Instructions to use MIDSCapstoneTeam/ContrailSentinel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use MIDSCapstoneTeam/ContrailSentinel 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://MIDSCapstoneTeam/ContrailSentinel") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Model description
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We achieve a Mean IOU of 0.6951 on the validation set.
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## Intended uses
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## Model description
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This TransUNet model identifies contrails in satellite images. It takes pre-processed .npy files (images) from the OpenContrails dataset [here](https://arxiv.org/abs/2304.02122) as its inputs, and returns a "mask" image showing only the contrails overlayed on the same area.
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We achieve a Mean IOU of 0.6951 on the validation set.
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## Intended uses
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