我已经在这个项目上工作了几个月，我正在尝试使用OpenCVSharp将眼动追踪集成到Unity中。我已经设法让一切工作，包括实际跟踪瞳孔等，但我有内存泄漏。基本上在程序运行20-30秒后冻结并且控制台错误说“无法分配（这里插入数字）位”。在查看程序运行期间的内存使用情况后，您可以看到它的使用情况稳步攀升，直至达到最大值然后崩溃。
现在我花了很长时间试图解决这个问题，并阅读了很多关于正确发布图像/存储等的帮助帖子。尽管事实上我正在这样做，但它似乎并没有正确释放它们。我尝试使用垃圾收集器强制它回收内存，但这似乎也没有用。我只是对图像做了一些根本性的错误以及我如何回收它们？或者每帧都创建新图像（即使我正在释放它们）导致问题。
非常感谢任何帮助。这是下面的代码，您可以忽略更新功能中的许多内容，因为它与实际跟踪部分和校准有关。我意识到代码非常混乱，抱歉！需要担心的主要部分是EyeDetection（）。
using UnityEngine;
using System.Collections;
using System;
using System.IO;
using OpenCvSharp;
using OpenCvSharp.Blob;
//using System.Xml;
//using System.Threading;
//using AForge;
//using OpenCvSharp.Extensions;
//using System.Windows.Media;
//using System.Windows.Media.Imaging;
public class CaptureScript2 : MonoBehaviour
{
//public GameObject planeObj;
public WebCamTexture webcamTexture; //Texture retrieved from the webcam
//public Texture2D texImage; //Texture to apply to plane
public string deviceName;
private int devId = 1;
private int imWidth = 800; //camera width
private int imHeight = 600; //camera height
private string errorMsg = "No errors found!";
private static IplImage camImage; //Ipl image of the converted webcam texture
//private static IplImage yuv;
//private static IplImage dst;
private CvCapture cap; //Current camera capture
//private IplImage eyeLeft;
//private IplImage eyeRight;
//private IplImage eyeLeftFinal;
//private IplImage eyeRightFinal;
private double leftEyeX;
private double leftEyeY;
private double rightEyeX;
private double rightEyeY;
private int calibState;
private double LTRCPx;
private double LTLCPx;
private double LBLCPy;
private double LTLCPy;
private double RTRCPx;
private double RTLCPx;
private double RBLCPy;
private double RTLCPy;
private double gazeWidth;
private double gazeHeight;
private double gazeScaleX;
private double gazeScaleY;
public static CvMemStorage storageFace;
public static CvMemStorage storage;
public static double gazePosX;
public static double gazePosY;
private bool printed = true;
//private CvRect r;
//private IplImage smallImg;
CvColor[] colors = new CvColor[]
{
new CvColor(0,0,255),
new CvColor(0,128,255),
new CvColor(0,255,255),
new CvColor(0,255,0),
new CvColor(255,128,0),
new CvColor(255,255,0),
new CvColor(255,0,0),
new CvColor(255,0,255),
};
//scale for small image
const double Scale = 1.25;
const double scaleEye = 10.0;
const double ScaleFactor = 2.5;
//must show 2 eyes on the screen
const int MinNeighbors = 2;
const int MinNeighborsFace = 1;
// Use this for initialization
void Start ()
{
//Webcam initialisation
WebCamDevice[] devices = WebCamTexture.devices;
Debug.Log ("num:" + devices.Length);
for (int i=0; i<devices.Length; i++)
{
print (devices [i].name);
if (devices [i].name.CompareTo (deviceName) == 1)
{
devId = i;
}
}
if (devId >= 0)
{
//mainImage = new IplImage (imWidth, imHeight, BitDepth.U8, 3);
}
//create capture from current device
cap = Cv.CreateCameraCapture(devId);
//set properties of the capture
Cv.SetCaptureProperty(cap, CaptureProperty.FrameWidth, imWidth);
Cv.SetCaptureProperty(cap, CaptureProperty.FrameHeight, imHeight);
//create window to display capture
//Cv.NamedWindow("Eye tracking", WindowMode.AutoSize);
Cv.NamedWindow ("EyeLeft", WindowMode.AutoSize);
Cv.NamedWindow ("EyeRight", WindowMode.AutoSize);
Cv.NamedWindow ("Face", WindowMode.AutoSize);
calibState = 1;
}
void Update ()
{
if(Input.GetKeyDown(KeyCode.Space) && calibState < 3)
