fix bug with annotation result gradient stops

add tensorrt engine

Azaion.Annotator/Annotator.xaml

@@ -8,6 +8,7 @@
         xmlns:controls1="clr-namespace:Azaion.Common.Controls;assembly=Azaion.Common"
         xmlns:controls2="clr-namespace:Azaion.Annotator.Controls;assembly=Azaion.Common"
         mc:Ignorable="d"
+        xmlns:local="clr-namespace:Azaion.Annotator"
         Title="Azaion Annotator" Height="800" Width="1100"
         WindowState="Maximized"
         >
@@ -49,6 +50,8 @@
                 </Trigger>
             </Style.Triggers>
         </Style>
+
+        <local:GradientStyleSelector x:Key="GradientStyleSelector"/>
     </Window.Resources>
 
     <Grid Name="GlobalGrid"
@@ -232,7 +235,6 @@
                       Grid.Row="1"
                       Grid.RowSpan="4"
                       Background="Black"
-                      RowBackground="#252525"
                       Foreground="White"
                       RowHeaderWidth="0"
                       Padding="2 0 0 0"
@@ -241,7 +243,8 @@
                       CellStyle="{DynamicResource DataGridCellStyle1}"
                       IsReadOnly="True"
                       CanUserResizeRows="False"
-                      CanUserResizeColumns="False">
+                      CanUserResizeColumns="False"
+                      RowStyleSelector="{StaticResource GradientStyleSelector}">
                 <DataGrid.Columns>
                     <DataGridTextColumn
                         Width="60"
@@ -264,20 +267,6 @@
                                 <Setter Property="Background" Value="#252525"></Setter>
                             </Style>
                         </DataGridTextColumn.HeaderStyle>
-                        <DataGridTextColumn.CellStyle>
-                            <Style TargetType="DataGridCell">
-                                <Setter Property="Background">
-                                    <Setter.Value>
-                                         <LinearGradientBrush StartPoint="0 0 " EndPoint="1 0">
-                                             <GradientStop Offset="0.3" Color="{Binding Path=ClassColor0}" />
-                                             <GradientStop Offset="0.5" Color="{Binding Path=ClassColor1}" />
-                                             <GradientStop Offset="0.8" Color="{Binding Path=ClassColor2}" />
-                                             <GradientStop Offset="0.99" Color="{Binding Path=ClassColor3}" />
-                                         </LinearGradientBrush>
-                                    </Setter.Value>
-                                </Setter>
-                            </Style>
-                        </DataGridTextColumn.CellStyle>
                     </DataGridTextColumn>
                 </DataGrid.Columns>
             </DataGrid>

Azaion.Annotator/Annotator.xaml.cs

@@ -328,7 +328,11 @@ public partial class Annotator
 
         var existingResult = _formState.AnnotationResults.FirstOrDefault(x => x.Annotation.Time == time);
         if (existingResult != null)
+        {
+            _logger.LogInformation($"remove annotation {existingResult.TimeStr} {existingResult.ClassName}!");
             _formState.AnnotationResults.Remove(existingResult);
+        }
+
 
         var dict = _formState.AnnotationResults
             .Select((x, i) => new { x.Annotation.Time, Index = i })
@@ -339,7 +343,8 @@ public partial class Annotator
             .Select(x => x.Value + 1)
             .FirstOrDefault();
 
-        _formState.AnnotationResults.Insert(index, new AnnotationResult(_appConfig.AnnotationConfig.DetectionClassesDict, annotation));
+        var annRes = new AnnotationResult(_appConfig.AnnotationConfig.DetectionClassesDict, annotation);
+        _formState.AnnotationResults.Insert(index, annRes);
     }
 
     private async Task ReloadFiles()
@@ -565,6 +570,7 @@ public partial class Annotator
                         await _mediator.Publish(new AnnotatorControlEvent(PlaybackControlEnum.Play), ct);
                     }
                 }
+
                 AddAnnotation(annotation);
 
                 if (FollowAI)
@@ -574,7 +580,7 @@ public partial class Annotator
                     $"{_appConfig.AnnotationConfig.DetectionClassesDict[det.ClassNumber].Name}: " +
                     $"xy=({det.CenterX:F2},{det.CenterY:F2}), " +
                     $"size=({det.Width:F2}, {det.Height:F2}), " +
-                    $"prob: {det.Probability*100:F0}%"));
+                    $"conf: {det.Confidence*100:F0}%"));
 
                 Dispatcher.Invoke(() =>
                 {
@@ -618,3 +624,42 @@ public partial class Annotator
         throw new NotImplementedException();
     }
 }
+
+public class GradientStyleSelector : StyleSelector
+{
+    public override Style? SelectStyle(object item, DependencyObject container)
+    {
+        if (container is not DataGridRow row || row.DataContext is not AnnotationResult result)
+            return null;
+
+        var style = new Style(typeof(DataGridRow));
+        var brush = new LinearGradientBrush
+        {
+            StartPoint = new Point(0, 0),
+            EndPoint = new Point(1, 0)
+        };
+
+        var gradients = new List<GradientStop>();
+        if (result.Colors.Count != 0)
+        {
+            var color = (Color)ColorConverter.ConvertFromString("#40DDDDDD");
+            gradients = [new GradientStop(color, 0.99)];
+        }
+        else
+        {
+            var increment = 1.0 / result.Colors.Count;
+            var currentStop = increment;
+            foreach (var c in result.Colors)
+            {
+                var resultColor = c.Color.ToConfidenceColor(c.Confidence);
+                brush.GradientStops.Add(new GradientStop(resultColor, currentStop));
+                currentStop += increment;
+            }
+        }
+        foreach (var gradientStop in gradients)
+            brush.GradientStops.Add(gradientStop);
+
+        style.Setters.Add(new Setter(DataGridRow.BackgroundProperty, brush));
+        return style;
+    }
+}

Azaion.Annotator/Controls/MapMatcher.xaml.cs

@@ -38,16 +38,19 @@ public partial class MapMatcher : UserControl
         SatelliteMap.Position = new PointLatLng(48.295985271707664, 37.14477539062501);
         SatelliteMap.MultiTouchEnabled = true;
 
-        GpsFiles.MouseDoubleClick += async (sender, args) =>
+        GpsFiles.MouseDoubleClick += async (sender, args) => { await OpenGpsLocation(GpsFiles.SelectedIndex); };
+    }
+
+    private async Task OpenGpsLocation(int gpsFilesIndex)
+    {
+        var media = GpsFiles.Items[gpsFilesIndex] as MediaFileInfo;
+        var ann = _annotations.GetValueOrDefault(Path.GetFileNameWithoutExtension(media.Name));
+        GpsImageEditor.Background = new ImageBrush
         {
-            var media = (GpsFiles.SelectedItem as MediaFileInfo)!;
+            ImageSource = await Path.Combine(_currentDir, ann.Name).OpenImage()
-            var ann = _annotations.GetValueOrDefault(Path.GetFileNameWithoutExtension(media.Name));
-            GpsImageEditor.Background = new ImageBrush
-            {
-                ImageSource = await Path.Combine(_currentDir, ann.Name).OpenImage()
-            };
-            SatelliteMap.Position = new PointLatLng(ann.Lat, ann.Lon);
         };
+        if (ann.Lat != 0 && ann.Lon != 0)
+            SatelliteMap.Position = new PointLatLng(ann.Lat, ann.Lon);
     }
 
