-module ImageAnalysis
-
-open System
-open System.Drawing
-
-open Emgu.CV
-open Emgu.CV.Structure
-
-open Utils
-open ImgTools
-open Config
-open Types
-
-(*type Result = {
- RBCPositions : Point list
- infectedRBCPositions : Point list
- img: Image<Bgr, byte>
-}*)
-
-let doAnalysis (img: Image<Bgr, byte>) (config: Config) : Classifier.Cell list =
-
- let imgFloat = img.Convert<Bgr, float32>()
- use scaledImg = if config.scale = 1.0 then imgFloat else imgFloat.Resize(config.scale, CvEnum.Inter.Area)
-
- (*use scaledImg =
- if config.scale = 1.0
- then
- img
- else
- let m = new Mat()
- CvInvoke.Resize(img, m, Size(roundInt (float img.Size.Width * config.scale), roundInt (float img.Size.Height * config.scale)))
- m*)
-
- use green = scaledImg.Item(1)
-
- //use green = new Matrix<byte>(scaledImg.Size)
- //CvInvoke.MixChannels(scaledImg, green, [| 1; 0 |])
-
- //let greenMatrix = new Matrix<byte>(green.Height, green.Width, green.DataPointer)
-
- //let test = greenMatrix.[10, 10]
-
- use filteredGreen = (gaussianFilter green config.doGSigma1) - config.doGLowFreqPercentageReduction * (gaussianFilter green config.doGSigma2)
-
- use sobelKernel =
- new ConvolutionKernelF(array2D [[ 1.0f; 0.0f; -1.0f ]
- [ 2.0f; 0.0f; -2.0f ]
- [ 1.0f; 0.0f; -1.0f ]], Point(0, 0))
-
- use xEdges = filteredGreen.Convolution(sobelKernel).Convert<Gray, float>()
- use yEdges = filteredGreen.Convolution(sobelKernel.Transpose()).Convert<Gray, float>()
-
- let xEdgesData = xEdges.Data
- let yEdgesData = yEdges.Data
- for r in 0..xEdges.Rows-1 do
- xEdgesData.[r, 0, 0] <- 0.0
- xEdgesData.[r, xEdges.Cols-1, 0] <- 0.0
- yEdgesData.[r, 0, 0] <- 0.0
- yEdgesData.[r, xEdges.Cols-1, 0] <- 0.0
-
- for c in 0..xEdges.Cols-1 do
- xEdgesData.[0, c, 0] <- 0.0
- xEdgesData.[xEdges.Rows-1, c, 0] <- 0.0
- yEdgesData.[0, c, 0] <- 0.0
- yEdgesData.[xEdges.Rows-1, c, 0] <- 0.0
-
- use magnitudes = new Matrix<float>(xEdges.Size)
- CvInvoke.CartToPolar(xEdges, yEdges, magnitudes, new Mat()) // Compute the magnitudes (without angles).
-
- let min = ref 0.0
- let minLocation = ref <| Point()
- let max = ref 0.0
- let maxLocation = ref <| Point()
- magnitudes.MinMax(min, max, minLocation, maxLocation)
-
- use magnitudesByte = ((magnitudes / !max) * 255.0).Convert<byte>() // Otsu from OpenCV only support 'byte'.
- use edges = new Matrix<byte>(xEdges.Size)
- CvInvoke.Threshold(magnitudesByte, edges, 0.0, 1.0, CvEnum.ThresholdType.Otsu ||| CvEnum.ThresholdType.Binary) |> ignore
-
- logTime "Finding edges" (fun() ->
- thin edges)
-
- logTime "Removing small connected components" (fun () ->
- removeArea edges 12)
-
- saveMat (edges * 255.0) "edges.png"
-
-
- let kmediansResults = KMedians.kmedians filteredGreen 1.0
-
- let parasites = ParasitesMarker.find green filteredGreen kmediansResults config
-
- saveImg parasites.darkStain "parasites_dark_stain.png"
- saveImg parasites.stain "parasites_stain.png"
- saveImg parasites.infection "parasites_infection.png"
-
- let radiusRange = config.scale * 20.0, config.scale * 40.0
- let windowSize = roundInt (1.6 * (snd radiusRange))
- let factorNbPick = 1.5
- let ellipses = logTime "Finding ellipses" (fun () ->
- Ellipse.find edges xEdges yEdges radiusRange windowSize factorNbPick) |> List.filter (fun e -> not (e.CutAVericalLine 0.0) &&
- not (e.CutAVericalLine (float img.Width)) &&
- not (e.CutAnHorizontalLine 0.0) &&
- not (e.CutAnHorizontalLine (float img.Height)))
-
- drawEllipses img ellipses (Bgr(0.0, 255.0, 255.0))
- //saveImg img "ellipses.png"
-
- Classifier.findCells ellipses parasites kmediansResults.fg
-
- //
-
- (*use imageHSV = scaledImage.Convert<Hsv, uint8>()
- let H, S = match imageHSV.Split() with // Warning: H is from 0 to 179°.
- | [| H; S; _|] -> H, S
- | _ -> failwith "unable to split the HSV channels"
-
- let hueShiftValue = 175
- // Modulo operator doesn't exist on matrix thus we have to apply a function to every pixels.
- let correctedH : Image<Gray, byte> = H.Convert(fun b _ _ ->
- (255 - int(b) * 255 / 179 + hueShiftValue) % 256 |> byte
- )
-
- let correctedS : Image<Gray, byte> = S.Not()
-
- let filteredH = correctedH.SmoothMedian(5)
- let filteredS = correctedS.SmoothMedian(5)*)
-
- //let greenChannel = scaledImage.Item(1)
-
- //let filteredImage = (gaussianFilter greenChannel config.doGSigma1) - config.doGLowFreqPercentageReduction * (gaussianFilter greenChannel config.doGSigma2)
-
- // let filteredImage = greenChannel.ThresholdAdaptive(Gray(255.), CvEnum.AdaptiveThresholdType.GaussianC, CvEnum.ThresholdType.Binary, 61, Gray(5.0))
- // let thresholdedImage = filteredImage.CopyBlank()
-
- // CvInvoke.Threshold(filteredImage, thresholdedImage, 0., 255., CvEnum.ThresholdType.Otsu ||| CvEnum.ThresholdType.BinaryInv) |> ignore
-
- // filteredImage <|
\ No newline at end of file