- Introduced tests for the Moge3 ONNX model, including input validation, inference, and caching mechanisms.
- Added tests for ONNX runtime configurations and session management.
- Implemented tests for image upscaling functionality using ONNX models, ensuring proper handling of alpha channels and memory management.
- Created tests for panorama generation, verifying depth and visibility metrics.
- Developed tests for prediction artifacts, ensuring correct depth and normal data handling.
- Added server job tests for background removal and depth plane geometry generation, validating input handling and output correctness.
- Included environment tests to ensure proper dependency management and CI configurations.
- Added validation documentation for AI model tiers.
- Introduced `background.py` for background removal logic, including inference functions for alpha and foreground extraction.
- Created `onnx_birefnet.py` to handle BiRefNet model sessions and alpha inference.
- Developed tests for background models, ensuring proper dispatch and session reuse.
- Added tests for BiRefNet ONNX model to validate alpha output and error handling for invalid values.
- Implemented model export scripts for BiRefNet and HAT Sharper, ensuring proper weight compression and licensing.
- Created `deform_sampling.py` for deformable convolution operations used in BiRefNet.
- Added utility functions for compressing ONNX weights without altering graph arithmetic.
- Introduced a reference plane node for depth field adjustments in geometry 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.
