- 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.
- 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.
- 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.
- Added `ben2_onnx.py` for BEN2 ONNX inference with preprocessing.
- Introduced `da3_onnx.py` for Depth Anything 3 inference, including camera projection calculations.
- Created `moge_onnx.py` for MoGe-2 ONNX inference and post-processing.
- Implemented shared ONNX Runtime session helpers in `onnx_runtime.py`.
- Added model synchronization script `sync_models.py` for downloading and verifying ONNX models.
- Developed unit tests for BEN2, Depth Anything 3, and MoGe ONNX models to ensure functionality.
- Updated `vendor.lock.toml` to remove unused artifacts.
- Created development.md for development setup and licensing information.
- Added features.md detailing functionalities and usage instructions for developers and users.
- Introduced index.md to serve as a navigation hub for the documentation.
- Developed outputs.md to explain output formats and their specifications.
- Established service.md to describe the AI Service architecture and environment setup.
- Created surface.md to outline the process of converting Image Empty to perspective meshes.
- Create a build workflow in `.github/workflows/build.yml` to automate the build process.
- Configure Python environment and install dependencies.
- Add steps for running tests and packaging the extension.
chore: Initialize project metadata and dependencies for Depth Anything 3
- Add `pyproject.toml` for project configuration and dependencies.
- Include optional dependencies for app and gs functionalities.
- Define project scripts and metadata.
chore: Add requirements file for Depth Anything 3 dependencies
- Create `requirements.txt` listing all necessary packages for the project.
feat: Implement export utility functions for Depth Anything 3
- Create `src/depth_anything_3/utils/export/__init__.py` to handle various export formats.
- Implement functions for exporting predictions in different formats.
feat: Add ray utility functions for homography estimation
- Create `src/depth_anything_3/utils/ray_utils.py` with functions for computing optimal rotation and homography using RANSAC.
feat: Implement vendor preparation script
- Add `prepare_vendor.py` to manage third-party dependencies and artifacts.
- Include functions for downloading and verifying artifacts based on a lock file.
test: Add unit tests for vendor preparation script
- Create `tests/test_prepare_vendor.py` to test artifact downloading and verification.
- Implement tests for handling hash mismatches and unsupported platforms.
chore: Add vendor lock file for dependency management
- Create `vendor.lock.toml` to define artifacts and platforms for the project.
- Bump SnapForm version in uv.lock from 0.9.30 to 0.10.10.
- Introduce comprehensive technical documentation for SnapForm, detailing features, usage instructions, and development guidelines.
- Introduced MODEL_NUMBERS for better model indexing.
- Improved enum_items function to cache results and handle download status.
- Updated ActiveJob class to manage temporary input paths and added displacement_via property.
- Changed IMAGE_DEPTH_PROCESS_RES_METHOD from "lower_bound_resize" to "upper_bound_resize".
- Enhanced RunJob operator to include new properties and improved error messages.
- Modified panel layout for better user experience and added runtime installation checks.
- Updated SnapFormSettings to reflect new model properties and defaults.
- Added temporary input path management in runtime.
- Refined worker functions to improve error handling and messaging.
- Expanded tests to cover new functionality and ensure backward compatibility.
- Fixed packaging script to align with versioning conventions.
- Implemented RuntimeModelsPanel and DebugPanel for UI integration in Blender.
- Created SnapFormPreferences to manage user settings for storage and runtime configuration.
- Defined SnapFormSettings to hold various properties related to input, model selection, and export options.
- Developed runtime management functions for installation, model downloading, and reconstruction commands.
- Added status bar functionality to display job progress and status in the Blender UI.
- Implemented worker script for handling model downloads and depth reconstruction tasks.
- Introduced unit tests for download progress reporting and image depth extraction functionalities.
- Added properties for Omoo DA3 settings in properties.py, including input path, video frames, model selection, and export format.
- Created runtime management in runtime.py, handling model downloads, job paths, and command execution for reconstruction.
- Developed status bar functionality in status_bar.py to display job progress and status.
- Implemented worker.py for image and video processing, including frame extraction and model inference.
- Added comprehensive unit tests covering addon registration, model handling, export processes, and UI interactions.
- Included a lock file for dependency management with uv.
