EMAG2 completion

Recovering Missing Regions of Earth Magnetic Anomaly Grid data (EMAG2) Using RePaint based on Diffusion Model

Set up

1. Environment

pip install numpy torch blobfile tqdm pyYaml pillow pandas    # e.g. torch 1.7.1+cu110.

2. Download pretrained model and EMAG2 data.

Name	Note
Completion results	Our completion results including csv and pdf
Public EMAG2 data	EMAG2 data
Pretrained model	Pretrained guided-diffusion model

Place the pretrained model under ./pretrain and original EMAG2 data under ./EMAG2.

3. Run example

We prepare an easy test for quick evaluation. The input images and masks are in ./data.

bash shell/easy_test.sh

Completion method

1. Step 0: Data preprocess

Download EMAG2_V3 and place it in ./EMAG2. Run the below command, you can preprocess the EMAG2_V3.

python scripts/preprocess.py

2. Step 1: Global completion

bash shell/step1.sh

3. Step 2: Local completion

bash shell/step2.sh

FAQ

How to apply it for other datasets?

If you want train new completion model on a new dataset, it is recommended to follow guided-diffusion repository to obtain guided-diffusion model, then follow our completion method.

Acknowledgements

Our code is built upon RePaint and guided-diffuion. We thank the authors for their excellent work.

If you have any question, feel free to contact fymao@zju.edu.cn or fangyuanmaocs@gmail.com .