---
library_name: unity-sentis
pipeline_tag: object-detection
---
# LaboroTomato for Unity Sentis (Version 1.4.0-pre.3*)

[LaboroTomato](https://github.com/laboroai/LaboroTomato) is is an image dataset of growing tomatoes at different stages of their ripening.

This model was trained on the LaboroTomato image dataset using the Ultralytics [YOLOv8n](https://docs.ultralytics.com/models/yolov8/) object detection framework. The sentis example implementation was copied from [sentis-YOLOv8n](https://huggingface.co/unity/sentis-YOLOv8n).

## How to Use
First get the package `com.unity.sentis` from the package manager.
You will also need the Unity UI package.

* Create a new scene in Unity 6.
* Install `com.unity.sentis` version `1.4.0-pre.3` from the package manager, and enable the 'Video' built-in module.
* Add the c# script to the Main Camera.
* Create a Raw Image in the scene and link it as the `displayImage`
* Drag the laboro_tomato_yolov8.sentis file into the model asset field
* Drag the classes.txt on to the labelAssets field
* Put a video file in the Assets/StreamingAssets folder and set the name of videoName to the filename in the script ("tomatoes.mp4")
* Set the fields for the bounding box texture sprite (you can [create your own one](https://docs.unity3d.com/Manual/9SliceSprites.html) using a transparent texture or use an inbuilt one) and the font


## Preview
If working correctly you should see something like this:

![preview](preview.png)

## Information
The onnx model was designed with the same inputs as [sentis-YOLOv8n](https://huggingface.co/unity/sentis-YOLOv8n). If you are using that implementation, you can simply swap out the model and labels with the ones in this project and it should work.

## References
For information on how the model was trained and exported to onnx, see the [project github page](https://github.com/DavidAtRedpine/LaboroTomatoYoloV8).

## Unity Sentis
Unity Sentis is the inference engine that runs in Unity 3D. More information can be found at [here](https://unity.com/products/sentis)

## License
Ultralytics YOLOv8 uses the GPLv3 license. Details [here](https://github.com/autogyro/yolo-V8?tab=readme-ov-file#license).

The LaboroTomato dataset uses the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Details [here](https://github.com/laboroai/LaboroTomato/blob/master/README.md#license).