protected virtual void DisposeOpticalFlow()
{
if (prevTrackPts != null)
{
prevTrackPts.Clear();
}
if (nextTrackPts != null)
{
nextTrackPts.Clear();
}
if (prevgray != null)
{
prevgray.Dispose();
}
if (gray != null)
{
gray.Dispose();
}
if (mOP2fPrevTrackPts != null)
{
mOP2fPrevTrackPts.Dispose();
}
if (mOP2fNextTrackPts != null)
{
mOP2fNextTrackPts.Dispose();
}
if (status != null)
{
status.Dispose();
}
if (err != null)
{
err.Dispose();
}
}
/// <summary>
/// Raises the web cam texture to mat helper disposed event.
/// </summary>
public void OnWebCamTextureToMatHelperDisposed()
{
Debug.Log("OnWebCamTextureToMatHelperDisposed");
matOpFlowThis.Dispose();
matOpFlowPrev.Dispose();
MOPcorners.Dispose();
mMOP2fptsThis.Dispose();
mMOP2fptsPrev.Dispose();
mMOP2fptsSafe.Dispose();
mMOBStatus.Dispose();
mMOFerr.Dispose();
}
/// <summary>
/// Raises the web cam texture to mat helper disposed event.
/// </summary>
public void OnWebCamTextureToMatHelperDisposed()
{
Debug.Log("OnWebCamTextureToMatHelperDisposed");
if (texture != null)
{
Texture2D.Destroy(texture);
texture = null;
}
if (matOpFlowThis != null)
{
matOpFlowThis.Dispose();
}
if (matOpFlowPrev != null)
{
matOpFlowPrev.Dispose();
}
if (MOPcorners != null)
{
MOPcorners.Dispose();
}
if (mMOP2fptsThis != null)
{
mMOP2fptsThis.Dispose();
}
if (mMOP2fptsPrev != null)
{
mMOP2fptsPrev.Dispose();
}
if (mMOP2fptsSafe != null)
{
mMOP2fptsSafe.Dispose();
}
if (mMOBStatus != null)
{
mMOBStatus.Dispose();
}
if (mMOFerr != null)
{
mMOFerr.Dispose();
}
}
void OnDisable()
{
Debug.Log("OnDisable");
if (matOpFlowThis != null)
{
matOpFlowThis.Dispose();
}
if (matOpFlowPrev != null)
{
matOpFlowPrev.Dispose();
}
if (MOPcorners != null)
{
MOPcorners.Dispose();
}
if (mMOP2fptsThis != null)
{
mMOP2fptsThis.Dispose();
}
if (mMOP2fptsPrev != null)
{
mMOP2fptsPrev.Dispose();
}
if (mMOP2fptsSafe != null)
{
mMOP2fptsSafe.Dispose();
}
if (mMOBStatus != null)
{
mMOBStatus.Dispose();
}
if (mMOFerr != null)
{
mMOFerr.Dispose();
}
//webCamTextureToMatHelper.Dispose();
}
/// <summary>
/// Postprocess the specified frame, outs and net.
/// </summary>
/// <param name="frame">Frame.</param>
/// <param name="outs">Outs.</param>
/// <param name="net">Net.</param>
private void postprocess(Mat frame, List <Mat> outs, Net net)
{
string outLayerType = outBlobTypes[0];
List <int> classIdsList = new List <int>();
List <float> confidencesList = new List <float>();
List <OpenCVForUnity.CoreModule.Rect> boxesList = new List <OpenCVForUnity.CoreModule.Rect>();
if (net.getLayer(new DictValue(0)).outputNameToIndex("im_info") != -1)
{
// Faster-RCNN or R-FCN
// Network produces output blob with a shape 1x1xNx7 where N is a number of
// detections and an every detection is a vector of values
// [batchId, classId, confidence, left, top, right, bottom]
if (outs.Count == 1)
{
outs[0] = outs[0].reshape(1, (int)outs[0].total() / 7);
//Debug.Log ("outs[i].ToString() " + outs [0].ToString ());
float[] data = new float[7];
for (int i = 0; i < outs[0].rows(); i++)
{
outs[0].get(i, 0, data);
float confidence = data[2];
if (confidence > confThreshold)
{
int class_id = (int)(data[1]);
int left = (int)(data[3] * frame.cols());
int top = (int)(data[4] * frame.rows());
int right = (int)(data[5] * frame.cols());
int bottom = (int)(data[6] * frame.rows());
int width = right - left + 1;
int height = bottom - top + 1;
classIdsList.Add((int)(class_id) - 0);
confidencesList.Add((float)confidence);
boxesList.Add(new OpenCVForUnity.CoreModule.Rect(left, top, width, height));
}
}
}
}
