This repository hosts the best CLEAR-Net checkpoint for cloud removal experiments on SEN12MS-CR style SAR and cloudy optical inputs.

The implementation, demo server, and local inference launcher are maintained in the GitHub repository:

GitHub: https://github.com/smturtle2/cr-project

The checkpoint is stored in the project training format. The inference code expects a PyTorch checkpoint containing a model state dict.

Checkpoint metadata:

Evaluation on the project test split:

Clone the project code:

Download the checkpoint:

Run the local demo:

If the SEN12MS-CR cache is stored outside the project default path, pass it through the demo arguments:

The demo opens a local CLEAR-Net scene inference server and uses the checkpoint from this repository.

This checkpoint is intended for research and demonstration of optical cloud removal using SAR-guided restoration on SEN12MS-CR style data.

The model card reports results from the project evaluation pipeline. Performance may differ with different preprocessing, dataset versions, sensor products, or scene tiling settings.