AnomalyMatch v1.3.0

[v1.3.0] – 2026-02-13

Added

• Multispectral image support for arbitrary channel count images with configurable channel_combination matrices
• UI separation into standalone anomaly_match_ui package for cleaner architecture
• Flux conversion configuration (apply_flux_conversion) ensuring training/prediction consistency
• timm model backend replacing efficientnet-specific packages for broader model support
• test-cnn model for fast unit/integration testing without heavy model downloads

Changed

• Replaced black and flake8 with ruff for linting and formatting
• Restructured test suite into unit/integration/e2e/ui directories with pytest markers and CI caching
• Deduplicated prediction code into shared prediction_utils.py module
• Auto-inference of n_output_channels from channel_combination matrix or FITS extension count
• PIL resize for CONVERSION_ONLY normalisation achieving up to 73x faster image loading
• Faster catalogue validation by skipping per-chunk FITS existence checks and using parquet metadata

Fixed

• Double normalisation in cutana streaming pipeline
• Normalisation consistency between cutana and training paths with channel_weights passthrough
• Session logging with eager directory creation and per-session log files
• Gallery not updating after prediction chunks complete
• Cutana source ID handling for non-string int64 source_ids
• Albumentations 2.0 compatibility renaming deprecated mode to border_mode
• Prediction progress bar with phase tracking for better user feedback
• Identity channel_combination auto-creation for multi-extension FITS configs
• ASinh parameters missing in cutana format config
• Filter name resolution from catalogue for cutana streaming
• Primary HDU validation raising ValueError when no image data found

Documentation

• Normalisation README with improved channel_combination and flux conversion documentation
• Auto-inference documentation updating multispectral config examples

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AnomalyMatch v1.2.0

[v1.2.0] – 2025-01-22

Added

• Cutana streaming integration for catalogue-based predictions with parquet and CSV support
• FitsBolt integration for consistent FITS normalization across training and prediction
• Iteration score storage for tracking unlabeled and test data scores per iteration
• Automatic batch size estimation using exponential and binary search for optimal GPU memory usage
• Full resolution image preview button in the UI for detailed inspection
• Dead code detection CI workflow using Vulture for codebase maintenance

Changed

• Refactored Widget architecture by extracting PreviewWidget for better code organization
• FitsBolt config persistence in model checkpoints for reproducible normalization
• Parquet format for Cutana buffer instead of CSV for improved performance
• Black line-length updated to 100 characters for better readability

Fixed

• Gallery filename display for long filenames with improved shortening (#237)
• Duplicate result accumulation in prediction process (#238)
• Error handling for iteration score CSV saves (#236)
• FITS extension handling in Cutana streaming
• Tensor handling improvements throughout the codebase

Removed

• Dead code cleanup removing unused functions and imports identified by Vulture
• IDE/editor files from repository with updated .gitignore

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AnomalyMatch v1.1.0

[v1.1.0] – 2025-07-07

Added

• Zarr file format support for scalable array storage and processing
• Session tracking and management with comprehensive iteration history
• Metadata handling for associating metadata with images in labeled_data.csv
• Configuration validation to ensure proper setup before training
• Label caching for improved performance in active learning loops
• Unlabeling functionality allowing users to remove labels from images
• Interpolation order configuration for image resizing operations
• ASinh normalization with grayscale/multichannel and RGB functionality

Changed

• Improved UI responsiveness with optimized image loading and display
• Enhanced session saving to capture training results and configurations
• Streamlined prediction process with better file type detection
• Reduced logging verbosity to minimize output spam
• Unified image resizing to use BILINEAR interpolation consistently
• Improved error handling for insufficient labeled data scenarios
• Better memory management in prediction processes

Fixed

• RGB display reset when using brightness/contrast sliders
• Train iterations slider usability issues
• Test ratio image reading bugs
• Cached image normalization not updating after training
• Channel ordering in TurboJPEG decoded files
• CPU fallback when CUDA is not available
• NaN/inf value handling in image processing
• Top image preservation across prediction batches
• Label count display in UI

Removed

• ZIP file support (kept for benchmarking, removed from prediction process)
• Redundant configuration options and deprecated functions

Performance

• Faster label lookups through intelligent caching mechanisms
• Optimized batch processing for HDF5 and Zarr formats
• Reduced memory usage in prediction workflows
• Improved UI responsiveness in ESA Datalabs environment

v1.0.0

Initial release of the AnomalyMatch software