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.models import SequenceTagger tagger = SequenceTagger.load("Bawil/wmh_leverage_normal_abnormal_segmentation") - Keras
How to use Bawil/wmh_leverage_normal_abnormal_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://Bawil/wmh_leverage_normal_abnormal_segmentation") - Notebooks
- Google Colab
- Kaggle
File size: 334 Bytes
d2fe28b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"timestamp": "20251124_171430",
"input_shape": [
256,
256,
1
],
"target_size": [
256,
256
],
"epochs": 50,
"batch_size": 8,
"learning_rate": 0.0001,
"validation_split": 0.1,
"random_state": 42,
"loss_options": {
"scenario1": "weighted_bce",
"scenario2": "weighted_categorical"
}
} |