- Introduced color_image.py for preparing standalone color images for tests.
- Added hdr_image.py to create HDR textures for testing.
- Implemented test_image_depth_panorama.py to evaluate panorama topology, UVs, and depth discontinuities.
- Created test_shadeless.py to validate the opacity and HDR color endpoints of the Shadeless group.
- Developed moge3_export.py for exporting dynamic MoGe-3 backbone and ONNX graphs.
- Added material.py to inherit material slots onto generated geometry.
- Built image_depth_panorama.py to construct a quad panorama with depth separation and sampling.
- Implemented the "O Image Relief Plane" Geometry Nodes group to create a fixed-base image relief using depth images and various parameters.
- Created the "O Shadeless" shader node group to display color without scene lighting while preserving shadows and reflections.
- Introduced a preview feature for node groups, allowing for interactive visualization of node arrangements in an HTML format.
- Added a template HTML file for rendering node previews with customizable views and controls.
- Removed unused model keys and functions from properties.py.
- Deleted projection.py as its functions were no longer needed.
- Cleaned up model_catalog.py by removing unused model directory function.
- Updated imports in various test files to reflect new module structure.
- Removed deprecated test cases related to image editing tools.
- Added new tests for ONNX runtime provider selection logic.
- Implemented `image_plane.py` to build the Image Plane Geometry Nodes group with customizable parameters for geometry, subdivide, and thickness.
- Created `image_plane_validation.py` to validate the functionality of the image plane, ensuring correct geometry generation and material assignment.
- Developed `material_layers.py` to construct shader node groups for image materials, including depth and normal handling.
- Authored `plane_layouts.py` to define node arrangements for image geometry assets.
- Introduced `shadeless.py` to create a shadeless shader node group that displays color without scene lighting while preserving shadows and reflections.
- Implemented `cutout_shell.py` to build front normals and shell positions for balloon geometry.
- Created `cutout_volume.py` to establish smooth center fields and manage balloon surface attributes.
- Introduced `pisa_sr_export.py` for exporting PiSA-SR components with dependencies and asset finalization.
- Introduced `test_edge_depth.py` to validate the functionality of edge depth extension, ensuring core alpha preservation, proper depth handling, and edge padding behavior.
- Created `test_empty_image_edits.py` to verify the behavior of image edits in Blender, focusing on shared edits, preservation of image properties, and handling of failed operations.
- Developed `test_material_view_adaptation.py` to test material adaptation preferences, ensuring color space and alpha settings are correctly applied and preserved across various scenarios.
- Introduced tests for color image handling, ensuring source preservation and premultiplied alpha usage.
- Implemented tests for brush stroke operations, validating segment boundaries and brush anti-aliasing.
- Added tests for frame anti-aliasing, confirming correct rendering behavior with various alpha values and depth settings.
- Created tests for frame projection, ensuring accurate overlap calculations and half-plane clipping.
- Developed tests for image premultiplied retention, verifying behavior during loading and packing processes.
- Added undo functionality tests for mask operations, ensuring single transaction behavior during edits.
- Renamed "Base Plane Depth" to "Reference Depth" across validate_cutout.py for consistency.
- Introduced a new specification for Cutout mesh sampling to ensure source pixel spacing is preserved and limits are applied correctly.
- Unified naming conventions for image editing results to maintain consistency across Remove Background, Upscale, and Crop operations.
- Updated the handling of Refine Selection to ensure it retains the original bounds and does not apply unnecessary cropping.
- Enhanced material generation logic to connect image color directly to IOR Level, improving the rendering of dark areas.
- Established clear requirements for geometry depth controls and image result materials to ensure consistent behavior across different components.
- Removed outdated logic and ensured all changes are documented and tested for regression.
- 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.
- Introduced a new memory management policy for ONNX Runtime to release temporary GPU memory after inference completion.
- Established a shared inference entry point for all ONNX models, differentiating between long-lived sessions and temporary memory arenas.
