/// <summary>
/// Raises the load button event.
/// </summary>
public void OnLoadButton()
{
Debug.Log("User clicked [Load] button.");
// Restart everything!
dispose();
if (facerecAlgorithm == "FaceRecognizer.Fisherfaces")
{
model = Face.createFisherFaceRecognizer();
}
else if (facerecAlgorithm == "FaceRecognizer.Eigenfaces")
{
model = Face.createEigenFaceRecognizer();
}
if (model == null)
{
Debug.LogError("ERROR: The FaceRecognizer algorithm [" + facerecAlgorithm + "] is not available in your version of OpenCV. Please update to OpenCV v2.4.1 or newer.");
m_mode = MODES.MODE_DETECTION;
return;
}
// load the train data.
model.load(Application.temporaryCachePath + "/traindata.yml");
int maxLabel = (int)Core.minMaxLoc(model.getLabels()).maxVal;
if (maxLabel <= 0)
{
Debug.Log("load failure.");
model.Dispose();
model = null;
m_mode = MODES.MODE_DETECTION;
return;
}
// Restore the save data.
m_numPersons = maxLabel + 1;
for (int i = 0; i < m_numPersons; ++i)
{
m_latestFaces.Add(i);
preprocessedFaces.Add(Imgcodecs.imread(Application.temporaryCachePath + "/preprocessedface" + i + ".jpg", 0));
if (preprocessedFaces [i].empty())
{
preprocessedFaces [i] = new Mat(faceHeight, faceWidth, CvType.CV_8UC1, new Scalar(128));
}
faceLabels.Add(i);
}
// go to the recognition mode!
m_mode = MODES.MODE_RECOGNITION;
}
/// <summary>
/// Raises the load button click event.
/// </summary>
public void LoadModel()
{
string loadDirectoryPath = Path.Combine(Application.persistentDataPath, saveDirectoryName);
if (!Directory.Exists(loadDirectoryPath))
{
Debug.Log("load failure. saved train data file does not exist.");
return;
}
// Restart everything!
dispose();
if (facerecAlgorithm == "FaceRecognizer.Fisherfaces")
{
model = FisherFaceRecognizer.create();
}
else if (facerecAlgorithm == "FaceRecognizer.Eigenfaces")
{
model = EigenFaceRecognizer.create();
}
if (model == null)
{
Debug.LogError("ERROR: The FaceRecognizer algorithm [" + facerecAlgorithm + "] is not available in your version of OpenCV. Please update to OpenCV v2.4.1 or newer.");
m_mode = R_MODES.MODE_DETECTION;
return;
}
// load the train data.
model.read(Path.Combine(loadDirectoryPath, "traindata.yml"));
int maxLabel = (int)Core.minMaxLoc(model.getLabels()).maxVal;
if (maxLabel < 0)
{
Debug.Log("load failure.");
model.Dispose();
return;
}
// Restore the save data.
#if UNITY_WEBGL && !UNITY_EDITOR
string format = "jpg";
#else
string format = "png";
#endif
m_numPersons = maxLabel + 1;
personsNames = new string[m_numPersons];
for (int i = 0; i < m_numPersons; ++i)
{
personsNames[i] = GameManager.instance.personsNames[i];
m_latestFaces.Add(i);
preprocessedFaces.Add(Imgcodecs.imread(Path.Combine(loadDirectoryPath, "preprocessedface" + i + "." + format), 0));
if (preprocessedFaces[i].total() == 0)
{
preprocessedFaces[i] = new Mat(faceHeight, faceWidth, CvType.CV_8UC1, new Scalar(128));
}
faceLabels.Add(i);
}
// go to the recognition mode!
m_mode = R_MODES.MODE_RECOGNITION;
}