Implement BiRefNet and HAT Sharper models with background removal capabilities
- 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.
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@@ -41,7 +41,7 @@ dev = [
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[package.metadata]
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]
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@@ -114,13 +114,19 @@ wheels = [
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