else if (outLayerType == "DetectionOutput")
{
// Network produces output blob with a shape 1x1xNx7 where N is a number of
// detections and an every detection is a vector of values
// [batchId, classId, confidence, left, top, right, bottom]
if (outs.Count == 1)
{
outs[0] = outs[0].reshape(1, (int)outs[0].total() / 7);
//Debug.Log ("outs[i].ToString() " + outs [0].ToString ());
float[] data = new float[7];
for (int i = 0; i < outs[0].rows(); i++)
{
outs[0].get(i, 0, data);
float confidence = data[2];
if (confidence > confThreshold)
{
int class_id = (int)(data[1]);
int left = (int)(data[3] * frame.cols());
int top = (int)(data[4] * frame.rows());
int right = (int)(data[5] * frame.cols());
int bottom = (int)(data[6] * frame.rows());
int width = right - left + 1;
int height = bottom - top + 1;
classIdsList.Add((int)(class_id) - 0);
confidencesList.Add((float)confidence);
boxesList.Add(new OpenCVForUnity.CoreModule.Rect(left, top, width, height));
}
}
}
}
else if (outLayerType == "Region")
{
for (int i = 0; i < outs.Count; ++i)
{
// Network produces output blob with a shape NxC where N is a number of
// detected objects and C is a number of classes + 4 where the first 4
// numbers are [center_x, center_y, width, height]
//Debug.Log ("outs[i].ToString() "+outs[i].ToString());
float[] positionData = new float[5];
float[] confidenceData = new float[outs[i].cols() - 5];
for (int p = 0; p < outs[i].rows(); p++)
{
outs[i].get(p, 0, positionData);
outs[i].get(p, 5, confidenceData);
int maxIdx = confidenceData.Select((val, idx) => new { V = val, I = idx }).Aggregate((max, working) => (max.V > working.V) ? max : working).I;
float confidence = confidenceData[maxIdx];
if (confidence > confThreshold)
{
int centerX = (int)(positionData[0] * frame.cols());
int centerY = (int)(positionData[1] * frame.rows());
int width = (int)(positionData[2] * frame.cols());
int height = (int)(positionData[3] * frame.rows());
int left = centerX - width / 2;
int top = centerY - height / 2;
classIdsList.Add(maxIdx);
confidencesList.Add((float)confidence);
boxesList.Add(new OpenCVForUnity.CoreModule.Rect(left, top, width, height));
}
}
}
}
else
{
Debug.Log("Unknown output layer type: " + outLayerType);
}
MatOfRect boxes = new MatOfRect();
boxes.fromList(boxesList);
MatOfFloat confidences = new MatOfFloat();
confidences.fromList(confidencesList);
MatOfInt indices = new MatOfInt();
Dnn.NMSBoxes(boxes, confidences, confThreshold, nmsThreshold, indices);
//Debug.Log ("indices.dump () "+indices.dump ());
//Debug.Log ("indices.ToString () "+indices.ToString());
for (int i = 0; i < indices.total(); ++i)
{
int idx = (int)indices.get(i, 0)[0];
OpenCVForUnity.CoreModule.Rect box = boxesList[idx];
drawPred(classIdsList[idx], confidencesList[idx], box.x, box.y,
box.x + box.width, box.y + box.height, frame);
}
indices.Dispose();
boxes.Dispose();
confidences.Dispose();
}
private IEnumerator init()
{
if (webCamTexture != null)
{
webCamTexture.Stop();
initDone = false;
rgbaMat.Dispose();
matOpFlowThis.Dispose();
matOpFlowPrev.Dispose();
MOPcorners.Dispose();
mMOP2fptsThis.Dispose();
mMOP2fptsPrev.Dispose();
mMOP2fptsSafe.Dispose();
mMOBStatus.Dispose();
mMOFerr.Dispose();
}
// Checks how many and which cameras are available on the device
for (int cameraIndex = 0; cameraIndex < WebCamTexture.devices.Length; cameraIndex++)
{
if (WebCamTexture.devices [cameraIndex].isFrontFacing == isFrontFacing)
{
Debug.Log(cameraIndex + " name " + WebCamTexture.devices [cameraIndex].name + " isFrontFacing " + WebCamTexture.devices [cameraIndex].isFrontFacing);
