object detection in csharp

main.cs
using TensorFlow;
using System.Linq;

public void DetectObjects(byte[] imageBytes)
{
    using (var graph = new TFGraph())
    {
        var model = File.ReadAllBytes("model.pb");
        graph.Import(model, "");

        using (var session = new TFSession(graph))
        {
            var tensor = ImageUtil.CreateTensorFromBytes(imageBytes);
            var runner = session.GetRunner();

            runner.AddInput(graph["image_tensor"][0], tensor)
                  .Fetch(graph["detection_boxes"][0],
                         graph["detection_scores"][0],
                         graph["detection_classes"][0],
                         graph["num_detections"][0]);

            var output = runner.Run();

            var boxes = (float[,,]) output[0].GetValue(jagged: false);
            var scores = (float[,]) output[1].GetValue(jagged: false);
            var classes = (float[,]) output[2].GetValue(jagged: false);
            var num = (float[]) output[3].GetValue(jagged: false);

            var filteredBoxes = FilterBoxes(boxes, scores, threshold: 0.5f);
            var objects = MapBoxesToObjects(filteredBoxes, classes);

            foreach (var obj in objects)
            {
                Console.WriteLine($"Object: {obj.Label} ({obj.Score})");
                Console.WriteLine($"    Box: [{obj.Box.Left}, {obj.Box.Top}, {obj.Box.Right}, {obj.Box.Bottom}]");
            }
        }
    }
}

public List<YoloResult> MapBoxesToObjects(float[,,] boxes, float[,] classes)
{
    var objects = new List<YoloResult>();

    for (int i = 0; i < boxes.GetLength(1); i++)
    {
        var scores = boxes[0, i, 4];

        if (scores > 0.5)
        {
            var box = new YoloBoundingBox(
                left: boxes[0, i, 1],
                top: boxes[0, i, 0],
                right: boxes[0, i, 3],
                bottom: boxes[0, i, 2]);

            int cls = classes[0, i].ConvertToInt32();
            string label = ObjectClasses.GetClassName(cls);

            objects.Add(new YoloResult() { Label = label, Box = box, Score = scores });
        }
    }

    return objects;
}

public static float IntersectionOverUnion(RectangleF rectA, RectangleF rectB)
{
    float areaA = rectA.Width * rectA.Height;
    float areaB = rectB.Width * rectB.Height;

    float minX = Math.Max(rectA.Left, rectB.Left);
    float minY = Math.Max(rectA.Top, rectB.Top);
    float maxX = Math.Min(rectA.Right, rectB.Right);
    float maxY = Math.Min(rectA.Bottom, rectB.Bottom);

    float intersectionArea = Math.Max(maxY - minY, 0) * Math.Max(maxX - minX, 0);
    float unionArea = areaA + areaB - intersectionArea;

    return intersectionArea / unionArea;
}

public static List<YoloBoundingBox> FilterBoxes(float[,,] boxes, float[,] scores, float threshold)
{
    var results = new List<YoloBoundingBox>();

    for (int i = 0; i < boxes.GetLength(1); i++)
    {
        float score = scores[0, i];

        if (score > threshold)
        {
            var box = new YoloBoundingBox(
                left: boxes[0, i, 1],
                top: boxes[0, i, 0],
                right: boxes[0, i, 3],
                bottom: boxes[0, i, 2]);

            results.Add(box);
        }
    }

    return results;
}
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