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https://clay-foundation.github.io/model/

The Clay Foundation Model - An open source AI model and interface for Earth
https://clay-foundation.github.io/model/

digital-elevation-model earth-observation embeddings foundation-model sentinel-1 sentinel-2

Last synced: about 1 month ago
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The Clay Foundation Model - An open source AI model and interface for Earth

Host: GitHub
URL: https://clay-foundation.github.io/model/
Owner: Clay-foundation
License: apache-2.0
Created: 2023-09-29T12:08:10.000Z (over 1 year ago)
Default Branch: main
Last Pushed: 2024-12-03T08:54:08.000Z (about 1 month ago)
Last Synced: 2024-12-04T11:39:22.150Z (about 1 month ago)
Topics: digital-elevation-model, earth-observation, embeddings, foundation-model, sentinel-1, sentinel-2
Language: Jupyter Notebook
Homepage: https://clay-foundation.github.io/model/
Size: 175 MB
Stars: 381
Watchers: 23
Forks: 48
Open Issues: 29
Metadata Files:
- Readme: README.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md

Awesome Lists containing this project

README

        # Clay Foundation Model

[![Jupyter Book Badge](https://jupyterbook.org/badge.svg)](https://clay-foundation.github.io/model)

[![Deploy Book Status](https://github.com/Clay-foundation/model/actions/workflows/deploy-docs.yml/badge.svg)](https://github.com/Clay-foundation/model/actions/workflows/deploy-docs.yml)

[![Continuous Integration Tests Status](https://github.com/Clay-foundation/model/actions/workflows/test.yml/badge.svg)](https://github.com/Clay-foundation/model/actions/workflows/test.yml)

An open source AI model and interface for Earth.

## Quickstart

Launch into a [JupyterLab](https://jupyterlab.readthedocs.io) environment on

| [Binder](https://mybinder.readthedocs.io/en/latest) | [SageMaker Studio Lab](https://studiolab.sagemaker.aws) |

|:--:|:--:|

| [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/Clay-foundation/model/main) | [![Open in SageMaker Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/Clay-foundation/model/blob/main/docs/tutorials/clay-v1-wall-to-wall.ipynb) |

## Installation

### Basic

To help out with development, start by cloning this [repo-url](/../../)

    git clone 

    cd model

Then we recommend [using mamba](https://mamba.readthedocs.io/en/latest/installation/mamba-installation.html)

to install the dependencies. A virtual environment will also be created with Python and

[JupyterLab](https://github.com/jupyterlab/jupyterlab) installed.

    mamba env create --file environment.yml

> [!NOTE]

> The command above will only work for Linux devices with CUDA GPUs. For installation

> on macOS devices (either Intel or ARM chips), follow the 'Advanced' section in

> https://clay-foundation.github.io/model/getting-started/installation.html#advanced

Activate the virtual environment first.

    mamba activate claymodel

Finally, double-check that the libraries have been installed.

    mamba list

## Usage

### Running jupyter lab

    mamba activate claymodel

    python -m ipykernel install --user --name claymodel  # to install virtual env properly

    jupyter kernelspec list --json                       # see if kernel is installed

    jupyter lab &

### Running the model

The neural network model can be ran via

[LightningCLI v2](https://pytorch-lightning.medium.com/introducing-lightningcli-v2supercharge-your-training-c070d43c7dd6).

To check out the different options available, and look at the hyperparameter

configurations, run:

    python trainer.py --help

To quickly test the model on one batch in the validation set:

    python trainer.py fit --model ClayMAEModule --data ClayDataModule --config configs/config.yaml --trainer.fast_dev_run=True

To train the model:

    python trainer.py fit --model ClayMAEModule --data ClayDataModule --config configs/config.yaml

More options can be found using `python trainer.py fit --help`, or at the

[LightningCLI docs](https://lightning.ai/docs/pytorch/2.1.0/cli/lightning_cli.html).

## Contributing

### Writing documentation

Our Documentation uses [Jupyter Book](https://jupyterbook.org/intro.html).

Install it with:

```bash

pip install -U jupyter-book

```

Then build it with:

```bash

jupyter-book build docs/

```

You can preview the site locally with:

```bash

python -m http.server --directory _build/html

```

There is a GitHub Action on `./github/workflows/deploy-docs.yml` that builds the site and pushes it to GitHub Pages.