depthmapper

KO | EN

gitlite — search

#javascript #python #typescript #android #machine-learning #rust #linux #cli #kubernetes #awesome-list #security #ios #mcp #openai

(★ 27)

Python utility to experiment with StereoBM and StereoSGBM

depthmapper 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# depthmapper

This is a (relatively) small utility to be used as a testbed for experimenting with stereo depth mapping in OpenCV.

I built this to find how well depth mapping works on the Nvidia Jetson Nano. Support is present for StereoBM and StereoSGBM, as well as experimental support for AANet+.

Hardware-wise, this utility has been used with the WaveShare IMX219-83 stereo camera.

Python 3.6 or higher is needed.

**See this YouTube video for a brief(-ish) overview:**

[![Stereo depth mapping with OpenCV and Jetson Nano | DIY drone pt. 2](https://github.com/Matchstic/depthmapper/raw/main/.assets/yt.png)](https://youtu.be/_fH4SPhKpPM)

### Running the utility

First, update submodules: `git submodule update --init --recursive`

You'll want to install requirements:

```bash
conda env create -f environment.yml
conda activate depthmapper
```

(note: PyTorch is optional)

Assuming you have a stereo camera board attached and available on `/dev/video0` and `/dev/video1`, you should be able to just run:

```bash
python3 main.py
```

By default, cameras are accessed using `nvarguscamerasrc` which is specific to the Nvidia Jetson family. You should change this in `lib/helpers.py` if this is incorrect for your hardware setup.

You can choose which algorithm is used via the `-m` command line switch:

```
python main.py -m <algorithm>

options:

-m stereobm
-m stereosgbm
-m aanet
```

StereoBM is the default if this option is omitted.

### Note on AANet

AANet is an optionally supported algorithm, and as such you don't need PyTorch installed if you don't plan to use it.

If you do want it, you'll want to download a pre-trained model for it. These can be downloaded from [here](https://github.com/haofeixu/aanet/blob/master/MODEL_ZOO.md), then placed into `./models`. Make sure to update `settings.conf` to the name of the model you wish to use.

### Output

For now, output is the generated disparity map and is shown in a new window. By default, the left hand frame the map corresponds to is shown too.

### Configuration

All configuration is to be done via a config file, named `settings.conf`. I've made sure to write comments in the default configuration file to give an understanding of what each parameter does.

This file needs to live next to `main.py`, and will be automatically loaded.

### Considerations

On the Nvidia Jetson, OpenCV is installed by default with Python bindings. However, you may wish to use a virtual environment for Python. I used an `arm64` version of Miniforge3.

### License

BSD 2-clause.

This software is freely available, but isn't very useful outside a bench testing scenario.

depthmapper

depthmapper 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

depthmapper

depthmapper 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README