Add illumination

[ternaus]

Summary by Sourcery

Add a new Illumination transform to the library, allowing users to simulate various lighting conditions on images. Update the README to include documentation for this new feature and add corresponding tests to validate its implementation.

New Features:

• Introduce the Illumination transform to apply various illumination effects to images, simulating different lighting conditions such as directional lighting, corner shadows, and spotlights.

Documentation:

• Add documentation for the new Illumination transform in the README, including a link to its detailed description.

Tests:

• Add test definitions for the new Illumination transform to ensure its functionality.

[sourcery-ai]

Reviewer's Guide by Sourcery

This PR introduces a new image augmentation transform called 'Illumination' that simulates various lighting effects. The implementation includes three different illumination modes (linear, corner, and gaussian) with configurable parameters for intensity, angle, position, and effect type. The transform is integrated into the albumentations library with proper documentation, type hints, and test coverage.

Class diagram for the new Illumination transform

classDiagram
    class Illumination {
        +Illumination(mode: Literal["linear", "corner", "gaussian"] = "linear", intensity_range: tuple[float, float] = (0.01, 0.2), effect_type: Literal["brighten", "darken", "both"] = "both", angle_range: tuple[float, float] = (0, 360), center_range: tuple[float, float] = (0.1, 0.9), sigma_range: tuple[float, float] = (0.2, 1.0), always_apply: bool = False, p: float = 0.5)
        +get_params() dict[str, Any]
        +apply(img: np.ndarray, **params: Any) np.ndarray
        +get_transform_init_args_names() tuple[str, ...]
    }
    class BaseTransformInitSchema {
    }
    Illumination --|> ImageOnlyTransform
    Illumination : +mode
    Illumination : +intensity_range
    Illumination : +effect_type
    Illumination : +angle_range
    Illumination : +center_range
    Illumination : +sigma_range
    Illumination : +p
    Illumination : +InitSchema
    class InitSchema {
        +mode: Literal["linear", "corner", "gaussian"]
        +intensity_range: Annotated[tuple[float, float], AfterValidator]
        +effect_type: Literal["brighten", "darken", "both"]
        +angle_range: Annotated[tuple[float, float], AfterValidator]
        +center_range: Annotated[tuple[float, float], AfterValidator]
        +sigma_range: Annotated[tuple[float, float], AfterValidator]
    }
    InitSchema --|> BaseTransformInitSchema
    note for Illumination "This class simulates various lighting effects on images."

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Class diagram for the new functional methods

classDiagram
    class Functional {
        +apply_linear_illumination(img: np.ndarray, intensity: float, angle: float) np.ndarray
        +apply_corner_illumination(img: np.ndarray, intensity: float, corner: int) np.ndarray
        +apply_gaussian_illumination(img: np.ndarray, intensity: float, center: tuple[float, float], sigma: float) np.ndarray
    }
    note for Functional "These methods apply different illumination effects to images."

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File-Level Changes

Change	Details	Files
Added new Illumination transform class with comprehensive configuration options	Implemented three illumination modes: linear (directional lighting), corner (corner shadows/highlights), and gaussian (spotlights) Added configurable parameters for intensity, effect type (brighten/darken), angle range, center position, and sigma Included detailed documentation with examples and references Added type validation using InitSchema	albumentations/augmentations/transforms.py
Implemented core illumination effect functions	Created apply_linear_illumination for directional gradient effects Added apply_corner_illumination for corner-based lighting Implemented apply_gaussian_illumination for spotlight effects Added clipping decorator to ensure proper image value ranges	albumentations/augmentations/functional.py
Updated project documentation and test configuration	Added Illumination to the list of available transforms in README.md Included Illumination in the test definitions	README.md tests/aug_definitions.py

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[sourcery-ai]

Hey @ternaus - I've reviewed your changes and found some issues that need to be addressed.

Blocking issues:

• Missing dedicated test file for the new Illumination transform (link)

Here's what I looked at during the review

• 🟡 General issues: 1 issue found
• 🟢 Security: all looks good
• 🔴 Testing: 1 blocking issue
• 🟡 Complexity: 1 issue found
• 🟢 Documentation: all looks good

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[codecov]

Codecov Report

Attention: Patch coverage is 62.19512% with 31 lines in your changes missing coverage. Please review.

Project coverage is 90.04%. Comparing base (b1a79c2) to head (ea19449).
Report is 287 commits behind head on main.

Files with missing lines	Patch %	Lines
albumentations/augmentations/functional.py	52.50%	19 Missing ⚠️
albumentations/augmentations/transforms.py	71.42%	12 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff            @@
##           main    #2155       +/-   ##
=========================================
+ Coverage      0   90.04%   +90.04%     
=========================================
  Files         0       48       +48     
  Lines         0     8481     +8481     
=========================================
+ Hits          0     7637     +7637     
- Misses        0      844      +844     

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

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