webCamDevice = WebCamTexture.devices [cameraIndex];
webCamTexture = new WebCamTexture(webCamDevice.name, width, height);
break;
}
}
if (webCamTexture == null)
{
webCamDevice = WebCamTexture.devices [0];
webCamTexture = new WebCamTexture(webCamDevice.name, width, height);
}
Debug.Log("width " + webCamTexture.width + " height " + webCamTexture.height + " fps " + webCamTexture.requestedFPS);
// Starts the camera
webCamTexture.Play();
while (true)
{
//If you want to use webcamTexture.width and webcamTexture.height on iOS, you have to wait until webcamTexture.didUpdateThisFrame == 1, otherwise these two values will be equal to 16. (http://forum.unity3d.com/threads/webcamtexture-and-error-0x0502.123922/)
#if UNITY_IPHONE && !UNITY_EDITOR
if (webCamTexture.width > 16 && webCamTexture.height > 16)
{
#else
if (webCamTexture.didUpdateThisFrame)
{
#endif
Debug.Log("width " + webCamTexture.width + " height " + webCamTexture.height + " fps " + webCamTexture.requestedFPS);
Debug.Log("videoRotationAngle " + webCamTexture.videoRotationAngle + " videoVerticallyMirrored " + webCamTexture.videoVerticallyMirrored + " isFrongFacing " + webCamDevice.isFrontFacing);
colors = new Color32[webCamTexture.width * webCamTexture.height];
rgbaMat = new Mat(webCamTexture.height, webCamTexture.width, CvType.CV_8UC4);
matOpFlowThis = new Mat();
matOpFlowPrev = new Mat();
MOPcorners = new MatOfPoint();
mMOP2fptsThis = new MatOfPoint2f();
mMOP2fptsPrev = new MatOfPoint2f();
mMOP2fptsSafe = new MatOfPoint2f();
mMOBStatus = new MatOfByte();
mMOFerr = new MatOfFloat();
texture = new Texture2D(webCamTexture.width, webCamTexture.height, TextureFormat.RGBA32, false);
gameObject.transform.eulerAngles = new Vector3(0, 0, 0);
#if (UNITY_ANDROID || UNITY_IPHONE) && !UNITY_EDITOR
gameObject.transform.eulerAngles = new Vector3(0, 0, -90);
#endif
// gameObject.transform.rotation = gameObject.transform.rotation * Quaternion.AngleAxis (webCamTexture.videoRotationAngle, Vector3.back);
gameObject.transform.localScale = new Vector3(webCamTexture.width, webCamTexture.height, 1);
// bool videoVerticallyMirrored = webCamTexture.videoVerticallyMirrored;
// float scaleX = 1;
// float scaleY = videoVerticallyMirrored ? -1.0f : 1.0f;
// if (webCamTexture.videoRotationAngle == 270)
// scaleY = -1.0f;
// gameObject.transform.localScale = new Vector3 (scaleX * gameObject.transform.localScale.x, scaleY * gameObject.transform.localScale.y, 1);
gameObject.GetComponent <Renderer> ().material.mainTexture = texture;
#if (UNITY_ANDROID || UNITY_IPHONE) && !UNITY_EDITOR
Camera.main.orthographicSize = webCamTexture.width / 2;
#else
Camera.main.orthographicSize = webCamTexture.height / 2;
#endif
initDone = true;
break;
}
else
{
yield return(0);
}
}
}
// Update is called once per frame
void Update()
{
if (!initDone)
{
return;
}
#if UNITY_IPHONE && !UNITY_EDITOR
if (webCamTexture.width > 16 && webCamTexture.height > 16)
{
#else
if (webCamTexture.didUpdateThisFrame)
{
#endif
Utils.webCamTextureToMat(webCamTexture, rgbaMat, colors);
if (webCamTexture.videoVerticallyMirrored)
{
if (webCamDevice.isFrontFacing)
{
if (webCamTexture.videoRotationAngle == 0)
{
Core.flip(rgbaMat, rgbaMat, 1);
}
else if (webCamTexture.videoRotationAngle == 90)
{
Core.flip(rgbaMat, rgbaMat, 0);
}
else if (webCamTexture.videoRotationAngle == 270)
{
Core.flip(rgbaMat, rgbaMat, 1);
}
}
else
{
if (webCamTexture.videoRotationAngle == 90)
{
}
else if (webCamTexture.videoRotationAngle == 270)
{
Core.flip(rgbaMat, rgbaMat, -1);
}
}
