Пример #1
0
        public static float IoU(OutputVector v1, OutputVector v2)
        {
            float x1   = Math.Max(v1.X, v2.X);
            float y1   = Math.Max(v1.Y, v2.Y);
            float x2   = Math.Min(v1.X + v1.W, v2.X + v2.W);
            float y2   = Math.Min(v1.Y + v1.H, v2.Y + v2.H);
            float area = Math.Max(0, (x2 - x1) * (y2 - y1));
            float iou  = area / (v1.W * v1.H + v2.W * v2.H - area);

            return(iou);
        }
Пример #2
0
        private static Task <IEnumerable <OutputVector> > FilterAsync(float[] output, string key)
        {
            return(new Task <IEnumerable <OutputVector> >(() =>
            {
                var result = new List <OutputVector>();
                var(anchors, stride, grids) = AnchorsDict[key];
                for (int channel = 0; channel < anchors.Length; channel++)
                {
                    for (int row = 0; row < grids; row++)
                    {
                        for (int col = 0; col < grids; col++)
                        {
                            var start = (grids * grids * channel + grids * row + col) * VECTOR_LENGTH;
                            var objectConfidence = Functions.Sigmoid(output[start + 4]);
                            if (objectConfidence < Params.ConfidenceThreshold)
                            {
                                continue;
                            }

                            var span = new ReadOnlySpan <float>(output, start, VECTOR_LENGTH);
                            var scores = span.Slice(5, VECTOR_LENGTH - 5).ToArray()
                                         .Select(c => Functions.Sigmoid(c));
                            var vector = new OutputVector
                            {
                                ObjectConfidence = objectConfidence,
                                X = (Functions.Sigmoid(span[0]) * 2 - 0.5f + col) * stride,
                                Y = (Functions.Sigmoid(span[1]) * 2 - 0.5f + row) * stride,
                                W = MathF.Pow(Functions.Sigmoid(span[2]) * 2, 2) * anchors[channel].width,
                                H = MathF.Pow(Functions.Sigmoid(span[3]) * 2, 2) * anchors[channel].height,
                                ClassScores = scores.ToArray()
                            };

                            if (vector.ClassMaxScore >= Params.ConfidenceThreshold)
                            {
                                result.Add(vector);
                            }
                        }
                    }
                }
                return result;
            }));
        }