async void RunCustomVision()
{
try
{
_misty.SkillLogger.Log("Taking picture to analyze");
_misty.SendDebugMessage("Taking picture to analyze", null);
ITakePictureResponse takePictureResponse = await _misty.TakePictureAsync("oretest.jpg", false, true, true, 640, 480);
_misty.SendDebugMessage("Picture taken", null);
SoftwareBitmap softwareBitmap;
using (IRandomAccessStream stream = new MemoryStream((byte[])takePictureResponse.Data.Image).AsRandomAccessStream())
{
stream.Seek(0);
// Create the decoder from the stream
BitmapDecoder decoder = await BitmapDecoder.CreateAsync(stream);
// Get the SoftwareBitmap representation of the file in BGRA8 format
softwareBitmap = await decoder.GetSoftwareBitmapAsync();
softwareBitmap = SoftwareBitmap.Convert(softwareBitmap, BitmapPixelFormat.Bgra8, BitmapAlphaMode.Premultiplied);
}
// Encapsulate the image in the WinML image type (VideoFrame) to be bound and evaluated
VideoFrame inputImage = VideoFrame.CreateWithSoftwareBitmap(softwareBitmap);
_misty.SendDebugMessage("Picture processed, sending to model", null);
// Evaluate the image
OnnxModelOutput output = await EvaluateVideoFrameAsync(inputImage);
_misty.SendDebugMessage("Model finished eval", null);
await _misty.DisplayImageAsync("e_DefaultContent.jpg", 100);
if (output == null)
{
_misty.SendDebugMessage("Model output empty", null);
_misty.ChangeLED(0, 0, 0, OnResponse);
alreadyRunning = false;
}
else
{
int vectorCount = output.detected_classes.GetAsVectorView().Count;
double initialScore = output.detected_scores.GetAsVectorView()[0];
long initialClass = output.detected_classes.GetAsVectorView()[0];
if (vectorCount == 0 || initialScore < 0.25)
{
_misty.ChangeLED(0, 0, 0, OnResponse);
alreadyRunning = false;
}
else if (initialClass == 1 && initialScore >= 0.25)
{
_misty.ChangeLED(255, 0, 0, OnResponse);
_misty.RunSkill("e1fcbf5b-9163-4d09-8707-bffd00ddcd5d", null, null);
alreadyRunning = false;
}
else if (initialClass == 0 && initialScore >= 0.25)
{
_misty.ChangeLED(0, 0, 255, OnResponse);
//Say found Ore
//_misty.RunSkill("a61832ab-6bc1-4f1a-9de1-0d1dc8bf3ff0", null, null);
var data = new StringContent("{ \"text\":\"Ore Found!\",\"pitch\":0,\"speechRate\":0,\"voice\":null,\"flush\":false,\"utteranceId\":null }", Encoding.UTF8, "application/json");
HttpResponseMessage result = await client.PostAsync("http://127.0.0.1/api/tts/speak?text=Ore Found!&pitch=0&speechRate=0&flush=false", data);
double calcTrajectory = yaw.getYaw() + (25 * (((output.detected_boxes.GetAsVectorView()[0] + output.detected_boxes.GetAsVectorView()[2]) / 2) - 0.5) * -1);
await _misty.SendDebugMessageAsync("Trajectory: " + calcTrajectory);
//Take the current yaw of the robot and then add the box X axis percentage
//The 20 number is approximately how many degrees you have to rotate to go from edge to center of the camera
if (calcTrajectory > yaw.getYaw())
{
await _misty.DriveAsync(0, 5);
}
else
{
await _misty.DriveAsync(0, -5);
}
//data = new StringContent("{ \"heading\":" + calcTrajectory.ToString() + ",\"radius\":0,\"timeMs\":3000,\"reverse\":false }", Encoding.UTF8, "application/json");
//result = await client.PostAsync("http://127.0.0.1/api/drive/arc", data);
yaw.setTargetYaw(calcTrajectory);
yaw.YawReached += HandleYawReached;
calcTrajectory = _currentHeadPitch + (80 * (((output.detected_boxes.GetAsVectorView()[1] + output.detected_boxes.GetAsVectorView()[3]) / 2) - 0.5));
await _misty.MoveHeadAsync(calcTrajectory, 0, 0, 100, AngularUnit.Degrees);
//_misty.DriveArc(calcTrajectory, 0.2, 2000, false, null);
//357.47 deg 50% at 2sec = 341.88 16 degree 342.46
}
}
}
catch (Exception ex)
{
alreadyRunning = false;
_misty.SendDebugMessage($"error: {ex.Message}", null);
_misty.SendDebugMessage("Picture processing failed", null);
}
}