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 inference | |
| - `scripts/finetune/lumen/`: lumen class ID, fine-tuning, test inference, single-DICOM inference | |
| - `scripts/finetune/shared/common.py`: shared annotation/split/data helpers | |
| Entrypoints: | |
| - `scripts/finetune/bifurcation/*.py` | |
| - `scripts/finetune/lumen/*.py` | |
| Model defaults: | |
| - `models/standalone/lumen` | |
| - `models/standalone/bifurcation/best_bifurcation_classifier.keras` | |