private void evaluate_Click(object sender, EventArgs e)
{
var bitmap = GetImage(this.textBox1.Text);
var output = (Bitmap)bitmap.Clone();
bitmap = BitmapTool.ResizeImage(bitmap, 300, 300);
bitmap.Save("input.jpg");
var boxes = new List <BoundingBox>();
int divisor = (int)this.divisorUpDown.Value;
var allExtracts = BitmapTool.SlideWindow(bitmap, 140, 140 / divisor)
.Concat(BitmapTool.SlideWindow(bitmap, 100, 100 / divisor))
.Concat(BitmapTool.SlideWindow(bitmap, 80, 80 / divisor))
.Concat(BitmapTool.SlideWindow(bitmap, 30, 30 / divisor));
foreach (var extracts in allExtracts.Batch(20))
{
boxes.AddRange(BitmapTool.Evaluate(extracts.ToList(), this._yhat, IMAGE_WIDTH, IMAGE_HEIGHT, (float)this.minProbaUpDown.Value / 100.0f));
}
this.currentBoundingBoxes.Clear();
var nms = new NonMaximumSuppresion();
var result = nms.Nms(boxes, (float)this.nmsUpDown.Value / 100.0f);
foreach (var boundingBox in result)
{
BitmapTool.DrawBoundingBox(output, boundingBox, Color.FromArgb(50, 0, 0, 255), false);
this.currentBoundingBoxes.Add(BitmapTool.Capture(bitmap, boundingBox));
}
this.pictureBox1.Image = output;
}
private void StartAI()
{
BuilderInstance <float> .Volume = new VolumeBuilder(); // Needed for GPU, must be done on AI thread
// Must be done after setting BuilderInstance<float>.Volume
this._yhat = SerializationExtensions.Load <float>("FaceDetection", false)[0];
while (true)
{
if (this._queueIn.TryDequeue(out var bitmap))
{
bitmap = BitmapTool.ResizeImage(bitmap, 300, 300);
var boxes = new List <BoundingBox>();
var allExtracts =
BitmapTool.SlideWindow(bitmap, 100, 100 / 9);
// .Concat(BitmapTool.SlideWindow(bitmap, 40, 40 / 3));
//.Concat(BitmapTool.SlideWindow(bitmap, 50, 50/3));
foreach (var extracts in allExtracts.Batch(10))
{
boxes.AddRange(BitmapTool.Evaluate(extracts.ToList(), this._yhat, IMAGE_WIDTH, IMAGE_HEIGHT, 0.8f));
}
this._queueOut.Enqueue(boxes);
}
}
}