- Introduced tests for boundary smoothing in `test_boundary_smoothing.py`, verifying that smoothing reduces stair-step artifacts while preserving boundary integrity.
- Added tests for cutout boundary behavior in `test_cutout_boundary.py`, ensuring proper handling of boundary triangles and normal blending.
- Created `test_temporary_attributes.py` to check the cleanup of temporary attributes across depth modifier branches, ensuring no warnings are raised.
- Implemented point culling functionality in `test_validity.py`, confirming that invalid points are removed without affecting adjacent geometry.
- Developed boundary smoothing logic in `boundary_smoothing.py`, allowing for depth smoothing while maintaining edge integrity.
- Added cutout boundary management in `cutout_boundary.py`, including functions for removing boundary triangles and tapering thickness profiles.
- Implemented validity checks in `validity.py` to ensure proper deletion of invalid vertices and associated wire edges.
- Introduced new utility functions in common nodes for evaluating fields and capturing attributes.
- Simplified volume field calculations in image depth cutout and panorama groups by utilizing new utility functions.
- Enhanced readability and maintainability of the image depth cutout and panorama node groups by removing redundant code and improving function usage.
- Adjusted default values for thickness and depth scale in image relief plane group for better user experience.
- Improved handling of geometry attributes and connections in image depth plane group to streamline processing.
- Added a proposal for depth surface strip cleanup, detailing the rationale and changes to the depth plane and cutout nodes.
- Created specifications for the new cleanup requirements, including scenarios for strip removal and boundary edge detection.
- Developed tasks for implementing shared strip detection logic and integrating new interfaces for depth nodes.
- Established a new CLI structure for organizing node groups and model commands, replacing old entry points with a more intuitive command structure.
- Introduced a prototype for panorama surface generation, including requirements for distance reconstruction and geometry node surfaces.
- Added comprehensive tests for depth strip cleanup functionality, ensuring correct behavior for various mesh topologies and edge cases.
- Implement tests for image layer functionality including alpha curve and depth layer behavior.
- Create tests for image plane evaluation and modifier input handling.
- Add tests to verify the saved asset inventory and its persistence.
- Introduce tests for the documentation command to ensure correct project version deployment.
- Validate the extension manifest structure and required permissions.
- Develop tests for the packaging process, ensuring correct platform handling and dependency management.
- Enhance image depth plane group functionality with new split threshold input and surface processing.
- 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.
- Implemented `cutout_depth_surface.py` for face separation and connected thickness calculations for depth surface assets.
- Created `cutout_depth_surface_layout.py` to arrange nodes for staggered calculation branches in depth surface processing.
- Authored `geometry_layouts.py` to define layouts for various geometry assets, including image cutouts and depth planes.
- Introduced `node_layout.py` for shared presentation rules, facilitating node arrangement and validation in geometry-node layouts.
- 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.
- 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.
- Updated the depth plane node group to load from an asset and simplified the interface.
- Created a new build script for depth plane geometry nodes.
- Introduced material layer groups for image and depth materials with appropriate sockets.
- Added functionality to connect balloon normal scale to the image material.
- Enhanced tests to validate the new node groups and their connections.
- Ensured that production code does not create node groups directly.
- 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.
- Added depth.py for MoGe-2 depth sampling and balloon deformation functionality.
- Introduced validate_balloon_asset.py to validate balloon shape modifiers and material properties in Blender.
- Enhanced test_server.py with new unit tests for balloon depth analysis and job progress tracking.
- Updated existing tests to improve code clarity and maintainability.
- Added BalloonTool workspace tool to facilitate the extraction of balloon meshes in the 3D viewport.
- Implemented ActivateBalloonTool operator to activate the Balloon Lasso Tool.
- Refactored BalloonLasso operator into ExtractBalloon for better clarity and functionality.
- Enhanced properties for balloon extraction, including mode, thickness, resolution, and material reuse options.
- Updated SnapFormSettings to include new balloon-related properties.
- Improved material and image handling for balloon extraction, ensuring compatibility and reusability.
- Added tests to validate the registration and functionality of the new balloon tools and properties.
- Implemented `DownloadModel` and `DownloadRequiredModels` operators for downloading models.
