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) : Result =

    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)    
    let threshold = CvInvoke.Threshold(magnitudesByte, edges, 0.0, 1.0, CvEnum.ThresholdType.Otsu ||| CvEnum.ThresholdType.Binary)

//    let filteredGreenMat = new Matrix<float32>(filteredGreen.Size)
//    filteredGreen.CopyTo(filteredGreenMat)
    let parasites = ParasitesMarker.find green filteredGreen config
    
    saveImg parasites.darkStain "parasites_dark_stain.png"
    saveImg parasites.stain "parasites_stain.png"
    saveImg parasites.infection "parasites_infection.png"
    
    logTime "Finding edges" (fun() ->
        thin edges)

    logTime "Removing small connected components" (fun () -> 
        removeArea edges 12)
    
    saveMat (edges * 255.0) "edges.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)
                
    drawEllipses img ellipses (Bgr(0.0, 255.0, 255.0))
    //saveImg img "ellipses.png"

    { RBCPositions = []; infectedRBCPositions = []; img = img }

    // 
   
    (*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 <|