Metadata-Version: 2.4
Name: poseviz
Version: 0.3.2
Summary: 3D human pose visualizer with multi-person, multi-view support.
Author-email: István Sárándi <istvan.sarandi@uni-tuebingen.de>
License: MIT License
        
        Copyright (c) 2023 István Sárándi
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
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        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
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        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: more-itertools
Requires-Dist: opencv-python
Requires-Dist: numpy
Requires-Dist: moderngl
Requires-Dist: glfw
Requires-Dist: imageio
Requires-Dist: deltacamera>=0.7.0
Requires-Dist: framepump
Requires-Dist: simplepyutils
Requires-Dist: rlemasklib
Requires-Dist: numba
Dynamic: license-file

# PoseViz – 3D Human Pose and Mesh Visualizer

<p align="center">
  <img src=screenshot.jpg width="30%">
  <img src=screenshot2.jpg width="30%">
  <img src=screenshot_multicam.jpg width="30%">
</p>

Multi-person, multi-camera 3D human pose and mesh visualization tool built using
OpenGL (via ModernGL). As used in [NLF](https://github.com/isarandi/nlf) and [MeTRAbs](https://github.com/isarandi/metrabs) visualizations.

**This repo does not contain pose estimation code, only the visualization part.**

## Gist of Usage

```python
import poseviz
import deltacamera

camera = deltacamera.Camera(...)

with poseviz.PoseViz(...) as viz:
    for frame in frames:
        bounding_boxes, poses3d = run_pose_estimation_model(frame)
        viz.update(frame=frame, boxes=bounding_boxes, poses=poses3d, camera=camera)
```

See also [```demo.py```](demo.py).

The main feature of this tool is that the graphical event loop is hidden from the library user. We
want to write code in terms of the *prediction loop* of the human pose estimator, not from the point
of view of the visualizer tool.

Behind the scenes, this is achieved through forking a dedicated visualization process and passing
new scene information via multiprocessing queues.

## Installation

```bash
pip install poseviz
```

Then run [demo.py](demo.py) to test if installation was successful.

