kernel_size' and 'sigma' for Gaussian method Updated get_params() to handle both sharpening methods Modified apply() to support both sharpening implementations	albumentations/augmentations/transforms.py
Implemented new Gaussian sharpening functionality	Added sharpen_gaussian function using OpenCV's GaussianBlur Implemented weighted addition of original and blurred images	albumentations/augmentations/functional.py
Enhanced documentation and validation	Added comprehensive mathematical formulations for both sharpening methods Updated docstring with detailed explanations and examples Added validation for kernel size to ensure odd values Expanded references section with relevant literature	albumentations/augmentations/transforms.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: 1 issue found
• 🟢 Security: all looks good
• 🟢 Testing: all looks good
• 🟡 Complexity: 1 issue found
• 🟢 Documentation: all looks good

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[codecov]

Codecov Report

Attention: Patch coverage is 81.48148% with 5 lines in your changes missing coverage. Please review.

Project coverage is 90.16%. Comparing base (b1a79c2) to head (e2c1c73).
Report is 282 commits behind head on main.

Files with missing lines	Patch %	Lines
albumentations/augmentations/transforms.py	86.95%	3 Missing ⚠️
albumentations/augmentations/functional.py	50.00%	2 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff            @@
##           main    #2150       +/-   ##
=========================================
+ Coverage      0   90.16%   +90.16%     
=========================================
  Files         0       48       +48     
  Lines         0     8267     +8267     
=========================================
+ Hits          0     7454     +7454     
- Misses        0      813      +813     

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