- 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.
- Updated ONNX Runtime to 1.24.4 and replaced OpenCV with PyAV 17.0.0 in the installation environment.
- Enhanced model downloading logic to prioritize Hugging Face and fallback to OmooLab R2, with improved error handling and status reporting.
- Introduced a new environment revision file for shared metadata.
- Refactored video frame extraction to utilize the PyAV library instead of OpenCV.
- Improved installation process to handle retries across specified PyPI indexes.
- Added tests for download progress reporting and model downloading behavior.
- 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.
- Introduced new MoGe-2 depth plane group with geometry and material displacement options.
- Updated existing depth plane group to improve background depth handling and subdivision settings.
- Enhanced tests to validate MoGe-2 models and ensure proper integration with existing systems.
- Modified installation environment to include new dependencies for MoGe-2 and utils3d.
- Updated vendor lock file to include new artifacts for MoGe and utils3d.
- Refactored download and model handling to accommodate new MoGe-2 models.
- Improved validation scripts for depth plane assets to ensure compliance with new specifications.
- Updated NODE_GROUP_NAME from "O Refine DA3 Surface" to "O DA3 Surface".
- Introduced `remove_surface_background` function to filter out background faces and compact geometry.
- Enhanced `build_image_mesh` to conditionally remove background faces based on a new property.
- Added `snapform_remove_background` and `snapform_keep_original` properties to operators for better control over background handling.
- Updated UI to reflect new properties and improved resolution scaling logic.
- Refactored tests to cover new background removal functionality and ensure proper geometry handling.
- Adjusted geometry nodes and validation scripts to remove references to background handling.
- Implement test to ensure foreground preserves source RGB and Ben2 alpha in WorkerTest.
- Remove outdated tests related to background distance and original background depth.
- Update geometry node asset to reflect new naming conventions and structure.
- Introduce validation for depth plane asset, ensuring correct input/output configurations and attribute handling.
- Adjust confidence and edge parameters in geometry node asset to support a wider range of values.
- Implemented a new geometry nodes asset in `build_geometry_nodes_asset.py` to handle mesh refinement and topology fixing.
- Created a validation script in `validate_geometry_nodes_asset.py` to ensure the integrity and functionality of the geometry node group.
- Added input handling for various parameters including resolution, iterations, and smoothing options.
- Included checks for node group structure and attributes to validate the geometry processing pipeline.
- Renamed DA3 and BEN2 debug panels for clarity and consistency.
- Added a new function to draw DA3 input settings to reduce code duplication.
- Implemented mesh export functionality, including confidence thresholding and edge filtering.
- Updated export format options to include new mesh type and adjusted related properties.
- Enhanced job handling to move generated inputs into job root and manage temporary directories.
- Improved error handling and file management during export processes.
- Added unit tests for new mesh functionality and ensured existing tests cover changes.
- Added `background_depth_distance` property to `ActiveJob` and `RunJob` classes to manage background depth settings.
- Updated job execution to handle background depth distance, allowing for fixed negative displacement in depth calculations.
- Introduced new functions in the worker module to apply background depth distance to depth frames and manage original background depth.
- Enhanced tests to cover new functionality, ensuring correct behavior of background depth processing and reference depth extraction.
- Refactored job submission to run in a separate thread, improving responsiveness during execution.
- Updated frame extraction logic to allow for single frame extraction.
- Integrated model readiness checks for BEN2 and DA3 models in relevant operators.
- Added directory name attribute to model specifications for better organization.
- Improved device selection logic for production and debug tasks.
- Refactored preferences to expose device settings and ensure they reflect available hardware.
- Enhanced runtime device detection and management, including support for CUDA and MPS.
- Updated tests to cover new device management features and model directory handling.
- Removed deprecated download model tests to streamline codebase.
- 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.
- Modified status messages and stage labels in `test_addon.py` for clarity and consistency.
- Added tests to ensure proper host termination and command execution in `test_addon.py`.
- Enhanced `test_bootstrap_runtime.py` with additional tests for installation behavior, including handling of CUDA and MPS devices, and improved error handling for disk space and network checks.
- Updated download progress reporting in `test_download_progress.py` to include download speed and improved message formatting.
- Added new tests in `test_worker.py` for device selection, NPZ file validation, and model downloading behavior with Hugging Face endpoints.
- Bumped version in `uv.lock` to 0.9.30.
- Added ai_host.py to handle AI tasks with FastAPI integration.
- Introduced HostState and ModelCache classes for managing client connections and model loading.
- Implemented job submission and cancellation endpoints in the AI host.
- Enhanced tests for AI host functionality, including client tracking and job cancellation.
- Updated existing tests to accommodate changes in the operator and command structure.
- Refactored runtime commands to use request-based architecture instead of command-line arguments.
- Improved model loading logic to handle CUDA memory management and reuse models efficiently.
- Introduced BEN2 model for background removal in the panel and properties.
- Updated runtime to handle background removal commands and model downloads.
- Implemented background removal logic in worker, including image processing and saving results.
- Enhanced tests to cover new background removal features and ensure proper integration.
- Updated version to 0.9.28 to reflect new features and improvements.
- 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.
