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
File size: 574 Bytes
1d197a4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | # 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`
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