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1.0.0 official release (#18)

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* fix bug in fix_BN

* gaitgl OUMVLP support.

* update ./doc/3.advance_usage.md Cross-Dataset Evalution & Data Agumentation

* update config

* update docs.3

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* add loss doc and gather input decorator

* refine the create model doc

* support rearrange directory of unzipped OUMVLP

* fix some bugs in loss_aggregator.py

* refine docs and little fix

* add oumvlp pretreatment description

* pretreatment dataset fix oumvlp description

* add gaitgl oumvlp result

* assert gaitgl input size

* add pipeline

* update the readme.

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Co-authored-by: 12131100 <12131100@mail.sustech.edu.cn>
Co-authored-by: noahshen98 <77523610+noahshen98@users.noreply.github.com>
Co-authored-by: Noah <595311942@qq.com>
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Junhao Liang
2021-12-08 20:05:28 +08:00
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**Note:**
This code is only used for **academic purposes**, people cannot use this code for anything that might be considered commercial use.
<img src="./assets/logo2.png" width = "320" height = "110" alt="logo" />
# OpenGait
<div align="center"><img src="./assets/nm.gif" width = "100" height = "100" alt="nm" /><img src="./assets/bg.gif" width = "100" height = "100" alt="bg" /><img src="./assets/cl.gif" width = "100" height = "100" alt="cl" /></div>
OpenGait is a flexible and extensible gait recognition project provided by the [Shiqi Yu Group](https://faculty.sustech.edu.cn/yusq/) and supported in part by [WATRIX.AI](http://www.watrix.ai). Just the pre-beta version is released now, and more documentations as well as the reproduced methods will be offered as soon as possible.
------------------------------------------
OpenGait is a flexible and extensible gait recognition project provided by the [Shiqi Yu Group](https://faculty.sustech.edu.cn/yusq/) and supported in part by [WATRIX.AI](http://www.watrix.ai).
**Highlighted features:**
- **Multiple Models Support**: We reproduced several SOTA methods, and reached the same or even better performance.
- **DDP Support**: The officially recommended [`Distributed Data Parallel (DDP)`](https://pytorch.org/tutorials/intermediate/ddp_tutorial.html) mode is used during the training and testing phases.
- **Multiple Models Support**: We reproduced several SOTA methods, and reached the same or even the better performance.
- **DDP Support**: The officially recommended [`Distributed Data Parallel (DDP)`](https://pytorch.org/tutorials/intermediate/ddp_tutorial.html) mode is used during both the training and testing phases.
- **AMP Support**: The [`Auto Mixed Precision (AMP)`](https://pytorch.org/tutorials/recipes/recipes/amp_recipe.html?highlight=amp) option is available.
- **Nice log**: We use [`tensorboard`](https://pytorch.org/docs/stable/tensorboard.html) and `logging` to log everything, which looks pretty.
# Model Zoo
## Model Zoo
### CASIA-B
| Model | NM | BG | CL | Configuration | Input Size | Inference Time | Model Size |
| :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :--------: | :--------: | :--------: | :------------------------------------------------------------------------------------------- | :--------: | :------------: | :------------: |
| Baseline | 96.3 | 92.2 | 77.6 | [baseline.yaml](config/baseline.yaml) | 64x44 | 12s | 3.78M |
| [GaitSet(AAAI2019)](https://arxiv.org/pdf/1811.06186.pdf) | 95.8(95.0) | 90.0(87.2) | 75.4(70.4) | [gaitset.yaml](config/gaitset.yaml) | 64x44 | 11s | 2.59M |
| [GaitPart(CVPR2020)](http://home.ustc.edu.cn/~saihui/papers/cvpr2020_gaitpart.pdf) | 96.1(96.2) | 90.7(91.5) | 78.7(78.7) | [gaitpart.yaml](config/gaitpart.yaml) | 64x44 | 22s | 1.20M |