}
else
{
if (webCamDevice.isFrontFacing)
{
if (webCamTexture.videoRotationAngle == 0)
{
Core.flip(rgbaMat, rgbaMat, 1);
}
else if (webCamTexture.videoRotationAngle == 90)
{
Core.flip(rgbaMat, rgbaMat, 0);
}
else if (webCamTexture.videoRotationAngle == 270)
{
Core.flip(rgbaMat, rgbaMat, 1);
}
}
else
{
if (webCamTexture.videoRotationAngle == 90)
{
}
else if (webCamTexture.videoRotationAngle == 270)
{
Core.flip(rgbaMat, rgbaMat, -1);
}
}
}
if (mMOP2fptsPrev.rows() == 0)
{
// first time through the loop so we need prev and this mats
// plus prev points
// get this mat
Imgproc.cvtColor(rgbaMat, matOpFlowThis, Imgproc.COLOR_RGBA2GRAY);
// copy that to prev mat
matOpFlowThis.copyTo(matOpFlowPrev);
// get prev corners
Imgproc.goodFeaturesToTrack(matOpFlowPrev, MOPcorners, iGFFTMax, 0.05, 20);
mMOP2fptsPrev.fromArray(MOPcorners.toArray());
// get safe copy of this corners
mMOP2fptsPrev.copyTo(mMOP2fptsSafe);
}
else
{
// we've been through before so
// this mat is valid. Copy it to prev mat
matOpFlowThis.copyTo(matOpFlowPrev);
// get this mat
Imgproc.cvtColor(rgbaMat, matOpFlowThis, Imgproc.COLOR_RGBA2GRAY);
// get the corners for this mat
Imgproc.goodFeaturesToTrack(matOpFlowThis, MOPcorners, iGFFTMax, 0.05, 20);
mMOP2fptsThis.fromArray(MOPcorners.toArray());
// retrieve the corners from the prev mat
// (saves calculating them again)
mMOP2fptsSafe.copyTo(mMOP2fptsPrev);
// and save this corners for next time through
mMOP2fptsThis.copyTo(mMOP2fptsSafe);
}
/*
* Parameters:
* prevImg first 8-bit input image
* nextImg second input image
* prevPts vector of 2D points for which the flow needs to be found; point coordinates must be single-precision floating-point numbers.
* nextPts output vector of 2D points (with single-precision floating-point coordinates) containing the calculated new positions of input features in the second image; when OPTFLOW_USE_INITIAL_FLOW flag is passed, the vector must have the same size as in the input.
* status output status vector (of unsigned chars); each element of the vector is set to 1 if the flow for the corresponding features has been found, otherwise, it is set to 0.
* err output vector of errors; each element of the vector is set to an error for the corresponding feature, type of the error measure can be set in flags parameter; if the flow wasn't found then the error is not defined (use the status parameter to find such cases).
*/
Video.calcOpticalFlowPyrLK(matOpFlowPrev, matOpFlowThis, mMOP2fptsPrev, mMOP2fptsThis, mMOBStatus, mMOFerr);
if (!mMOBStatus.empty())
{
List <Point> cornersPrev = mMOP2fptsPrev.toList();
List <Point> cornersThis = mMOP2fptsThis.toList();
List <byte> byteStatus = mMOBStatus.toList();
int x = 0;
int y = byteStatus.Count - 1;
for (x = 0; x < y; x++)
{
if (byteStatus [x] == 1)
{
Point pt = cornersThis [x];
Point pt2 = cornersPrev [x];
Core.circle(rgbaMat, pt, 5, colorRed, iLineThickness - 1);
Core.line(rgbaMat, pt, pt2, colorRed, iLineThickness);
}
}
}
Utils.matToTexture2D(rgbaMat, texture, colors);
gameObject.GetComponent <Renderer> ().material.mainTexture = texture;
}
}
void OnDisable()
{
webCamTexture.Stop();
}
void OnGUI()
{
float screenScale = Screen.width / 240.0f;
Matrix4x4 scaledMatrix = Matrix4x4.Scale(new Vector3(screenScale, screenScale, screenScale));
GUI.matrix = scaledMatrix;
GUILayout.BeginVertical();
if (GUILayout.Button("back"))
{
Application.LoadLevel("OpenCVForUnitySample");
}
if (GUILayout.Button("change camera"))
{
isFrontFacing = !isFrontFacing;
StartCoroutine(init());
}
GUILayout.EndVertical();
