public void TestMethod4()
{
Debug.WriteLine("[TestMethod4]");
EmotionDetectionAsset eda = new EmotionDetectionAsset();
// http://stackoverflow.com/questions/13605013/pass-bitmap-from-c-sharp-to-c
// https://msdn.microsoft.com/en-us/library/vs/alm/dd183402(v=vs.85).aspx
//
eda.Initialize(@".", "shape_predictor_68_face_landmarks.dat");
eda.ParseRules(File.ReadAllLines(@".\FURIA Fuzzy Logic Rules.txt"));
if (eda.ProcessImage((Bitmap)Bitmap.FromFile(@".\Kiavash1.jpg")))
{
Debug.WriteLine(String.Format("{0} Face(s detected.", eda.Faces.Count));
if (eda.ProcessFaces())
{
Int32 i = 1;
foreach (KeyValuePair <RECT, List <POINT> > kvp in eda.Faces)
{
Debug.WriteLine(String.Format("{0} Landmark(s) detected in Face {1} at {2}.", kvp.Value.Count, i++, kvp.Key));
}
if (eda.ProcessLandmarks())
{
//! Not coded yet.
}
}
}
}
void Start()
{
WebCamDevice[] devices = WebCamTexture.devices;
for (int i = 0; i < devices.Length; i++)
{
print("Webcam available: " + devices[i].name);
}
webcam = new WebCamTexture(640, 480);
rawimage.texture = webcam;
rawimage.material.mainTexture = webcam;
data = new Color32[webcam.width * webcam.height];
eda = new EmotionDetectionAsset();
eda.Bridge = new dlib_csharp.Bridge();
eda.Initialize(@"Assets\", database);
String[] lines = File.ReadAllLines(furia);
eda.ParseRules(lines);
Debug.Log("Emotion detection Ready for Use");
}
public void TestMethod3()
{
Debug.WriteLine("[TestMethod3]");
EmotionDetectionAsset eda = new EmotionDetectionAsset();
if (eda.ParseRules(File.ReadAllLines(@"..\..\..\database\FURIA Fuzzy Logic Rules.txt")))
{
// Output:
//Emotions = Happy(CF = 0.97)
//(V30 in [159.608, 160.424, inf, inf])
//(V35 in [30.0655, 30.2536, inf, inf])
//eda.CheckValues(eda.expressions.Skip(0).First(), "V30", new Double[] { 20, 160, 180 });
//eda.CheckValues(eda.expressions.Skip(0).First(), "V35", new Double[] { 20, 30.0655, 30.0656, 30.1, 30.2535, 30.2536, 32 });
}
Debug.Print("{0} Emotions found in Rules", eda.Emotions.Count);
}
/// <summary>
/// Use this for initialization.
/// </summary>
void Start()
{
Debug.Log("체크1" + furia);
Debug.Log("체크2" + database);
emo_txt_read();
em_t = GameObject.Find("EM_Text");
em_s = GameObject.Find("EM_St");
btns = GameObject.Find("Bottom_btns");
picture = GameObject.Find("Picture_btns");
/*
* string date = DateTime.Now.ToString("yyyy_MM_dd_HH");
* Debug.Log(date);
* if (date == "2020_02_11_20")
* {
* Time.timeScale = 0;
* }
*/
//1) Enumerate webcams
//
WebCamDevice[] devices = WebCamTexture.devices;
//2) for debugging purposes, prints available devices to the console
//
for (int i = 0; i < devices.Length; i++)
{
print("Webcam available: " + devices[i].name);
}
//! http://answers.unity3d.com/questions/909967/getting-a-web-cam-to-play-on-ui-texture-image.html
//WebCamTexture webcam = new WebCamTexture();
//rawimage.texture = webcam;
//rawimage.material.mainTexture = webcam;
//webcamTexture.Play();
//! https://answers.unity3d.com/questions/1101792/how-to-post-process-a-webcamtexture-in-realtime.html
//3) Create a WebCamTexture (size should not be to big)
webcam = new WebCamTexture(640, 480); // (Screen.width, Screen.height)
//4) Assign the texture to an image in the UI to see output (these two lines are not necceasary if you do
// not want to show the webcam video, but might be handy for debugging purposes)
rawimage.texture = webcam;
rawimage.material.mainTexture = webcam;
//5) Start capturing the webcam.
//
webcam.Play();
//6) ??
//output = new Texture2D(webcam.width, webcam.height);
//GetComponent<Renderer>().material.mainTexture = output;
// 7) Create an array to hold the ARGB data of a webcam video frame texture.
//
data = new Color32[webcam.width * webcam.height];
//8) Create an EmotionDetectionAsset
//
// The asset will load the appropriate dlibwrapper depending on process and OS.
// Note that during development unity tends to use the 32 bits version where
// during playing it uses either 32 or 64 bits version dependend on the OS.
//
eda = new EmotionDetectionAsset();
//9) Assign a bridge (no interfaces are required but ILog is convenient during development.
//
eda.Bridge = new dlib_csharp.Bridge();
//10) Init the EmotionDetectionAsset.
// Note this takes a couple of seconds as it need to read/parse the shape_predictor_68_face_landmarks database
//
eda.Initialize(@"Assets", database);
//11) Read the fuzzy logic rules and parse them.
//
String[] lines = File.ReadAllLines(furia);
eda.ParseRules(lines);
Debug.Log("Emotion detection Ready for Use");
}
