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A Blender addon for generating synthetic ground truth data for Computer Vision applications
| Date | Stars |
|---|---|
| 2026-07-31 | 529 |
| 2026-08-06 | 529 |
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# vision_blender
[](https://github.com/Cartucho/vision_blender)
A Blender user-interface to generate synthetic ground truth data (benchmarks) for Computer Vision applications.
<img src="https://user-images.githubusercontent.com/15831541/94527156-7b944d80-022e-11eb-85bd-0b387fd519fb.png" width="100%">
<img src="https://user-images.githubusercontent.com/15831541/94527180-8353f200-022e-11eb-9bf5-5ebd6102bc9f.png" width="100%">
VisionBlender is a synthetic computer vision dataset generator that adds a user interface to Blender, allowing users to generate monocular/stereo video sequences with ground truth maps of depth, disparity, segmentation masks, surface normals, optical flow, object pose, and camera parameters.
[](https://www.youtube.com/watch?v=LHpogw6INgU "Tutorial - Click to Watch!")
[YouTube link](https://www.youtube.com/watch?v=LHpogw6INgU)
## Installation
To install the addon simply go to `Edit > Preferences > Add-on tab > Install an add-on`
, then select the file `path/to/vision_blender/addon_ground_truth_generation.py` and click `Install Add-on`.
Finally you have to enable the add-on; Search `VisionBlender` and tick the check-box.
<img src="https://media.giphy.com/media/8hi33WFpulQgNS0aKZ/giphy.gif" width="50%">
You should now be able to find the `VisionBlender UI` in the bottom of the `Output Properties`.
<img src="https://media.giphy.com/media/yohYefBMecG2zxTt6T/giphy.gif" width="50%">
## How to generate ground truth data?
### 1. Select render engine
If you want to get ground truth `Segmentation masks` or `Optical flow` you need first to set blender to use the `Cycles` Render Engine. Otherwise, use `Eevee` (it will be faster!) which is set by default.
<img src="https://media.giphy.com/media/s87Yo48JPQITTzVnbl/giphy.gif" width="50%">
##### How to set-up segmentation masks? #####
To set-up the segmentation masks you need to choose a pass index other than zero (!= 0) for each object:
`Object Properties > Relations > Pass Index`
<img src="https://media.giphy.com/media/FLL3LQWg1x01efAc1e/giphy.gif" width="50%">
Each integer (e.g., `Pass Index = 1`) represents a class of objects to be segmented.
##### How to set-up optical flow? #####
You will only have optical flow if the camera or the objects are moving during an animation. In the following gif, I show you an example of how to move an object between frames:
<img src="https://media.giphy.com/media/N77idgOsPjkxbk5tfd/giphy.gif" width="50%">
### 2. Set output path
Set up the output path in `Output Properties > Output > Output Path`. This is the path where both your rendered images and ground truth will be saved.
<img src="https://media.giphy.com/media/pkonIVp8o8slvsC3Nf/giphy.gif" width="50%">
### 3. Select ground truth maps and render
First, tick the boxes of what you want to save as ground truth in the `VisionBlender UI`. Then, start rendering. To start rendering you click `Render > Render Image` or `Render > Render Animation...`, alternatively you can click `F12` for image and `Ctrl F12` for animation.
<img src="https://media.giphy.com/media/evpNpfJMYzwEyaHeQG/giphy.gif" width="50%">
Note: The ground-truth maps are always calculated using meters [m] as unit of distance.
### How to read the data after generating it?
You simply have to load the numpy arrays from thr `.npz` files.
Go to [vision_blender/samples](https://github.com/Cartucho/vision_blender/tree/master/samples) and have a look at the example there!
## Paper
This work received the best paper award at a MICCAI 2020 workshop!
The paper can be found at [this link](https://www.tandfonline.com/doi/full/10.1080/21681163.2020.1835546)
If you use this tool please consider citing our paper:
```bibtex
@article{cartucho2020visionblender,
title={VisionBlenderExcerpt of 4,359 characters
Read on GitHub
Cartucho · Imperial College London
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matched fp:e983998605c03a29, desc:computer vision