| [GLN*(ECCV2020)](http://home.ustc.edu.cn/~saihui/papers/eccv2020_gln.pdf) | 96.4(95.6) | 93.1(92.0) | 81.0(77.2) | [gln_phase1.yaml](config/gln/gln_phase1.yaml), [gln_phase2.yaml](config/gln/gln_phase2.yaml) | 128x88 | 14s | 8.54M / 14.70M |
| [GaitGL(ICCV2021)](https://openaccess.thecvf.com/content/ICCV2021/papers/Lin_Gait_Recognition_via_Effective_Global-Local_Feature_Representation_and_Local_Temporal_ICCV_2021_paper.pdf) | 97.4(97.4) | 94.5(94.5) | 83.8(83.6) | [gaitgl.yaml](config/gaitgl.yaml) | 64x44 | 31s | 3.10M |
| [GaitSet(AAAI2019)](https://arxiv.org/pdf/1811.06186.pdf) | 95.8(95.0) | 90.0(87.2) | 75.4(70.4) | [gaitset.yaml](config/gaitset.yaml) | 64x44 | 13s | 2.59M |
| [GaitPart(CVPR2020)](http://home.ustc.edu.cn/~saihui/papers/cvpr2020_gaitpart.pdf) | 96.1(96.2) | 90.7(91.5) | 78.7(78.7) | [gaitpart.yaml](config/gaitpart.yaml) | 64x44 | 56s | 1.20M |
| [GLN*(ECCV2020)](http://home.ustc.edu.cn/~saihui/papers/eccv2020_gln.pdf) | 96.4(95.6) | 93.1(92.0) | 81.0(77.2) | [gln_phase1.yaml](config/gln/gln_phase1.yaml), [gln_phase2.yaml](config/gln/gln_phase2.yaml) | 128x88 | 47s/46s | 8.54M / 14.70M |
| [GaitGL(ICCV2021)](https://openaccess.thecvf.com/content/ICCV2021/papers/Lin_Gait_Recognition_via_Effective_Global-Local_Feature_Representation_and_Local_Temporal_ICCV_2021_paper.pdf) | 97.4(97.4) | 94.5(94.5) | 83.8(83.6) | [gaitgl.yaml](config/gaitgl.yaml) | 64x44 | 38s | 3.10M |
### OUMVLP
| Model | Rank@1 | Configuration | Input Size | Inference Time | Model Size |
| :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :--------: | :------------------------------------------: | :--------: | :------------- | :--------: |
| Baseline | 86.7 | [baseline.yaml](config/OUMVLP/baseline.yaml) | 64x44 | 1m13s | 44.11M |
| [GaitSet(AAAI2019)](https://arxiv.org/pdf/1811.06186.pdf) | 87.2(87.1) | [gaitset.yaml](config/OUMVLP/gaitset.yaml) | 64x44 | 1m26s | 6.31M |
| [GaitPart(CVPR2020)](http://home.ustc.edu.cn/~saihui/papers/cvpr2020_gaitpart.pdf) | 88.6(88.7) | [gaitpart.yaml](config/OUMVLP/gaitpart.yaml) | 64x44 | 8m04s | 3.78M |
| [GaitGL(ICCV2021)](https://openaccess.thecvf.com/content/ICCV2021/papers/Lin_Gait_Recognition_via_Effective_Global-Local_Feature_Representation_and_Local_Temporal_ICCV_2021_paper.pdf) | 89.9(89.7) | [gaitgl.yaml](config/OUMVLP/gaitgl.yaml) | 64x44 | 5m23s | 95.62M |
The results in the parentheses are mentioned in the papers
**Note**:
- All the models were tested on [CASIA-B](http://www.cbsr.ia.ac.cn/english/Gait%20Databases.asp) (Rank@1, excluding identical-view cases).
- All results are Rank@1, excluding identical-view cases.
- The shown result of GLN is implemented without compact block.
- Only 2 RTX6000 are used during the inference phase.
- The results on [OUMVLP](http://www.am.sanken.osaka-u.ac.jp/BiometricDB/GaitMVLP.html) will be released soon.
It's inference process just cost about 90 secs(Baseline & 8 RTX6000).
- Only two RTX3090 are used for infering CASIA-B, and eight are used for infering OUMVLP.
# Get Started
## Installation
## Get Started
### Installation
1. clone this repo.
```
git clone https://github.com/ShiqiYu/OpenGait.git
@@ -57,56 +66,66 @@ It's inference process just cost about 90 secs(Baseline & 8 RTX6000).
pip install tqdm pyyaml tensorboard opencv-python
pip install torch==1.6.0 torchvision==0.7.0
```
## Prepare dataset
See [prepare dataset](doc/prepare_dataset.md).
### Prepare dataset
See [prepare dataset](docs/0.prepare_dataset.md).
## Get trained model
### Get trained model
- Option 1:
```
python misc/download_pretrained_model.py
```
- Option 2: Go to the [release page](https://github.com/ShiqiYu/OpenGait/releases/), then download the model file and uncompress it to `output`.
- Option 2: Go to the [release page](https://github.com/ShiqiYu/OpenGait/releases/), then download the model file and uncompress it to [output](output).
## Train
### Train
Train a model by
```
CUDA_VISIBLE_DEVICES=0,1 python -m torch.distributed.launch --nproc_per_node=2 lib/main.py --cfgs ./config/baseline.yaml --phase train
```
- `python -m torch.distributed.launch` Our implementation uses DistributedDataParallel.
