// +build !nocv package main import ( "errors" "fmt" "image" "math" "gocv.io/x/gocv" ) // Turbidity Sensor. type TurbiditySensor struct { template, standard gocv.Mat k1, k2, sobelFilterSize int alpha, scale float64 } // Given a slice of test images, return the sharpness and contrast scores. func (ts TurbiditySensor) Evaluate(imgs []gocv.Mat) (Results, error) { var result Results result.new(len(imgs)) for i := range imgs { // Transform image. marker, err := ts.Transform(imgs[i]) if err != nil { return result, fmt.Errorf("Image %v: %w", i, err) } // Apply sobel filter. edge := ts.Sobel(marker) // Evaluate image. scores, err := ts.EvaluateImage(marker, edge) if err != nil { return result, err } result.update(scores[0], scores[1], float64(i*10), i) } return result, nil } // Evaluate image sharpness and contrast using blocks of size k1 by k2. Return a slice of the respective scores. func (ts TurbiditySensor) EvaluateImage(img, edge gocv.Mat) ([]float64, error) { result := make([]float64, 2) // [0.0, 0.0] if img.Rows()%ts.k1 != 0 || img.Cols()%ts.k2 != 0 { return nil, fmt.Errorf("Dimensions not compatible (%v, %v)", ts.k1, ts.k2) } lStep := int(img.Rows() / ts.k1) kStep := int(img.Cols() / ts.k2) for l := 0; l < img.Rows(); l = l + lStep { for k := 0; k < img.Cols(); k = k + kStep { // Enhancement Measure Estimation (EME), provides a measure of the sharpness. err := ts.EvaluateBlock(edge, l, k, l+lStep, k+kStep, result, "EME", ts.alpha) if err != nil { return nil, err } // AMEE, provides a measure of the contrast. err = ts.EvaluateBlock(img, l, k, l+lStep, k+kStep, result, "AMEE", ts.alpha) if err != nil { return nil, err } } } // EME. result[0] = 2.0 / (float64(ts.k1) * float64(ts.k2)) * result[0] // AMEE. result[1] = -1.0 / (float64(ts.k1) * float64(ts.k2)) * result[1] return result, nil } // Evaluate a block within an image and add to to the result slice. func (ts TurbiditySensor) EvaluateBlock(img gocv.Mat, xStart, yStart, xEnd, yEnd int, result []float64, operation string, alpha float64) error { max := -math.MaxFloat64 min := math.MaxFloat64 for i := xStart; i < xEnd; i++ { for j := yStart; j < yEnd; j++ { value := float64(img.GetUCharAt(i, j)) // Check max/min conditions, zero values are ignored. if value > max && value != 0.0 { max = value } if value < min && value != 0.0 { min = value } } } // Blocks which have no information are ignored. if max != -math.MaxFloat64 && min != math.MaxFloat64 && max != min { if operation == "EME" { result[0] += math.Log(max / min) } else if operation == "AMEE" { contrast := (max + min) / (max - min) result[1] += math.Pow(alpha*(contrast), alpha) * math.Log(contrast) } else { return fmt.Errorf("Invalid operation: %v", operation) } } return nil } // Search image for matching template. Returns the transformed image which best match the template. func (ts TurbiditySensor) Transform(img gocv.Mat) (gocv.Mat, error) { out := gocv.NewMat() mask := gocv.NewMat() corners_img := gocv.NewMat() corners_template := gocv.NewMat() // Find corners in image. if !gocv.FindChessboardCorners(ts.standard, image.Pt(3, 3), &corners_img, gocv.CalibCBNormalizeImage) { // Apply default if transformation fails. fmt.Println("Corner detection failed applying standard transformation") if !gocv.FindChessboardCorners(ts.standard, image.Pt(3, 3), &corners_img, gocv.CalibCBNormalizeImage) { return out, errors.New("Could not find corners in default image") } } // Find corners in template. if !gocv.FindChessboardCorners(ts.template, image.Pt(3, 3), &corners_template, gocv.CalibCBNormalizeImage) { return out, errors.New("Could not find corners in template") } // Find and apply transformation. H := gocv.FindHomography(corners_img, &corners_template, gocv.HomograpyMethodRANSAC, 3.0, &mask, 2000, 0.995) gocv.WarpPerspective(img, &out, H, image.Pt(ts.template.Rows(), ts.template.Cols())) return out, nil } // Apply sobel filter to an image with a given scale and return the result. func (ts TurbiditySensor) Sobel(img gocv.Mat) gocv.Mat { dx := gocv.NewMat() dy := gocv.NewMat() sobel := gocv.NewMat() // Apply filter. gocv.Sobel(img, &dx, gocv.MatTypeCV64F, 0, 1, ts.sobelFilterSize, ts.scale, 0.0, gocv.BorderConstant) gocv.Sobel(img, &dy, gocv.MatTypeCV64F, 1, 0, ts.sobelFilterSize, ts.scale, 0.0, gocv.BorderConstant) // Convert to unsigned. gocv.ConvertScaleAbs(dx, &dx, 1.0, 0.0) gocv.ConvertScaleAbs(dy, &dy, 1.0, 0.0) // Add x and y components. gocv.AddWeighted(dx, 0.5, dy, 0.5, 0, &sobel) return sobel }