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https://github.com/xiong-zhitong/GeoFM
Easy fine-tuning of Geo foundation models
https://github.com/xiong-zhitong/GeoFM
Last synced: about 1 month ago
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Easy fine-tuning of Geo foundation models
- Host: GitHub
- URL: https://github.com/xiong-zhitong/GeoFM
- Owner: xiong-zhitong
- License: apache-2.0
- Created: 2024-11-10T14:27:00.000Z (2 months ago)
- Default Branch: main
- Last Pushed: 2024-11-21T14:28:47.000Z (about 2 months ago)
- Last Synced: 2024-11-21T15:25:25.608Z (about 2 months ago)
- Language: Python
- Size: 27.6 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Evaluation of Foundation Models for Earth Observation
This repository provides tools for evaluating various foundation models on Earth Observation tasks. For detailed instructions on **pretraining and deploying [DOFA](https://arxiv.org/abs/2403.15356)**, please refer to the [main DOFA repository](https://github.com/zhu-xlab/DOFA).
---
## Setup
To get started, ensure you have the following dependencies installed:
```bash
pip install torch==2.1.2
pip install torchvision==0.16.2
pip install numpy==1.26.4
pip install openmim
mim install mmengine
mim install "mmcv==2.1.0"
mim install mmsegmentation
pip install tensorboard
pip install loguru
pip install timm
pip install git+https://github.com/ServiceNow/geo-bench.git
pip install torchmetrics
pip install ftfy
pip install regex
pip install einops
pip install yacs
pip install kornia
pip install pydantic
pip install omegaconf
pip install wandb
pip install python-dotenv
pip install torchgeo
pip install fastparquet
```
Install them by:
```bash
pip install -e .
```
### Model Weights
Pretrained model weights are available on [Hugging Face](https://huggingface.co/XShadow/GeoFMs). Download the necessary weights for your evaluation tasks.
The SoftCon weights are available on a different [HF repo](https://huggingface.co/wangyi111/softcon).
DOFA weights are available in this [HF repo](https://huggingface.co/XShadow/DOFA).
SATMAE++ weights are available in this [HF repo](https://huggingface.co/mubashir04/checkpoint_ViT-L_pretrain_fmow_sentinel).
### download the pre-trained weights and put them to the `src/fm_weights` folder.
---
## Available Models
This repository includes the following models for evaluation:
- CROMA
- DOFA
- GFM
- RemoteCLIP
- SatMAE
- ScaleMAE
- SoftCON
- on-going...
---
## Supported Datasets
The following datasets are currently supported:
- GeoBench
- **Spectral Earth** *(in progress)*
---
## Adding New Models and Datasets
To add a new model or dataset for evaluation, follow these steps:
1. **Add a Model Wrapper:**
- Create a new model wrapper in the [`foundation_models`](foundation_models) folder.
- Add the new model to `__init__.py` for integration.
- Register the model in [`factory.py`](factory.py) by adding its name to make it accessible via the `model_type` parameter.
2. **Add a Dataset Wrapper:**
- Create a new dataset wrapper in the [`datasets`](datasets) folder.
- Register the dataset in [`factory.py`](factory.py) to ensure access.
3. **Configuration Setup:**
- Define the configuration settings in [`config.py`](util/config.py).
---
## Running the Evaluation
To run the evaluation script, use the following command:
```bash
python scripts/exp_config.py
```
This script initiates training for model evaluation on GeoBench with CROMA.
---
## Contributing
We welcome contributions! If you'd like to add new models, datasets, or evaluation scripts, please submit a pull request, and ensure that you have tested your changes.