| # Transformer-based Fine-Grained Fungi Classification in an Open-Set Scenario | |
| This repository is targeted towards solving the FungiCLEF 2023 (https://huggingface.co/spaces/competitions/FungiCLEF2023) challenge. It is based on MMPreTrain (https://github.com/open-mmlab/mmpretrain). | |
| ## Usage | |
| ### Installation | |
| ```bash | |
| conda create -n fungi2023 python=3.10 pytorch=2.0.1 torchvision=0.15.2 pytorch-cuda=11.8 -c pytorch -c nvidia | |
| conda activate fungi2023 | |
| pip install -r requirements.txt | |
| mim install "mmpretrain==1.0.0rc7" | |
| ``` | |
| ### Data | |
| The challenge data has to be downloaded and put into _data/fungiclef2022/_. | |
| ### Training | |
| ```bash | |
| bash tools/dist_train.sh configs/swinv2_base_w24_b32x4-fp16_fungi+val_res_384_cb_epochs_6.py 4 | |
| ``` | |
| ### Inference on pre-trained models | |
| ```bash | |
| python tools/test_generate_result_pre-consensus_tta.py models/swinv2_base_w24_b32x4-fp16_fungi+val_res_384_cb_epochs_6.py models/swinv2_base_w24_b32x4-fp16_fungi+val_res_384_cb_epochs_6_20230524-a251a50a.pth results.csv --threshold 0.2 --no-scores | |
| ``` | |