     private void GpsFilesContextOpening(object sender, ContextMenuEventArgs e)
@@ -104,8 +107,11 @@ public partial class MapMatcher : UserControl
         _allMediaFiles = mediaFiles;
         GpsFiles.ItemsSource = new ObservableCollection<MediaFileInfo>(_allMediaFiles);
         var annotations = SetFromCsv(mediaFiles);
+        Cursor = Cursors.Wait;
         await Task.Delay(TimeSpan.FromSeconds(10));
         SetMarkers(annotations);
+        Cursor = Cursors.Arrow;
+        await OpenGpsLocation(0);
     }
 
     private Dictionary<string, Annotation> SetFromCsv(List<MediaFileInfo> mediaFiles)
@@ -117,7 +123,9 @@ public partial class MapMatcher : UserControl
         }).ToDictionary(x => Path.GetFileNameWithoutExtension(x.OriginalMediaName));
 
         var csvResults = GpsCsvResult.ReadFromCsv(Constants.CSV_PATH);
-        var csvDict = csvResults.ToDictionary(x => x.Image);
+        var csvDict = csvResults
+            .Where(x => x.MatchType == "stitched")
+            .ToDictionary(x => x.Image);
         foreach (var ann in _annotations)
         {
             var csvRes = csvDict.GetValueOrDefault(ann.Key);
@@ -137,7 +145,7 @@ public partial class MapMatcher : UserControl
 
         var firstAnnotation = annotations.FirstOrDefault();
         SatelliteMap.Position = new PointLatLng(firstAnnotation.Value.Lat, firstAnnotation.Value.Lon);
-        foreach (var ann in annotations)
+        foreach (var ann in annotations.Where(x => x.Value.Lat != 0 && x.Value.Lon != 0))
         {
             var marker = new GMapMarker(new PointLatLng(ann.Value.Lat, ann.Value.Lon));
             var circle =  new CircleVisual(marker, System.Windows.Media.Brushes.Blue)
@@ -147,6 +155,6 @@ public partial class MapMatcher : UserControl
             marker.Shape = circle;
             SatelliteMap.Markers.Add(marker);
         }
-
+        SatelliteMap.ZoomAndCenterMarkers(null);
     }
 }

Azaion.Common/Constants.cs

@@ -90,5 +90,5 @@ public class Constants
 
     #endregion
 
-    public const string CSV_PATH = "D:\\matches.csv";
+    public const string CSV_PATH = "matches.csv";
 }

Azaion.Common/Controls/CanvasEditor.cs

@@ -54,7 +54,7 @@ public class CanvasEditor : Canvas
             _verticalLine.Fill = value.ColorBrush;
             _horizontalLine.Stroke = value.ColorBrush;
             _horizontalLine.Fill = value.ColorBrush;
-            _classNameHint.Text = value.Name;
+            _classNameHint.Text = value.ShortName;
             
             _newAnnotationRect.Stroke = value.ColorBrush;
             _newAnnotationRect.Fill = value.ColorBrush;
@@ -84,7 +84,7 @@ public class CanvasEditor : Canvas
         };
         _classNameHint = new TextBlock
         {
-            Text = CurrentAnnClass?.Name ?? "asd",
+            Text = CurrentAnnClass?.ShortName ?? "",
             Foreground = new SolidColorBrush(Colors.Black),
             Cursor = Cursors.Arrow,
             FontSize = 16,
@@ -313,14 +313,14 @@ public class CanvasEditor : Canvas
         foreach (var detection in detections)
         {
             var annClass = DetectionClass.FromYoloId(detection.ClassNumber, detectionClasses);
-            var canvasLabel = new CanvasLabel(detection, RenderSize, videoSize, detection.Probability);
+            var canvasLabel = new CanvasLabel(detection, RenderSize, videoSize, detection.Confidence);
             CreateDetectionControl(annClass, time, canvasLabel);
         }
     }
 
     private void CreateDetectionControl(DetectionClass annClass, TimeSpan time, CanvasLabel canvasLabel)
     {
-        var detectionControl = new DetectionControl(annClass, time, AnnotationResizeStart, canvasLabel.Probability)
+        var detectionControl = new DetectionControl(annClass, time, AnnotationResizeStart, canvasLabel.Confidence)
         {
             Width = canvasLabel.Width,
             Height = canvasLabel.Height

Azaion.Common/Controls/DetectionClasses.xaml

@@ -68,7 +68,7 @@
             </DataTemplate>
           </DataGridTemplateColumn.CellTemplate>
         </DataGridTemplateColumn>
-        <DataGridTextColumn Width="*" Header="Назва" Binding="{Binding Path=Name}" CanUserSort="False">
+        <DataGridTextColumn Width="*" Header="Назва" Binding="{Binding Path=ShortName}" CanUserSort="False">
           <DataGridTextColumn.HeaderStyle>
             <Style TargetType="DataGridColumnHeader">
               <Setter Property="Background" Value="#252525"/>

Azaion.Common/DTO/AnnotationResult.cs

@@ -1,52 +1,33 @@
 using System.Windows.Media;
 using Azaion.Common.Database;
-using Azaion.Common.Extensions;
-using Newtonsoft.Json;
 
 namespace Azaion.Common.DTO;
 
 public class AnnotationResult
 {
     public Annotation Annotation { get; set; }
+    public List<(Color Color, double Confidence)> Colors { get; private set; }
 
     public string           ImagePath   { get; set; }
     public string           TimeStr     { get; set; }
-
     public string           ClassName   { get; set; }
 
-    public Color            ClassColor0 { get; set; }
-    public Color            ClassColor1 { get; set; }
-    public Color            ClassColor2 { get; set; }
-    public Color            ClassColor3 { get; set; }
-
-
     public AnnotationResult(Dictionary<int, DetectionClass> allDetectionClasses, Annotation annotation)
     {
+
         Annotation = annotation;
-        var detections = annotation.Detections.ToList();
-
-        Color GetAnnotationClass(List<int> detectionClasses, int colorNumber)
-        {
-            if (detections.Count == 0)
-                return (-1).ToColor();
-
-            return colorNumber >= detectionClasses.Count
-                ? allDetectionClasses[detectionClasses.LastOrDefault()].Color
-                : allDetectionClasses[detectionClasses[colorNumber]].Color;
-        }
 
         TimeStr = $"{annotation.Time:h\\:mm\\:ss}";
         ImagePath = annotation.ImagePath;
 
-        var detectionClasses = detections.Select(x => x.ClassNumber).Distinct().ToList();
+        var detectionClasses = annotation.Detections.Select(x => x.ClassNumber).Distinct().ToList();
+
+        Colors = annotation.Detections
+            .Select(d => (allDetectionClasses[d.ClassNumber].Color, d.Confidence))
+            .ToList();
 
         ClassName = detectionClasses.Count > 1
             ? string.Join(", ", detectionClasses.Select(x => allDetectionClasses[x].UIName))
             : allDetectionClasses[detectionClasses.FirstOrDefault()].UIName;
-
-        ClassColor0 = GetAnnotationClass(detectionClasses, 0);
-        ClassColor1 = GetAnnotationClass(detectionClasses, 1);
-        ClassColor2 = GetAnnotationClass(detectionClasses, 2);
-        ClassColor3 = GetAnnotationClass(detectionClasses, 3);
     }
 }

Azaion.Common/DTO/Config/AnnotationConfig.cs

@@ -23,6 +23,7 @@ public class AnnotationConfig
                 {
                     Id = cls.Id,
                     Name = cls.Name,
+                    Color = cls.Color,
                     ShortName = cls.ShortName,
                     PhotoMode = mode
                 }))

Azaion.Common/DTO/DetectionClass.cs

@@ -1,5 +1,4 @@
 using System.Windows.Media;
-using Azaion.Common.Extensions;
 using Newtonsoft.Json;
 
 namespace Azaion.Common.DTO;
@@ -11,6 +10,8 @@ public class DetectionClass
     public string Name { get; set; } = null!;
     public string ShortName { get; set; } = null!;
 
