crosstyan/OpenGait
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

add gaitedge and reorgnize repo

Browse Source
This commit is contained in:
darkliang
2022-07-05 21:52:41 +08:00
parent 1b17bac455
commit 4205c5f283
28 changed files with 153 additions and 135 deletions
Download Patch File Download Diff File Expand all files Collapse all files
README.md
+11 -108
View File
@@ -8,6 +8,7 @@ OpenGait is a flexible and extensible gait recognition project provided by the [
## What's New
- [Jul 2022] Our paper "[GaitEdge: Beyond Plain End-to-end Gait Recognition for Better Practicality](configs/gaitedge/README.md)" has been accepted by ECCV 2022.
- [Jun 2022] Paper "[A Comprehensive Survey on Deep Gait Recognition: Algorithms, Datasets and Challenges](https://arxiv.org/pdf/2206.13732.pdf)" is available now.
- [Jun 2022] Paper "[Learning Gait Representation from Massive Unlabelled Walking Sequences: A Benchmark](https://arxiv.org/pdf/2206.13964.pdf)" is available now. And the code will be released as soon as possible.
- [Mar 2022] More results on [GREW](https://www.grew-benchmark.org) are supported, and the model files are coming soon.
@@ -21,116 +22,18 @@ OpenGait is a flexible and extensible gait recognition project provided by the [
- **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.
## Getting Started
Please see [0.get_started.md](docs/0.get_started.md). We also provide the following tutorials for your reference:
- [Prepare dataset](docs/2.prepare_dataset.md)
- [Detailed configuration](docs/3.detailed_config.md)
- [Customize model](docs/4.how_to_create_your_model.md)
- [Advanced usages](docs/5.advanced_usages.md)
## Model Zoo
Results and models are available in the [model zoo](docs/1.model_zoo.md).
### [CASIA-B](http://www.cbsr.ia.ac.cn/english/Gait%20Databases.asp)
| Model | NM | BG | CL | Configuration | Input Size | Inference Time | Model Size |
| :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :--------: | :--------: | :--------: | :-------------------------------------------------------------------------------------------: | :--------: | :------------: | :------------: |
| Baseline | 96.3 | 92.2 | 77.6 | [baseline.yaml](config/baseline/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/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/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/gaitgl.yaml) | 64x44 | 38s | 3.10M |
### [OUMVLP](http://www.am.sanken.osaka-u.ac.jp/BiometricDB/GaitMVLP.html)
| Model | Rank@1 | Configuration | Input Size | Inference Time | Model Size |
| :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :--------: | :------------------------------------------: | :--------: | :-------------: | :--------: |
| Baseline | 86.7 | [baseline.yaml](config/baseline/baseline_OUMVLP.yaml) | 64x44 | 1m13s | 44.11M |
| [GaitSet(AAAI2019)](https://arxiv.org/pdf/1811.06186.pdf) | 87.2(87.1) | [gaitset.yaml](config/gaitset/gaitset_OUMVLP.yaml) | 64x44 | 1m26s | 6.31M |
| [GaitPart(CVPR2020)](http://home.ustc.edu.cn/~saihui/papers/cvpr2020_gaitpart.pdf) | 88.6(88.7) | [gaitpart.yaml](config/gaitpart/gaitpart_OUMVLP.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/gaitgl/gaitgl_OUMVLP.yaml) | 64x44 | 5m23s | 95.62M |
### [GREW](https://www.grew-benchmark.org)
| Model | Rank@1 | Configuration | Input Size | Inference Time | Model Size |
| :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :--------: | :------------------------------------------: | :--------: | :-------------: | :--------: |
| Baseline | 48.5 | [baseline.yaml](config/baseline/baseline_GREW.yaml) | 64x44 | 2m23s | 84.12M |
| [GaitSet(AAAI2019)](https://arxiv.org/pdf/1811.06186.pdf) | 48.4 | [gaitset.yaml](config/gaitset/gaitset_GREW.yaml) | 64x44 | - | - |
| [GaitPart(CVPR2020)](http://home.ustc.edu.cn/~saihui/papers/cvpr2020_gaitpart.pdf) | 47.6 | [gaitpart.yaml](config/gaitpart/gaitpart_GREW.yaml) | 64x44 | - | - |
| [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) | 41.5 | [gaitgl.yaml](config/gaitgl/gaitgl_GREW.yaml) | 64x44 | - | - |
| [GaitGL(BNNeck)(ICCV2021)](https://openaccess.thecvf.com/content/ICCV2021/papers/Lin_Gait_Recognition_via_Effective_Global-Local_Feature_Representation_and_Local_Temporal_ICCV_2021_paper.pdf) | 51.7 | [gaitgl.yaml](config/gaitgl/gaitgl_GREW_BNNeck.yaml) | 64x44 | - | - |
| [RealGait(Arxiv now)](https://arxiv.org/pdf/2201.04806.pdf)| (54.1) | - | - | - | - |
------------------------------------------
The results in the parentheses are mentioned in the papers.
**Note**:
- All results are Rank@1, excluding identical-view cases.
- The shown result of GLN is implemented without compact block.
- Only two RTX3090 are used for infering CASIA-B, and eight are used for infering OUMVLP.
## Get Started
### Installation
1. clone this repo.
```
git clone https://github.com/ShiqiYu/OpenGait.git
```
2. Install dependenices:
- pytorch >= 1.6
- torchvision
- pyyaml
- tensorboard
- opencv-python
- tqdm
- py7zr
Install dependenices by [Anaconda](https://conda.io/projects/conda/en/latest/user-guide/install/index.html):
```
conda install tqdm pyyaml tensorboard opencv py7zr
conda install pytorch==1.6.0 torchvision -c pytorch
```
Or, Install dependenices by pip:
```
pip install tqdm pyyaml tensorboard opencv-python py7zr
pip install torch==1.6.0 torchvision==0.7.0
```
### Prepare dataset
See [prepare dataset](docs/0.prepare_dataset.md).
### 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](output).
### Train
Train a model by
```
CUDA_VISIBLE_DEVICES=0,1 python -m torch.distributed.launch --nproc_per_node=2 opengait/main.py --cfgs ./config/baseline/baseline.yaml --phase train
```
- `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 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
Evaluate the trained model by
```
CUDA_VISIBLE_DEVICES=0,1 python -m torch.distributed.launch --nproc_per_node=2 opengait/main.py --cfgs ./config/baseline/baseline.yaml --phase test
```
- `--phase` Specified as `test`.
- `--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. 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
- 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.
## Authors:
**Open Gait Team (OGT)**