private static void extract_voxel(string lfile, string rfile, string prefix)
{
int w = 1920;
int h = 1080;
int shift = 0;
int count = 0;
VideoCapture lcap = new VideoCapture(lfile);
VideoCapture rcap = new VideoCapture(rfile);
while (true)
{
Image l = LoadArgs.get_image_from_stream(lcap);
Image r = LoadArgs.get_image_from_stream(rcap);
if (l.W == 0 || r.W == 0)
{
break;
}
if (count % 100 == 0)
{
shift = LoadArgs.best_3d_shift_r(l, r, -l.H / 100, l.H / 100);
Console.Write($"{shift}\n");
}
Image ls = LoadArgs.crop_image(l, (l.W - w) / 2, (l.H - h) / 2, w, h);
Image rs = LoadArgs.crop_image(r, 105 + (r.W - w) / 2, (r.H - h) / 2 + shift, w, h);
string buff = $"{prefix}_{count:05}_l";
LoadArgs.save_image(ls, buff);
buff = $"{prefix}_{count:05}_r";
LoadArgs.save_image(rs, buff);
++count;
}
}
private static void fetch_in_thread()
{
inputImage = LoadArgs.get_image_from_stream(vidCap);
if (inputImage.Data.Length == 0)
{
Utils.Error("Stream closed.");
}
inS = LoadArgs.resize_image(inputImage, net.W, net.H);
}
private static void demo_art(string cfgfile, string weightfile, int camIndex)
{
Network net = Parser.parse_network_cfg(cfgfile);
if (string.IsNullOrEmpty(weightfile))
{
Parser.load_weights(net, weightfile);
}
Network.set_batch_network(net, 1);
Utils.Rand = new Random(2222222);
using (VideoCapture cap = new VideoCapture(camIndex))
{
string window = "ArtJudgementBot9000!!!";
if (cap != null)
{
Utils.Error("Couldn't connect to webcam.\n");
}
int i;
int[] idx = { 37, 401, 434 };
int n = idx.Length;
while (true)
{
Image ini = LoadArgs.get_image_from_stream(cap);
Image inS = LoadArgs.resize_image(ini, net.W, net.H);
LoadArgs.show_image(ini, window);
float[] p = Network.network_predict(net, inS.Data);
Console.Write($"\033[2J");
Console.Write($"\033[1;1H");
float score = 0;
for (i = 0; i < n; ++i)
{
float s = p[idx[i]];
if (s > score)
{
score = s;
}
}
Console.Write($"I APPRECIATE THIS ARTWORK: %10.7f%%\n", score * 100);
Console.Write($"[");
int upper = 30;
for (i = 0; i < upper; ++i)
{
Console.Write($"%c", ((i + .5) < score * upper) ? 219 : ' ');
}
Console.Write($"]\n");
CvInvoke.WaitKey(1);
}
}
}
private static void generate_vid_rnn(string cfgfile, string weightfile)
{
Network extractor = Parser.parse_network_cfg("cfg/extractor.recon.cfg");
Parser.load_weights(extractor, "/home/pjreddie/trained/yolo-coco.conv");
Network net = Parser.parse_network_cfg(cfgfile);
if (string.IsNullOrEmpty(weightfile))
{
Parser.load_weights(net, weightfile);
}
Network.set_batch_network(extractor, 1);
Network.set_batch_network(net, 1);
int i;
VideoCapture cap = new VideoCapture("/extra/vid/ILSVRC2015/Data.Data/VID/snippets/val/ILSVRC2015_val_00007030.mp4");
float[] feat;
float[] next;
next = null;
Image last = null;
for (i = 0; i < 25; ++i)
{
Image im = LoadArgs.get_image_from_stream(cap);
Image re = LoadArgs.resize_image(im, extractor.W, extractor.H);
feat = Network.network_predict(extractor, re.Data);
if (i > 0)
{
Console.Write($"%f %f\n", Utils.mean_array(feat, 14 * 14 * 512), Utils.variance_array(feat, 14 * 14 * 512));
Console.Write($"%f %f\n", Utils.mean_array(next, 14 * 14 * 512), Utils.variance_array(next, 14 * 14 * 512));
Console.Write($"%f\n", Utils.mse_array(feat, 14 * 14 * 512));
Blas.Axpy_cpu(14 * 14 * 512, -1, feat, next);
Console.Write($"%f\n", Utils.mse_array(next, 14 * 14 * 512));
}
next = Network.network_predict(net, feat);
if (i == 24)
{
last = new Image(re);
}
}
for (i = 0; i < 30; ++i)
{
next = Network.network_predict(net, next);