}
}
}
private IEnumerator init()
{
if (webCamTexture != null)
{
webCamTexture.Stop();
initDone = false;
rgbaMat.Dispose();
matOpFlowThis.Dispose();
matOpFlowPrev.Dispose();
MOPcorners.Dispose();
mMOP2fptsThis.Dispose();
mMOP2fptsPrev.Dispose();
mMOP2fptsSafe.Dispose();
mMOBStatus.Dispose();
mMOFerr.Dispose();
}
// Checks how many and which cameras are available on the device
for (int cameraIndex = 0; cameraIndex < WebCamTexture.devices.Length; cameraIndex++)
{
if (WebCamTexture.devices [cameraIndex].isFrontFacing == shouldUseFrontFacing)
{
Debug.Log(cameraIndex + " name " + WebCamTexture.devices [cameraIndex].name + " isFrontFacing " + WebCamTexture.devices [cameraIndex].isFrontFacing);
webCamDevice = WebCamTexture.devices [cameraIndex];
webCamTexture = new WebCamTexture(webCamDevice.name, width, height);
break;
}
}
if (webCamTexture == null)
{
webCamDevice = WebCamTexture.devices [0];
webCamTexture = new WebCamTexture(webCamDevice.name, width, height);
}
Debug.Log("width " + webCamTexture.width + " height " + webCamTexture.height + " fps " + webCamTexture.requestedFPS);
// Starts the camera
webCamTexture.Play();
while (true)
{
//If you want to use webcamTexture.width and webcamTexture.height on iOS, you have to wait until webcamTexture.didUpdateThisFrame == 1, otherwise these two values will be equal to 16. (http://forum.unity3d.com/threads/webcamtexture-and-error-0x0502.123922/)
#if UNITY_IOS && !UNITY_EDITOR && (UNITY_4_6_3 || UNITY_4_6_4 || UNITY_5_0_0 || UNITY_5_0_1)
if (webCamTexture.width > 16 && webCamTexture.height > 16)
{
#else
if (webCamTexture.didUpdateThisFrame)
{
#if UNITY_IOS && !UNITY_EDITOR && UNITY_5_2
while (webCamTexture.width <= 16)
{
webCamTexture.GetPixels32();
yield return(new WaitForEndOfFrame());
}
#endif
#endif
Debug.Log("width " + webCamTexture.width + " height " + webCamTexture.height + " fps " + webCamTexture.requestedFPS);
Debug.Log("videoRotationAngle " + webCamTexture.videoRotationAngle + " videoVerticallyMirrored " + webCamTexture.videoVerticallyMirrored + " isFrongFacing " + webCamDevice.isFrontFacing);
colors = new Color32[webCamTexture.width * webCamTexture.height];
rgbaMat = new Mat(webCamTexture.height, webCamTexture.width, CvType.CV_8UC4);
matOpFlowThis = new Mat();
matOpFlowPrev = new Mat();
MOPcorners = new MatOfPoint();
mMOP2fptsThis = new MatOfPoint2f();
mMOP2fptsPrev = new MatOfPoint2f();
mMOP2fptsSafe = new MatOfPoint2f();
mMOBStatus = new MatOfByte();
mMOFerr = new MatOfFloat();
texture = new Texture2D(webCamTexture.width, webCamTexture.height, TextureFormat.RGBA32, false);
gameObject.GetComponent <Renderer> ().material.mainTexture = texture;
updateLayout();
screenOrientation = Screen.orientation;
initDone = true;
break;
}
else
{
yield return(0);
}
}
}
protected override void postprocess(Mat frame, List <Mat> outs, Net net, int backend = Dnn.DNN_BACKEND_OPENCV)
{
List <int> classIdsList = new List <int>();
List <float> confidencesList = new List <float>();
List <Rect2d> boxesList = new List <Rect2d>();
List <Point[]> pointsList = new List <Point[]>();
if (outs.Count == 2)
{
// reshape mat : outs[0]:[1, x, 4] to [x, 4], outs[1]:[1, x, 2] to [x, 2]
Mat boxes_m = outs[0].reshape(1, new int[] { outs[0].size(1), outs[0].size(2) });
Mat scores_m = outs[1].reshape(1, new int[] { outs[1].size(1), outs[1].size(2) });
//Debug.Log("boxes_m: " + boxes_m);
//Debug.Log("scores_m: " + scores_m);
//Debug.Log("priors: " + priors);
convertLocationsToBoxes(boxes_m, priors, 0.1f, 0.2f);
centerFormToCornerForm(boxes_m);
