//go:build withcv // +build withcv /* DESCRIPTION Testing functions for the turbidity sensor using images from previous experiment. AUTHORS Russell Stanley LICENSE Copyright (C) 2021-2022 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 turbidity import ( "fmt" "io" "testing" "bitbucket.org/ausocean/utils/logging" "gocv.io/x/gocv" "gonum.org/v1/gonum/stat" "gonum.org/v1/plot" "gonum.org/v1/plot/plotutil" "gopkg.in/natefinch/lumberjack.v2" ) const ( nImages = 13 // Number of images to test. (Max 13) nSamples = 10 // Number of samples for each image. (Max 10) increment = 2.5 // Increment of the turbidity level. ) // Logging configuration. const ( logPath = "/var/log/netsender/netsender.log" logMaxSize = 500 // MB logMaxBackup = 10 logMaxAge = 28 // days logVerbosity = logging.Info logSuppress = true ) // TestImages will read a library of test images and calculate the sharpness and contrast scores. // A plot of the results will be generated and stored in the plots directory. func TestImages(t *testing.T) { const ( k1, k2 = 4, 4 filterSize = 3 scale, alpha = 1.0, 1.0 ) // Create lumberjack logger. fileLog := &lumberjack.Logger{ Filename: logPath, MaxSize: logMaxSize, MaxBackups: logMaxBackup, MaxAge: logMaxAge, } log := logging.New(logVerbosity, io.MultiWriter(fileLog), logSuppress) template := gocv.IMRead("images/template.jpg", gocv.IMReadGrayScale) transformMatrix, err := FindTransform("images/default.jpg", "images/template.jpg") if err != nil { t.Fatalf("could not find transformation: %v", err) } t.Log(formatMat(transformMatrix)) imgs := make([][]gocv.Mat, nImages) // Load test images. for i := range imgs { imgs[i] = make([]gocv.Mat, nSamples) for j := range imgs[i] { imgs[i][j] = gocv.IMRead(fmt.Sprintf("images/t-%v/000%v.jpg", i, j), gocv.IMReadColor) } } ts, err := NewTurbiditySensor(template, transformMatrix, k1, k2, filterSize, scale, alpha, log) if err != nil { t.Fatalf("could not create turbidity sensor: %v", err) } results, err := NewResults(nImages) if err != nil { t.Fatalf("could not create results: %v", err) } // Score each image by calculating the average score from camera burst. for i := range imgs { // Evaluate camera burst. sample_result, err := ts.Evaluate(imgs[i]) if err != nil { t.Fatalf("evaluation Failed: %v", err) } // Add the average result from camera burst. results.Update(stat.Mean(sample_result.Sharpness, nil), stat.Mean(sample_result.Contrast, nil), float64(i)*increment, i) } err = plotResults(results.Turbidity, normalize(results.Sharpness), normalize(results.Contrast)) if err != nil { t.Fatalf("plotting Failed: %v", err) } t.Logf("Sharpness: %v", results.Sharpness) t.Logf("Contrast: %v", results.Contrast) } // plotResults plots sharpness and contrast scores against the level of almond milk in the container func plotResults(x, sharpness, contrast []float64) error { err := plotToFile( "Results", "Almond Milk (ml)", "Score", func(p *plot.Plot) error { return plotutil.AddLinePoints(p, "Contrast", plotterXY(x, contrast), "Sharpness", plotterXY(x, sharpness), ) }, ) if err != nil { return fmt.Errorf("Could not plot results: %w", err) } return nil } // formatMat creates a formatted transformation matrix string for use in vidgrind. func formatMat(transformMatrix gocv.Mat) string { var out string for i := 0; i < transformMatrix.Rows(); i++ { for j := 0; j < transformMatrix.Cols(); j++ { out += fmt.Sprintf(" %.10f", transformMatrix.GetDoubleAt(i, j)) if i < 2 || j < 2 { out += "," } } } return out }