Image newi = save_reconstruction(extractor, last, next, "new", i);
last = newi;
}
}
private static void gun_classifier(string datacfg, string cfgfile, string weightfile, int camIndex, string filename)
{
int[] badCats = { 218, 539, 540, 1213, 1501, 1742, 1911, 2415, 4348, 19223, 368, 369, 370, 1133, 1200, 1306, 2122, 2301, 2537, 2823, 3179, 3596, 3639, 4489, 5107, 5140, 5289, 6240, 6631, 6762, 7048, 7171, 7969, 7984, 7989, 8824, 8927, 9915, 10270, 10448, 13401, 15205, 18358, 18894, 18895, 19249, 19697 };
Console.Write($"Classifier Demo\n");
Network net = Parser.parse_network_cfg(cfgfile);
if (string.IsNullOrEmpty(weightfile))
{
Parser.load_weights(net, weightfile);
}
Network.set_batch_network(net, 1);
var options = OptionList.read_data_cfg(datacfg);
Utils.Rand = new Random(2222222);
using (VideoCapture cap = !string.IsNullOrEmpty(filename)
? new VideoCapture(filename)
: new VideoCapture(camIndex))
{
int top = OptionList.option_find_int(options, "top", 1);
string nameList = OptionList.option_find_str(options, "names", "");
string[] names = Data.Data.get_labels(nameList);
int[] indexes = new int[top];
if (cap.IsOpened)
{
Utils.Error("Couldn't connect to webcam.\n");
}
float fps = 0;
int i;
while (true)
{
var sw = new Stopwatch();
sw.Start();
Image ini = LoadArgs.get_image_from_stream(cap);
Image inS = LoadArgs.resize_image(ini, net.W, net.H);
LoadArgs.show_image(ini, "Threat Detection");
float[] predictions = Network.network_predict(net, inS.Data);
Network.top_predictions(net, top, indexes);
Console.Write($"\033[2J");
Console.Write($"\033[1;1H");
bool threat = false;
for (i = 0; i < badCats.Length; ++i)
{
int index = badCats[i];
if (predictions[index] > .01)
{
Console.Write($"Threat Detected!\n");
threat = true;
break;
}
}
if (threat)
{
Console.Write($"Scanning...\n");
}
for (i = 0; i < badCats.Length; ++i)
{
int index = badCats[i];
if (predictions[index] > .01)
{
Console.Write($"%s\n", names[index]);
}
}
CvInvoke.WaitKey(10);
sw.Stop();
float curr = 1000.0f / sw.ElapsedMilliseconds;
fps = .9f * fps + .1f * curr;
}
}
}
private static void threat_classifier(string datacfg, string cfgfile, string weightfile, int camIndex, string filename)
{
float threat = 0;
float roll = .2f;
Console.Write($"Classifier Demo\n");
Network net = Parser.parse_network_cfg(cfgfile);
if (string.IsNullOrEmpty(weightfile))
{
Parser.load_weights(net, weightfile);
}
Network.set_batch_network(net, 1);
var options = OptionList.read_data_cfg(datacfg);
Utils.Rand = new Random(2222222);
using (VideoCapture cap = !string.IsNullOrEmpty(filename)
? new VideoCapture(filename)
: new VideoCapture(camIndex))
{
int top = OptionList.option_find_int(options, "top", 1);
string nameList = OptionList.option_find_str(options, "names", "");
string[] names = Data.Data.get_labels(nameList);
int[] indexes = new int[top];
if (!cap.IsOpened)
{
Utils.Error("Couldn't connect to webcam.\n");
}
float fps = 0;
int i;
int count = 0;
while (true)
{
++count;
var sw = new Stopwatch();
sw.Start();
Image ini = LoadArgs.get_image_from_stream(cap);
if (ini.Data.Length == 0)
{
break;
}
Image inS = LoadArgs.resize_image(ini, net.W, net.H);
Image outo = ini;
int x1 = outo.W / 20;
int y1 = outo.H / 20;
int x2 = 2 * x1;
int y2 = outo.H - outo.H / 20;
int border = (int)(.01f * outo.H);
int h = y2 - y1 - 2 * border;
int w = x2 - x1 - 2 * border;
float[] predictions = Network.network_predict(net, inS.Data);
float currThreat = 0;
currThreat = predictions[0] * 0f +
predictions[1] * .6f +