- Created `ClearModels` operator to clear model resources.
- Added `ConvertToSurface` operator for converting image empties into textured surfaces.
- Introduced `GenerateDa3Surface` and `GenerateMoge2Surface` operators for generating surfaces using DA3 and MoGe-2 models respectively.
- Developed utility functions for handling image mesh data, assigning attributes, and managing geometry nodes.
- Established runtime configuration and post-installation model downloading in `runtime.py`.
- Introduced new guides for Depth Plane, Surface, and animation workflows.
- Added installation instructions and FAQs to assist users in setup and troubleshooting.
- Created a quick-start guide for first-time users to convert images to Depth Planes.
- Documented the process for removing backgrounds from images.
- Established a models and storage section to clarify data management.
- Included a stylesheets file for improved documentation styling.
- Updated mkdocs configuration for better navigation and theme settings.
- Changed the logic in `remove_background_faces` to keep only faces with all foreground vertices.
- Updated background job to save foreground images with a new naming convention (`color.0001.png`).
- Replaced `copy_frames` with `copy_color_images` in various jobs to ensure consistent image naming.
- Introduced a new function `copy_color_images` to handle the copying of images with a specific naming format.
- Updated the BEN2 model to save output images with a new prefix for better clarity.
- Modified tests to reflect changes in image naming and processing logic.
- Added a new shadeless node group for improved material handling in geometry nodes.
- Enhanced validation scripts to check for new image naming conventions and ensure proper functionality.
- Implemented surface generation functionality in `surface.py`, including geometry estimation and texture writing.
- Introduced media input handling in `input.py`, supporting image and video frame extraction.
- Added model management for geometry adapters in `models/__init__.py`.
- Created BEN2 and DA3 model inference logic in `ben2.py` and `da3.py`, respectively.
- Developed ONNX model inference utilities for BEN2 and DA3 in `onnx_ben2.py` and `onnx_da3.py`.
- Added support for MoGe-2 model inference in `moge2.py` with necessary ONNX utilities.
- Implemented output handling for depth and surface data in `depth.py` and `surface.py`.
- Created debug output utilities for DA3 and MoGe-2 predictions in `debug_da3.py` and `debug_moge2.py`.
- Enhanced ONNX runtime session management in `onnx_runtime.py`.
- Updated `__init__.py` files to include new modules and functions for better organization.
- Introduced ModelSpec dataclass to define model attributes.
- Added multiple models including DA3 Small, Base, Giant 1.1, Nested Giant Large 1.1, and MoGe-2 variants.
- Implemented functions to retrieve model details and metadata.
- Included BEN2 model specifications for background removal.
- Introduced `onnx_moge2.py` for MoGe-2 ONNX inference with NumPy post-processing.
- Added `onnx_ben2.py` for BEN2 ONNX inference with Pillow and NumPy preprocessing.
- Created `onnx_da3.py` for Depth Anything 3 inference with ONNX Runtime and NumPy.
- Implemented shared ONNX Runtime session helpers in `onnx_runtime.py`.
- Developed unit tests for server functionalities in `test_server.py`, including model caching and job management.
- Enhanced job server to handle frame extraction without requiring models.
- Implement JobClient for handling HTTP requests to the JobServer.
- Create ModalJobOperatorBase for managing Blender job lifecycle.
- Introduce JobContext and JobServer for job management and state handling.
- Add ServiceConnection and ServiceController for managing service processes.
- Implement job submission, cancellation, and resource management endpoints in the server.
- Ensure proper error handling and job state updates throughout the service.
- Updated version in pyproject.toml and blender_manifest.toml to 0.11.2.
- Enhanced uv executable path documentation in client.py.
- Added inference_mode parameter to reconstruct_request function in client.py.
- Implemented uv download functionality in install_env.py with improved error handling and checksum verification.
- Modified install_uv function to download and extract uv binary instead of using bundled version.
- Updated job progress handling in operators.py to track progress stages.
- Improved download progress reporting in worker.py and adjusted related tests.
- Refactored tests to accommodate changes in status reporting and model downloading.
- Removed vendor.lock.toml as part of the cleanup process.
