- Replace 'mps' with 'coreml' as the identifier for Apple CoreML Execution Provider across the codebase.
- Remove Apple chip generation checks and ensure CoreML is available on all macOS arm64 devices.
- Adjust ONNX Runtime session creation to use default CoreML configurations without forcing 'MLProgram'.
- Implement support for MoGe-2 to utilize CoreML with static input shape requirements.
- Enhance server panel to display restart and stop controls consistently across running states, including 'BUSY'.
- Update UI tests to verify new behavior for server controls and cached model display.
- Bump blendjob dependency version to 0.1.16 in packaging tests and configurations.
- Introduced a new design for selection rasterization that decouples the selection geometry from the image content, ensuring that the SelectionMask is independent of the source image's alpha and color.
- Updated the `rasterize_selection_path` function to only accept selection paths and image dimensions, removing parameters related to source alpha and alpha thresholds.
- Implemented a new approach for handling selection paths using non-zero winding fill, ensuring overlapping areas are preserved.
- Enhanced performance by utilizing a scanline algorithm for rasterization, significantly reducing processing time for high-resolution images.
- Updated internal documentation and added comprehensive tests to validate the new behavior and performance improvements.
- Ensured backward compatibility by maintaining existing interfaces where necessary while introducing breaking changes in the selection processing logic.
- Implemented viewport.py for handling 3D view projections, gestures, and overlay drawing.
- Created refine_image_selection.py to manage the refinement of gesture masks and output image bounds.
- Added selection module with refine_selection.py to process and crop images based on alpha channel visibility.
- Introduced __init__.py for selection module to expose refine_selection function.
- Implement sync_models.py for preparing and uploading ONNX artifacts.
- Create build_node.py for building and validating Blender scripts.
- Add docs.py for building and previewing documentation with Mike or MkDocs.
- Introduce model_exports.py for exporting PyTorch models to ONNX format.
- Develop pack.py for packaging the project with dependencies for different platforms.
- Add test_sync_models.py to validate sync_models functionality.
- Add test_tool_commands.py to ensure repository tools have correct command scripts.
- Initialize tools package with __init__.py.
- Added interaction helpers for cutout region validation and shape menu interaction.
- Created main operator for converting image regions into cutout shapes, including AI artifact generation.
- Introduced object creation logic for cutout shapes, handling depth and normal textures.
- Defined cutout shape identifiers and node groups for various shape types.
- Implemented depth texture writing and prediction artifact generation for MoGe-2.
- Developed server jobs for generating cutout artifacts, depth planes, and refining image regions.
- Added region refinement logic to enhance gesture masks using BEN2.
- Implemented `build_mesh_plane.py` to create a geometry node group for mesh planes with customizable parameters.
- Created `build_shadeless.py` for a shader node group that displays color without scene lighting while preserving shadows and reflections.
- Added `validate.py` to validate the integrity of the newly created node groups and their inputs.
- Introduced `validate_cutout.py` to ensure the functionality of cutout node groups and their dependencies.
- Developed `validate_mesh_plane.py` to test the mesh plane creation and its modifier settings.