predictions[2];
threat = roll * currThreat + (1 - roll) * threat;
LoadArgs.draw_box_width(outo, x2 + border, (int)(y1 + .02 * h), (int)(x2 + .5 * w), (int)(y1 + .02 * h + border), border, 0, 0,
0);
if (threat > .97)
{
LoadArgs.draw_box_width(outo, (int)(x2 + .5 * w + border),
(int)(y1 + .02 * h - 2 * border),
(int)(x2 + .5 * w + 6 * border),
(int)(y1 + .02 * h + 3 * border), 3 * border, 1, 0, 0);
}
LoadArgs.draw_box_width(outo, (int)(x2 + .5 * w + border),
(int)(y1 + .02 * h - 2 * border),
(int)(x2 + .5 * w + 6 * border),
(int)(y1 + .02 * h + 3 * border), (int)(.5 * border), 0, 0, 0);
LoadArgs.draw_box_width(outo, x2 + border, (int)(y1 + .42 * h), (int)(x2 + .5 * w), (int)(y1 + .42 * h + border), border, 0, 0,
0);
if (threat > .57)
{
LoadArgs.draw_box_width(outo, (int)(x2 + .5 * w + border),
(int)(y1 + .42 * h - 2 * border),
(int)(x2 + .5 * w + 6 * border),
(int)(y1 + .42 * h + 3 * border), 3 * border, 1, 1, 0);
}
LoadArgs.draw_box_width(outo, (int)(x2 + .5 * w + border),
(int)(y1 + .42 * h - 2 * border),
(int)(x2 + .5 * w + 6 * border),
(int)(y1 + .42 * h + 3 * border), (int)(.5 * border), 0, 0, 0);
LoadArgs.draw_box_width(outo, x1, y1, x2, y2, border, 0, 0, 0);
for (i = 0; i < threat * h; ++i)
{
float ratio = (float)i / h;
float r = (ratio < .5f) ? (2 * (ratio)) : 1;
float g = (ratio < .5f) ? 1 : 1 - 2 * (ratio - .5f);
LoadArgs.draw_box_width(outo, x1 + border, y2 - border - i, x2 - border, y2 - border - i, 1, r, g, 0);
}
Network.top_predictions(net, top, indexes);
string buff = $"/home/pjreddie/tmp/threat_{count:06}";
Console.Write($"\033[2J");
Console.Write($"\033[1;1H");
Console.Write($"\nFPS:%.0f\n", fps);
for (i = 0; i < top; ++i)
{
int index = indexes[i];
Console.Write($"%.1f%%: %s\n", predictions[index] * 100, names[index]);
}
LoadArgs.show_image(outo, "Threat");
CvInvoke.WaitKey(10);
sw.Stop();
float curr = 1000.0f / sw.ElapsedMilliseconds;
fps = .9f * fps + .1f * curr;
}
}
}
private static void demo_classifier(string datacfg, string cfgfile, string weightfile, int camIndex, string filename)
{
Console.Write($"Classifier Demo\n");
Network net = Parser.parse_network_cfg(cfgfile);
if (string.IsNullOrEmpty(weightfile))
{
Parser.load_weights(net, weightfile);
}
Network.set_batch_network(net, 1);
var options = OptionList.read_data_cfg(datacfg);
Utils.Rand = new Random(2222222);
using (VideoCapture cap = !string.IsNullOrEmpty(filename)
? new VideoCapture(filename)
: new VideoCapture(camIndex))
{
int top = OptionList.option_find_int(options, "top", 1);
string nameList = OptionList.option_find_str(options, "names", "");
string[] names = Data.Data.get_labels(nameList);
int[] indexes = new int[top];
if (cap != null)
{
Utils.Error("Couldn't connect to webcam.\n");
}
float fps = 0;
int i;
while (true)
{
var sw = new Stopwatch();
sw.Start();
Image ini = LoadArgs.get_image_from_stream(cap);
Image inS = LoadArgs.resize_image(ini, net.W, net.H);
LoadArgs.show_image(ini, "Classifier");
float[] predictions = Network.network_predict(net, inS.Data);
if (net.Hierarchy != null)
{
net.Hierarchy.Hierarchy_predictions(predictions, 0, net.Outputs, true);
}
Network.top_predictions(net, top, indexes);
Console.Write($"\033[2J");
Console.Write($"\033[1;1H");
Console.Write($"\nFPS:%.0f\n", fps);
for (i = 0; i < top; ++i)
{
int index = indexes[i];
Console.Write($"%.1f%%: %s\n", predictions[index] * 100, names[index]);
}
CvInvoke.WaitKey(10);
sw.Stop();
float curr = 1000.0f / sw.ElapsedMilliseconds;
fps = .9f * fps + .1f * curr;
}
}
}
