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https://github.com/locaal-ai/obs-detect

Object Detection in OBS, real-time, local, GPU optional
https://github.com/locaal-ai/obs-detect

computer-vision live-streaming livestreaming object-detection object-tracking obs-studio obs-studio-plugin obsproject video-object-tracking yolo

Last synced: 5 days ago
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Object Detection in OBS, real-time, local, GPU optional

Host: GitHub
URL: https://github.com/locaal-ai/obs-detect
Owner: locaal-ai
License: gpl-2.0
Created: 2024-03-26T18:20:14.000Z (8 months ago)
Default Branch: master
Last Pushed: 2024-06-02T04:46:23.000Z (6 months ago)
Last Synced: 2024-11-06T02:25:18.618Z (9 days ago)
Topics: computer-vision, live-streaming, livestreaming, object-detection, object-tracking, obs-studio, obs-studio-plugin, obsproject, video-object-tracking, yolo
Language: C++
Homepage: https://obsproject.com/forum/resources/detect-object-detection-tracking-built-in-obs.1911/
Size: 25 MB
Stars: 82
Watchers: 5
Forks: 7
Open Issues: 16
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

# OBS Detect - Object Detection and Masking Filter

[![GitHub](https://img.shields.io/github/license/occ-ai/obs-detect)](https://github.com/occ-ai/obs-detect/blob/main/LICENSE)
[![GitHub Workflow Status](https://img.shields.io/github/actions/workflow/status/occ-ai/obs-detect/push.yaml)](https://github.com/occ-ai/obs-detect/actions/workflows/push.yaml)
[![Total downloads](https://img.shields.io/github/downloads/occ-ai/obs-detect/total)](https://github.com/occ-ai/obs-detect/releases)
[![GitHub release (latest by date)](https://img.shields.io/github/v/release/occ-ai/obs-detect)](https://github.com/occ-ai/obs-detect/releases)
[![Discord](https://img.shields.io/discord/1200229425141252116)](https://discord.gg/KbjGU2vvUz)

A plugin for [OBS Studio](https://obsproject.com/) that allows you to detect many types of objects in any source, track them and apply masking.

If you like this work, which is given to you completely free of charge, please consider supporting it by sponsoring us on GitHub:

- https://github.com/sponsors/royshil
- https://github.com/sponsors/umireon

This work uses the great contributions from [EdgeYOLO-ROS](https://github.com/fateshelled/EdgeYOLO-ROS) and [PINTO-Model-Zoo](https://github.com/PINTO0309/PINTO_model_zoo). The Hungarian algorithm is taken from https://github.com/Gluttton/munkres-cpp under the GPLv2 license.

## Usage

- Add the "Detect" filter to any source with an image (Media, Browser, VLC, Image, etc.)
- Enable "Masking" or "Tracking"

Use Detect to track your pet, or blur out people in your video!

More information and usage tutorials to follow soon.

## Features

Current features:

- Detect over 80 categories of objects, using an efficient model ([EdgeYOLO](https://github.com/LSH9832/edgeyolo))
- 3 Model sizes: Small, Medium and Large
- Face detection model, fast and efficient ([YuNet](https://github.com/opencv/opencv_zoo/tree/main/models/face_detection_yunet))
- Load custom ONNX detection models from disk
- Filter by: Minimal Detection confidence, Object category (e.g. only "Person"), Object Minimal Size
- Masking: Blur, Pixelate, Solid color, Transparent, output binary mask (combine with other plugins!)
- Tracking: Single object / Biggest / Oldest / All objects, Zoom factor, smooth transition
- SORT algorithm for tracking smoothness and continuity
- Save detections to file in real-time, for integrations e.g. with Streamer.bot

Roadmap features:
- Precise object mask, beyond bounding box
- Multiple object category selection (e.g. Dog + Cat + Duck)
- Make available detection information for other plugins through settings

## Train and use a custom detection model

Follow the instructions in [docs/train_model.md](docs/train_model.md) to train and use your own custom model.

## Building

The plugin was built and tested on Mac OSX (Intel & Apple silicon), Windows and Linux.

Start by cloning this repo to a directory of your choice.

### Mac OSX

Using the CI pipeline scripts, locally you would just call the zsh script. By default this builds a universal binary for both Intel and Apple Silicon. To build for a specific architecture please see `.github/scripts/.build.zsh` for the `-arch` options.

```sh
$ ./.github/scripts/build-macos -c Release
```

#### Install
The above script should succeed and the plugin files (e.g. `obs-ocr.plugin`) will reside in the `./release/Release` folder off of the root. Copy the `.plugin` file to the OBS directory e.g. `~/Library/Application Support/obs-studio/plugins`.

To get `.pkg` installer file, run for example
```sh
$ ./.github/scripts/package-macos -c Release
```
(Note that maybe the outputs will be in the `Release` folder and not the `install` folder like `pakage-macos` expects, so you will need to rename the folder from `build_x86_64/Release` to `build_x86_64/install`)

### Linux (Ubuntu)

Use the CI scripts again
```sh
$ ./.github/scripts/build-linux.sh
```

Copy the results to the standard OBS folders on Ubuntu
```sh
$ sudo cp -R release/RelWithDebInfo/lib/* /usr/lib/x86_64-linux-gnu/
$ sudo cp -R release/RelWithDebInfo/share/* /usr/share/
```
Note: The official [OBS plugins guide](https://obsproject.com/kb/plugins-guide) recommends adding plugins to the `~/.config/obs-studio/plugins` folder.

### Windows

Use the CI scripts again, for example:

```powershell
> .github/scripts/Build-Windows.ps1 -Target x64
```

The build should exist in the `./release` folder off the root. You can manually install the files in the OBS directory.