Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目,它使游戏和模拟能够作为训练智能代理的环境。
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using System;
using System.Reflection;
using NUnit.Framework;
using UnityEngine;
using Unity.MLAgents.Sensors;
namespace Unity.MLAgents.Tests
{
[TestFixture]
public class CameraSensorComponentTest
{
[Test]
public void TestCameraSensorComponent()
{
foreach (var grayscale in new[] { true, false })
{
foreach (SensorCompressionType compression in Enum.GetValues(typeof(SensorCompressionType)))
{
var width = 24;
var height = 16;
var camera = Camera.main;
var agentGameObj = new GameObject("agent");
var cameraComponent = agentGameObj.AddComponent<CameraSensorComponent>();
cameraComponent.Camera = camera;
cameraComponent.Height = height;
cameraComponent.Width = width;
cameraComponent.Grayscale = grayscale;
cameraComponent.CompressionType = compression;
var sensor = cameraComponent.CreateSensors()[0];
var expectedShape = new InplaceArray<int>(height, width, grayscale ? 1 : 3);
Assert.AreEqual(expectedShape, sensor.GetObservationSpec().Shape);
Assert.AreEqual(typeof(CameraSensor), sensor.GetType());
// Make sure cleaning up the component cleans up the sensor too
cameraComponent.Dispose();
var flags = BindingFlags.Instance | BindingFlags.NonPublic;
var cameraComponentSensor = (CameraSensor)typeof(CameraSensorComponent).GetField("m_Sensor", flags).GetValue(cameraComponent);
Assert.IsNull(cameraComponentSensor);
var cameraTexture = (Texture2D)typeof(CameraSensor).GetField("m_Texture", flags).GetValue(sensor);
Assert.IsNull(cameraTexture);
}
}
}
}
}