Update corner illumination

[ternaus]

Summary by Sourcery

Enhance the corner illumination functionality by optimizing the apply_corner_illumination function for efficiency and adding extensive tests to ensure correct behavior across various scenarios.

Enhancements:

• Optimize the apply_corner_illumination function by pre-computing diagonal length and using distance transform for efficiency.

Tests:

• Add comprehensive tests for corner illumination, including tests for brightest point, shape and type preservation, intensity range, identity with zero intensity, symmetry, and multichannel consistency.

[sourcery-ai]

Reviewer's Guide by Sourcery

This pull request introduces new test cases for the corner illumination feature, ensuring its correctness and robustness. Additionally, the apply_corner_illumination function has been refactored for improved performance and maintainability, utilizing OpenCV's distanceTransform and optimizing pattern creation.

Sequence diagram for the updated corner illumination process

sequenceDiagram
    participant C as Client
    participant AI as apply_corner_illumination
    participant CV as OpenCV

    C->>AI: apply_corner_illumination(img, intensity, corner)
    alt intensity == 0
        AI-->>C: return img.copy()
    else intensity != 0
        AI->>AI: Calculate diagonal_length
        AI->>AI: Create mask (uint8)
        AI->>CV: distanceTransform(mask)
        CV-->>AI: pattern
        AI->>CV: multiply(pattern, -intensity/diagonal_length)
        AI->>CV: add(pattern, 1)
        alt Multi-channel image
            AI->>CV: merge([pattern] * channels)
        end
        AI->>AI: multiply_by_array(img, pattern)
        AI-->>C: return result
    end

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Flow diagram for corner illumination algorithm

flowchart TD
    A[Start] --> B{intensity == 0?}
    B -->|Yes| C[Return copy of input image]
    B -->|No| D[Calculate diagonal length]
    D --> E[Create uint8 mask]
    E --> F[Set corner point to 0]
    F --> G[Apply distance transform]
    G --> H[Scale pattern by intensity]
    H --> I[Normalize pattern]
    I --> J{Is multi-channel?}
    J -->|Yes| K[Replicate pattern for each channel]
    J -->|No| L[Use pattern as is]
    K --> M[Multiply image by pattern]
    L --> M
    M --> N[Return result]

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File-Level Changes

Change	Details	Files
Added new test cases for corner illumination functionality.	Added test for brightest point in corner illumination. Added test to ensure shape and type preservation in corner illumination. Added test for intensity range in corner illumination. Added test for zero intensity identity in corner illumination. Added test for symmetry in corner illumination. Added test for multichannel consistency in corner illumination.	tests/functional/test_functional.py
Refactored apply_corner_illumination function to improve performance and maintainability.	Removed unnecessary conditional checks by using array indexing for corner selection. Replaced manual distance calculation with OpenCV's distanceTransform for efficiency. Optimized pattern creation by combining operations to reduce array copies. Ensured multichannel images are handled by merging patterns across channels.	albumentations/augmentations/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: all looks good
• 🟢 Security: all looks good
• 🟡 Testing: 1 issue found
• 🟢 Complexity: all looks good
• 🟢 Documentation: all looks good

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