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📖 Add example usage script
- Demonstrates BYOL model loading and feature extraction
- Shows preprocessing pipeline for inference
- Includes batch processing examples
- Feature similarity computation example
- Complete documentation for model usage
Ready-to-use code for:
✅ Loading pre-trained BYOL model
✅ Feature extraction from mammogram tiles
✅ Batch processing capabilities
✅ Downstream task preparation -
🏥 Add BYOL Mammogram Classification Model
- Self-supervised BYOL pre-training for mammogram analysis
- ResNet50 backbone with medical-optimized augmentations
- Aggressive background rejection and intelligent tissue segmentation
- A100 GPU optimized training with mixed precision
- Complete model checkpoints: best and final weights
- Classification fine-tuning pipeline with inference script
- Comprehensive model card and usage documentation
Key Features:
✅ Medical-grade tile extraction (512x512px)
✅ Multi-level background filtering
✅ BYOL self-supervised learning
✅ Ready for downstream classification tasks
✅ Clinical-safe augmentation strategy
Model weights: 528MB total (best + final checkpoints)
Training: 100 epochs on high-quality breast tissue tiles -
initial commit
