Resource constraint crop damage classification using depth channel shuffling[Paper]
Md Tanvir Islam 1, Safkat Shahrier Swapnil 2, Md. Masum Billal 3, Asif Karim 4, *, Niusha Shafiabady 5, Md. Mehedi Hassan 6, *
| 1. Sungkyunkwan University, South Korea | 2. RUET, Bangladesh | 3. USTC, China | 4. Charles Darwin University, Australia | 5. Australian Catholic University, Australia | 6. Khulna University, Bangladesh || *Corresponding Authors |
dataset/
└── data/
├── train/
│ ├── damaged/
│ │ ├── image1.jpg
│ │ ├── image2.jpg
│ │ └── ...
│ └── non_damaged/
│ ├── image3.jpg
│ ├── image4.jpg
│ └── ...
└── test/
├── damaged/
│ ├── image101.jpg
│ ├── image102.jpg
│ └── ...
└── non_damaged/
├── image103.jpg
├── image104.jpg
└── ...
Download Model Weight (will upload soon)
conda create --name lightCDC python=3.9
conda activate lightCDC
conda install pytorch==2.5.1 torchvision==0.20.1 torchaudio==2.5.1 pytorch-cuda=11.8 -c pytorch -c nvidia
pip install -r requirements.txt
python train.py --config <name_of_your_config> --batch_size <batch_size> --lr <learning_rate>
For other paramaetrs you can edit the configs.py file of the config folder.
python test.py --mode single --model_weight <model_weight_path> --image_path <your_image_path>
python inference.py --mode multiple --model_weight <model_weight_path>
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@article{islam2025resource,
title={Resource constraint crop damage classification using depth channel shuffling},
author={Islam, Md Tanvir and Swapnil, Safkat Shahrier and Billal, Md Masum and Karim, Asif and Shafiabady, Niusha and Hassan, Md Mehedi},
journal={Engineering Applications of Artificial Intelligence},
volume={144},
pages={110117},
year={2025},
publisher={Elsevier}
}