+    public Color Color { get; set; }
+
     [JsonIgnore]
     public string UIName
     {
@@ -31,9 +32,6 @@ public class DetectionClass
     [JsonIgnore]
     public PhotoMode PhotoMode { get; set; }
 
-    [JsonIgnore]
-    public Color Color => Id.ToColor();
-
     [JsonIgnore] //For UI
     public int ClassNumber => Id + 1;
 

Azaion.Common/DTO/Label.cs

@@ -26,22 +26,22 @@ public class CanvasLabel : Label
     public double Y { get; set; }
     public double Width { get; set; }
     public double Height { get; set; }
-    public double? Probability { get; }
+    public double? Confidence { get; }
 
     public CanvasLabel()
     {
     }
 
-    public CanvasLabel(int classNumber, double x, double y, double width, double height, double? probability = null) : base(classNumber)
+    public CanvasLabel(int classNumber, double x, double y, double width, double height, double? confidence = null) : base(classNumber)
     {
         X = x;
         Y = y;
         Width = width;
         Height = height;
-        Probability = probability;
+        Confidence = confidence;
     }
 
-    public CanvasLabel(YoloLabel label, Size canvasSize, Size? videoSize = null, double? probability = null)
+    public CanvasLabel(YoloLabel label, Size canvasSize, Size? videoSize = null, double confidence = 1)
     {
         var cw = canvasSize.Width;
         var ch = canvasSize.Height;
@@ -75,7 +75,7 @@ public class CanvasLabel : Label
             Width = label.Width * realWidth;
             Height = label.Height * ch;
         }
-        Probability = probability;
+        Confidence = confidence;
     }
 }
 
@@ -189,12 +189,12 @@ public class YoloLabel : Label
 public class Detection : YoloLabel
 {
     [JsonProperty(PropertyName = "an")][Key("an")] public string AnnotationName { get; set; } = null!;
-    [JsonProperty(PropertyName = "p")][Key("p")]  public double? Probability { get; set; }
+    [JsonProperty(PropertyName = "p")][Key("p")]  public double  Confidence { get; set; }
 
     //For db & serialization
     public Detection(){}
 
-    public Detection(string annotationName, YoloLabel label, double? probability = null)
+    public Detection(string annotationName, YoloLabel label, double confidence = 1)
     {
         AnnotationName = annotationName;
         ClassNumber = label.ClassNumber;
@@ -202,6 +202,6 @@ public class Detection : YoloLabel
         CenterY = label.CenterY;
         Height = label.Height;
         Width = label.Width;
-        Probability = probability;
+        Confidence = confidence;
     }
 }

Azaion.Common/Extensions/ColorExtensions.cs

@@ -4,25 +4,12 @@ namespace Azaion.Common.Extensions;
 
 public static class ColorExtensions
 {
-    public static Color ToColor(this int id)
+    private const int MIN_ALPHA = 20;
+    private const int MAX_ALPHA = 100;
+
+    public static Color ToConfidenceColor(this Color color, double confidence )
     {
-        var index = id % ColorValues.Length;
+        color.A = (byte)(MIN_ALPHA + (int)Math.Round(confidence * (MAX_ALPHA - MIN_ALPHA)));
-        var hex = index == -1
-            ? "#40DDDDDD"
-            : $"#40{ColorValues[index]}";
-        var color =(Color)ColorConverter.ConvertFromString(hex);
         return color;
     }
-    
-    private static readonly string[] ColorValues =
-    [
-        "FF0000", "00FF00", "0000FF", "FFFF00", "FF00FF", "00FFFF", "000000",
-        "800000", "008000", "000080", "808000", "800080", "008080", "808080", 
-        "C00000", "00C000", "0000C0", "C0C000", "C000C0", "00C0C0", "C0C0C0", 
-        "400000", "004000", "000040", "404000", "400040", "004040", "404040", 
-        "200000", "002000", "000020", "202000", "200020", "002020", "202020", 
-        "600000", "006000", "000060", "606000", "600060", "006060", "606060", 
-        "A00000", "00A000", "0000A0", "A0A000", "A000A0", "00A0A0", "A0A0A0", 
-        "E00000", "00E000", "0000E0", "E0E000", "E000E0", "00E0E0", "E0E0E0"
-    ];
 }

Azaion.CommonSecurity/DTO/ExternalClientsConfig.cs

@@ -13,4 +13,7 @@ public class InferenceClientConfig : ExternalClientConfig
     public string ResourcesFolder { get; set; } = "";
 }
 
-public class GpsDeniedClientConfig : ExternalClientConfig;
+public class GpsDeniedClientConfig : ExternalClientConfig
+{
+    public int ZeroMqReceiverPort { get; set; }
+}

Azaion.CommonSecurity/Services/ExternalClient.cs

@@ -40,7 +40,7 @@ public abstract class BaseZeroMqExternalClient : IExternalClient
             using var process = new Process();
             process.StartInfo = new ProcessStartInfo
             {
-                FileName = ClientPath
+                FileName = ClientPath,
                 //Arguments = $"-e {credentials.Email} -p {credentials.Password} -f {apiConfig.ResourcesFolder}",
                 //RedirectStandardOutput = true,
                 //RedirectStandardError = true,

Azaion.CommonSecurity/Services/HardwareService.cs

@@ -14,9 +14,11 @@ public interface IHardwareService
 public class HardwareService : IHardwareService
 {
     private const string WIN32_GET_HARDWARE_COMMAND =
-        "wmic OS get TotalVisibleMemorySize /Value && " +
+        "powershell -Command \"" +
-        "wmic CPU get Name /Value && " +
+        "Get-CimInstance -ClassName Win32_Processor | Select-Object -ExpandProperty Name | Write-Output; " +
-        "wmic path Win32_VideoController get Name /Value";
+        "Get-CimInstance -ClassName Win32_VideoController | Select-Object -ExpandProperty Name | Write-Output; " +
+        "Get-CimInstance -ClassName Win32_OperatingSystem | Select-Object -ExpandProperty TotalVisibleMemorySize | Write-Output" +
+        "\"";
 
     private const string UNIX_GET_HARDWARE_COMMAND =
         "/bin/bash -c \"free -g | grep Mem: | awk '{print $2}' && " +

Azaion.Dataset/DatasetExplorer.xaml.cs

@@ -77,11 +77,11 @@ public partial class DatasetExplorer
                     await DeleteAnnotations();
                     break;
                 case Key.Enter:
-                    await EditAnnotation();
+                    await EditAnnotation(ThumbnailsView.SelectedIndex);
                     break;
             }
         };
-        ThumbnailsView.MouseDoubleClick += async (_, _) => await EditAnnotation();
+        ThumbnailsView.MouseDoubleClick += async (_, _) => await EditAnnotation(ThumbnailsView.SelectedIndex);
 
         ThumbnailsView.SelectionChanged += (_, _) =>
         {
@@ -152,7 +152,7 @@ public partial class DatasetExplorer
             .Select(gr => new
             {
                 gr.Key,
-                _annotationConfig.DetectionClassesDict[gr.Key].Name,
+                _annotationConfig.DetectionClassesDict[gr.Key].ShortName,
                 _annotationConfig.DetectionClassesDict[gr.Key].Color,
                 ClassCount = gr.Value.Count
             })
@@ -175,7 +175,7 @@ public partial class DatasetExplorer
 
         foreach (var x in data)
         {
-            var label = ClassDistribution.Plot.Add.Text(x.Name, 50, -1.5 * x.Key + 1.1);
+            var label = ClassDistribution.Plot.Add.Text(x.ShortName, 50, -1.5 * x.Key + 1.1);
             label.LabelFontColor = foregroundColor;
             label.LabelFontSize = 18;
         }
@@ -204,16 +204,17 @@ public partial class DatasetExplorer
         RefreshThumbnailsButtonItem.Visibility = Visibility.Visible;
     }
 
