av/filter/knn.go

133 lines
3.7 KiB
Go

//go:build !nocv
// +build !nocv
/*
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"
"gocv.io/x/gocv"
"bitbucket.org/ausocean/av/revid/config"
)
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 i := 0; i < allContours.Size(); i++ {
if gocv.ContourArea(allContours.At(i)) > m.area {
contours = append(contours, allContours.At(i).ToPoints())
}
}
// Draw debug information.
m.debugging.show(*img, imgDelta, len(contours) > 0, &contours)
// Return if there is motion.
return len(contours) > 0
}