Speed up elastic

[ternaus]

Summary by Sourcery

Improve the performance and memory efficiency of the elastic transform by optimizing displacement field generation and map creation. Use vectorized operations and in-place modifications to reduce memory usage and speed up computations.

Enhancements:

• Optimize displacement field generation for elastic transform.
• Vectorize map coordinate calculations for elastic transform.

Tests:

• Add comprehensive tests for the elastic transform displacement field generation, including parameter variations, reproducibility checks, blur effect verification, and memory efficiency tests.

[sourcery-ai]

Reviewer's Guide by Sourcery

This pull request focuses on optimizing the generate_displacement_fields function in functional.py for improved performance and memory efficiency. It also includes comprehensive tests to ensure the correctness of the implementation.

Sequence diagram for optimized elastic transform

sequenceDiagram
    participant M as Main Process
    participant G as Random Generator
    participant B as Gaussian Blur
    M->>G: Request noise fields
    G-->>M: Return pre-allocated fields
    M->>B: Apply blur to all fields at once
    B-->>M: Return blurred fields
    Note over M: Scale fields by alpha
    Note over M: Return field views

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Flow diagram for optimized elastic transform process

flowchart TD
    A[Start] --> B[Generate Fields]
    B --> C{Same DXDY?}
    C -->|Yes| D[Generate single field]
    C -->|No| E[Generate two fields]
    D --> F[Apply Gaussian Blur]
    E --> F
    F --> G[Scale by Alpha]
    G --> H[Return displacement fields]
    H --> I[End]

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File-Level Changes

Change	Details	Files
Optimized displacement field generation	Pre-allocate memory for noise fields. Generate and normalize noise in a single step. Apply Gaussian blur using fast OpenCV operations. Return views of the array to avoid copies.	albumentations/augmentations/geometric/functional.py
Added comprehensive tests for displacement field generation	Added tests for various image shapes, alpha values, sigma values, and kernel sizes. Added tests for both gaussian and uniform noise distributions. Added tests for same_dxdy behavior. Added tests for alpha scaling. Added tests for value ranges for uniform distribution. Added tests for reproducibility. Added tests to ensure that Gaussian blur is actually smoothing the displacement field. Added tests to ensure memory efficiency.	tests/functional/test_geometric.py
Vectorized map generation in ElasticTransform	Use np.meshgrid and np.stack to generate coordinate maps. Avoid explicit loops for map generation.	albumentations/augmentations/geometric/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: all looks good
• 🟢 Security: all looks good
• 🟡 Testing: 1 issue found
• 🟢 Complexity: all looks good
• 🟢 Documentation: all looks good

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