-    private async Task EditAnnotation()
+    public async Task EditAnnotation(int index)
     {
         try
         {
             ThumbnailLoading = true;
-
+            if (index == -1)
-            if (ThumbnailsView.SelectedItem == null)
                 return;
 
-            CurrentAnnotation = (ThumbnailsView.SelectedItem as AnnotationThumbnail)!;
+            CurrentAnnotation = (ThumbnailsView.Items[index] as AnnotationThumbnail)!;
+            ThumbnailsView.SelectedIndex = index;
+
             var ann = CurrentAnnotation.Annotation;
             ExplorerEditor.Background = new ImageBrush
             {
@@ -224,7 +225,6 @@ public partial class DatasetExplorer
             var time = ann.Time;
             ExplorerEditor.RemoveAllAnns();
             ExplorerEditor.CreateDetections(time, ann.Detections, _annotationConfig.DetectionClasses, ExplorerEditor.RenderSize);
-            ThumbnailLoading = false;
         }
         catch (Exception e)
         {
@@ -233,7 +233,11 @@ public partial class DatasetExplorer
         }
         finally
         {
-            ThumbnailLoading = false;
+            _ = Task.Run(async () =>
+            {
+                await Task.Delay(100);
+                ThumbnailLoading = false;
+            });
         }
 
     }
@@ -260,7 +264,7 @@ public partial class DatasetExplorer
         }
     }
 
-    private async Task DeleteAnnotations()
+    public async Task DeleteAnnotations()
     {
         var tempSelected = ThumbnailsView.SelectedIndex;
         var result = MessageBox.Show("Чи дійсно видалити аннотації?","Підтвердження видалення", MessageBoxButton.YesNo, MessageBoxImage.Question);

Azaion.Dataset/DatasetExplorerEventHandler.cs

@@ -1,4 +1,5 @@
 using System.IO;
+using System.Windows;
 using System.Windows.Input;
 using Azaion.Common.DTO;
 using Azaion.Common.DTO.Queue;
@@ -22,7 +23,9 @@ public class DatasetExplorerEventHandler(
         { Key.Delete, PlaybackControlEnum.RemoveSelectedAnns },
         { Key.X, PlaybackControlEnum.RemoveAllAnns },
         { Key.Escape, PlaybackControlEnum.Close },
-        { Key.V, PlaybackControlEnum.ValidateAnnotations}
+        { Key.Down, PlaybackControlEnum.Next },
+        { Key.Up, PlaybackControlEnum.Previous },
+        { Key.V, PlaybackControlEnum.ValidateAnnotations},
     };
 
     public async Task Handle(DatasetExplorerControlEvent notification, CancellationToken cancellationToken)
@@ -63,15 +66,28 @@ public class DatasetExplorerEventHandler(
                 var detections = datasetExplorer.ExplorerEditor.CurrentDetections
                     .Select(x => new Detection(a.Name, x.GetLabel(datasetExplorer.ExplorerEditor.RenderSize)))
                     .ToList();
+                var index = datasetExplorer.ThumbnailsView.SelectedIndex;
                 await annotationService.SaveAnnotation(a.OriginalMediaName, a.Time, detections, SourceEnum.Manual, token: cancellationToken);
-                datasetExplorer.SwitchTab(toEditor: false);
+                await datasetExplorer.EditAnnotation(index + 1);
                 break;
             case PlaybackControlEnum.RemoveSelectedAnns:
-                datasetExplorer.ExplorerEditor.RemoveSelectedAnns();
+                if (datasetExplorer.ExplorerEditor.CurrentDetections.Any(x => x.IsSelected))
+                    datasetExplorer.ExplorerEditor.RemoveSelectedAnns();
+                else
+                {
+                    await datasetExplorer.DeleteAnnotations();
+                    await datasetExplorer.EditAnnotation(datasetExplorer.ThumbnailsView.SelectedIndex);
+                }
                 break;
             case PlaybackControlEnum.RemoveAllAnns:
                 datasetExplorer.ExplorerEditor.RemoveAllAnns();
                 break;
+            case PlaybackControlEnum.Next:
+                await datasetExplorer.EditAnnotation(datasetExplorer.ThumbnailsView.SelectedIndex + 1);
+                break;
+            case PlaybackControlEnum.Previous:
+                await datasetExplorer.EditAnnotation(datasetExplorer.ThumbnailsView.SelectedIndex - 1);
+                break;
             case PlaybackControlEnum.Close:
                 datasetExplorer.SwitchTab(toEditor: false);
                 break;

Azaion.Inference/README.md

@@ -72,5 +72,5 @@ In case of  fbgemm.dll  error (Windows specific):
 
 <h3>Build exe</h3>
 ```
-    .\build.exe
+    .\build.cmd
 ```

Azaion.Inference/api_client.pxd

@@ -14,4 +14,4 @@ cdef class ApiClient:
 
     cdef load_bytes(self, str filename, str folder=*)
     cdef upload_file(self, str filename, str folder=*)
-    cdef load_ai_model(self)
+    cdef load_ai_model(self, bint is_tensor=*)

Azaion.Inference/api_client.pyx

@@ -73,6 +73,7 @@ cdef class ApiClient:
 
     cdef load_bytes(self, str filename, str folder=None):
         folder = folder or self.credentials.folder
+
         hardware_service = HardwareService()
         cdef HardwareInfo hardware = hardware_service.get_hardware_info()
 
@@ -110,11 +111,20 @@ cdef class ApiClient:
         constants.log(<str>f'Downloaded file: {filename}, {len(data)} bytes')
         return data
 
-    cdef load_ai_model(self):
+    cdef load_ai_model(self, bint is_tensor=False):
-        with open(<str>constants.AI_MODEL_FILE_BIG, 'rb') as binary_file:
+        if is_tensor:
-            encrypted_bytes_big = binary_file.read()
+            big_file = <str> constants.AI_TENSOR_MODEL_FILE_BIG
-        encrypted_bytes_small = self.load_bytes(constants.AI_MODEL_FILE_SMALL)
+            small_file = <str> constants.AI_TENSOR_MODEL_FILE_SMALL
+        else:
+            big_file = <str>constants.AI_ONNX_MODEL_FILE_BIG
+            small_file = <str> constants.AI_ONNX_MODEL_FILE_SMALL
 
+        with open(big_file, 'rb') as binary_file:
+            encrypted_bytes_big = binary_file.read()
+        print('read encrypted big file')
+        print(f'small file: {small_file}')
+        encrypted_bytes_small = self.load_bytes(small_file)
+        print('read encrypted small file')
         encrypted_model_bytes = encrypted_bytes_small + encrypted_bytes_big
         key = Security.get_model_encryption_key()
 

