// +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 <ella@ausocean.org> 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 ( "image" "io" "bitbucket.org/ausocean/av/revid/config" "gocv.io/x/gocv" ) const ( defaultKNNMinArea = 25.0 defaultKNNThreshold = 300 defaultKNNHistory = 300 defaultKNNKernel = 4 ) // NewKNN returns a pointer to a new KNN motion filter. func NewKNN(dst io.WriteCloser, c config.Config) *Motion { // Validate parameters. if c.MotionMinArea <= 0 { c.LogInvalidField("MotionMinArea", defaultKNNMinArea) c.MotionMinArea = defaultKNNMinArea } if c.MotionThreshold <= 0 { c.LogInvalidField("MotionThreshold", defaultKNNThreshold) c.MotionThreshold = defaultKNNThreshold } if c.MotionHistory == 0 { c.LogInvalidField("MotionHistory", defaultKNNHistory) c.MotionHistory = defaultKNNHistory } if c.MotionKernel <= 0 { c.LogInvalidField("MotionKernel", defaultKNNKernel) c.MotionKernel = defaultKNNKernel } bs := gocv.NewBackgroundSubtractorKNNWithParams(int(c.MotionHistory), c.MotionThreshold, false) alg := &KNN{ area: c.MotionMinArea, bs: &bs, knl: gocv.GetStructuringElement(gocv.MorphRect, image.Pt(int(c.MotionKernel), int(c.MotionKernel))), debugging: newWindows("KNN"), } return NewMotion(dst, alg, c) } // KNN is motion detection algorithm. KNN is short for // K-Nearest Neighbours method. type KNN struct { debugging debugWindows area float64 // The minimum area that a contour can be found in. bs *gocv.BackgroundSubtractorKNN // Uses the KNN algorithm to find the difference between the current and background frame. knl gocv.Mat // Matrix that is used for calculations. } // Close frees resources used by gocv. It has to be done manually, // due to gocv using c-go. func (m *KNN) Close() error { m.bs.Close() m.knl.Close() m.debugging.close() return nil } // Detect performs the motion detection on a frame. It returns true // if motion is detected. func (m *KNN) Detect(img *gocv.Mat) bool { 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. m.debugging.show(*img, imgDelta, len(contours) > 0, &contours) // Return if there is motion. return len(contours) > 0 }