X-Git-Url: http://git.euphorik.ch/?p=master-thesis.git;a=blobdiff_plain;f=Parasitemia%2FParasitemia%2FImgTools.fs;h=c34b9c76469c17d49d4af615781391db67cfb08a;hp=cc09405b3477005646cf8f560eea32016e54dbcf;hb=e76da913cd58078ad2479357b2430ed62a6e0777;hpb=ba64921fb9a0c36cd8cf802cbf1b2c0f79bc25f6 diff --git a/Parasitemia/Parasitemia/ImgTools.fs b/Parasitemia/Parasitemia/ImgTools.fs index cc09405..c34b9c7 100644 --- a/Parasitemia/Parasitemia/ImgTools.fs +++ b/Parasitemia/Parasitemia/ImgTools.fs @@ -9,14 +9,23 @@ open Emgu.CV.Structure open Utils +// Normalize image values between 0uy and 255uy. +let normalizeAndConvert (img: Image) : Image = + let min = ref [| 0.0 |] + let minLocation = ref <| [| Point() |] + let max = ref [| 0.0 |] + let maxLocation = ref <| [| Point() |] + img.MinMax(min, max, minLocation, maxLocation) + ((img - (!min).[0]) / ((!max).[0] - (!min).[0]) * 255.0).Convert() + let gaussianFilter (img : Image<'TColor, 'TDepth>) (standardDeviation : float) : Image<'TColor, 'TDepth> = let size = 2 * int (ceil (4.0 * standardDeviation)) + 1 img.SmoothGaussian(size, size, standardDeviation, standardDeviation) -// Zhang and Suen algorithm. +// Zhang and Suen algorithm. // Modify 'mat' in place. -let thin (mat: Matrix) = - let neighbors = [| +let thin (mat: Matrix) = + let neighbors = [| (-1, 0) // p2 (-1, 1) // p3 ( 0, 1) // p4 @@ -32,15 +41,15 @@ let thin (mat: Matrix) = let mutable data2 = Array2D.zeroCreate h w // Return the list of neighbor values. - let neighborsValues (p1i, p1j) = - Array.map (fun (ni, nj) -> + let neighborsValues (p1i, p1j) = + Array.map (fun (ni, nj) -> let pi = p1i + ni let pj = p1j + nj if pi < 0 || pi >= h || pj < 0 || pj >= w then 0uy else data1.[pi, pj] ) neighbors // Return the number of 01 pattern in 'values' in a circular way. - let pattern01 (values: byte[]) = + let pattern01 (values: byte[]) = let mutable nb = 0 let mutable lastValue = 255uy for v in values do @@ -52,7 +61,7 @@ let thin (mat: Matrix) = then nb <- nb + 1 nb - + let mutable pixelChanged = true let mutable oddIteration = true while pixelChanged do @@ -75,16 +84,22 @@ let thin (mat: Matrix) = else data2.[i, j] <- 0uy - oddIteration <- not oddIteration + oddIteration <- not oddIteration let tmp = data1 data1 <- data2 data2 <- tmp - + + + +let pop (l: List<'a>) : 'a = + let n = l.[l.Count - 1] + l.RemoveAt(l.Count - 1) + n // Remove all 8-connected pixels with an area equal or greater than 'areaSize'. // Modify 'mat' in place. let removeArea (mat: Matrix) (areaSize: int) = - let neighbors = [| + let neighbors = [| (-1, 0) // p2 (-1, 1) // p3 ( 0, 1) // p4 @@ -93,29 +108,24 @@ let removeArea (mat: Matrix) (areaSize: int) = ( 1, -1) // p7 ( 0, -1) // p8 (-1, -1) |] // p9 - + let mat' = new Matrix(mat.Size) let w = mat'.Width let h = mat'.Height - mat.CopyTo(mat') - + mat.CopyTo(mat') + let data = mat.Data let data' = mat'.Data for i in 0..h-1 do for j in 0..w-1 do - if data'.[i, j] = 1uy + if data'.[i, j] = 1uy then let neighborhood = List<(int*int)>() let neighborsToCheck = List<(int*int)>() - neighborsToCheck.Add((i, j)) + neighborsToCheck.Add((i, j)) data'.[i, j] <- 0uy - let pop (l: List<'a>) : 'a = - let n = l.[l.Count - 1] - l.RemoveAt(l.Count - 1) - n - while neighborsToCheck.Count > 0 do let (ci, cj) = pop neighborsToCheck neighborhood.Add((ci, cj)) @@ -131,47 +141,107 @@ let removeArea (mat: Matrix) (areaSize: int) = for (ni, nj) in neighborhood do data.