** Contributor
JongHwan Park : bomebug15@ds.seoultech.ac.kr
HoHyeun Hwang : hhhwang94@naver.com
JuHee Han : fgtr153@ds.seoultech.ac.kr
For Plant Diseases Classification , We use data from https://www.kaggle.com/vipoooool/new-plant-diseases-dataset
We used two datasets, a small dataset consisting only of apple disease, and the entire dataset did not name it separately. And we compared the performance of the three models of plant disease classification. CNN Model is based on LeNet5, and other models is supposed by torch or other package(efficientnet is not supposed by pytorch official).
If you want to train or demo on small dataset, try
small_main.py, small_model.py, small_dataloader.py
If you want to use all dataset, try
main.py, model.py, dataloader.py
pip install torch, argparse, wandb(if you want to monitor on wandb), seaborn, tqdm, torchvision
pip install efficientnet_pytorch
python small_main.py or main.py --batch_size(int) --model[efficientnet,resnet, CNN] --device[cpu, gpu] --epoch(int) --mode[train,visualization]
python model_summary.py