diff --git a/filter/filters_circleci.go b/filter/filters_circleci.go index b5286f97..e9fc155a 100644 --- a/filter/filters_circleci.go +++ b/filter/filters_circleci.go @@ -35,3 +35,7 @@ import ( func NewMOGFilter(dst io.WriteCloser, area, threshold float64, history, kernelSize int, debug bool) *NoOp { return &NoOp{dst: dst} } + +func NewKNNFilter(dst io.WriteCloser, area, threshold float64, history, kernelSize int, debug bool) *NoOp { + return &NoOp{dst: dst} +} diff --git a/filter/knn.go b/filter/knn.go new file mode 100644 index 00000000..4ce51d9e --- /dev/null +++ b/filter/knn.go @@ -0,0 +1,133 @@ +// +build !circleci + +/* +DESCRIPTION + A filter that detects motion and discards frames without motion. The + filter uses a K-Nearest Neighbours (KNN) to determine what is + background and what is foreground. + +AUTHORS + Ella Pietraroia + +LICENSE + KNN.go is Copyright (C) 2019 the Australian Ocean Lab (AusOcean) + + It is free software: you can redistribute it and/or modify them + under the terms of the GNU General Public License as published by the + Free Software Foundation, either version 3 of the License, or (at your + option) any later version. + + It is distributed in the hope that it will be useful, but WITHOUT + ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or + FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License + for more details. + + You should have received a copy of the GNU General Public License + in gpl.txt. If not, see http://www.gnu.org/licenses. +*/ + +package filter + +import ( + "fmt" + "image" + "image/color" + "io" + + "gocv.io/x/gocv" +) + +// KNNFilter is a filter that provides basic motion detection. KNN is short for +// K-Nearest Neighbours method. +type KNNFilter struct { + dst io.WriteCloser + area float64 + bs *gocv.BackgroundSubtractorKNN + knl gocv.Mat + debug bool + windows []*gocv.Window +} + +// NewKNNFilter returns a pointer to a new KNNFilter. +func NewKNNFilter(dst io.WriteCloser, area, threshold float64, history, kernelSize int, debug bool) *KNNFilter { + bs := gocv.NewBackgroundSubtractorKNNWithParams(history, threshold, false) + k := gocv.GetStructuringElement(gocv.MorphRect, image.Pt(kernelSize, kernelSize)) + var windows []*gocv.Window + if debug { + windows = []*gocv.Window{gocv.NewWindow("Debug: Bounding boxes"), gocv.NewWindow("Debug: Motion")} + } + return &KNNFilter{dst, area, &bs, k, debug, windows} +} + +// Implements io.Closer. +// Close frees resources used by gocv, because it has to be done manually, due to +// it using c-go. +func (m *KNNFilter) Close() error { + m.bs.Close() + m.knl.Close() + for _, window := range m.windows { + window.Close() + } + return nil +} + +// Implements io.Writer. +// Write applies the motion filter to the video stream. Only frames with motion +// are written to the destination encoder, frames without are discarded. +func (m *KNNFilter) Write(f []byte) (int, error) { + img, err := gocv.IMDecode(f, gocv.IMReadColor) + if err != nil { + return 0, fmt.Errorf("can't decode image: %w", err) + } + defer img.Close() + + imgDelta := gocv.NewMat() + defer imgDelta.Close() + + // Seperate foreground and background. + m.bs.Apply(img, &imgDelta) + + // Threshold imgDelta. + gocv.Threshold(imgDelta, &imgDelta, 25, 255, gocv.ThresholdBinary) + + // Remove noise. + gocv.Erode(imgDelta, &imgDelta, m.knl) + gocv.Dilate(imgDelta, &imgDelta, m.knl) + + // Fill small holes. + gocv.Dilate(imgDelta, &imgDelta, m.knl) + gocv.Erode(imgDelta, &imgDelta, m.knl) + + // Find contours and reject ones with a small area. + var contours [][]image.Point + allContours := gocv.FindContours(imgDelta, gocv.RetrievalExternal, gocv.ChainApproxSimple) + for _, c := range allContours { + if gocv.ContourArea(c) > m.area { + contours = append(contours, c) + } + } + + // Draw debug information. + if m.debug { + for _, c := range contours { + rect := gocv.BoundingRect(c) + gocv.Rectangle(&img, rect, color.RGBA{0, 0, 255, 0}, 1) + } + + if len(contours) > 0 { + gocv.PutText(&img, "Motion", image.Pt(32, 32), gocv.FontHersheyPlain, 2.0, color.RGBA{255, 0, 0, 0}, 2) + } + + m.windows[0].IMShow(img) + m.windows[1].IMShow(imgDelta) + m.windows[0].WaitKey(1) + } + + // Don't write to destination if there is no motion. + if len(contours) == 0 { + return -1, nil + } + + // Write to destination. + return m.dst.Write(f) +} diff --git a/revid/config/config.go b/revid/config/config.go index 00c4dda0..d13157b2 100644 --- a/revid/config/config.go +++ b/revid/config/config.go @@ -113,6 +113,7 @@ const ( FilterNoOp = iota FilterMOG FilterVariableFPS + FilterKNN ) // Config provides parameters relevant to a revid instance. A new config must diff --git a/revid/revid.go b/revid/revid.go index d2558057..fd3f83cf 100644 --- a/revid/revid.go +++ b/revid/revid.go @@ -76,6 +76,15 @@ const ( rtmpConnectionTimeout = 10 ) +// KNN filter properties +const ( + knnMinArea = 25.0 + knnThreshold = 300 + knnHistory = 300 + knnKernel = 9 + knnShowWindows = true +) + const pkg = "revid: " type Logger interface { @@ -335,6 +344,8 @@ func (r *Revid) setupPipeline(mtsEnc func(dst io.WriteCloser, rate float64) (io. r.filter = filter.NewMOGFilter(r.encoders, 25, 20, 500, 3, true) case config.FilterVariableFPS: r.filter = filter.NewVariableFPSFilter(r.encoders, 1.0, filter.NewMOGFilter(r.encoders, 25, 20, 500, 3, true)) + case config.FilterKNN: + r.filter = filter.NewKNNFilter(r.encoders, knnMinArea, knnThreshold, knnHistory, knnKernel, knnShowWindows) default: panic("Undefined Filter") } @@ -647,7 +658,7 @@ func (r *Revid) Update(vars map[string]string) error { r.cfg.Logger.Log(logger.Warning, pkg+"invalid VerticalFlip param", "value", value) } case "Filter": - m := map[string]int{"NoOp": config.FilterNoOp, "MOG": config.FilterMOG, "VariableFPS": config.FilterVariableFPS} + m := map[string]int{"NoOp": config.FilterNoOp, "MOG": config.FilterMOG, "VariableFPS": config.FilterVariableFPS, "KNN": config.FilterKNN} v, ok := m[value] if !ok { r.cfg.Logger.Log(logger.Warning, pkg+"invalid FilterMethod param", "value", value)