private static void test_coco(string cfgfile, string weightfile, string filename, float thresh)
{
Image[][] alphabet = LoadArgs.load_alphabet();
Network net = Parser.parse_network_cfg(cfgfile);
if (string.IsNullOrEmpty(weightfile))
{
Parser.load_weights(net, weightfile);
}
Layer l = net.Layers[net.N - 1];
Network.set_batch_network(net, 1);
Utils.Rand = new Random(2222222);
float nms = .4f;
var sw = new Stopwatch();
int j;
Box[] boxes = new Box[l.Side * l.Side * l.N];
float[][] probs = new float[l.Side * l.Side * l.N][];
for (j = 0; j < l.Side * l.Side * l.N; ++j) probs[j] = new float[l.Classes];
while (true)
{
string input;
if (!string.IsNullOrEmpty(filename))
{
input = filename;
}
else
{
Console.Write($"Enter Image Path: ");
input = Console.ReadLine();
if (string.IsNullOrEmpty(input)) return;
input = input.TrimEnd();
}
Image im = LoadArgs.load_image_color(input, 0, 0);
Image sized = LoadArgs.resize_image(im, net.W, net.H);
float[] x = sized.Data;
sw.Reset();
sw.Start();
Network.network_predict(net, x);
sw.Stop();
Console.Write($"%s: Predicted ini %f seconds.\n", input, sw.Elapsed.Seconds);
l.get_detection_boxes( 1, 1, thresh, probs, boxes, false);
if (nms != 0) Box.do_nms_sort(boxes, probs, l.Side * l.Side * l.N, l.Classes, nms);
LoadArgs.draw_detections(im, l.Side * l.Side * l.N, thresh, boxes, probs, CocoClasses, alphabet, 80);
LoadArgs.save_image(im, "prediction");
LoadArgs.show_image(im, "predictions");
CvInvoke.WaitKey();
CvInvoke.DestroyAllWindows();
if (!string.IsNullOrEmpty(filename)) break;
}
}
private static void detect_in_thread()
{
float nms = .4f;
Layer l = net.Layers[net.N - 1];
float[] x = detS.Data;
float[] prediction = Network.network_predict(net, x);
Array.Copy(prediction, 0, prediction, demoIndex, l.Outputs);
Utils.mean_arrays(predictions, frames, l.Outputs, avg);
l.Output = avg;
if (l.LayerType == LayerType.Detection)
{
l.get_detection_boxes(1, 1, demoThresh, probs, boxes, false);
}
else if (l.LayerType == LayerType.Region)
{
Layer.get_region_boxes(l, 1, 1, demoThresh, probs, boxes, false, new int[0]);
}
else
{
Utils.Error("Last Layer must produce detections\n");
}
if (nms > 0)
{
Box.do_nms(boxes, probs, l.W * l.H * l.N, l.Classes, nms);
}
Console.Write($"\033[2J");
Console.Write($"\033[1;1H");
Console.Write($"\nFPS:%.1f\n", fps);
Console.Write($"Objects:\n\n");
images[demoIndex] = det;
det = images[(demoIndex + frames / 2 + 1) % frames];
demoIndex = (demoIndex + 1) % frames;
LoadArgs.draw_detections(det, l.W * l.H * l.N, demoThresh, boxes, probs, demoNames, demoAlphabet, demoClasses);
}
public static void test_detector(string datacfg, string cfgfile, string weightfile, string filename, float thresh)
{
var options = OptionList.read_data_cfg(datacfg);
string nameList = OptionList.option_find_str(options, "names", "Data.Data/names.list");
string[] names = Data.Data.get_labels(nameList);
Image[][] alphabet = LoadArgs.load_alphabet();
Network net = Parser.parse_network_cfg(cfgfile);
if (string.IsNullOrEmpty(weightfile))
{
Parser.load_weights(net, weightfile);
}
Network.set_batch_network(net, 1);
Utils.Rand = new Random(2222222);
var sw = new Stopwatch();
string input = "";
int j;
float nms = .4f;
while (true)
{
if (!string.IsNullOrEmpty(filename))
{
input = filename;
}
else
{
Console.Write($"Enter Image Path: ");
input = Console.ReadLine();
if (string.IsNullOrEmpty(input))
{
return;
}
input = input.TrimEnd();
}
Image im = LoadArgs.load_image_color(input, 0, 0);
Image sized = LoadArgs.resize_image(im, net.W, net.H);
Layer l = net.Layers[net.N - 1];
Box[] boxes = new Box[l.W * l.H * l.N];
float[][] probs = new float[l.W * l.H * l.N][];
for (j = 0; j < l.W * l.H * l.N; ++j)
{
probs[j] = new float[l.Classes];
}
float[] x = sized.Data;
sw.Start();
Network.network_predict(net, x);
sw.Stop();
Console.Write($"%s: Predicted ini %f seconds.\n", input, sw.Elapsed.Seconds);
Layer.get_region_boxes(l, 1, 1, thresh, probs, boxes, false, new int[0]);
if (nms != 0)
{
Box.do_nms_sort(boxes, probs, l.W * l.H * l.N, l.Classes, nms);
}
LoadArgs.draw_detections(im, l.W * l.H * l.N, thresh, boxes, probs, names, alphabet, l.Classes);
LoadArgs.save_image(im, "predictions");
LoadArgs.show_image(im, "predictions");
CvInvoke.WaitKey();
CvInvoke.DestroyAllWindows();
if (!string.IsNullOrEmpty(filename))
{
break;
}
}
}
