public void DetectObjectsUsingModel(ImageInputData imageInputData)
{
var probs = predictionEngine.Predict(imageInputData).PredictedLabels;
List <BoundingBox> boundingBoxes = outputParser.ParseOutputs(probs);
filteredBoxes = outputParser.FilterBoundingBoxes(boundingBoxes, 5, .5F);
}
public List <BoundingBox> DetectObjectsUsingModel(ImageInputData imageInputData)
{
var labels = customVisionPredictionEngine?.Predict(imageInputData).PredictedLabels ?? tinyYoloPredictionEngine?.Predict(imageInputData).PredictedLabels;
var boundingBoxes = outputParser.ParseOutputs(labels);
var filteredBoxes = outputParser.FilterBoundingBoxes(boundingBoxes, 5, 0.5f);
return(filteredBoxes);
}
public void Test1()
{
var onnxPath = @"../../../../TinyYolo/Data/TinyYolo2_model.onnx";
var testDataPath = @"../../../Data";
var ml = new MLContext();
var train = new Train(ml);
var yolo = new TinyYoloModel(CommonHelper.GetAbsolutionPath(onnxPath, typeof(TinyYoloModel)));
var transformer = train.LoadOnnx(yolo);
var testImage = Path.Combine(testDataPath, "Image1.jpg" /** Image file here */);
testImage = CommonHelper.GetAbsolutionPath(testImage, typeof(UnitTest1));
var image = Image.FromFile(testImage);
var bitmap = (Bitmap)image;
var testImageData = new ImageNetData {
Image = bitmap
};
var objectDetection = ml.Model.CreatePredictionEngine <ImageNetData, TinyYoloPrediction>(transformer);
TinyYoloPrediction result = new TinyYoloPrediction();
objectDetection.Predict(testImageData, ref result);
OnnxOutputParser parser = new OnnxOutputParser(yolo);
var boxes = parser.ParseOutputs(result.PredictedLabels);
boxes = parser.FilterBoundingBoxes(boxes, 3, .5f);
if (boxes.Any())
{
var saveLocation = CommonHelper.GetAbsolutionPath(testDataPath + "/result", typeof(UnitTest1));
CommonHelper.DrawRect(testDataPath, saveLocation, "Image1.jpg", boxes);
}
else
{
Assert.False(true);
}
}