{
calibState++;
}
if(Input.GetMouseButtonDown(0) && calibState < 4)
{
printed = false;
calibState++;
Cv.DestroyAllWindows();
Cv.ReleaseCapture(cap);
cap = Cv.CreateCameraCapture(devId);
}
//if device is connected
if (devId >= 0)
{
//cap = Cv.CreateCameraCapture(devId);
//Cv.Release
//retrieve the current frame from camera
camImage = Cv.QueryFrame(cap);
//detect eyes and apply circles
//
EyeDetection();
Cv.ReleaseImage(camImage);
//PupilTracking();
switch(calibState)
{
case 1:
LTRCPx = leftEyeX;
RTRCPx = rightEyeX;
break;
case 2:
LTLCPx = leftEyeX;
LTLCPy = leftEyeY;
RTLCPx = rightEyeX;
RTLCPy = rightEyeY;
break;
case 3:
LBLCPy = leftEyeY;// + rightEyeY) /2 ;
RBLCPy = rightEyeY;
break;
case 4:
//gazeWidth = (((LTRCPx - LTLCPx) + (RTRCPx - RTLCPx)) / 2) * -1;
//gazeHeight = ((LBLCPy - LTLCPy) + (RBLCPy - RTLCPy)) /2;
gazeWidth = LTLCPx -LTRCPx;
gazeHeight = LBLCPy - LTLCPy;
gazeScaleX = (Screen.width/gazeWidth);
gazeScaleY = Screen.height/gazeHeight;
gazePosX = gazeScaleX *(leftEyeX - LTRCPx);
gazePosY = gazeScaleY *(leftEyeY - LTLCPy);
break;
}
//Cv.ReleaseCapture(cap);
}
else
{
Debug.Log ("Can't find camera!");
}
//print (calibState);
if(printed == false)
{
print ("Gaze pos x = " + gazePosX);
print ("Gaze pos Y = " + gazePosY);
print ("Scale x = " + gazeScaleX);
print ("Scale y = " + gazeScaleY);
print ("Gaze width = " + gazeWidth);
print ("Gaze Height = " + gazeHeight);
print ("left eye x = " + leftEyeX);
print ("left eye Y = " + leftEyeY);
print ("calib state = " + calibState);
printed = true;
}
//Cv.ShowImage("Eye tracking", mainImage);
//Cv.ShowImage ("EyeLeft", grayEyeLeft);
//Cv.ShowImage ("EyeRight", grayEyeRight);
}
void EyeDetection()
{
IplImage mainImage = new IplImage (imWidth, imHeight, BitDepth.U8, 3);
IplImage smallImg = new IplImage(mainImage.Width, mainImage.Height ,BitDepth.U8, 1);
Cv.Resize (camImage, mainImage, Interpolation.Linear);
IplImage gray = new IplImage(mainImage.Size, BitDepth.U8, 1);
Cv.CvtColor (mainImage, gray, ColorConversion.BgrToGray);
Cv.Resize(gray, smallImg, Interpolation.Linear);
Cv.EqualizeHist(smallImg, smallImg);
Cv.ReleaseImage (gray);
//IplImage hack = Cv.LoadImage("\\Users\\User\\Desktop\\Honours Projects\\Project10\\Project\\Assets\\bug.jpeg");
//Cv.Erode (hack, hack);
//Cv.ReleaseImage (hack);
//uint sizeStore = 2877212;
CvHaarClassifierCascade cascadeFace = CvHaarClassifierCascade.FromFile("\\Users\\User\\Documents\\opencv\\sources\\data\\haarcascades\\haarcascade_frontalface_alt2.xml");
CvMemStorage storageFace = new CvMemStorage();
storageFace.Clear ();
CvSeq<CvAvgComp> faces = Cv.HaarDetectObjects(smallImg, cascadeFace, storageFace, ScaleFactor, MinNeighborsFace, 0, new CvSize(30,30));
for(int j = 0; j < faces.Total; j++)
{
CvRect face = faces[j].Value.Rect;
CvHaarClassifierCascade cascadeEye = CvHaarClassifierCascade.FromFile ("\\Users\\User\\Documents\\opencv\\sources\\data\\haarcascades\\haarcascade_eye.xml");
IplImage faceImg = new IplImage(face.Width, face.Height, BitDepth.U8, 1);
IplImage faceImgColour = new IplImage(face.Width, face.Height, BitDepth.U8, 3);
CvMemStorage storage = new CvMemStorage();
storage.Clear ();
Cv.SetImageROI(smallImg, face);
Cv.Copy (smallImg, faceImg);
Cv.ResetImageROI(smallImg);
Cv.SetImageROI(mainImage, face);
Cv.Copy (mainImage, faceImgColour);
Cv.ResetImageROI(mainImage);
Cv.ShowImage ("Face", faceImgColour);