Mat boxes_0_4 = new Mat(boxes_m, new Range(0, boxes_m.rows()), new Range(0, 4));
float[] boxes_arr = new float[boxes_0_4.rows() * boxes_0_4.cols()];
MatUtils.copyFromMat(boxes_0_4, boxes_arr);
Mat scores_1_2 = new Mat(scores_m, new Range(0, scores_m.rows()), new Range(1, 2));
float[] confidences_arr = new float[scores_1_2.rows()];
MatUtils.copyFromMat(scores_1_2, confidences_arr);
for (int i = 0; i < boxes_m.rows(); i++)
{
float confidence = confidences_arr[i];
if (confidence > confThreshold)
{
int boxes_index = i * 4;
float left = boxes_arr[boxes_index] * frame.cols();
float top = boxes_arr[boxes_index + 1] * frame.rows();
float right = boxes_arr[boxes_index + 2] * frame.cols();
float bottom = boxes_arr[boxes_index + 3] * frame.rows();
float width = right - left + 1f;
float height = bottom - top + 1f;
classIdsList.Add(0);
confidencesList.Add(confidence);
boxesList.Add(new Rect2d(left, top, width, height));
}
}
if (boxes_m.cols() > 4 && boxes_m.cols() % 2 == 0)
{
Mat points = new Mat(boxes_m, new Range(0, boxes_m.rows()), new Range(4, boxes_m.cols()));
float[] points_arr = new float[points.rows() * points.cols()];
MatUtils.copyFromMat(points, points_arr);
for (int i = 0; i < boxes_m.rows(); i++)
{
float confidence = confidences_arr[i];
if (confidence > confThreshold)
{
int points_index = i * points.cols();
Point[] p_arr = new Point[points.cols() / 2];
for (int index = 0; index < points.cols() / 2; index++)
{
float x = points_arr[points_index + index * 2] * frame.cols();
float y = points_arr[points_index + index * 2 + 1] * frame.rows();
p_arr[index] = new Point(x, y);
}
pointsList.Add(p_arr);
}
}
}
}
MatOfRect2d boxes = new MatOfRect2d();
boxes.fromList(boxesList);
MatOfFloat confidences = new MatOfFloat();
confidences.fromList(confidencesList);
MatOfInt indices = new MatOfInt();
Dnn.NMSBoxes(boxes, confidences, confThreshold, nmsThreshold, indices);
//Debug.Log("indices.dump () " + indices.dump());
//Debug.Log ("indices.ToString () "+indices.ToString());
for (int i = 0; i < indices.total(); ++i)
{
int idx = (int)indices.get(i, 0)[0];
Rect2d box = boxesList[idx];
drawPred(classIdsList[idx], confidencesList[idx], box.x, box.y,
box.x + box.width, box.y + box.height, frame);
if (pointsList.Count > 0)
{
drawPredPoints(pointsList[idx], frame);
}
}
indices.Dispose();
boxes.Dispose();
confidences.Dispose();
}
/// <summary>
/// Postprocess the specified frame, outs and net.
/// </summary>
/// <param name="frame">Frame.</param>
/// <param name="outs">Outs.</param>
/// <param name="net">Net.</param>
private void postprocess(Mat frame, List <Mat> outs, Net net)
{
string outLayerType = outBlobTypes[0];
List <int> classIdsList = new List <int>();
List <float> confidencesList = new List <float>();
List <OpenCVForUnity.CoreModule.Rect> boxesList = new List <OpenCVForUnity.CoreModule.Rect>();
if (outLayerType == "Region")
{
for (int i = 0; i < outs.Count; ++i)
{
// Network produces output blob with a shape NxC where N is a number of
// detected objects and C is a number of classes + 4 where the first 4
// numbers are [center_x, center_y, width, height]
//Debug.Log("outs[i].ToString() " + outs[i].ToString());
float[] positionData = new float[5];
float[] confidenceData = new float[outs[i].cols() - 5];
for (int p = 0; p < outs[i].rows(); p++)
{
outs[i].get(p, 0, positionData);
outs[i].get(p, 5, confidenceData);
int maxIdx = confidenceData.Select((val, idx) => new { V = val, I = idx }).Aggregate((max, working) => (max.V > working.V) ? max : working).I;
float confidence = confidenceData[maxIdx];
