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gm-scenet's Introduction

Structured Context Enhancement Network for Mouse Pose Estimation

This repository provides a PyTorch implementation of the paper Structured Context Enhancement Network for Mouse Pose Estimation.

Demo

Requirements

Tested with:

PyTorch 1.4.0
Torchvision 0.5.0
Python 3.6.8

Data Preparation

Download the data from DeepLabCut Mouse Pose and DeepPoseKit Animal Pose. Then put them under the data directory:
```
 -labeled-data\  
 
   -mouse\  
        ...
   -flyimage\ 
        ...   
   -zebraimage\  
        ...
```

Training

Before running train.py, we need to compile Directionmax operation used in our paper, which is inspired by the corner pooling scheme in CornerNet.

`cd <CornerNet dir>/models/py_utils/_cpools/`
`python setup.py install --user`

Then train the model

`python train.py`

Ethical Proof

All experimental procedures were performed in accordance with the Guidance on the Operation of the Animals (Scientific Procedures) Act, 1986 (UK) and approved by the Queen’s University Belfast Animal.

Citation

If you find this repository useful, please cite our paper:

@article{zhou2021structured,
  title={Structured Context Enhancement Network for Mouse Pose Estimation},
  author={Zhou, Feixiang and Jiang, Zheheng and Liu, Zhihua and Chen, Fang and Chen, Long and Tong, Lei and Yang, Zhile and Wang, Haikuan and Fei, Minrui and Li, Ling and others},
  journal={IEEE Transactions on Circuits and Systems for Video Technology},
  year={2021},
  publisher={IEEE}
}

Contact

For any questions, feel free to contact: [email protected]

gm-scenet's People

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3monochloride4 yuqi9797

gm-scenet's Issues

关于data_load_RGB_multiscale.py文件，缺文件问题。

作者您好，
请问data_load_RGB_multiscale.py文件中，需要导入datapreprocess文件中的多个模块，请问这部分代码在哪里呢？

Anyone have the warning?

Warning: masked_scatter_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead. (masked_scatter__cuda at /tmp/pip-req-build-ufslq_a9/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:57)

Implementation release

Hello, i would be interested in testing your implementation. Do you have an approximate date on when it should be released ?
Thank you in advance.

inference code

Hi, bro! I am intersted in your work. Can you release your inference code? Looking forward your reply.

Not found data_load_RGB_multiscale, AttentionCRFmodel.mainStackedHourGlass_full_finalcas2_C3GM2

Hello, I am very sorry to disturb you. While checking the train.py file, I found that the statements importing library functions from data_load_RGB_multiscale import MouseKeypointsDataset and from AttentionCRFmodel.mainStackedHourGlass_full_ finalcas2_C3GM2 import * the data_load_RGB_multiscale, AttentionCRFmodel.mainStackedHourGlass_full_finalcas2_C3GM2 are not found in the file, can the author provide it?

The code question

Hello Author:
https://github.com/FeixiangZhou/GM-SCENet/blob/main/utilis/metrics.py#L80
norm = np.ones((pred.shape[0], 2)) * np.array([w, h]) / 6

why there is not np.array([h, w])??

Any plans to release the PDMB dataset?

I plan to integrate the PDMB dataset in MMPose, an open-source toolbox for pose estimation related tasks.

Do you have any plans to release the PDMB dataset?

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