mirror of https://bitbucket.org/ausocean/av.git
144 lines
4.3 KiB
Go
144 lines
4.3 KiB
Go
// +build !circleci
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/*
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DESCRIPTION
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A filter that detects motion and discards frames without motion. The
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filter uses a K-Nearest Neighbours (KNN) to determine what is
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background and what is foreground.
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AUTHORS
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Ella Pietraroia <ella@ausocean.org>
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LICENSE
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KNN.go is Copyright (C) 2019 the Australian Ocean Lab (AusOcean)
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It is free software: you can redistribute it and/or modify them
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under the terms of the GNU General Public License as published by the
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Free Software Foundation, either version 3 of the License, or (at your
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option) any later version.
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It is distributed in the hope that it will be useful, but WITHOUT
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ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
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FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
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for more details.
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You should have received a copy of the GNU General Public License
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in gpl.txt. If not, see http://www.gnu.org/licenses.
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*/
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package filter
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import (
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"fmt"
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"image"
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"io"
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"gocv.io/x/gocv"
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)
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// KNN is a filter that provides basic motion detection. KNN is short for
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// K-Nearest Neighbours method.
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type KNN struct {
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debugWindows
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dst io.WriteCloser // Destination to which motion containing frames go.
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area float64 // The minimum area that a contour can be found in.
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bs *gocv.BackgroundSubtractorKNN // Uses the KNN algorithm to find the difference between the current and background frame.
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knl gocv.Mat // Matrix that is used for calculations.
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hold [][]byte // Will hold all frames up to hf (so only every hf frame is motion detected).
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hf int // The number of frames to be held.
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hfCount int // Counter for the hold array.
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scale float64 // The factor that frames will be downscaled by for motion detection.
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}
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// NewKNN returns a pointer to a new KNN filter struct.
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func NewKNN(dst io.WriteCloser, area, threshold float64, history, kernelSize int, hf int, scaleFactor int) *KNN {
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bs := gocv.NewBackgroundSubtractorKNNWithParams(history, threshold, false)
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k := gocv.GetStructuringElement(gocv.MorphRect, image.Pt(kernelSize, kernelSize))
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m := &KNN{
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dst: dst,
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area: area,
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bs: &bs,
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knl: k,
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hold: make([][]byte, hf-1),
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hf: hf,
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scale: 1 / float64(scaleFactor),
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}
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m.newWindows("KNN")
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return m
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}
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// Implements io.Closer.
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// Close frees resources used by gocv, because it has to be done manually, due to
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// it using c-go.
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func (m *KNN) Close() error {
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m.bs.Close()
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m.knl.Close()
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m.closeWindows()
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return nil
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}
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// Implements io.Writer.
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// Write applies the motion filter to the video stream. Only frames with motion
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// are written to the destination encoder, frames without are discarded.
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func (m *KNN) Write(f []byte) (int, error) {
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if m.hfCount < (m.hf - 1) {
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m.hold[m.hfCount] = f
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m.hfCount++
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return len(f), nil
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}
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m.hfCount = 0
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img, err := gocv.IMDecode(f, gocv.IMReadColor)
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if err != nil {
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return 0, fmt.Errorf("can't decode image: %w", err)
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}
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defer img.Close()
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imgDelta := gocv.NewMat()
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defer imgDelta.Close()
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// Downsize image to speed up calculations.
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gocv.Resize(img, &img, image.Point{}, m.scale, m.scale, gocv.InterpolationNearestNeighbor)
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// Seperate foreground and background.
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m.bs.Apply(img, &imgDelta)
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// Threshold imgDelta.
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gocv.Threshold(imgDelta, &imgDelta, 25, 255, gocv.ThresholdBinary)
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// Remove noise.
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gocv.Erode(imgDelta, &imgDelta, m.knl)
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gocv.Dilate(imgDelta, &imgDelta, m.knl)
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// Fill small holes.
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gocv.Dilate(imgDelta, &imgDelta, m.knl)
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gocv.Erode(imgDelta, &imgDelta, m.knl)
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// Find contours and reject ones with a small area.
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var contours [][]image.Point
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allContours := gocv.FindContours(imgDelta, gocv.RetrievalExternal, gocv.ChainApproxSimple)
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for _, c := range allContours {
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if gocv.ContourArea(c) > m.area {
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contours = append(contours, c)
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}
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}
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// Draw debug information.
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m.showDebug(img, imgDelta, len(contours) > 0, contours)
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// Don't write to destination if there is no motion.
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if len(contours) == 0 {
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return len(f), nil
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}
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// Write to destination, past 4 frames then current frame.
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for i, h := range m.hold {
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_, err := m.dst.Write(h)
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m.hold[i] = nil
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if err != nil {
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return len(f), fmt.Errorf("could not write previous frames: %w", err)
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}
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}
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return m.dst.Write(f)
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}
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