Image Segmentation
Flair
Keras
tensorflow
medical-imaging
white-matter-hyperintensities
mri
deep-learning
neurology
multiple-sclerosis
Instructions to use Bawil/wmh_leverage_normal_abnormal_segmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Flair
How to use Bawil/wmh_leverage_normal_abnormal_segmentation with Flair:
from flair.data import Sentence from flair.models import SequenceTagger tagger = SequenceTagger.load("Bawil/wmh_leverage_normal_abnormal_segmentation") sentence = Sentence("George Washington went to Washington.") tagger.predict(sentence) print(sentence) - Keras
How to use Bawil/wmh_leverage_normal_abnormal_segmentation with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://Bawil/wmh_leverage_normal_abnormal_segmentation") - Notebooks
- Google Colab
- Kaggle
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