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
Evaluation Layout
Canonical bifurcation classification data:
evals/frame_bank_merged/: merged per-video annotation banks (old + newly labeled samples)evals/splits/ivus_split_merged_600.json: canonical train/val/test split used by both lumen and bifurcation scripts
Intermediate data:
evals/frame_bank_merged/new_bifurcation_samples_300.jsonl: sampled frame list used for manual bifurcation labelingevals/frame_bank_merged/new_bifurcation_samples_300.csv: companion spreadsheet export for labeling workflow