- `--nproc_per_node` The number of gpu to use, it must equal the length of `CUDA_VISIBLE_DEVICES`.
- `--cfgs` The path of config file.
- `python -m torch.distributed.launch` [DDP](https://pytorch.org/tutorials/intermediate/ddp_tutorial.html) launch instruction.
- `--nproc_per_node` The number of gpus to use, and it must equal the length of `CUDA_VISIBLE_DEVICES`.
- `--cfgs` The path to config file.
- `--phase` Specified as `train`.
- `--iter` You can specify a number of iterations or use `restore_hint` in the configuration file and resume training from there.
- `--log_to_file` If specified, log will be written on disk simultaneously.
<!-- - `--iter` You can specify a number of iterations or use `restore_hint` in the config file and resume training from there. -->
- `--log_to_file` If specified, the terminal log will be written on disk simultaneously.
You can run commands in [train.sh](train.sh) for training different models.
## Test
Use trained model to evaluate by
### Test
Evaluate the trained model by
```
CUDA_VISIBLE_DEVICES=0,1 python -m torch.distributed.launch --nproc_per_node=2 lib/main.py --cfgs ./config/baseline.yaml --phase test
```
- `--phase` Specified as `test`.
- `--iter` You can specify a number of iterations or or use `restore_hint` in the configuration file and restore model from there.
- `--iter` Specify a iteration checkpoint.
**Tip**: Other arguments are the same as train phase.
You can run commands in [test.sh](test.sh) for testing different models.
## Customize
1. First, you need to read the [config documentation](doc/detailed_config.md) to figure out the usage of every item.
2. If you want create your own model, see [here](doc/how_to_create_your_model.md).
1. Read the [detailed config](docs/1.detailed_config.md) to figure out the usage of needed setting items;
2. See [how to create your model](docs/2.how_to_create_your_model.md);
3. There are some advanced usages, refer to [advanced usages](docs/3.advanced_usages.md), please.
# Warning
## Warning
- Some models may not be compatible with `AMP`, you can disable it by setting `enable_float16` **False**.
- In `DDP` mode, zombie processes may be generated when the program terminates abnormally. You can use this command `kill $(ps aux | grep main.py | grep -v grep | awk '{print $2}')` to clear them.
- In `DDP` mode, zombie processes may be generated when the program terminates abnormally. You can use this command [sh misc/clean_process.sh](./misc/clean_process.sh) to clear them.
- We implemented the functionality about testing while training, but it slightly affected the results. None of our published models use this functionality. You can disable it by setting `with_test` **False**.
- Recommended Pytorch version: 1.6-1.8
# Authors:
## Authors:
**Open Gait Team (OGT)**
- [Chao Fan (樊超)](https://faculty.sustech.edu.cn/?p=128578&tagid=yusq&cat=2&iscss=1&snapid=1&orderby=date)
- [Chuanfu Shen (沈川福)](https://faculty.sustech.edu.cn/?p=95396&tagid=yusq&cat=2&iscss=1&snapid=1&orderby=date)
- [Junhao Liang (梁峻豪)](https://faculty.sustech.edu.cn/?p=95401&tagid=yusq&cat=2&iscss=1&snapid=1&orderby=date)
- [Chao Fan (樊超)](https://faculty.sustech.edu.cn/?p=128578&tagid=yusq&cat=2&iscss=1&snapid=1&orderby=date), 12131100@mail.sustech.edu.cn
- [Chuanfu Shen (沈川福)](https://faculty.sustech.edu.cn/?p=95396&tagid=yusq&cat=2&iscss=1&snapid=1&orderby=date), 11950016@mail.sustech.edu.cn
- [Junhao Liang (梁峻豪)](https://faculty.sustech.edu.cn/?p=95401&tagid=yusq&cat=2&iscss=1&snapid=1&orderby=date), 12132342@mail.sustech.edu.cn
# Acknowledgement
## Acknowledgement
- GLN: [Saihui Hou (侯赛辉)](http://home.ustc.edu.cn/~saihui/index_english.html)
- GaitGL: Beibei Lin (林贝贝)
- GaitGL: [Beibei Lin (林贝贝)](https://scholar.google.com/citations?user=KyvHam4AAAAJ&hl=en&oi=ao)
<!-- ## Citation
```
``` -->
**Note:**
This code is only used for **academic purposes**, people cannot use this code for anything that might be considered commercial use.