/// <summary>
/// Initializes a new instance of the <see cref="FastRCNN"/> class.
/// </summary>
/// <param name="model">The model to use.</param>
public FastRCNN(FastRCNNModel model)
{
this.model = model;
actualValues = new Dictionary <int, string>();
ExpandoObject jsonValues = Newtonsoft.Json.JsonConvert.DeserializeObject <ExpandoObject>(PredMap.Cifar10);
foreach (var item in jsonValues)
{
actualValues.Add(Convert.ToInt32(item.Key), item.Value.ToString());
}
}
/// <summary>
/// Generates the rois.
/// </summary>
/// <param name="bmp">The BMP.</param>
/// <param name="model">The model.</param>
/// <returns></returns>
private List <float> GenerateROIS(Bitmap bmp, FastRCNNModel model)
{
int selectRois = 4000;
int selectionParam = 100;
if (model == FastRCNNModel.Grocery100)
{
selectRois = 100;
selectionParam = 1500;
}
float[] roiList = new float[selectRois * 4];
List <float> inArg3 = new List <float>();
var imgArray = bmp.ToByteArray();
var img = DlibDotNet.Dlib.LoadImageData <DlibDotNet.RgbAlphaPixel>(imgArray, 1000, 1000, 1);
var rects = DlibDotNet.Dlib.FindCandidateObjectLocations(img);
if (!img.IsDisposed)
{
img.Dispose();
}
int counter = 0;
foreach (var item in rects)
{
if (counter >= selectRois * 4)
{
break;
}
roiList[counter] = item.Top * 4; counter++;
roiList[counter] = item.Left * 4; counter++;
roiList[counter] = item.Width * 4; counter++;
roiList[counter] = item.Height * 4; counter++;
proposedBoxes.Add(new Rectangle(item.Left * 4, item.Top * 4, (int)item.Width * 4, (int)item.Height * 4));
}
if (counter <= selectRois)
{
for (int i = counter; i < selectRois; i++)
{
roiList[i] = -1;
}
}
return(roiList.ToList());
}
/// <summary>
/// Generates the rois.
/// </summary>
/// <param name="bmp">The BMP.</param>
/// <param name="model">The model.</param>
/// <returns></returns>
private List <float> GenerateROIS(Bitmap bmp, FastRCNNModel model)
{
int selectRois = 4000;
int selectionParam = 100;
if (model == FastRCNNModel.Grocery100)
{
selectRois = 100;
selectionParam = 1500;
}
float[] roiList = new float[selectRois * 4];
Emgu.CV.Image <Bgr, byte> img = new Image <Bgr, byte>(bmp);
Emgu.CV.XImgproc.SelectiveSearchSegmentation seg = new Emgu.CV.XImgproc.SelectiveSearchSegmentation();
var resizedImg = img.Resize(250, 250, Emgu.CV.CvEnum.Inter.Nearest);
seg.SetBaseImage(resizedImg);
seg.SwitchToSelectiveSearchQuality(selectionParam, selectionParam);
var rects = seg.Process();
//rects = rects.OrderBy(x => (x.X)).ToArray();
int counter = 0;
foreach (var item in rects)
{
if (counter >= selectRois * 4)
{
break;
}
roiList[counter] = item.X * 4; counter++;
roiList[counter] = item.Y * 4; counter++;
roiList[counter] = item.Width * 4; counter++;
roiList[counter] = item.Height * 4; counter++;
proposedBoxes.Add(new Rectangle(item.X * 4, item.Y * 4, item.Width * 4, item.Height * 4));
}
if (counter <= selectRois)
{
for (int i = counter; i < selectRois; i++)
{
roiList[i] = -1;
}
}
return(roiList.ToList());
}
/// <summary>
/// Gets the output variable.
/// </summary>
/// <param name="model">The model.</param>
/// <returns></returns>
private Variable GetOutputVar(FastRCNNModel model)
{
switch (model)
{
case FastRCNNModel.Pascal:
return(modelFunc.Outputs.Where(x => (x.Shape.TotalSize == 84000)).ToList()[0]);
case FastRCNNModel.Grocery100:
return(modelFunc.Outputs.Where(x => (x.Shape.TotalSize == 1700)).ToList()[0]);
default:
break;
}
return(null);
}
/// <summary>
/// Gets the labels.
/// </summary>
/// <param name="model">The model.</param>
/// <returns></returns>
private string[] GetLabels(FastRCNNModel model)
{
string[] result = null;
switch (model)
{
case FastRCNNModel.Grocery100:
result = new[] { "__background__", "avocado", "orange", "butter", "champagne", "egg_Box", "gerkin", "yogurt", "ketchup", "orange_juice", "onion", "pepper", "tomato", "water", "milk", "tabasco", "mustard" };
break;
case FastRCNNModel.Pascal:
result = new[] { "__background__", "aeroplane", "bicycle", "bird", "boat", "bottle", "bus", "car", "cat", "chair", "cow", "dining_table", "dog", "horse", "motor_bike", "person", "potted_plant", "sheep", "sofa", "train", "tv_monitor" };
break;
default:
break;
}
return(result);
}
