Awesome

Preparation

• Install the required packages: pip install -r requirements.txt
• Download the remote sensing change captioning datasets. We have adopted LEVIR-MCI in this repository.
• The data structure of LEVIR-MCI is organized as follows:

├─/root/Data/LEVIR-MCI-dataset/
        ├─LevirCCcaptions.json
        ├─images
             ├─train
             │  ├─A
             │  ├─B
             │  ├─label
             │  ├─semi_mask
             │  ├─supervised_mask
             │  ├─video_data
             ├─val
             │  ├─A
             │  ├─B
             │  ├─label
             │  ├─semi_mask
             │  ├─supervised_mask
             │  ├─video_data
             ├─test
             │  ├─A
             │  ├─B
             │  ├─label
             │  ├─semi_mask
             │  ├─supervised_mask
             │  ├─video_data

where folder A contains images of pre-phase, folder B contains images of post-phase.

The semi_mask represents labels obtained from the 5% semi-supervised method, while supervised_mask represents using supervised method.

They can be acquired by using the SemiCD method.

To generate the video and prepare the data:

$ python generate_MP4.py
$ python preprocess_data.py

Download the video_encoder.pth from MV-CC checkpoints and put it in checkpoints folder.

Download the model from InternVideo2_Chat_8B_InternLM2_5 and place it in the /root/video_model folder.

Training

• Ensure you have completed the data preparation steps above, and then proceed to train the model as follows:

$ python train_video_sty.py

!NOTE: If the program encounters the error: "'Meteor' object has no attribute 'lock'," we recommend installing it with sudo apt install openjdk-11-jdk to resolve this issue.

Alternatively, you can obtain our pretrained models from MV-CC checkpoints.

Caption Generation

• To generate captions, run the following command:

$ python test_video_sty.py

Mask mode

Mask mode is set by args.mode

5% semi-supervised method: semi_mask

Supervised method: supervised_mask

GT method: label

Paper

MV-CC: Mask Enhanced Video Model for Remote Sensing Change Caption

Please cite the following paper if you find it useful for your research:

@misc{liu2024mvccmaskenhancedvideo,
      title={MV-CC: Mask Enhanced Video Model for Remote Sensing Change Caption}, 
      author={Ruixun Liu and Kaiyu Li and Jiayi Song and Dongwei Sun and Xiangyong Cao},
      year={2024},
      eprint={2410.23946},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2410.23946}, 
}

Acknowledgement

The authors would like to thank the contributors to the LEVIR-MCI.

License

This repo is distributed under MIT License. The code can be used for academic purposes only.