Instructions to use OWLab/Optic-flow-CNN-ReLU-15x15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use OWLab/Optic-flow-CNN-ReLU-15x15 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://OWLab/Optic-flow-CNN-ReLU-15x15") - Notebooks
- Google Colab
- Kaggle
Commit History
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Create README.md
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Create README.md
Verified signatureFrom our paper: Layton, Peng, & Steinmetz (2024). ReLU, Sparseness, and the Encoding of Optic Flow in Neural Networks. Sensors.43fc787 -
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Verified signatureModel + pickled hyperparameters used for training.4198f18 -
initial commit
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