Instructions to use Aditya2162/ivus-segmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Aditya2162/ivus-segmentation with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Aditya2162/ivus-segmentation") - Notebooks
- Google Colab
- Kaggle
Finetune Scripts
Canonical split:
evals/splits/ivus_split_merged_600.json
Folder layout:
scripts/finetune/bifurcation/: bifurcation sampling, annotation merge, split, training, test inferencescripts/finetune/lumen/: lumen class ID, fine-tuning, test inference, single-DICOM inferencescripts/finetune/shared/common.py: shared annotation/split/data helpers
Entrypoints:
scripts/finetune/bifurcation/*.pyscripts/finetune/lumen/*.py
Model defaults:
models/standalone/lumenmodels/standalone/bifurcation/best_bifurcation_classifier.keras