LIO/classification

• Classification with LIO
• • Setup
  • • Install dependencies
    • Prepare dataset
  • Train a model
  • Help
  • Citation

Classification with LIO

This page provides basic tutorials about the usage of Look-into-Object for image classfication.

This code is tested with PyTorch 1.3.0 and torchvision 0.4.1.

Setup

Install dependencies

python -m pip install -r requirements.txt

Prepare dataset

You can follow the Datasets Prepare Section in DCL.

Note: The label_num in annotations starts from 1 rather than 0.

Train a model

Run train_index.py to train CUB/STCAR/AIR.

Train with last stage and 3 positive images on CUB (LIO/ResNet-50 7x7):

python train_index.py --data CUB --stage 3 --num_positive 3

Help

Feel free to open an issue if you encounter troubles.

Citation

If you use this codebase in your research, please cite our paper:

@InProceedings{Zhou_2020_CVPR,
author = {Zhou, Mohan and Bai, Yalong and Zhang, Wei and Zhao, Tiejun and Mei, Tao},
title = {Look-Into-Object: Self-Supervised Structure Modeling for Object Recognition},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}