https://github.com/tensorboy/centerpose
Push the Extreme of the pose estimation
https://github.com/tensorboy/centerpose
Last synced: 10 months ago
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Push the Extreme of the pose estimation
- Host: GitHub
- URL: https://github.com/tensorboy/centerpose
- Owner: tensorboy
- License: mit
- Created: 2019-10-11T18:38:50.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2020-02-26T18:51:10.000Z (almost 6 years ago)
- Last Synced: 2025-05-05T02:55:14.267Z (10 months ago)
- Language: Python
- Size: 51.5 MB
- Stars: 239
- Watchers: 10
- Forks: 45
- Open Issues: 16
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# The repo is based on [CenterNet](https://arxiv.org/abs/1904.07850), which aimed for push the boundary of human pose estimation
multi person pose estimation using center point detection:
## Main results
### Keypoint detection on COCO validation 2017
| Backbone | AP | FPS | TensorRT Speed | GFLOPs |Download |
|--------------|-----------|--------------|----------|----------|----------|
|DLA-34 | 62.7 | 23 | - | - |[model](https://drive.google.com/open?id=1IahJ3vpjTVu1p-Okf6lcn-bM7fVKNg6N) |
|Resnet-50 | 54.5 | 28 | 33 | - |[model](https://drive.google.com/open?id=1oBgWrfigo2fGtpQJXQ0stADTgVFxPWGq) |
|MobilenetV3 | 46.0 | 30 | - | - |[model](https://drive.google.com/open?id=1snJnADAD1NUzyO1QXCftuZu1rsr8095G) |
|ShuffleNetV2 | 43.9 | 25 | - | - |[model](https://drive.google.com/open?id=1FK7YQzCB6mLcb0v4SOmlqtRJfA-PQSvN) |
|[HRNet_W32](https://drive.google.com/open?id=1mJoK7KEx35Wgf6uAZ-Ez5IwAeOk1RYw0)| 63.8 | 16 | - | - |[model](https://drive.google.com/open?id=1X0yxGeeNsD4VwU2caDo-BaH_MoCAnU_J) |
|[HardNet](https://github.com/PingoLH/FCHarDNet)| 46.0 | 30 | - | - |[model](https://drive.google.com/open?id=1CFc_qAAT4NFfrAG8JOxRVG8CAw9ySuYp) |
|[Darknet53]()| 34.2 | 30 | - | - |[model](https://drive.google.com/open?id=1S8spP_QKHqIYmWpfF9Bb4-4OoUXIOnkh) |
|[EfficientDet]()| 38.2 | 30 | - | - |[model](https://drive.google.com/open?id=1S8spP_QKHqIYmWpfF9Bb4-4OoUXIOnkh) |
## Installation
git submodule init&git submodule update
Please refer to [INSTALL.md](readme/INSTALL.md) for installation instructions.
## Use CenterNet
We support demo for image/ image folder, video, and webcam.
First, download the model [DLA-34](https://drive.google.com/open?id=1OkHjjViB0dzbuicdtIam-YcoT0sYpmjP)
from the [Model zoo](https://drive.google.com/open?id=1UG2l8XtjOfBtG_GLpSdxlWS2wxFR8hQF) and put them in anywhere.
Run:
~~~
cd tools; python demo.py --cfg ../experiments/dla_34_512x512.yaml --TESTMODEL /your/model/path/dla34_best.pth --DEMOFILE ../images/33823288584_1d21cf0a26_k.jpg --DEBUG 1
~~~
The result for the example images should look like:
## Evaluation
~~~
cd tools; python evaluate.py --cfg ../experiments/dla_34_512x512.yaml --TESTMODEL /your/model/path/dla34_best.pth --DEMOFILE --DEBUG 0
~~~
## Training
After [installation](readme/INSTALL.md), follow the instructions in [DATA.md](readme/DATA.md) to setup the datasets.
We provide config files for all the experiments in the [experiments](experiments) folder.
```
cd ./tools python -m torch.distributed.launch --nproc_per_node 4 train.py --cfg ../experiments/*yalm
```
## Demo
the demo files located in the `demo` directory, which is would be a very robust human detection+tracking+face reid system.
## License
MIT License (refer to the LICENSE file for details).
## Citation
If you find this project useful for your research, please use the following BibTeX entry.
@inproceedings{zhou2019objects,
title={Objects as Points},
author={Zhou, Xingyi and Wang, Dequan and Kr{\"a}henb{\"u}hl, Philipp},
booktitle={arXiv preprint arXiv:1904.07850},
year={2019}
}