Flutter app for offline bird identification
For the detecting task, we uses pretrained model ssd mobilenet.
For the classification task, ResNet34 model structure was adopted, take MetaFGNet/L_Bird_pretrain/checkpoints as a pretrained model, trained on DongNiao DIB-10K using Gorilla-Lab-SCUT/MetaFGNet.
Structure of assets folder:
- assets
- icons (all in git)
- db
- labels
- models
- bird_model.onnx (the quantized onnx version of model20240824.pth)
- ssd_mobilenet.onnx (the quantized version of pre-trained model from onnx modelzoo)
Download all files by running assets_download.sh.
If you want to run batch classification for multiple photos, please check osea-cli.