Getting Started
Quick Primer
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Quick Primer
Last updated
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To begin, import NatML to your Unity project by adding the following lines to your Unity project's Packages > manifest.json
file:
{
"scopedRegistries": [
{
"name": "NatML",
"url": "https://registry.npmjs.com",
"scopes": ["ai.natml"]
}
],
"dependencies": {
"ai.natml.natml": "1.1.8",
...
}
}
Once NatML has been imported, you can run ML models right in the Editor. For this example, we will classify an image using the popular MobileNet classifier architecture:
First, we'll import the MobileNet predictor into our project by following the import instructions:
{
...,
"dependencies": {
"ai.natml.natml": "1.1.8",
"ai.natml.vision.mobilenet-v2": "1.0.3",
...
}
}
We will fetch our models from NatML Hub, . To do so, we need to retrieve our access key:
Once you have an access key, you can add it to your Unity project in Project Settings > NatML
:
Next, import the image below (download it into your Unity project):
Make sure that in the advanced settings, you enable the Read/Write Enabled
setting:
Now, we can write a small script to classify the image:
using UnityEngine;
using NatML.Vision;
public class Classifier : MonoBehaviour {
[Header(@"Prediction")]
public Texture2D image;
async void Start () {
// Create the MobileNet predictor
using var predictor = await MobileNetv2Predictor.Create();
// Classify the image feature
var (label, confidence) = predictor.Predict(image);
// Log the result
Debug.Log($"Image contains {label} with confidence {confidence}");
}
}
Now, let us add our script to the scene and assign the inspector variables:
Now, we run the script to confirm that our model predicted the image correctly!
Classifier
script we just created.