mirror of https://bitbucket.org/ausocean/av.git
turbidity files tagged for (not) nocv
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parent
74355b1ba8
commit
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2
go.mod
2
go.mod
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@ -1,6 +1,6 @@
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module bitbucket.org/ausocean/av
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go 1.17
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go 1.16
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require (
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bitbucket.org/ausocean/iot v1.3.0
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@ -0,0 +1,150 @@
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// +build !nocv
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package main
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import (
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"fmt"
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"log"
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"math"
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"gonum.org/v1/plot"
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"gonum.org/v1/plot/plotter"
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"gonum.org/v1/plot/plotutil"
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"gonum.org/v1/plot/vg"
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"gocv.io/x/gocv"
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)
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const (
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nImages = 13
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nSamples = 10
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)
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func main() {
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// Load template and standard image.
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template := gocv.IMRead("template.jpg", gocv.IMReadGrayScale)
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standard := gocv.IMRead("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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// Create turbidity sensor.
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ts := TurbiditySensor{template: template, standard: standard, k1: 8, k2: 8, sobelFilterSize: 3, scale: 1.0, alpha: 1.0}
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var finalRes Results
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finalRes.new(nImages)
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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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log.Fatalf("Evaluation Failed: %v", err)
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}
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// Add the average result from camera burst.
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finalRes.update(average(sample_result.saturation), average(sample_result.contrast), float64(i)*2.5, i)
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}
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// Plot the final results.
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err := plotResults(finalRes.turbidity, normalize(finalRes.saturation), normalize(finalRes.contrast))
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if err != nil {
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log.Fatalf("Plotting Failed: %v", err)
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}
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log.Printf("Saturation: %v", finalRes.saturation)
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log.Printf("Contrast: %v", finalRes.contrast)
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}
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// Plotting Functions.
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// Normalize values in a slice between 0 and 1.
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func normalize(slice []float64) []float64 {
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max := -math.MaxFloat64
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min := math.MaxFloat64
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out := make([]float64, len(slice))
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if len(slice) <= 1 {
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return slice
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}
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for i := range slice {
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if slice[i] > max {
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max = slice[i]
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}
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if slice[i] < min {
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min = slice[i]
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}
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}
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for i := range slice {
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out[i] = (slice[i] - min) / (max - min)
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}
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return out
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}
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// Return the average of a slice.
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func average(slice []float64) float64 {
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out := 0.0
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for i := range slice {
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out += slice[i]
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}
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return out / float64(len(slice))
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}
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func plotResults(x, saturation, 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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"Saturation", plotterXY(x, saturation),
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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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// plotToFile creates a plot with a specified name and x&y titles using the
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// provided draw function, and then saves to a PNG file with filename of name.
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func plotToFile(name, xTitle, yTitle string, draw func(*plot.Plot) error) error {
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p := plot.New()
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p.Title.Text = name
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p.X.Label.Text = xTitle
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p.Y.Label.Text = yTitle
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err := draw(p)
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if err != nil {
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return fmt.Errorf("could not draw plot contents: %w", err)
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}
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if err := p.Save(15*vg.Centimeter, 15*vg.Centimeter, "plots/"+name+".png"); err != nil {
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return fmt.Errorf("could not save plot: %w", err)
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}
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return nil
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}
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// plotterXY provides a plotter.XYs type value based on the given x and y data.
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func plotterXY(x, y []float64) plotter.XYs {
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xy := make(plotter.XYs, len(x))
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for i := range x {
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xy[i].X = x[i]
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xy[i].Y = y[i]
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}
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return xy
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}
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@ -1,3 +1,5 @@
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// +build !nocv
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package main
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// struct to hold the results of the turbidity sensor.
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@ -1,3 +1,5 @@
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// +build !nocv
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package main
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import (
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