docs: remove edge_threshold parameter from example workflow to align with new automatic edge thresholding feature
docs(README): simplify and condense VACE Annotator Scribble documentation for clarity and ease of use
docs: add help-page style documentation for VACEScribbleAnnotator node to improve user guidance and usability
feat(annotator_models): add ContourInference and VendorResidualBlock classes for enhanced model architecture
feat(annotator_models): implement postprocess_vendor_scribble_output function for vendor-specific output processing
fix(annotator_models): update load_scribble_model to handle vendor state dicts and improve model loading logic
refactor(preprocess_scribble_input): add normalize_mode parameter for flexible input normalization options
fix(_quantile_threshold): improve scale handling for user-defined thresholds in quantile calculations
refactor(vace_scribble_annotator.py): remove edge_threshold parameter and use a default constant for edge detection to simplify the code
feat(vace_scribble_annotator.py): add support for vendor-specific postprocessing of scribble output to enhance functionality
- Introduced vendoring for the VACE scribble generator to allow usage without the full upstream repository.
- Added `VENDORING.md` to document vendored files and update instructions.
- Updated `README.md` to include vendoring notes.
- Modified `IMPLEMENTATION_SUMMARY.md` to reflect changes in the scribble node.
- Enhanced `VACE_ANNOTATORS.md` with new parameters for inference mode and edge threshold.
- Created `scribble.py` and `scribble_loader.py` for model loading and preprocessing.
- Updated `vace_scribble_annotator.py` to integrate new model loading logic and fallback mechanisms.
- Added smoke tests for both fallback and model inference scenarios.
- Included a sample input image for testing purposes.
Sammy Kumar