Azaion.Inference/azaion-inference.spec

@@ -0,0 +1,73 @@
+# -*- mode: python ; coding: utf-8 -*-
+from PyInstaller.utils.hooks import collect_all
+
+datas = []
+binaries = []
+hiddenimports = ['constants', 'annotation', 'credentials', 'file_data', 'user', 'security', 'secure_model', 'api_client', 'hardware_service', 'remote_command', 'ai_config', 'inference_engine', 'inference', 'remote_command_handler']
+tmp_ret = collect_all('pyyaml')
+datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
+tmp_ret = collect_all('jwt')
+datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
+tmp_ret = collect_all('requests')
+datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
+tmp_ret = collect_all('psutil')
+datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
+tmp_ret = collect_all('msgpack')
+datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
+tmp_ret = collect_all('zmq')
+datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
+tmp_ret = collect_all('cryptography')
+datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
+tmp_ret = collect_all('cv2')
+datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
+tmp_ret = collect_all('onnxruntime')
+datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
+tmp_ret = collect_all('tensorrt')
+datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
+tmp_ret = collect_all('pycuda')
+datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
+tmp_ret = collect_all('re')
+datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
+
+
+a = Analysis(
+    ['start.py'],
+    pathex=[],
+    binaries=binaries,
+    datas=datas,
+    hiddenimports=hiddenimports,
+    hookspath=[],
+    hooksconfig={},
+    runtime_hooks=[],
+    excludes=[],
+    noarchive=False,
+    optimize=0,
+)
+pyz = PYZ(a.pure)
+
+exe = EXE(
+    pyz,
+    a.scripts,
+    [],
+    exclude_binaries=True,
+    name='azaion-inference',
+    debug=False,
+    bootloader_ignore_signals=False,
+    strip=False,
+    upx=True,
+    console=True,
+    disable_windowed_traceback=False,
+    argv_emulation=False,
+    target_arch=None,
+    codesign_identity=None,
+    entitlements_file=None,
+)
+coll = COLLECT(
+    exe,
+    a.binaries,
+    a.datas,
+    strip=False,
+    upx=True,
+    upx_exclude=[],
+    name='azaion-inference',
+)

Azaion.Inference/build.cmd

@@ -1,4 +1,4 @@
-pyinstaller --onefile ^
+pyinstaller --name=azaion-inference ^
 --collect-all pyyaml ^
 --collect-all jwt ^
 --collect-all requests ^
@@ -8,6 +8,9 @@ pyinstaller --onefile ^
 --collect-all cryptography ^
 --collect-all cv2 ^
 --collect-all onnxruntime ^
+--collect-all tensorrt ^
+--collect-all pycuda ^
+--collect-all re ^
 --hidden-import constants ^
 --hidden-import annotation ^
 --hidden-import credentials ^
@@ -19,6 +22,7 @@ pyinstaller --onefile ^
 --hidden-import hardware_service ^
 --hidden-import remote_command ^
 --hidden-import ai_config ^
+--hidden-import inference_engine ^
 --hidden-import inference ^
 --hidden-import remote_command_handler ^
 start.py

Azaion.Inference/constants.pxd

@@ -6,8 +6,13 @@ cdef str ANNOTATIONS_QUEUE     # Name of the annotations queue in rabbit
 
 cdef str API_URL               # Base URL for the external API
 cdef str QUEUE_CONFIG_FILENAME # queue config filename to load from api
-cdef str AI_MODEL_FILE_BIG     # AI Model file (BIG part)
+
-cdef str AI_MODEL_FILE_SMALL   # AI Model file (small part)
+cdef str AI_ONNX_MODEL_FILE_BIG
+cdef str AI_ONNX_MODEL_FILE_SMALL
+
+cdef str AI_TENSOR_MODEL_FILE_BIG
+cdef str AI_TENSOR_MODEL_FILE_SMALL
+
 
 cdef bytes DONE_SIGNAL
 

Azaion.Inference/constants.pyx

@@ -8,8 +8,12 @@ cdef str ANNOTATIONS_QUEUE = "azaion-annotations"
 
 cdef str API_URL = "https://api.azaion.com"  # Base URL for the external API
 cdef str QUEUE_CONFIG_FILENAME = "secured-config.json"
-cdef str AI_MODEL_FILE_BIG = "azaion.onnx.big"
+
-cdef str AI_MODEL_FILE_SMALL = "azaion.onnx.small"
+cdef str AI_ONNX_MODEL_FILE_BIG = "azaion.onnx.big"
+cdef str AI_ONNX_MODEL_FILE_SMALL = "azaion.onnx.small"
+
+cdef str AI_TENSOR_MODEL_FILE_BIG = "azaion.engine.big"
+cdef str AI_TENSOR_MODEL_FILE_SMALL = "azaion.engine.small"
 
 cdef log(str log_message, bytes client_id=None):
     local_time = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime())

Azaion.Inference/hardware_service.pxd

@@ -5,4 +5,7 @@ cdef class HardwareInfo:
 cdef class HardwareService:
     cdef bint is_windows
     cdef get_mac_address(self, interface=*)
+
+    @staticmethod
+    cdef has_nvidia_gpu()
     cdef HardwareInfo get_hardware_info(self)

Azaion.Inference/hardware_service.pyx

@@ -1,3 +1,4 @@
+import re
 import subprocess
 import psutil
 
@@ -42,6 +43,18 @@ cdef class HardwareService:
                         return addr.address.replace('-', '')
         return None
 
+    @staticmethod
+    cdef has_nvidia_gpu():
+        try:
+            output = subprocess.check_output(['nvidia-smi']).decode()
+            match = re.search(r'CUDA Version:\s*([\d.]+)', output)
+            if match:
+                return float(match.group(1)) > 11
+            return False
+        except Exception as e:
+            print(e)
+            return False
+
     cdef HardwareInfo get_hardware_info(self):
         if self.is_windows:
             os_command = (

Azaion.Inference/inference.pxd

@@ -2,10 +2,11 @@ from remote_command cimport RemoteCommand
 from annotation cimport Annotation, Detection
 from ai_config cimport AIRecognitionConfig
 from api_client cimport ApiClient
+from inference_engine cimport InferenceEngine
 
 cdef class Inference:
     cdef ApiClient api_client
-    cdef object session
+    cdef InferenceEngine engine
     cdef object on_annotation
     cdef Annotation _previous_annotation
     cdef AIRecognitionConfig ai_config

Azaion.Inference/inference.pyx

@@ -1,40 +1,40 @@
 import json
 import mimetypes
+import subprocess
 
 import cv2
 import numpy as np
-import onnxruntime as onnx
-
-cimport constants
 from remote_command cimport RemoteCommand
 from annotation cimport Detection, Annotation
 from ai_config cimport AIRecognitionConfig
+from inference_engine cimport OnnxEngine, TensorRTEngine
+from hardware_service cimport HardwareService
 
 cdef class Inference:
     def __init__(self, api_client, on_annotation):
         self.api_client = api_client
         self.on_annotation = on_annotation
         self.stop_signal = False
-        self.session = None
         self.model_input = None
         self.model_width = 0
         self.model_height = 0
+        self.engine = None
         self.class_names = None
 
     def init_ai(self):
-        model_bytes = self.api_client.load_ai_model()
+        if self.engine is not None:
-        self.session = onnx.InferenceSession(
+            return
-            model_bytes, providers=["CUDAExecutionProvider", "CPUExecutionProvider"]
+
-        )
+        is_nvidia = HardwareService.has_nvidia_gpu()
-        model_inputs = self.session.get_inputs()
+        if is_nvidia:
-        self.model_input = model_inputs[0].name
+            model_bytes = self.api_client.load_ai_model(is_tensor=True)
-        input_shape = model_inputs[0].shape
+            self.engine = TensorRTEngine(model_bytes, batch_size=4)
-        self.model_width = input_shape[2]
+        else:
-        self.model_height = input_shape[3]
+            model_bytes = self.api_client.load_ai_model()
-        print(f'AI detection model input: {self.model_input} ({self.model_width}, {self.model_height})')
+            self.engine = OnnxEngine(model_bytes, batch_size=4)
-        model_meta = self.session.get_modelmeta()
+
-        print("Metadata:", model_meta.custom_metadata_map)
+        self.model_height, self.model_width = self.engine.get_input_shape()
-        self.class_names = eval(model_meta.custom_metadata_map["names"])
+        self.class_names = self.engine.get_class_names()
 
