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The source code of Paper: Cross-Modal Attention Wavelet Subband Attention Model for the Remote Sensing Copy-Move Question Answering

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Cross-Modal Attention Wavelet Subband Attention Model for the Remote Sensing Copy-Move Question Answering

This is the initial version of the Real-RSCM dataset and CMA-WSA Framework.

Installation

conda create -n CMA-WSA python=3.11
conda activate CMA-WSA
pytorch

install pytorch

# e.g. CUDA 11.8
# with conda
conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia
# with pip
pip install torch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1 --index-url https://download.pytorch.org/whl/cu118
Install Packages
pip install -r requirements.txt

Download Datasets

Download pre-trained weights

Download clip-b-32 weights from Hugging Face

  • Clip Directory: models/clipModels/openai_clip_b_32/

Download U-Net weights from Github

  • U-Net Directory: models/imageModels/milesial_UNet/

Start Training

python main.py
  • Modify the experiment settings and hyperparameters in src/config.py

License

CC BY-NC-SA 4.0

All images and their associated annotations in Global-TQA can be used for academic purposes only, but any commercial use is prohibited.

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The source code of Paper: Cross-Modal Attention Wavelet Subband Attention Model for the Remote Sensing Copy-Move Question Answering

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