# ML_GCN

**Repository Path**: HEART1/ML_GCN

## Basic Information

- **Project Name**: ML_GCN
- **Description**: PyTorch implementation of Multi-Label Image Recognition with Graph Convolutional Networks, CVPR 2019.
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2019-10-20
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# ML_GCN.pytorch
PyTorch implementation of [Multi-Label Image Recognition with Graph Convolutional Networks](https://arxiv.org/abs/1904.03582), CVPR 2019.



### Requirements
Please, install the following packages
- numpy
- torch-0.3.1
- torchnet
- torchvision-0.2.0
- tqdm

### Download pretrain models
checkpoint/coco ([GoogleDrive](https://drive.google.com/open?id=1ivLi1Rc-dCUmN1ProcMk76zxF1DSvlIk))

checkpoint/voc ([GoogleDrive](https://drive.google.com/open?id=1lhbmW5g-Mo9KgI07nmc1kwSbEnb6t-YA))

or

[Baidu](https://pan.baidu.com/s/17j3lTjMRmXvWHT86zhaaVA)

### Options
- `lr`: learning rate
- `lrp`: factor for learning rate of pretrained layers. The learning rate of the pretrained layers is `lr * lrp`
- `batch-size`: number of images per batch
- `image-size`: size of the image
- `epochs`: number of training epochs
- `evaluate`: evaluate model on validation set
- `resume`: path to checkpoint

### Demo VOC 2007
```sh
python3 demo_voc2007_gcn.py data/voc --image-size 448 --batch-size 32 -e --resume checkpoint/voc/voc_checkpoint.pth.tar
```

### Demo COCO 2014
```sh
python3 demo_coco_gcn.py data/coco --image-size 448 --batch-size 32 -e --resume checkpoint/coco/coco_checkpoint.pth.tar
```

## Citing this repository
If you find this code useful in your research, please consider citing us:

```
@inproceedings{ML_GCN_CVPR_2019,
author = {Zhao-Min, Chen and Xiu-Shen, Wei and Peng, Wang and Yanwen, Guo},
title = {{Multi-Label Image Recognition with Graph Convolutional Networks}},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2019}
}
```
## Reference
This project is based on https://github.com/durandtibo/wildcat.pytorch

## Tips
If you have any questions about our work, please do not hesitate to contact us by emails.