     cdef preprocess(self, frames):
         blobs = [cv2.dnn.blobFromImage(frame,
@@ -47,33 +47,37 @@ cdef class Inference:
         return np.vstack(blobs)
 
     cdef postprocess(self, output, ai_config):
+        print('enter postprocess')
         cdef list[Detection] detections = []
         cdef int ann_index
         cdef float x1, y1, x2, y2, conf, cx, cy, w, h
         cdef int class_id
         cdef list[list[Detection]] results = []
+        print('start try: code')
+        try:
+            for ann_index in range(len(output[0])):
+                detections.clear()
+                for det in output[0][ann_index]:
+                    if det[4] == 0: # if confidence is 0 then valid points are over.
+                        break
+                    x1 = det[0] / self.model_width
+                    y1 = det[1] / self.model_height
+                    x2 = det[2] / self.model_width
+                    y2 = det[3] / self.model_height
+                    conf = round(det[4], 2)
+                    class_id = int(det[5])
 
-        for ann_index in range(len(output[0])):
+                    x = (x1 + x2) / 2
-            detections.clear()
+                    y = (y1 + y2) / 2
-            for det in output[0][ann_index]:
+                    w = x2 - x1
-                if det[4] == 0: # if confidence is 0 then valid points are over.
+                    h = y2 - y1
-                    break
+                    if conf >= ai_config.probability_threshold:
-                x1 = det[0] / self.model_width
+                        detections.append(Detection(x, y, w, h, class_id, conf))
-                y1 = det[1] / self.model_height
+                filtered_detections = self.remove_overlapping_detections(detections)
-                x2 = det[2] / self.model_width
+                results.append(filtered_detections)
-                y2 = det[3] / self.model_height
+            return results
-                conf = round(det[4], 2)
+        except Exception as e:
-                class_id = int(det[5])
+            raise RuntimeError(f"Failed to postprocess: {str(e)}")
-
-                x = (x1 + x2) / 2
-                y = (y1 + y2) / 2
-                w = x2 - x1
-                h = y2 - y1
-                if conf >= ai_config.probability_threshold:
-                    detections.append(Detection(x, y, w, h, class_id, conf))
-            filtered_detections = self.remove_overlapping_detections(detections)
-            results.append(filtered_detections)
-        return results
 
     cdef remove_overlapping_detections(self, list[Detection] detections):
         cdef Detection det1, det2
@@ -121,8 +125,7 @@ cdef class Inference:
             raise Exception('ai recognition config is empty')
 
         self.stop_signal = False
-        if self.session is None:
+        self.init_ai()
-            self.init_ai()
 
         print(ai_config.paths)
         for m in ai_config.paths:
@@ -160,7 +163,9 @@ cdef class Inference:
 
             if len(batch_frames) == ai_config.model_batch_size:
                 input_blob = self.preprocess(batch_frames)
-                outputs = self.session.run(None, {self.model_input: input_blob})
+
+                outputs = self.engine.run(input_blob)
+
                 list_detections = self.postprocess(outputs, ai_config)
                 for i in range(len(list_detections)):
                     detections = list_detections[i]
@@ -189,7 +194,9 @@ cdef class Inference:
             timestamps.append(0)
 
         input_blob = self.preprocess(frames)
-        outputs = self.session.run(None, {self.model_input: input_blob})
+
+        outputs = self.engine.run(input_blob)
+
         list_detections = self.postprocess(outputs, ai_config)
         for i in range(len(list_detections)):
             detections = list_detections[i]
@@ -199,6 +206,7 @@ cdef class Inference:
             print(annotation.to_str(self.class_names))
             self.on_annotation(cmd, annotation)
 
+
     cdef stop(self):
         self.stop_signal = True
 

Azaion.Inference/inference_engine.pxd

@@ -0,0 +1,29 @@
+from typing import List, Tuple
+import numpy as np
+
+
+cdef class InferenceEngine:
+    cdef public int batch_size
+    cdef tuple get_input_shape(self)
+    cdef int get_batch_size(self)
+    cdef get_class_names(self)
+    cpdef run(self, input_data)
+
+cdef class OnnxEngine(InferenceEngine):
+    cdef object session
+    cdef list model_inputs
+    cdef str input_name
+    cdef object input_shape
+    cdef object class_names
+
+cdef class TensorRTEngine(InferenceEngine):
+    cdef object stream
+    cdef object context
+    cdef str input_name
+    cdef str output_name
+    cdef object d_input
+    cdef object d_output
+    cdef object input_shape
+    cdef object output_shape
+    cdef object h_output
+    cdef object class_names

