2022-01-12 04:55:58 +03:00
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//go:build !nocv
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// +build !nocv
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2022-01-06 06:25:40 +03:00
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/*
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DESCRIPTION
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Testing functions for the turbidity sensor using images from
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previous experiment.
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AUTHORS
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Russell Stanley <russell@ausocean.org>
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LICENSE
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2022-01-07 04:10:20 +03:00
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Copyright (C) 2021-2022 the Australian Ocean Lab (AusOcean)
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2022-01-06 06:25:40 +03:00
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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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2022-01-07 04:10:20 +03:00
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package turbidity
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import (
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"fmt"
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"io"
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"testing"
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2022-02-04 06:16:55 +03:00
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"bitbucket.org/ausocean/utils/logger"
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"gocv.io/x/gocv"
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"gonum.org/v1/gonum/stat"
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"gonum.org/v1/plot"
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"gonum.org/v1/plot/plotutil"
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"gopkg.in/natefinch/lumberjack.v2"
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)
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const (
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nImages = 10 // Number of images to test. (Max 13)
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nSamples = 1 // Number of samples for each image. (Max 10)
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increment = 2.5 // Increment of the turbidity level.
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)
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// Logging configuration.
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const (
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logPath = "/var/log/netsender/netsender.log"
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logMaxSize = 500 // MB
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logMaxBackup = 10
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logMaxAge = 28 // days
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logVerbosity = logger.Info
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logSuppress = true
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)
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2022-01-12 04:55:58 +03:00
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// TestImages will read a library of test images and calculate the sharpness and contrast scores.
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// A plot of the results will be generated and stored in the plots directory.
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func TestImages(t *testing.T) {
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const (
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k1, k2 = 8, 8
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filterSize = 3
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scale, alpha = 1.0, 1.0
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)
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// Create lumberjack logger.
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fileLog := &lumberjack.Logger{
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Filename: logPath,
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MaxSize: logMaxSize,
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MaxBackups: logMaxBackup,
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MaxAge: logMaxAge,
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}
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log := *logger.New(logVerbosity, io.MultiWriter(fileLog), logSuppress)
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template := gocv.IMRead("images/template.jpg", gocv.IMReadGrayScale)
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standard := gocv.IMRead("images/default.jpg", gocv.IMReadGrayScale)
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imgs := make([][]gocv.Mat, nImages)
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// Load test images.
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for i := range imgs {
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imgs[i] = make([]gocv.Mat, nSamples)
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for j := range imgs[i] {
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imgs[i][j] = gocv.IMRead(fmt.Sprintf("images/t-%v/000%v.jpg", i, j), gocv.IMReadGrayScale)
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}
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}
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ts, err := NewTurbiditySensor(template, standard, k1, k2, filterSize, scale, alpha, log)
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if err != nil {
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t.Fatalf("could not create turbidity sensor: %v", err)
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}
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results, err := NewResults(nImages)
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if err != nil {
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t.Fatalf("could not create results: %v", err)
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}
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// Score each image by calculating the average score from camera burst.
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for i := range imgs {
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// Evaluate camera burst.
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sample_result, err := ts.Evaluate(imgs[i])
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if err != nil {
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t.Fatalf("evaluation Failed: %v", err)
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}
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// Add the average result from camera burst.
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results.Update(stat.Mean(sample_result.Sharpness, nil), stat.Mean(sample_result.Contrast, nil), float64(i)*increment, i)
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}
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err = plotResults(results.Turbidity, results.Sharpness, results.Contrast)
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if err != nil {
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t.Fatalf("plotting Failed: %v", err)
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}
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t.Logf("Sharpness: %v", results.Sharpness)
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t.Logf("Contrast: %v", results.Contrast)
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}
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2022-01-12 04:55:58 +03:00
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// plotResults plots sharpness and contrast scores against the level of almond milk in the container
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func plotResults(x, sharpness, contrast []float64) error {
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err := plotToFile(
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"Results",
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"Almond Milk (ml)",
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"Score",
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func(p *plot.Plot) error {
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return plotutil.AddLinePoints(p,
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"Contrast", plotterXY(x, contrast),
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"Sharpness", plotterXY(x, sharpness),
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)
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},
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)
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if err != nil {
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return fmt.Errorf("Could not plot results: %w", err)
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}
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return nil
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}
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