// +build !circleci /* DESCRIPTION A filter that detects motion and discards frames without motion. The algorithm uses a Mixture of Gaussians method (MoG) to determine what is background and what is foreground. AUTHORS Scott Barnard LICENSE mog.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 ( defaultMOGMinArea = 25.0 defaultMOGThreshold = 20.0 defaultMOGHistory = 500 defaultMOGKernel = 3 ) // NewMOG returns a pointer to a new MOG motion filter. func NewMOG(dst io.WriteCloser, c config.Config) *Motion { // Validate parameters. if c.MotionMinArea <= 0 { c.LogInvalidField("MotionMinArea", defaultMOGMinArea) c.MotionMinArea = defaultMOGMinArea } if c.MotionThreshold <= 0 { c.LogInvalidField("MotionThreshold", defaultMOGThreshold) c.MotionThreshold = defaultMOGThreshold } if c.MotionHistory == 0 { c.LogInvalidField("MotionHistory", defaultMOGHistory) c.MotionHistory = defaultMOGHistory } if c.MotionKernel <= 0 { c.LogInvalidField("MotionKernel", defaultMOGKernel) c.MotionKernel = defaultMOGKernel } bs := gocv.NewBackgroundSubtractorMOG2WithParams(int(c.MotionHistory), c.MotionThreshold, false) alg := &MOG{ area: c.MotionMinArea, bs: &bs, knl: gocv.GetStructuringElement(gocv.MorphRect, image.Pt(3, 3)), debugging: newWindows("MOG"), } return NewMotion(dst, alg, c) } // MOG is a motion detection algorithm. MoG is short for // Mixture of Gaussians method. type MOG struct { debugging debugWindows area float64 // The minimum area that a contour can be found in. bs *gocv.BackgroundSubtractorMOG2 // Uses the MOG 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 *MOG) 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 *MOG) 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 }