- 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.
