public List <Item> Run(int frameIndex, List <Item> ltDNNItemList, List <Tuple <string, int[]> > lines, Dictionary <string, int> category, ref long teleCountsHeavyDNN, bool savePictures = false)
{
if (ltDNNItemList == null)
{
return(null);
}
List <Item> ccDNNItem = new List <Item>();
foreach (Item ltDNNItem in ltDNNItemList)
{
if (ltDNNItem.Confidence >= DNNConfig.CONFIDENCE_THRESHOLD)
{
ccDNNItem.Add(ltDNNItem);
continue;
}
else
{
List <Item> analyzedTrackingItems = null;
Console.WriteLine("** Calling Heavy DNN **");
analyzedTrackingItems = frameDNNOnnxYolo.Run(Cv2.ImDecode(ltDNNItem.RawImageData, ImreadModes.Color), frameIndex, category, System.Drawing.Brushes.Yellow, ltDNNItem.TriggerLineID, DNNConfig.MIN_SCORE_FOR_LINEBBOX_OVERLAP_LARGE);
teleCountsHeavyDNN++;
// object detected by heavy YOLO
if (analyzedTrackingItems != null)
{
foreach (Item item in analyzedTrackingItems)
{
item.RawImageData = ltDNNItem.RawImageData;
item.TriggerLine = ltDNNItem.TriggerLine;
item.TriggerLineID = ltDNNItem.TriggerLineID;
item.Model = "Heavy";
ccDNNItem.Add(item);
// output heavy YOLO results
if (savePictures)
{
string blobName_Heavy = $@"frame-{frameIndex}-Heavy-{item.Confidence}.jpg";
string fileName_Heavy = @OutputFolder.OutputFolderCcDNN + blobName_Heavy;
File.WriteAllBytes(fileName_Heavy, item.TaggedImageData);
File.WriteAllBytes(@OutputFolder.OutputFolderAll + blobName_Heavy, item.TaggedImageData);
}
return(ccDNNItem); // if we only return the closest object detected by heavy model
}
}
else
{
Console.WriteLine("** Not detected by Heavy DNN **");
}
}
}
return(ccDNNItem);
}
public List <Item> Run(Mat frame, int frameIndex, Dictionary <string, int> counts, List <Tuple <string, int[]> > lines, Dictionary <string, int> category, ref long teleCountsCheapDNN, bool savePictures = false)
{
// buffer frame
frameBufferLtDNNOnnxYolo.Buffer(frame);
if (counts_prev.Count != 0)
{
foreach (string lane in counts.Keys)
{
int diff = Math.Abs(counts[lane] - counts_prev[lane]);
if (diff > 0) //object detected by BGS
{
if (frameIndex >= DNNConfig.FRAME_SEARCH_RANGE)
{
// call onnx cheap model for crosscheck
int lineID = Array.IndexOf(counts.Keys.ToArray(), lane);
Mat[] frameBufferArray = frameBufferLtDNNOnnxYolo.ToArray();
int frameIndexOnnxYolo = frameIndex - 1;
List <Item> analyzedTrackingItems = null;
while (frameIndex - frameIndexOnnxYolo < DNNConfig.FRAME_SEARCH_RANGE)
{
Console.WriteLine("** Calling DNN on " + (DNNConfig.FRAME_SEARCH_RANGE - (frameIndex - frameIndexOnnxYolo)));
Mat frameOnnx = frameBufferArray[DNNConfig.FRAME_SEARCH_RANGE - (frameIndex - frameIndexOnnxYolo)];
analyzedTrackingItems = frameDNNOnnxYolo.Run(frameOnnx, (DNNConfig.FRAME_SEARCH_RANGE - (frameIndex - frameIndexOnnxYolo)), category, System.Drawing.Brushes.Pink, lineID, DNNConfig.MIN_SCORE_FOR_LINEBBOX_OVERLAP_LARGE);
teleCountsCheapDNN++;
// object detected by cheap model
if (analyzedTrackingItems != null)
{
List <Item> ltDNNItem = new List <Item>();
foreach (Item item in analyzedTrackingItems)
{
item.RawImageData = Utils.Utils.ImageToByteBmp(OpenCvSharp.Extensions.BitmapConverter.ToBitmap(frameOnnx));
item.TriggerLine = lane;
item.TriggerLineID = lineID;
item.Model = "Cheap";
ltDNNItem.Add(item);
// output cheap onnx results
if (savePictures)
{
string blobName_Cheap = $@"frame-{frameIndex}-DNN-{item.Confidence}.jpg";
string fileName_Cheap = @OutputFolder.OutputFolderLtDNN + blobName_Cheap;
File.WriteAllBytes(fileName_Cheap, item.TaggedImageData);
File.WriteAllBytes(@OutputFolder.OutputFolderAll + blobName_Cheap, item.TaggedImageData);
}
}
updateCount(counts);
return(ltDNNItem);
}
frameIndexOnnxYolo--;
}
}
}
}
}
updateCount(counts);
return(null);
}