CvSeq<CvAvgComp> eyes = Cv.HaarDetectObjects(faceImg, cascadeEye, storage, ScaleFactor, MinNeighbors, 0, new CvSize(30, 30));
for(int i = 0; i < eyes.Total; i++)
{
CvRect r = eyes[i].Value.Rect;
Cv.SetImageROI(faceImgColour, r);
if(i == 1)
{
IplImage eyeLeft = new IplImage(new CvSize(r.Width, r.Height), BitDepth.U8, 3);
Cv.Copy(faceImgColour, eyeLeft);
IplImage yuv = new IplImage(eyeLeft.Size, BitDepth.U8, 3);
IplImage dst = new IplImage(eyeLeft.Size, BitDepth.U8, 3);
IplImage grayEyeLeft = new IplImage(eyeLeft.Size, BitDepth.U8, 1);
IplImage eyeLeftFinal = new IplImage(Cv.Round(grayEyeLeft.Width * scaleEye), Cv.Round(grayEyeLeft.Height * scaleEye), BitDepth.U8, 1);
Cv.CvtColor(eyeLeft, yuv, ColorConversion.BgrToCrCb);
Cv.Not(yuv, dst);
Cv.CvtColor(dst,eyeLeft,ColorConversion.CrCbToBgr);
Cv.CvtColor(eyeLeft, grayEyeLeft, ColorConversion.BgrToGray);
Cv.Resize (grayEyeLeft, eyeLeftFinal, Interpolation.Linear);
Cv.Threshold(eyeLeftFinal, eyeLeftFinal, 230, 230, ThresholdType.Binary);
CvBlobs b1 = new CvBlobs(eyeLeftFinal);
if(b1.Count > 0)
{
leftEyeX = b1.LargestBlob().Centroid.X;
leftEyeY = b1.LargestBlob().Centroid.Y;
}
Cv.ShowImage ("EyeLeft", eyeLeftFinal);
Cv.ReleaseImage (yuv);
Cv.ReleaseImage (dst);
Cv.ReleaseImage (grayEyeLeft);
Cv.ReleaseImage (eyeLeftFinal);
b1.Clear();
Cv.ReleaseImage (eyeLeft);
}
if(i == 0)
{
IplImage eyeRight = new IplImage(new CvSize(r.Width, r.Height), BitDepth.U8, 3);
Cv.Copy(faceImgColour, eyeRight);
IplImage yuv2 = new IplImage(eyeRight.Size, BitDepth.U8, 3);
IplImage dst2 = new IplImage(eyeRight.Size, BitDepth.U8, 3);
IplImage grayEyeRight = new IplImage(eyeRight.Size, BitDepth.U8, 1);
IplImage eyeRightFinal = new IplImage(Cv.Round(grayEyeRight.Width * scaleEye), Cv.Round(grayEyeRight.Height * scaleEye), BitDepth.U8, 1);
Cv.CvtColor(eyeRight, yuv2, ColorConversion.BgrToCrCb);
Cv.Not(yuv2, dst2);
Cv.CvtColor(dst2,eyeRight,ColorConversion.CrCbToBgr);
Cv.CvtColor(eyeRight, grayEyeRight, ColorConversion.BgrToGray);
Cv.Resize (grayEyeRight, eyeRightFinal, Interpolation.Linear);
Cv.Threshold(eyeRightFinal, eyeRightFinal, 230, 230, ThresholdType.Binary);
CvBlobs b2 = new CvBlobs(eyeRightFinal);
if(b2.Count > 0)
{
rightEyeX = b2.LargestBlob().Centroid.X;
rightEyeY = b2.LargestBlob().Centroid.Y;
}
Cv.ShowImage ("EyeRight", eyeRightFinal);
Cv.ReleaseImage (yuv2);
Cv.ReleaseImage (dst2);
Cv.ReleaseImage (grayEyeRight);
Cv.ReleaseImage (eyeRightFinal);
b2.Clear ();
Cv.ReleaseImage (eyeRight);
}
Cv.ResetImageROI(faceImgColour);
}
//Cv.ShowImage("Eye tracking", mainImage);
Cv.ReleaseImage (faceImg);
Cv.ReleaseImage (faceImgColour);
Cv.ReleaseMemStorage(storage);
Cv.ReleaseHaarClassifierCascade(cascadeEye);
}
Cv.ReleaseMemStorage(storageFace);
Cv.ReleaseHaarClassifierCascade(cascadeFace);
//PupilTracking ();
Cv.ReleaseImage(smallImg);
Cv.ReleaseImage (mainImage);
GC.Collect();
}
void OnGUI ()
{
GUI.Label (new Rect (200, 200, 100, 90), errorMsg);
}
void OnDestroy()
{
Cv.DestroyAllWindows();
Cv.ReleaseCapture(cap);
}
答案 0 :(得分：1)
我不熟悉OpenCV，但作为一般规则：
new CvMemStorage() CvHaarClassifierCascade.FromFile("\\Users\\User\\Documents\\opencv\\sources\\data\\haarcascades\\haarcascade_frontalface_alt2.xml");这应该在启动时加载一次并分配给类变量。我发现在大多数情况下都有足够的内存。我在Start()上分配了一遍又一遍地使用的内容，特别是在Update()循环中每秒60次！
但是，加载XML数据，分配和释放storage或cascadeEye等变量，一定会在应用程序尝试每秒60次时产生问题。
创建和销毁对象是非常非常非常昂贵的。这样做是明智而谨慎的，尤其是在处理OpenCV对象，位图或加载器等复杂数据结构时。
第h