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ab2-gbl
/
ECG_segmentation_using_U-Net

Keras
Model card Files Files and versions
xet
Community

Instructions to use ab2-gbl/ECG_segmentation_using_U-Net with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Keras

    How to use ab2-gbl/ECG_segmentation_using_U-Net with Keras:

    # Available backend options are: "jax", "torch", "tensorflow".
    import os
    os.environ["KERAS_BACKEND"] = "jax"
    
    import keras
    
    model = keras.saving.load_model("hf://ab2-gbl/ECG_segmentation_using_U-Net")
    
  • Notebooks
  • Google Colab
  • Kaggle
ECG_segmentation_using_U-Net
377 MB
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  • 1 contributor
History: 2 commits
ab2-gbl's picture
ab2-gbl
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fe9009c verified 11 months ago
  • others
    Upload folder using huggingface_hub 11 months ago
  • .gitattributes
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  • CNN-LSTM.keras
    3.74 MB
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  • README.md
    224 Bytes
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  • R_detection.h5
    129 kB
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  • TCN.keras
    3.85 MB
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  • ecg_multi_class_model.pkl
    103 MB
    xet
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  • mlp_normal_vs_abnormal_model.pkl

    Detected Pickle imports (7)

    • "_codecs.encode",
    • "numpy.ndarray",
    • "numpy.core.multiarray._reconstruct",
    • "sklearn.neural_network._multilayer_perceptron.MLPClassifier",
    • "joblib.numpy_pickle.NumpyArrayWrapper",
    • "numpy.dtype",
    • "sklearn.preprocessing._label.LabelBinarizer"

    How to fix it?

    671 kB
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  • normal_vs_abnormal_model.pkl
    141 MB
    xet
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  • sb_vs_else_model.pkl
    24.2 MB
    xet
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  • unet1d_ecg_qrs.pth
    74.5 MB
    xet
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