private const float nmsThreshold = 0.3f; //threshold for nms
public YoloBatchedDnnDetector(ILogger <YoloBatchedDnnDetector> logger, IOptions <Yolo3Options> yoloOptions, IOptions <VideoStreamsOptions> streamOptions) :
base(logger, yoloOptions)
{
_roiConfig = GetValidatedOptions <VideoStreamsOptions>(streamOptions).
ToDictionary(o => o.Id, o => o.ROI);
//YOLOv3 File locations
//Cfg: https://github.com/pjreddie/darknet/blob/master/cfg/yolov3.cfg
//Weight: https://pjreddie.com/media/files/yolov3.weights
//Names: https://github.com/pjreddie/darknet/blob/master/data/coco.names
var cfg = Path.Combine(Options.RootPath, Options.ConfigFile);
var weight = Path.Combine(Options.RootPath, Options.WeightsFile);
var names = Path.Combine(Options.RootPath, Options.NamesFile);
//random assign color to each label
Labels = File.ReadAllLines(names).ToArray();
//get labels from coco.names
Colors = Enumerable.Repeat(false, Labels.Length).Select(x => Scalar.RandomColor()).ToArray();
Logger.LogInformation("Loading Neural Net");
//Does not result in a null object, but will trow exception on errors, so safe to assume non-null
nnet = OpenCvSharp.Dnn.CvDnn.ReadNetFromDarknet(cfg, weight) !;
_outNames = nnet.GetUnconnectedOutLayersNames() !;
outs = Enumerable.Repeat(false, _outNames.Length).Select(_ => new Mat()).ToArray();
}
public Yolo2DnnDetector(ILogger <IDnnDetector> logger)
{
_logger = logger;
nnet = OpenCvSharp.Dnn.CvDnn.ReadNetFromDarknet(Cfg, Weight);
//nnet.SetPreferableBackend(Net.Backend.INFERENCE_ENGINE);
//nnet.SetPreferableTarget(Net.Target.CPU);
_outNames = nnet.GetUnconnectedOutLayersNames() !;
}
public Yolo3BatchedDnnDetector(ILogger <IDnnDetector> logger, IConfiguration configuration)
{
if (configuration is null)
{
throw new ArgumentNullException(nameof(configuration));
}
if (logger is null)
{
throw new ArgumentNullException(nameof(logger));
}
_logger = logger;
var options = new Yolo3Options();
configuration.GetSection(Yolo3Options.Yolo3).Bind(options);
Cfg = Path.Combine(options.RootPath, options.ConfigFile);
Weight = Path.Combine(options.RootPath, options.WeightsFile);
Names = Path.Combine(options.RootPath, options.NamesFile);
//random assign color to each label
Labels = File.ReadAllLines(Names).ToArray();
//get labels from coco.names
Colors = Enumerable.Repeat(false, Labels.Length).Select(x => Scalar.RandomColor()).ToArray();
_logger.LogInformation("Loading Neural Net");
nnet = OpenCvSharp.Dnn.CvDnn.ReadNetFromDarknet(Cfg, Weight);
//nnet.SetPreferableBackend(Net.Backend.INFERENCE_ENGINE);
//nnet.SetPreferableTarget(Net.Target.OPENCL);
_outNames = nnet.GetUnconnectedOutLayersNames() !;
outs = Enumerable.Repeat(false, _outNames.Length).Select(_ => new Mat()).ToArray();
_logger.LogInformation("Warm Up Neural Net with Dummy images");
//Initialize();
}
