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254 lines (221 loc) · 8.88 KB
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// Copyright (c) 2021 homuler
//
// Use of this source code is governed by an MIT-style
// license that can be found in the LICENSE file or at
// https://opensource.org/licenses/MIT.
using System;
using System.Collections.Generic;
using System.Linq;
using UnityEngine;
using Google.Protobuf;
namespace Mediapipe.Unity.Objectron
{
public class ObjectronGraph : GraphRunner
{
[Serializable]
public enum Category
{
Camera,
Chair,
Cup,
Sneaker,
};
public Category category;
public int maxNumObjects = 5;
private float _minDetectionConfidence = 0.5f;
public float minDetectionConfidence
{
get => _minDetectionConfidence;
set => _minDetectionConfidence = Mathf.Clamp01(value);
}
private float _minTrackingConfidence = 0.99f;
public float minTrackingConfidence
{
get => _minTrackingConfidence;
set => _minTrackingConfidence = Mathf.Clamp01(value);
}
public Vector2 focalLength
{
get
{
if (inferenceMode == InferenceMode.GPU)
{
return new Vector2(2.0975f, 1.5731f); // magic numbers MediaPipe uses internally
}
return Vector2.one;
}
}
public Vector2 principalPoint => Vector2.zero;
public event EventHandler<OutputEventArgs<FrameAnnotation>> OnLiftedObjectsOutput
{
add => _liftedObjectsStream.AddListener(value);
remove => _liftedObjectsStream.RemoveListener(value);
}
public event EventHandler<OutputEventArgs<List<NormalizedRect>>> OnMultiBoxRectsOutput
{
add => _multiBoxRectsStream.AddListener(value);
remove => _multiBoxRectsStream.RemoveListener(value);
}
public event EventHandler<OutputEventArgs<List<NormalizedLandmarkList>>> OnMultiBoxLandmarksOutput
{
add => _multiBoxLandmarksStream.AddListener(value);
remove => _multiBoxLandmarksStream.RemoveListener(value);
}
private const string _InputStreamName = "input_video";
private const string _LiftedObjectsStreamName = "lifted_objects";
private const string _MultiBoxRectsStreamName = "multi_box_rects";
private const string _MultiBoxLandmarksStreamName = "multi_box_landmarks";
private OutputStream<FrameAnnotationPacket, FrameAnnotation> _liftedObjectsStream;
private OutputStream<NormalizedRectVectorPacket, List<NormalizedRect>> _multiBoxRectsStream;
private OutputStream<NormalizedLandmarkListVectorPacket, List<NormalizedLandmarkList>> _multiBoxLandmarksStream;
protected long prevLiftedObjectsMicrosec = 0;
protected long prevMultiBoxRectsMicrosec = 0;
protected long prevMultiBoxLandmarksMicrosec = 0;
public override void StartRun(ImageSource imageSource)
{
if (runningMode.IsSynchronous())
{
_liftedObjectsStream.StartPolling().AssertOk();
_multiBoxRectsStream.StartPolling().AssertOk();
_multiBoxLandmarksStream.StartPolling().AssertOk();
}
StartRun(BuildSidePacket(imageSource));
}
public override void Stop()
{
_liftedObjectsStream?.Close();
_liftedObjectsStream = null;
_multiBoxRectsStream?.Close();
_multiBoxRectsStream = null;
_multiBoxLandmarksStream?.Close();
_multiBoxLandmarksStream = null;
base.Stop();
}
public void AddTextureFrameToInputStream(TextureFrame textureFrame)
{
AddTextureFrameToInputStream(_InputStreamName, textureFrame);
}
public bool TryGetNext(out FrameAnnotation liftedObjects, out List<NormalizedRect> multiBoxRects, out List<NormalizedLandmarkList> multiBoxLandmarks, bool allowBlock = true)
{
var currentTimestampMicrosec = GetCurrentTimestampMicrosec();
var r1 = TryGetNext(_liftedObjectsStream, out liftedObjects, allowBlock, currentTimestampMicrosec);
var r2 = TryGetNext(_multiBoxRectsStream, out multiBoxRects, allowBlock, currentTimestampMicrosec);
var r3 = TryGetNext(_multiBoxLandmarksStream, out multiBoxLandmarks, allowBlock, currentTimestampMicrosec);
return r1 || r2 || r3;
}
protected override IList<WaitForResult> RequestDependentAssets()
{
return new List<WaitForResult> {
WaitForAsset("object_detection_ssd_mobilenetv2_oidv4_fp16.bytes"),
