tagperson-blender

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tagperson-blender

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# TAGPerson-Blender
This repo contains the rendering codes of the paper `TAGPerson: A Target-Aware Generation pipeline for Person Re-identification`.

We use [BlenderPy](https://github.com/TylerGubala/blenderpy) to render images under parameterized control.

The training codes are in another project [tagperson-reid](https://github.com/tagperson/tagperson-reid), which uses PyTorch to train the models.

## 1. Get Started

#### 1.1 Install Python Environment

Create the conda env:
```
conda create -n tagperson-blender python=3.7.10
conda activate tagperson-blender
```

Download the bpy wheel `bpy-2.91a0-cp37-cp37m-manylinux2014_x86_64.whl`, and then:
```
pip install bpy-2.91a0-cp37-cp37m-manylinux2014_x86_64.whl
```
Execute the post-processing command:
```
bpy_post_install
```

If encounter error:
```
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ImportError: libXrender.so.1: cannot open shared object file: No such file or directory
```
You should switch to root user and install the lib.

On Ubuntu:
```
sudo apt-get install libxrender1
```

On CentOS:
```
sudo yum install libXrender.x86_64
```

**Note: install `bpy` by `pip install bpy` does not work for me.**

Since we use plugins for blender to load models from `MakeHuman`, we need to put some plugin codes into the library path.

Put the plugin `import_runtime_mhx2` and `makewalk` into the installation location of `bpy`, such as:
```
mv import_runtime_mhx2 makewalk ~/miniconda3/envs/tagperson-blender/lib/python3.7/site-packages/2.91/scripts/addons
```
The `bpy-2.91a0-cp37-cp37m-manylinux2014_x86_64.whl`, `import_runtime_mhx2` and `makewalk` can be download from the link described in `1.2 Prepare Data`

Install other python dependencies:
```
pip install -r requirements.txt
```

#### 1.2 Prepare Data

In order to prepare the blender rendering, we need to prepare necessary data in `data/` folder:
- `data/makehuman/makehuman_2954_mhx2_standing02`: 3D human models to render
- `data/bg_collection`: background images
- `data/pose`: pose structure json files
- `data/attribute_distribution`: The target-aware attribute_distribution information
- `data/shield_v2`: [Optional] The images used to create shield cases.

The `attribute_distribution` and `shield_v2` are optional. All names of these paths can be modified, as long as they are correctly specified in the configuration file.

You can download these data from [the link](https://drive.google.com/drive/folders/1eiFvsk78OqxerKSceRkORTlk5B7EB3ao).

## 2. Demo
Suppose the 3D human models have been downloaded to `data/makehuman` folder.

We can run a demo script to render one person to a static image:
```
PYTHONPATH=. python demo/01_render_one_person.py --mesh_path data/makehuman/makehuman_2954_mhx2_standing02/193_Standing02.mhx2 --save_path tmp/sample_person.jpg
```
The rendered image is saved to `tmp/sample_person.jpg`.

You can also run the script with `--demo_camera_azim` option to observe the changes in rendering option values:
```
PYTHONPATH=. python demo/01_render_one_person.py --mesh_path data/makehuman/makehuman_2954_mhx2_standing02/193_Standing02.mhx2 --save_path tmp/sample_person.gif --demo_camera_azim
```
The rendered animation image is saved to `tmp/sample_person.gif`.

You can specify different human models by the `--mesh_path` option.

## 3. Render Multiple Images

Ensure that the `data/makehuman/makehuman_2954_mhx2_standing02` folder exists, or create it by soft link:
```
ln -s data/makehuman/makehuman_2954_mhx2_standing02_mini data/makehuman/makehuman_2954_mhx2_standing02
```

To render a person ReID dataset, you can specific a config file and run:
```
PYTHONPATH=. python tools/batch_generate.py --config-file configs/TAGPerson/01_direct_transfer/tagp_base.yml
```

The images will be saved to the path specified in the `OUTPUT_DIR_FOR_IMAGE` config item.

If the 3D human models in the `data/makehuman/` folder are not complete, you can use `PROCESS.FIRST_INDEX` and `PROCESS.LAST_INDEX` to limit the range:
```
PYTHONPATH=. python tools/batch_generate.py --config-file configs/TAGPerson/01_direct_transfer/tagp_base.yml PROCESS.FIRST_INDEX 193 PROCESS.LAST_INDEX 193
```

## 4. Rendering Options
We describe parts of the rendering options below.

![Description of rendering options](https://raw.githubusercontent.com/tagperson/tagperson-blender/master/static/rendering-options.png)

We visualize some effects of changing different values for certain rendering options.

![Camera Azimuth and Depression Angle](https://raw.githubusercontent.com/tagperson/tagperson-blender/master/static/193_camera_azim_elev.gif)
![Light Azimuth](https://raw.githubusercontent.com/tagperson/tagperson-blender/master/static/193_light_azim.gif)
![Light Depression Angle](https://raw.githubusercontent.com/tagperson/tagperson-blender/master/static/193_light_elev.gif)
![Color Bias](https://raw.githubusercontent.com/tagperson/tagperson-blender/master/static/193_color_bias_continue.gif)
![Color Bias](https://raw.githubusercontent.com/tagperson/tagperson-blender/master/static/193_color_bias_continue_g.gif)
![Color Bias](https://raw.githubusercontent.com/tagperson/tagperson-blender/master/static/193_color_bias_continue_b.gif)

Rendering options for each experiment can be found in the configure files in [this link](https://drive.google.com/drive/folders/1eiFvsk78OqxerKSceRkORTlk5B7EB3ao).

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