Metadata-Version: 2.1
Name: metnet
Version: 2.0.3
Summary: PyTorch MetNet Implementation
Home-page: https://github.com/openclimatefix/metnet
Author: Jacob Bieker
Author-email: jacob@openclimatefix.org
License: MIT License
Keywords: artificial intelligence,deep learning,transformer,attention mechanism,metnet,forecasting,remote-sensing
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: einops (>=0.3.0)
Requires-Dist: numpy (>=1.19.5)
Requires-Dist: torchvision (>=0.10.0)
Requires-Dist: antialiased-cnns
Requires-Dist: axial-attention
Requires-Dist: pytorch-msssim
Requires-Dist: huggingface-hub

# MetNet and MetNet-2

PyTorch Implementation of Google Research's MetNet for short term weather forecasting (https://arxiv.org/abs/2003.12140), inspired from https://github.com/tcapelle/metnet_pytorch/tree/master/metnet_pytorch

MetNet-2 (https://arxiv.org/pdf/2111.07470.pdf) is a further extension of MetNet that takes in a larger context image to predict up to 12 hours ahead, and is also implemented in PyTorch here.

## Installation

Clone the repository, then run
```shell
pip install -r requirements.txt
pip install -e .
````

Alternatively, you can also install a usually older version through ```pip install metnet```


## Pretrained Weights
Pretrained model weights for MetNet and MetNet-2 have not been publicly released, and there is some difficulty in reproducing their training. We release weights for both MetNet and MetNet-2 trained on cloud mask and satellite imagery data with the same parameters as detailed in the papers on HuggingFace Hub for [MetNet](https://huggingface.co/openclimatefix/metnet) and [MetNet-2](https://huggingface.co/openclimatefix/metnet-2). These weights can be downloaded and used using:

```python
from metnet import MetNet, MetNet2
model = MetNet().from_pretrained("openclimatefix/metnet")
model = MetNet2().from_pretrained("openclimatefix/metnet-2")
```