WaitForAsset("object_detection_oidv4_labelmap.txt"),
WaitForAsset(GetModelAssetName(category), "object_detection_3d.bytes", true),
};
}
protected override Status ConfigureCalculatorGraph(CalculatorGraphConfig config)
{
if (runningMode == RunningMode.NonBlockingSync)
{
_liftedObjectsStream = new OutputStream<FrameAnnotationPacket, FrameAnnotation>(
calculatorGraph, _LiftedObjectsStreamName, config.AddPacketPresenceCalculator(_LiftedObjectsStreamName), timeoutMicrosec);
_multiBoxRectsStream = new OutputStream<NormalizedRectVectorPacket, List<NormalizedRect>>(
calculatorGraph, _MultiBoxRectsStreamName, config.AddPacketPresenceCalculator(_MultiBoxRectsStreamName), timeoutMicrosec);
_multiBoxLandmarksStream = new OutputStream<NormalizedLandmarkListVectorPacket, List<NormalizedLandmarkList>>(
calculatorGraph, _MultiBoxLandmarksStreamName, config.AddPacketPresenceCalculator(_MultiBoxLandmarksStreamName), timeoutMicrosec);
}
else
{
_liftedObjectsStream = new OutputStream<FrameAnnotationPacket, FrameAnnotation>(calculatorGraph, _LiftedObjectsStreamName, true, timeoutMicrosec);
_multiBoxRectsStream = new OutputStream<NormalizedRectVectorPacket, List<NormalizedRect>>(calculatorGraph, _MultiBoxRectsStreamName, true, timeoutMicrosec);
_multiBoxLandmarksStream = new OutputStream<NormalizedLandmarkListVectorPacket, List<NormalizedLandmarkList>>(calculatorGraph, _MultiBoxLandmarksStreamName, true, timeoutMicrosec);
}
using (var validatedGraphConfig = new ValidatedGraphConfig())
{
var status = validatedGraphConfig.Initialize(config);
if (!status.Ok()) { return status; }
var extensionRegistry = new ExtensionRegistry() { TensorsToDetectionsCalculatorOptions.Extensions.Ext, ThresholdingCalculatorOptions.Extensions.Ext };
var cannonicalizedConfig = validatedGraphConfig.Config(extensionRegistry);
var tensorsToDetectionsCalculators = cannonicalizedConfig.Node.Where((node) => node.Calculator == "TensorsToDetectionsCalculator").ToList();
var thresholdingCalculators = cannonicalizedConfig.Node.Where((node) => node.Calculator == "ThresholdingCalculator").ToList();
foreach (var calculator in tensorsToDetectionsCalculators)
{
if (calculator.Options.HasExtension(TensorsToDetectionsCalculatorOptions.Extensions.Ext))
{
var options = calculator.Options.GetExtension(TensorsToDetectionsCalculatorOptions.Extensions.Ext);
options.MinScoreThresh = minDetectionConfidence;
}
}
foreach (var calculator in thresholdingCalculators)
{
if (calculator.Options.HasExtension(ThresholdingCalculatorOptions.Extensions.Ext))
{
var options = calculator.Options.GetExtension(ThresholdingCalculatorOptions.Extensions.Ext);
options.Threshold = minTrackingConfidence;
}
}
return calculatorGraph.Initialize(cannonicalizedConfig);
}
}
private SidePacket BuildSidePacket(ImageSource imageSource)
{
var sidePacket = new SidePacket();
SetImageTransformationOptions(sidePacket, imageSource);
sidePacket.Emplace("allowed_labels", new StringPacket(GetAllowedLabels(category)));
sidePacket.Emplace("max_num_objects", new IntPacket(maxNumObjects));
Logger.LogInfo(TAG, $"Category = {category}");
Logger.LogInfo(TAG, $"Max Num Objects = {maxNumObjects}");
return sidePacket;
}
private string GetAllowedLabels(Category category)
{
switch (category)
{
case Category.Camera:
{
return "Camera";
}
case Category.Chair:
{
return "Chair";
}
case Category.Cup:
{
return "Coffee cup,Mug";
}
case Category.Sneaker:
{
return "Footwear";
}
default:
{
throw new ArgumentException($"Unknown category: {category}");
}
}
}
private string GetModelAssetName(Category category)
{
switch (category)
{
case Category.Camera:
{
return "object_detection_3d_camera.bytes";
}
case Category.Chair:
{
return "object_detection_3d_chair.bytes";
}
case Category.Cup:
{
return "object_detection_3d_chair.bytes";
}
case Category.Sneaker:
{
return "object_detection_3d_sneakers.bytes";
}
default:
{
throw new ArgumentException($"Unknown category: {category}");
}
}
}
}
}