private void OnClassifyImage(object sender, EventArgs e)
{
try
{
_loggingService.Log("Classify drawing has started");
var imagePreprocessor = new ImagePreprocessor();
double[] pixels = imagePreprocessor.Preprocess(_uploadImageView.Image);
IPredictionModel predictionModel = Global.PredictionModel;
double[] prediction = predictionModel.Predict(pixels);
_uploadImageView.ProcessPrediction(prediction);
_loggingService.Log("Classify drawing has completed");
}
catch (NullReferenceException exception)
{
_loggingService.Log(exception);
_messageService.ShowMessage("No image was uploaded. Please upload an image and try again.", "Upload error", icon: MessageBoxIcon.Information);
}
catch (Exception exception)
{
_loggingService.Log(exception);
_messageService.ShowMessage("An error ocurred while classyfing the drawing. Please try again.", "Classification error", icon: MessageBoxIcon.Information);
}
}
public async Task <Prediction> PredictAsync(Image <Rgba32> image)
{
var preprocessor = new ImagePreprocessor(Rgba32.White, Rgba32.Black);
image = preprocessor.Preprocess(image);
var inputs = PrepareMLStudioInput(image);
using (var client = new HttpClient())
{
var requestContent = new StringContent(inputs);
requestContent.Headers.ContentType = new MediaTypeHeaderValue("application/json");
client.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Bearer", _apiKey);
var response = await client.PostAsync(_apiUrl, requestContent);
var responseContent = response.Content is HttpContent c ? await c.ReadAsStringAsync() : null;
var prediction = JsonConvert.DeserializeObject <MLStudioResponseObject>(responseContent);
var tag = prediction.results.WebServiceOutput0.FirstOrDefault()?["Scored Labels"];
return(new Prediction
{
Tag = Convert.ToInt32(tag),
Probability = 1
});
}
}
private void OnClassifyDrawing(object sender, EventArgs e)
{
try
{
_loggingService.Log("Classify drawing has started");
var imagePreprocessor = new ImagePreprocessor();
IPredictionModel predictionModel = Global.PredictionModel;
Image img = _slidingWindowView.Drawing;
foreach (Size windowSize in WindowSizes)
{
foreach (BoundingBox boundingBox in ImageUtilities.SlidingWindow(img, windowSize, 112))
{
try
{
double[] pixels = imagePreprocessor.Preprocess(boundingBox.Image);
double[] prediction = predictionModel.Predict(pixels);
// If classification is over 99% draw a bounding box at this location
int predicted = prediction.ArgMax();
double predictedAccuracy = prediction[prediction.ArgMax()];
if (predictedAccuracy >= 0.95)
{
_slidingWindowView.DrawBoundingBox(boundingBox, predicted, predictedAccuracy);
}
}
catch (Exception exception)
{
_loggingService.Log(exception);
}
}
}
_loggingService.Log("Classify drawing has completed");
}
catch (Exception exception)
{
_loggingService.Log(exception);
_messageService.ShowMessage("An error ocurred while classyfing the drawing. Please try again.", "Classification error", icon: MessageBoxIcon.Information);
}
}
