GNOEYHEAT / LowResolution_ImgClf

저해상도 조류 이미지 분류 AI 경진대회, DACON (2024.04.08 ~ 2024.05.06)

LowResolution_ImgClf

The following codes are the solutions (3st place, private score: 0.98274) for the dacon competition.

Setup

git clone https://github.com/GNOEYHEAT/LowResolution_ImgClf.git
cd LowResolution_ImgClf
conda create -n bird_cls python=3.10 
conda activate bird_cls
conda install pytorch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 pytorch-cuda=11.8 -c pytorch -c nvidia
pip install -r requirements.txt

• Tested on NVIDIA RTX 3090, A100

Dataset

• The dataset can be downloaded from the dacon link.
• Place the downloaded data inside lowResolution_ImgClf directory,

LowResolution_ImgClf
├── data
│   ├── train
│   │   ├── TRAIN_00000.jpg
│   │   ├── ...
│   ├── test
│   │   ├── TEST_00000.jpg
│   │   ├── ...
│   ├── upscale_train
│   │   ├── TRAIN_00000.jpg
│   │   ├── ...
│   ├── train.csv
│   ├── test.csv
│   └── sample_submission.csv

or modify train_csv_path and test_csv_path in configs/base.yaml. It is recommended to input the absolute paths for train_csv_path and test_csv_path.

Train and Make Submission File

• If you want to train the model and generate the submission file all at once, execute the script below.

python main.py

Train

• If you only want to train, execute the script below.

python scripts/train.py

Make Submission File

• If you want to generate the submission file using prediction files, execute the script below.

python scripts/submission.py