Introduction

This project is the award-winning work of Chinese Collegiate Computing Competition (4C 2023). We have built a front-end and back-end system to display bird audio classification results and encyclopedia information.

Start

Before running the project, you need to download some necessary files.

1. Please unzip example_audio.zip in the server/media/example-audio folder.

2. Please download the pretrained model to any location and configure the absolute path of the model in server/configure/model.py. We provide 2 pretrained model:

• val_TimmClassifier_efficientnet_b4_0_f1_score_v1
• val_TimmClassifier_efficientnet_b4_0_f1_score_v2

3. If you need to use the email registration function, please configure the email server in server/email.py

server

cd server/
pip install -r ./requirements.txt
python ./manage.py makemigrations
python ./manage.py migrate
python ./manage.py runserver 8000

client

npm install
npm run serve

Contact

If you have any questions about this project, please contact:

model: [email protected]
client: [email protected]
server: [email protected]

Citation

If this project is helpful to you, please cite it in your paper:

@software{Bird_Sound_Classification,
  author = {Xiang Li and Fang Wu and Haidong Xin},
  title = {{Bird_Sound_Classification}},
  url = {https://github.com/xhd0728/Bird_Sound_Classification},
  version = {1.0},
  year = {2024}
}