if (confidence > confThreshold)
{
int centerX = (int)(positionData[0] * frame.cols());
int centerY = (int)(positionData[1] * frame.rows());
int width = (int)(positionData[2] * frame.cols());
int height = (int)(positionData[3] * frame.rows());
int left = centerX - width / 2;
int top = centerY - height / 2;
classIdsList.Add(maxIdx);
confidencesList.Add((float)confidence);
boxesList.Add(new OpenCVForUnity.CoreModule.Rect(left, top, width, height));
}
}
}
}
else
{
Debug.Log("Unknown output layer type: " + outLayerType);
}
MatOfRect boxes = new MatOfRect();
boxes.fromList(boxesList);
MatOfFloat confidences = new MatOfFloat();
confidences.fromList(confidencesList);
MatOfInt indices = new MatOfInt();
Dnn.NMSBoxes(boxes, confidences, confThreshold, nmsThreshold, indices);
//Check the Language selected
switch (menuVariables.GetLanguage())
{
case "EN":
vocOffset = 0;
break;
case "ES":
vocOffset = 80;
break;
case "FR":
vocOffset = 160;
break;
case "DE":
vocOffset = 240;
break;
case "IT":
vocOffset = 320;
break;
default:
vocOffset = 0;
break;
}
//Draw the bouding box only if its in the center of the image (On Cursor)
for (int i = 0; i < indices.total(); ++i)
{
int idx = (int)indices.get(i, 0)[0];
OpenCVForUnity.CoreModule.Rect box = boxesList[idx];
if (isOnCursor(box, cursorObject.GetComponent <Cursor>()))
{
drawPred(vocOffset + classIdsList[idx], confidencesList[idx], box.x, box.y,
box.x + box.width, box.y + box.height, frame);
wordDisplay.text = classNames[classIdsList[idx]];
//Update the text summarizing the object encountered
if (!vocIDList.Contains(classIdsList[idx]))
{
//Update the vocabulary learned
vocIDList.Add(classIdsList[idx]);
EnglishText.text += "\n" + classNames[classIdsList[idx]] + "\n";
SpanishText.text += "\n" + classNames[80 + classIdsList[idx]] + "\n";
FrenchText.text += "\n" + classNames[160 + classIdsList[idx]] + "\n";
GermanText.text += "\n" + classNames[240 + classIdsList[idx]] + "\n";
ItalianText.text += "\n" + classNames[320 + classIdsList[idx]] + "\n";
}
}
}
indices.Dispose();
boxes.Dispose();
confidences.Dispose();
}
/// <summary>
/// Process
/// </summary>
/// <returns></returns>
private async void Process()
{
float DOWNSCALE_RATIO = 1.0f;
while (true)
{
// Check TaskCancel
if (tokenSource.Token.IsCancellationRequested)
{
break;
}
rgbaMat = webCamTextureToMatHelper.GetMat();
// Debug.Log ("rgbaMat.ToString() " + rgbaMat.ToString ());
Mat downScaleRgbaMat = null;
DOWNSCALE_RATIO = 1.0f;
if (enableDownScale)
{
downScaleRgbaMat = imageOptimizationHelper.GetDownScaleMat(rgbaMat);
DOWNSCALE_RATIO = imageOptimizationHelper.downscaleRatio;
}
else
{
downScaleRgbaMat = rgbaMat;
DOWNSCALE_RATIO = 1.0f;
}
Imgproc.cvtColor(downScaleRgbaMat, bgrMat, Imgproc.COLOR_RGBA2BGR);
await Task.Run(() =>
{
// detect faces on the downscale image
if (!enableSkipFrame || !imageOptimizationHelper.IsCurrentFrameSkipped())
{
if (net == null)
{
Imgproc.putText(rgbaMat, "model file is not loaded.", new Point(5, rgbaMat.rows() - 30), Imgproc.FONT_HERSHEY_SIMPLEX, 0.7, new Scalar(255, 255, 255, 255), 2, Imgproc.LINE_AA, false);
Imgproc.putText(rgbaMat, "Please read console message.", new Point(5, rgbaMat.rows() - 10), Imgproc.FONT_HERSHEY_SIMPLEX, 0.7, new Scalar(255, 255, 255, 255), 2, Imgproc.LINE_AA, false);
}
else
{
// Create a 4D blob from a frame.
Size inpSize = new Size(inpWidth > 0 ? inpWidth : bgrMat.cols(),
inpHeight > 0 ? inpHeight : bgrMat.rows());
Mat blob = Dnn.blobFromImage(bgrMat, scale, inpSize, mean, swapRB, false);
// Run a model.