- Updated CUDA sessions to utilize a shrinkable memory arena, reclaiming GPU memory post-inference.
- Ensured consistent memory release semantics across BEN2, DA3, MoGe-2, and Upscale models while reusing existing sessions.
- Added lifecycle tests to validate temporary memory release and session reuse.
- Modified model adapters to integrate the new memory management features, ensuring backward compatibility with existing inference behavior.
- Enhanced unit tests to cover new memory release scenarios and verify correct behavior across different execution providers.
- 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.
- 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.
- Added a new cutout tool for selecting regions in images, allowing users to choose mesh shapes based on selected areas.
- Introduced depth generation capabilities for rasterized images, including normal data extraction.
- Created jobs for generating depth planes and region data, enhancing the AI data generation workflow.
- Developed a selection refinement process for cutout regions, improving accuracy in generated outputs.
- Established a new region module for handling rasterized image regions and their associated AI generation tasks.
- Enhanced node graph builders for asset generation, facilitating smoother integration of new features.
- 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.
- Implemented cotangent Poisson field and Poisson balloon profile in cutout_profile.py.
- Added teddy balloon heights calculation and related functions in cutout_teddy.py.
- Introduced interaction utilities for image editing in interaction.py.
- Developed depth normalization and analysis functions in cutout_depth.py.
- Created a validation script for cutout assets in validate_cutout_asset.py.
- Updated the naming convention for upscaled images to include underscores and file extensions.
- Renamed properties related to cutout pixel size to point spacing for clarity.
- Adjusted alpha region calculations to use a half-alpha threshold for better accuracy.
- Enhanced the handling of foreground mesh masks to consider half-alpha values.
- Introduced new functions for unbounded selections and cutout images, ensuring proper handling of source and selection images.
- Improved test coverage for cutout functionalities, including bounds mapping and alpha preservation.
- Updated tests to reflect changes in naming conventions and functionality adjustments.
- Introduced `test_cutout.py` to validate cutout pie menu behavior, image lasso options, and mesh detail calculations.
- Added `test_mesh.py` to ensure correct tangent normal rasterization, plane source topology, and depth surface evaluations.
- Created `test_mesh_blender.py` to verify material node groups, tangent baking, and local cutout building from Blender images.
- Implemented tests for handling alpha regions and ensuring geometry nodes maintain expected behavior.
- Added upscale operator to handle image upscaling by 4x using AI models.
- Introduced new jobs for upscale processing in the server, including debug and standard upscale jobs.
- Created a new ONNX model handler for upscale operations, supporting tiled inference and resource management.
- Updated tests to cover new upscale functionality, including input validation and output verification.
- Added documentation for the upscale feature, detailing usage and model options.
- Implemented the Image Perspective tool for editing image corners in Blender.
- Created a new operator `EditImagePerspective` to handle the perspective transformation.
- Added a preview feature for the perspective adjustment.
- Introduced the `ImagePolylineTool` for editing image masks with polylines.
- Developed backend support for Real-ESRGAN model inference, including ONNX integration.
- Added functionality for image masking and background removal.
- Created unit tests for the Real-ESRGAN ONNX model to ensure correct preprocessing and inference.
- Implemented ExtractImageRegion operator for extracting image regions using box or lasso selection.
- Added RemoveImageRegionBackground job for background removal from selected image regions.
- Created utility functions for polygon bounds, selection canvas creation, and applying selection masks.
- Integrated image processing using PIL and numpy for efficient pixel manipulation.
- Enhanced user experience with modal drawing and status updates during extraction.
- Implemented a comprehensive test suite for the clipboard image module, covering various functionalities including operator registration, context handling, and image processing.
- Created a new mesh plane asset with customizable parameters and integrated it into the geometry node system.
- Developed a validation script to ensure the correct behavior of the mesh plane asset, including input handling and output verification.
