Changelog

All notable changes to this project will be documented in this file.

[2.0.0] - 2025-12-01

Intel GPU Support: Added support for Intel Arc and Data Center GPUs using Intel Extension for PyTorch (IPEX).
Unified Device Management: Implemented deoldify.device to automatically detect and manage CUDA, XPU (Intel), and CPU devices.
Documentation:
- docs/nvidia_setup.md: Comprehensive guide for setting up NVIDIA GPUs with CUDA 12.x.
- docs/intel_gpu_setup.md: Guide for setting up Intel GPUs.
Verification Script: Added verify_refactor.py to validate environment setup and model instantiation.
Compatibility Layer: Created deoldify/fastai_compat.py to replace the obsolete fastai 1.x library, ensuring compatibility with modern PyTorch.
Requirements Files: Added requirements.txt and requirements_intel.txt for pip users.
Code Quality:
- Comprehensive module docstring for fastai_compat.py.
- Type hints throughout compatibility layer.
- README badges for Python, PyTorch, CUDA versions, and license.

Core Dependencies:
- Removed dependency on fastai 1.x.
- Upgraded PyTorch to 2.5+.
- Upgraded CUDA support to 12.x.
- Updated environment.yml for modern NVIDIA environments.
- Created environment_intel.yml for Intel environments.
Refactoring:
- Refactored visualize.py, filters.py, generators.py, unet.py, and layers.py to use pure PyTorch and the new compatibility layer.
- Replaced FastAI-specific image processing with standard torchvision transforms.
Device Handling: Updated Learner and DataBunch shims to use the new unified device manager.
.gitignore: Enhanced to exclude model weights in models/ directory, logs, IDE files, and OS-specific files.

Legacy Code: Removed direct imports of fastai throughout the codebase.
Archived Status: The project is now actively maintained for modern hardware.