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186 行
7.0 KiB
186 行
7.0 KiB
using System;
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using System.Collections.Generic;
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using System.Diagnostics.CodeAnalysis;
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using System.IO;
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using Unity.Collections;
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using Unity.Profiling;
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using Unity.Simulation;
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using UnityEditor;
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using UnityEngine;
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using UnityEngine.Experimental.Rendering;
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using UnityEngine.Profiling;
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namespace UnityEngine.Perception.GroundTruth
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{
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/// <summary>
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/// Produces instance segmentation for each frame.
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/// </summary>
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[Serializable]
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public sealed class InstanceSegmentationLabeler : CameraLabeler, IOverlayPanelProvider
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{
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///<inheritdoc/>
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public override string description
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{
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get => "Produces an instance segmentation image for each frame. The image will render the pixels of each labeled object in a distinct color.";
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protected set { }
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}
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/// <inheritdoc/>
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protected override bool supportsVisualization => true;
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static readonly string k_Directory = "InstanceSegmentation" + Guid.NewGuid().ToString();
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const string k_FilePrefix = "Instance_";
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/// <summary>
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/// The GUID to associate with annotations produced by this labeler.
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/// </summary>
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[Tooltip("The id to associate with instance segmentation annotations in the dataset.")]
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public string annotationId = "1ccebeb4-5886-41ff-8fe0-f911fa8cbcdf";
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/// <summary>
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/// The <see cref="idLabelConfig"/> which associates objects with labels.
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/// </summary>
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public IdLabelConfig idLabelConfig;
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AnnotationDefinition m_AnnotationDefinition;
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static ProfilerMarker s_OnObjectInfoReceivedCallback = new ProfilerMarker("OnInstanceSegmentationObjectInformationReceived");
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static ProfilerMarker s_OnImageReceivedCallback = new ProfilerMarker("OnInstanceSegmentationImagesReceived");
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Dictionary<int, AsyncAnnotation> m_AsyncAnnotations;
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Texture m_CurrentTexture;
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/// <inheritdoc cref="IOverlayPanelProvider"/>
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// ReSharper disable once ConvertToAutoPropertyWithPrivateSetter
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public Texture overlayImage => m_CurrentTexture;
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/// <inheritdoc cref="IOverlayPanelProvider"/>
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public string label => "InstanceSegmentation";
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[SuppressMessage("ReSharper", "InconsistentNaming")]
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[SuppressMessage("ReSharper", "NotAccessedField.Local")]
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struct InstanceColorValue
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{
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public uint instance_id;
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public Color32 color;
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}
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string m_InstancePath;
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List<InstanceColorValue> m_InstanceColorValues;
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struct AsyncWrite
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{
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public NativeArray<Color32> data;
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public int width;
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public int height;
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public string path;
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}
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/// <summary>
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/// Creates a new InstanceSegmentationLabeler. Be sure to assign <see cref="idLabelConfig"/> before adding to a <see cref="PerceptionCamera"/>.
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/// </summary>
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public InstanceSegmentationLabeler() { }
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/// <summary>
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/// Creates a new InstanceSegmentationLabeler with the given <see cref="IdLabelConfig"/>.
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/// </summary>
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/// <param name="labelConfig">The label config for resolving the label for each object.</param>
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public InstanceSegmentationLabeler(IdLabelConfig labelConfig)
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{
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this.idLabelConfig = labelConfig;
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}
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void OnRenderedObjectInfosCalculated(int frame, NativeArray<RenderedObjectInfo> renderedObjectInfos)
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{
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if (!m_AsyncAnnotations.TryGetValue(frame, out var annotation))
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return;
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m_AsyncAnnotations.Remove(frame);
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using (s_OnObjectInfoReceivedCallback.Auto())
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{
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m_InstanceColorValues.Clear();
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foreach (var objectInfo in renderedObjectInfos)
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{
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if (!idLabelConfig.TryGetLabelEntryFromInstanceId(objectInfo.instanceId, out var labelEntry))
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continue;
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m_InstanceColorValues.Add(new InstanceColorValue
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{
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instance_id = objectInfo.instanceId,
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color = objectInfo.instanceColor
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});
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}
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annotation.ReportFileAndValues(m_InstancePath, m_InstanceColorValues);
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}
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}
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void OnImageCaptured(int frame, NativeArray<Color32> data, RenderTexture renderTexture)
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{
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using (s_OnImageReceivedCallback.Auto())
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{
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m_CurrentTexture = renderTexture;
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m_InstancePath = $"{k_Directory}/{k_FilePrefix}{frame}.png";
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var localPath = $"{Manager.Instance.GetDirectoryFor(k_Directory)}/{k_FilePrefix}{frame}.png";
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var colors = new NativeArray<Color32>(data, Allocator.TempJob);
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var asyncRequest = Manager.Instance.CreateRequest<AsyncRequest<AsyncWrite>>();
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asyncRequest.data = new AsyncWrite
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{
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data = colors,
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width = renderTexture.width,
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height = renderTexture.height,
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path = localPath
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};
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asyncRequest.Enqueue(r =>
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{
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Profiler.BeginSample("InstanceSegmentationEncode");
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var pngBytes = ImageConversion.EncodeArrayToPNG(r.data.data.ToArray(), GraphicsFormat.R8G8B8A8_UNorm, (uint)r.data.width, (uint)r.data.height);
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Profiler.EndSample();
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Profiler.BeginSample("InstanceSegmentationWritePng");
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File.WriteAllBytes(r.data.path, pngBytes);
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Manager.Instance.ConsumerFileProduced(r.data.path);
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Profiler.EndSample();
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r.data.data.Dispose();
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return AsyncRequest.Result.Completed;
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});
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asyncRequest.Execute();
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}
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}
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/// <inheritdoc/>
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protected override void OnBeginRendering()
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{
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m_AsyncAnnotations[Time.frameCount] = perceptionCamera.SensorHandle.ReportAnnotationAsync(m_AnnotationDefinition);
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}
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/// <inheritdoc/>
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protected override void Setup()
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{
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if (idLabelConfig == null)
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throw new InvalidOperationException("InstanceSegmentationLabeler's idLabelConfig field must be assigned");
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m_InstanceColorValues = new List<InstanceColorValue>();
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perceptionCamera.InstanceSegmentationImageReadback += OnImageCaptured;
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perceptionCamera.RenderedObjectInfosCalculated += OnRenderedObjectInfosCalculated;
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m_AsyncAnnotations = new Dictionary<int, AsyncAnnotation>();
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m_AnnotationDefinition = DatasetCapture.RegisterAnnotationDefinition(
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"instance segmentation",
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idLabelConfig.GetAnnotationSpecification(),
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"pixel-wise instance segmentation label",
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"PNG",
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Guid.Parse(annotationId));
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visualizationEnabled = supportsVisualization;
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}
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}
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}
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