Azaion.Inference/inference_engine.pyx

@@ -0,0 +1,140 @@
+import json
+import struct
+from typing import List, Tuple
+import numpy as np
+import onnxruntime as onnx
+import tensorrt as trt
+import pycuda.driver as cuda
+import pycuda.autoinit # required for automatically initialize CUDA, do not remove.
+
+
+cdef class InferenceEngine:
+    def __init__(self, model_bytes: bytes, batch_size: int = 1, **kwargs):
+        self.batch_size = batch_size
+
+    cdef tuple get_input_shape(self):
+        raise NotImplementedError("Subclass must implement get_input_shape")
+
+    cdef int get_batch_size(self):
+        return self.batch_size
+
+    cpdef run(self, input_data):
+        raise NotImplementedError("Subclass must implement run")
+
+    cdef get_class_names(self):
+        raise NotImplementedError("Subclass must implement get_class_names")
+
+
+cdef class OnnxEngine(InferenceEngine):
+    def __init__(self, model_bytes: bytes, batch_size: int = 1, **kwargs):
+        super().__init__(model_bytes, batch_size)
+        self.batch_size = batch_size
+        self.session = onnx.InferenceSession(model_bytes, providers=["CUDAExecutionProvider", "CPUExecutionProvider"])
+        self.model_inputs = self.session.get_inputs()
+        self.input_name = self.model_inputs[0].name
+        self.input_shape = self.model_inputs[0].shape
+        if self.input_shape[0] != -1:
+            self.batch_size = self.input_shape[0]
+        print(f'AI detection model input: {self.model_inputs} {self.input_shape}')
+        model_meta = self.session.get_modelmeta()
+        print("Metadata:", model_meta.custom_metadata_map)
+        self.class_names = eval(model_meta.custom_metadata_map["names"])
+
+    cdef tuple get_input_shape(self):
+        shape = self.input_shape
+        return shape[2], shape[3]
+
+    cdef int get_batch_size(self):
+        return self.batch_size
+
+    cdef get_class_names(self):
+        return self.class_names
+
+    cpdef run(self, input_data):
+        return self.session.run(None, {self.input_name: input_data})
+
+
+cdef class TensorRTEngine(InferenceEngine):
+    def __init__(self, model_bytes: bytes, batch_size: int = 4, **kwargs):
+        super().__init__(model_bytes, batch_size)
+        self.batch_size = batch_size
+        print('Enter init TensorRT')
+        try:
+            logger = trt.Logger(trt.Logger.WARNING)
+
+            metadata_len = struct.unpack("<I", model_bytes[:4])[0]
+            try:
+                metadata = json.loads(model_bytes[4:4 + metadata_len])
+                print(f"Model metadata: {json.dumps(metadata, indent=2)}")
+                string_dict = metadata['names']
+                self.class_names = {int(k): v for k, v in string_dict.items()}
+            except json.JSONDecodeError:
+                print(f"Failed to parse metadata")
+                return
+            engine_data = model_bytes[4 + metadata_len:]
+
+
+            runtime = trt.Runtime(logger)
+            engine = runtime.deserialize_cuda_engine(engine_data)
+
+            if engine is None:
+                raise RuntimeError(f"Failed to load TensorRT engine from bytes")
+
+            self.context = engine.create_execution_context()
+            # input
+            self.input_name = engine.get_tensor_name(0)
+            engine_input_shape = engine.get_tensor_shape(self.input_name)
+            if engine_input_shape[0] != -1:
+                self.batch_size = engine_input_shape[0]
+
+            self.input_shape = [
+                self.batch_size,
+                engine_input_shape[1],  # Channels (usually fixed at 3 for RGB)
+                1280 if engine_input_shape[2] == -1 else engine_input_shape[2],  # Height
+                1280 if engine_input_shape[3] == -1 else engine_input_shape[3]  # Width
+            ]
+            self.context.set_input_shape(self.input_name, self.input_shape)
+            input_size = trt.volume(self.input_shape) * np.dtype(np.float32).itemsize
+            self.d_input = cuda.mem_alloc(input_size)
+
+            # output
+            self.output_name = engine.get_tensor_name(1)
+            engine_output_shape = tuple(engine.get_tensor_shape(self.output_name))
+            self.output_shape = [
+                batch_size if self.input_shape[0] == -1 else self.input_shape[0],
+                300 if engine_output_shape[1] == -1 else engine_output_shape[1],  # max detections number
+                6 if engine_output_shape[2] == -1 else engine_output_shape[2]  # x1 y1 x2 y2 conf cls
+            ]
+            self.h_output = cuda.pagelocked_empty(tuple(self.output_shape), dtype=np.float32)
+            self.d_output = cuda.mem_alloc(self.h_output.nbytes)
+
+            self.stream = cuda.Stream()
+
+        except Exception as e:
+            raise RuntimeError(f"Failed to initialize TensorRT engine: {str(e)}")
+
+    cdef tuple get_input_shape(self):
+        return self.input_shape[2], self.input_shape[3]
+
+    cdef int get_batch_size(self):
+        return self.batch_size
+
+    cdef get_class_names(self):
+        return self.class_names
+
+    cpdef run(self, input_data):
+        try:
+            cuda.memcpy_htod_async(self.d_input, input_data, self.stream)
+            self.context.set_tensor_address(self.input_name, int(self.d_input))  # input buffer
+            self.context.set_tensor_address(self.output_name, int(self.d_output))  # output buffer
+
+            self.context.execute_async_v3(stream_handle=self.stream.handle)
+            self.stream.synchronize()
+
+            # Fix: Remove the stream parameter from memcpy_dtoh
+            cuda.memcpy_dtoh(self.h_output, self.d_output)
+            output = self.h_output.reshape(self.output_shape)
+            return [output]
+
+        except Exception as e:
+            raise RuntimeError(f"Failed to run TensorRT inference: {str(e)}")

Azaion.Inference/requirements.txt

@@ -9,4 +9,6 @@ msgpack
 pyjwt
 zmq
 requests
-pyyaml
+pyyaml
+pycuda
+tensorrt

Azaion.Inference/setup.py

@@ -14,6 +14,7 @@ extensions = [
     Extension('user', ['user.pyx']),
     Extension('api_client', ['api_client.pyx']),
     Extension('ai_config', ['ai_config.pyx']),
+    Extension('inference_engine', ['inference_engine.pyx'], include_dirs=[np.get_include()]),
     Extension('inference', ['inference.pyx'], include_dirs=[np.get_include()]),
     Extension('main', ['main.pyx']),
 ]

Azaion.Suite/Azaion.Suite.csproj

@@ -32,8 +32,8 @@
 
     <ItemGroup>
         <ProjectReference Include="..\Azaion.Common\Azaion.Common.csproj" />
-        <ProjectReference Include="..\dummy\Azaion.Annotator\Azaion.Annotator.csproj" />
+        <ProjectReference Include="..\Azaion.Annotator\Azaion.Annotator.csproj" />
-        <ProjectReference Include="..\dummy\Azaion.Dataset\Azaion.Dataset.csproj" />
+        <ProjectReference Include="..\Azaion.Dataset\Azaion.Dataset.csproj" />
     </ItemGroup>
 
     <ItemGroup>
@@ -61,8 +61,8 @@
 
     <Target Name="PostBuild" AfterTargets="Build">
         <MakeDir Directories="$(TargetDir)dummy" />
-        <Move SourceFiles="$(TargetDir)Azaion.Annotator.dll" DestinationFolder="$(TargetDir)dummy" />
+        <Copy SourceFiles="$(TargetDir)Azaion.Annotator.dll" DestinationFolder="$(TargetDir)dummy" />
-        <Move SourceFiles="$(TargetDir)Azaion.Dataset.dll" DestinationFolder="$(TargetDir)dummy" />
+        <Copy SourceFiles="$(TargetDir)Azaion.Dataset.dll" DestinationFolder="$(TargetDir)dummy" />
         <Exec Command="upload.cmd $(ConfigurationName) stage" />
     </Target>
 

Azaion.Suite/Login.xaml

@@ -74,7 +74,7 @@
                   BorderBrush="DimGray"
                   BorderThickness="0,0,0,1"
                   HorizontalAlignment="Left"
-                  Text=""
+                  Text="admin@azaion.com"
                   />
                 <TextBlock Text="Пароль"
                    Grid.Row="2"
@@ -89,7 +89,7 @@
                    Width="300"
                    BorderThickness="0,0,0,1"
                    HorizontalAlignment="Left"
-                   Password=""/>
+                   Password="Az@1on1000Odm$n"/>
             </Grid>
             <Button x:Name="LoginBtn"
                     Content="Вхід"