net.setInput(blob);
if (net.getLayer(new DictValue(0)).outputNameToIndex("im_info") != -1)
{ // Faster-RCNN or R-FCN
Imgproc.resize(bgrMat, bgrMat, inpSize);
Mat imInfo = new Mat(1, 3, CvType.CV_32FC1);
imInfo.put(0, 0, new float[] {
(float)inpSize.height,
(float)inpSize.width,
1.6f
});
net.setInput(imInfo, "im_info");
}
TickMeter tm = new TickMeter();
tm.start();
List <Mat> outs = new List <Mat>();
net.forward(outs, outBlobNames);
tm.stop();
// Debug.Log ("Inference time, ms: " + tm.getTimeMilli ());
postprocess(bgrMat, outs, net);
for (int i = 0; i < outs.Count; i++)
{
outs[i].Dispose();
}
blob.Dispose();
if (enableDownScale)
{
for (int i = 0; i < _boxesList.Count; ++i)
{
var rect = _boxesList[i];
_boxesList[i] = new OpenCVForUnity.CoreModule.Rect(
(int)(rect.x * DOWNSCALE_RATIO),
(int)(rect.y * DOWNSCALE_RATIO),
(int)(rect.width * DOWNSCALE_RATIO),
(int)(rect.height * DOWNSCALE_RATIO));
}
}
}
//Imgproc.rectangle(rgbaMat, new Point(0, 0), new Point(rgbaMat.width(), rgbaMat.height()), new Scalar(0, 0, 0, 0), -1);
MatOfRect boxes = new MatOfRect();
boxes.fromList(_boxesList);
MatOfFloat confidences = new MatOfFloat();
confidences.fromList(_confidencesList);
MatOfInt indices = new MatOfInt();
Dnn.NMSBoxes(boxes, confidences, confThreshold, nmsThreshold, indices);
// Debug.Log ("indices.dump () "+indices.dump ());
// Debug.Log ("indices.ToString () "+indices.ToString());
for (int i = 0; i < indices.total(); ++i)
{
int idx = (int)indices.get(i, 0)[0];
OpenCVForUnity.CoreModule.Rect box = _boxesList[idx];
drawPred(_classIdsList[idx], _confidencesList[idx], box.x, box.y,
box.x + box.width, box.y + box.height, rgbaMat);
}
indices.Dispose();
boxes.Dispose();
confidences.Dispose();
}
});
Utils.fastMatToTexture2D(rgbaMat, texture);
Thread.Sleep(10);
}
}
/// <summary>
/// Scanning the specified frame, outs and net.
/// </summary>
/// <param name="frame">Frame.</param>
/// <param name="outs">Outs.</param>
/// <param name="net">Net.</param>
private void postscan(Mat frame, List <Mat> outs, Net net)
{
string outLayerType = outBlobTypes[0];
List <int> classIdsList = new List <int>();
List <float> confidencesList = new List <float>();
List <OpenCVForUnity.CoreModule.Rect> boxesList = new List <OpenCVForUnity.CoreModule.Rect>();
if (outLayerType == "Region")
{
for (int i = 0; i < outs.Count; ++i)
{
// Network produces output blob with a shape NxC where N is a number of
// detected objects and C is a number of classes + 4 where the first 4
// numbers are [center_x, center_y, width, height]
//Debug.Log("outs[i].ToString() " + outs[i].ToString());
float[] positionData = new float[5];
float[] confidenceData = new float[outs[i].cols() - 5];
for (int p = 0; p < outs[i].rows(); p++)
{
outs[i].get(p, 0, positionData);
outs[i].get(p, 5, confidenceData);
int maxIdx = confidenceData.Select((val, idx) => new { V = val, I = idx }).Aggregate((max, working) => (max.V > working.V) ? max : working).I;
float confidence = confidenceData[maxIdx];
if (confidence > confThreshold)
{
int centerX = (int)(positionData[0] * frame.cols());
int centerY = (int)(positionData[1] * frame.rows());
int width = (int)(positionData[2] * frame.cols());
int height = (int)(positionData[3] * frame.rows());
int left = centerX - width / 2;
int top = centerY - height / 2;
classIdsList.Add(maxIdx);
confidencesList.Add((float)confidence);
boxesList.Add(new OpenCVForUnity.CoreModule.Rect(left, top, width, height));
}
}
}
}
else
{
Debug.Log("Unknown output layer type: " + outLayerType);
}
MatOfRect boxes = new MatOfRect();
boxes.fromList(boxesList);
MatOfFloat confidences = new MatOfFloat();
confidences.fromList(confidencesList);
MatOfInt indices = new MatOfInt();
Dnn.NMSBoxes(boxes, confidences, confThreshold, nmsThreshold, indices);
//for-loop for the mini game - if a new class appears, add it to the
for (int i = 0; i < indices.total(); ++i)
{
int idx = (int)indices.get(i, 0)[0];
if (!minigameList.Contains(classIdsList[idx]))
{
Debug.Log(classNames[classIdsList[idx]]);
minigameList.Add(classIdsList[idx]);
if (minigameList.Count() > 1)
{
wordDisplay.text = minigameList.Count().ToString() + " words";
}
else
{
wordDisplay.text = minigameList.Count().ToString() + " word";
}
}
}
indices.Dispose();
boxes.Dispose();
confidences.Dispose();
}
