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This is the offical code for MCFNet

Getting Started

This is an example of how you may give instructions on setting up your project locally. To get a local copy up and running follow these simple example steps. Pretrained model will come soon.

Prerequisites

This project is based on Python, PyTorch.

  • requirements
    ntorch>=0.4.1
    torchvision>=0.2.1
    dominate>=2.3.1
    visdom>=0.1.8.3

Testing

  1. Add the NIR images to the folder: /dataset/Validation, please make sure the png images contains "nir" in the filename. Otherwise, please do necssary rectification in /data/VCIP_nir2rgb_dataset.py, class VCIPNir2RGBDataset_gen(BaseDataset): self.A_paths= [f for f in self.dir_A.glob('nir.png') if is_image(f)]
  2. In launch.json, please find the "name": "Python: Generate_results", change the "--gpu_ids" to "0" or "1" accordingly.
  3. Run the test-NIR.py
  4. Go to "/final_results/results/test_latest_iter950/images", the generated RGB files are inside this folder.

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Contact

Alex - yangxingxing817@gmail.com

Huiyu Zhai - wenyu.zhy@gmail.com

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Citation

Welcome to cite our paper if it inspires you!

  @misc{zhai2024multiscale,
   title={Multi-scale HSV Color Feature Embedding for High-fidelity NIR-to-RGB Spectrum Translation}, 
   author={Huiyu Zhai and Mo Chen and Xingxing Yang and Gusheng Kang},
   year={2024},
   eprint={2404.16685},
   archivePrefix={arXiv},
   primaryClass={cs.CV}
   }

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