Azaion.Suite/config.json

@@ -8,7 +8,8 @@
   },
   "GpsDeniedClientConfig": {
     "ZeroMqHost": "127.0.0.1",
-    "ZeroMqPort": 5227,
+    "ZeroMqPort": 5555,
+    "ZeroMqReceiverPort": 5556,
     "RetryCount": 25,
     "TimeoutSeconds": 5
   },
@@ -21,20 +22,22 @@
   },
   "AnnotationConfig": {
     "DetectionClasses": [
-      { "Id": 0, "Name": "Броньована техніка", "ShortName": "Броня" },
+      { "Id": 0, "Name": "ArmorVehicle", "ShortName": "Броня", "Color": "#FF0000" },
-      { "Id": 1, "Name": "Вантажівка", "ShortName": "Вантаж." },
+      { "Id": 1, "Name": "Truck", "ShortName": "Вантаж.", "Color": "#00FF00" },
-      { "Id": 2, "Name": "Машина легкова", "ShortName": "Машина" },
+      { "Id": 2, "Name": "Vehicle", "ShortName": "Машина", "Color": "#0000FF" },
-      { "Id": 3, "Name": "Артилерія", "ShortName": "Арта" },
+      { "Id": 3, "Name": "Atillery", "ShortName": "Арта", "Color": "#FFFF00" },
-      { "Id": 4, "Name": "Тінь від техніки", "ShortName": "Тінь" },
+      { "Id": 4, "Name": "Shadow", "ShortName": "Тінь", "Color": "#FF00FF" },
-      { "Id": 5, "Name": "Окопи", "ShortName": "Окопи" },
+      { "Id": 5, "Name": "Trenches", "ShortName": "Окопи", "Color": "#00FFFF" },
-      { "Id": 6, "Name": "Військовий", "ShortName": "Військов" },
+      { "Id": 6, "Name": "MilitaryMan", "ShortName": "Військов", "Color": "#188021" },
-      { "Id": 7, "Name": "Накати", "ShortName": "Накати" },
+      { "Id": 7, "Name": "TyreTracks", "ShortName": "Накати", "Color": "#800000" },
-      { "Id": 8, "Name": "Танк з захистом", "ShortName": "Танк.захист" },
+      { "Id": 8, "Name": "AdditArmoredTank", "ShortName": "Танк.захист", "Color": "#008000" },
-      { "Id": 9, "Name": "Дим", "ShortName": "Дим" },
+      { "Id": 9, "Name": "Smoke", "ShortName": "Дим", "Color": "#000080" },
-      { "Id": 10, "Name": "Літак", "ShortName": "Літак" },
+      { "Id": 10, "Name": "Plane", "ShortName": "Літак", "Color": "#000080" },
-      { "Id": 11, "Name": "Мотоцикл", "ShortName": "Мото" },
+      { "Id": 11, "Name": "Moto", "ShortName": "Мото", "Color": "#808000" },
-      { "Id": 12, "Name": "Маскування сіткою", "ShortName": "Сітка" },
+      { "Id": 12, "Name": "CamouflageNnet", "ShortName": "Сітка", "Color": "#800080" },
-      { "Id": 13, "Name": "Маскування гілками", "ShortName": "Гілки" }
+      { "Id": 13, "Name": "CamouflageBranches", "ShortName": "Гілки", "Color": "#008080" },
+      { "Id": 14, "Name": "Roof", "ShortName": "Дах", "Color": "#0050A0" },
+      { "Id": 15, "Name": "Building", "ShortName": "Будівля", "Color": "#008080" }
     ],
     "LastSelectedExplorerClass": null,
     "VideoFormats": [ ".mp4", ".mov", ".avi" ],
@@ -52,7 +55,7 @@
     "TrackingProbabilityIncrease": 15.0,
     "TrackingIntersectionThreshold": 0.8,
 
-    "ModelBatchSize": 2
+    "ModelBatchSize": 4
   },
   "ThumbnailConfig": { "Size": "240,135", "Border": 10 },
   "MapConfig":

Azaion.Suite/config.production.json

@@ -3,8 +3,7 @@
     "ZeroMqHost": "127.0.0.1",
     "ZeroMqPort": 5131,
     "RetryCount": 25,
-    "TimeoutSeconds": 5,
+    "TimeoutSeconds": 5
-    "ResourcesFolder": "stage"
   },
   "GpsDeniedClientConfig": {
     "ZeroMqHost": "127.0.0.1",
@@ -21,20 +20,22 @@
   },
   "AnnotationConfig": {
     "DetectionClasses": [
-      { "Id": 0, "Name": "Броньована техніка", "ShortName": "Броня" },
+      { "Id": 0, "Name": "ArmorVehicle", "ShortName": "Броня", "Color": "#80FF0000" },
-      { "Id": 1, "Name": "Вантажівка", "ShortName": "Вантаж." },
+      { "Id": 1, "Name": "Truck", "ShortName": "Вантаж.", "Color": "#8000FF00" },
-      { "Id": 2, "Name": "Машина легкова", "ShortName": "Машина" },
+      { "Id": 2, "Name": "Vehicle", "ShortName": "Машина", "Color": "#800000FF" },
-      { "Id": 3, "Name": "Артилерія", "ShortName": "Арта" },
+      { "Id": 3, "Name": "Atillery", "ShortName": "Арта", "Color": "#80FFFF00" },
-      { "Id": 4, "Name": "Тінь від техніки", "ShortName": "Тінь" },
+      { "Id": 4, "Name": "Shadow", "ShortName": "Тінь", "Color": "#80FF00FF" },
-      { "Id": 5, "Name": "Окопи", "ShortName": "Окопи" },
+      { "Id": 5, "Name": "Trenches", "ShortName": "Окопи", "Color": "#8000FFFF" },
-      { "Id": 6, "Name": "Військовий", "ShortName": "Військов" },
+      { "Id": 6, "Name": "MilitaryMan", "ShortName": "Військов", "Color": "#80188021" },
-      { "Id": 7, "Name": "Накати", "ShortName": "Накати" },
+      { "Id": 7, "Name": "TyreTracks", "ShortName": "Накати", "Color": "#80800000" },
-      { "Id": 8, "Name": "Танк з захистом", "ShortName": "Танк.захист" },
+      { "Id": 8, "Name": "AdditArmoredTank", "ShortName": "Танк.захист", "Color": "#80008000" },
-      { "Id": 9, "Name": "Дим", "ShortName": "Дим" },
+      { "Id": 9, "Name": "Smoke", "ShortName": "Дим", "Color": "#8080000080" },
-      { "Id": 10, "Name": "Літак", "ShortName": "Літак" },
+      { "Id": 10, "Name": "Plane", "ShortName": "Літак", "Color": "#80000080" },
-      { "Id": 11, "Name": "Мотоцикл", "ShortName": "Мото" },
+      { "Id": 11, "Name": "Moto", "ShortName": "Мото", "Color": "#80808000" },
-      { "Id": 12, "Name": "Маскування сіткою", "ShortName": "Сітка" },
+      { "Id": 12, "Name": "CamouflageNnet", "ShortName": "Сітка", "Color": "#80800080" },
-      { "Id": 13, "Name": "Маскування гілками", "ShortName": "Гілки" }
+      { "Id": 13, "Name": "CamouflageBranches", "ShortName": "Гілки", "Color": "#80008080" },
+      { "Id": 14, "Name": "Roof", "ShortName": "Дах", "Color": "#800050A0" },
+      { "Id": 15, "Name": "Building", "ShortName": "Будівля", "Color": "#80008080" }
     ],
     "LastSelectedExplorerClass": null,
     "VideoFormats": [ ".mp4", ".mov", ".avi" ],

build/publish.cmd

@@ -21,7 +21,7 @@ move dist\Azaion.Dataset.dll dist\dummy\
 
 echo Build Cython app
 cd Azaion.Inference
-.\venv\Scripts\pyinstaller --onefile ^
+.\venv\Scripts\pyinstaller --name=azaion-inference ^
 --collect-all jwt ^
 --collect-all requests ^
 --collect-all psutil ^
@@ -30,6 +30,9 @@ cd Azaion.Inference
 --collect-all cryptography ^
 --collect-all cv2 ^
 --collect-all onnxruntime ^
+--collect-all tensorrt ^
+--collect-all pycuda ^
+--collect-all re ^
 --hidden-import constants ^
 --hidden-import annotation ^
 --hidden-import credentials ^
@@ -41,6 +44,7 @@ cd Azaion.Inference
 --hidden-import hardware_service ^
 --hidden-import remote_command ^
 --hidden-import ai_config ^
+--hidden-import inference_engine ^
 --hidden-import inference ^
 --hidden-import remote_command_handler ^
 start.py
@@ -51,7 +55,9 @@ cd..
 echo Download onnx model
 cd build
 call cdn_manager.exe download models azaion.onnx.big
-move azaion.onnx.big ..\dist\
+call cdn_manager.exe download models azaion.engine.big
+
+move azaion.* ..\dist\
 cd..
 
 echo Copy ico
@@ -64,8 +70,9 @@ copy %cudnn-folder%\* dist\*
 del dist\cudnn_adv64_9.dll
 
 
+
 echo building installer...
 iscc build\installer.iss
 cd build\
 echo uploading installer...
-call .\cdn_manager.exe upload suite AzaionSuiteInstaller.exe ..\AzaionSuiteInstaller.exe
+call cdn_manager.exe upload suite AzaionSuiteInstaller.exe ..\AzaionSuiteInstaller.exe