[ni, nj] <- 0uy +let connectedComponents (img: Image) (startPoints: List) : List = + let w = img.Width + let h = img.Height + + let pointChecked = HashSet() + let pointToCheck = List(startPoints); + + let data = img.Data + + while pointToCheck.Count > 0 do + let next = pop pointToCheck + pointChecked.Add(next) |> ignore + for ny in -1 .. 1 do + for nx in -1 .. 1 do + if ny <> 0 && nx <> 0 + then + let p = Point(next.X + nx, next.Y + ny) + if p.X >= 0 && p.X < w && p.Y >= 0 && p.Y < h && data.[p.Y, p.X, 0] > 0uy && not (pointChecked.Contains p) + then + pointToCheck.Add(p) + + List(pointChecked) -let saveImg (img: Image<'TColor, 'TDepth>) (name: string) = - img.Save("output/" + name) - -let saveMat (mat: Matrix<'TDepth>) (name: string) = +let saveImg (img: Image<'TColor, 'TDepth>) (filepath: string) = + img.Save(filepath) + + +let saveMat (mat: Matrix<'TDepth>) (filepath: string) = use img = new Image(mat.Size) mat.CopyTo(img) - saveImg img name - + saveImg img filepath + (*let drawEllipse (img: Image<'TColor, 'TDepth>) (e: Types.Ellipse) (color: 'TColor) = let e' = Ellipse(PointF(float32 e.cx, float32 e.cy), SizeF(2.0f * float32 e.a, 2.0f * float32 e.b), float32 e.alpha) img.Draw(e', color)*) -let drawLine (img: Image<'TColor, 'TDepth>) (color: 'TColor) (x0: float) (y0: float) (x1: float) (y1: float) = +let drawLine (img: Image<'TColor, 'TDepth>) (color: 'TColor) (x0: int) (y0: int) (x1: int) (y1: int) = + img.Draw(LineSegment2D(Point(x0, y0), Point(x1, y1)), color, 1); + +let drawLineF (img: Image<'TColor, 'TDepth>) (color: 'TColor) (x0: float) (y0: float) (x1: float) (y1: float) = let x0, y0, x1, y1 = roundInt(x0), roundInt(y0), roundInt(x1), roundInt(y1) + drawLine img color x0 y0 x1 y1 - img.Draw(LineSegment2D(Point(x0, y0), Point(x1, y1)), color, 1); +let drawEllipse (img: Image<'TColor, 'TDepth>) (e: Types.Ellipse) (color: 'TColor) = + let cosAlpha = cos e.Alpha + let sinAlpha = sin e.Alpha -let drawEllipse (img: Image<'TColor, 'TDepth>) (e: Types.Ellipse) (color: 'TColor) = - let cosAlpha = cos e.alpha - let sinAlpha = sin e.alpha - let mutable x0 = 0.0 let mutable y0 = 0.0 let mutable first_iteration = true - + let n = 40 let thetaIncrement = 2.0 * Math.PI / (float n) - + for theta in 0.0 .. thetaIncrement .. 2.0 * Math.PI do let cosTheta = cos theta let sinTheta = sin theta - let x = e.cx + cosAlpha * e.a * cosTheta - sinAlpha * e.b * sinTheta - let y = e.cy + sinAlpha * e.a * cosTheta + cosAlpha * e.b * sinTheta + let x = e.Cx + cosAlpha * e.A * cosTheta - sinAlpha * e.B * sinTheta + let y = e.Cy + sinAlpha * e.A * cosTheta + cosAlpha * e.B * sinTheta if not first_iteration then - drawLine img color x0 y0 x y + drawLineF img color x0 y0 x y else first_iteration <- false x0 <- x - y0 <- y \ No newline at end of file + y0 <- y + +let drawEllipses (img: Image<'TColor, 'TDepth>) (ellipses: Types.Ellipse list) (color: 'TColor) = + List.iter (fun e -> drawEllipse img e color) ellipses + + +let rngCell = System.Random() +let drawCell (img: Image) (drawCellContent: bool) (c: Types.Cell) = + if drawCellContent + then + let colorB = rngCell.Next(20, 70) + let colorG = rngCell.Next(20, 70) + let colorR = rngCell.Next(20, 70) + + for y in 0 .. c.elements.Height - 1 do + for x in 0 .. c.elements.Width - 1 do + if c.elements.[y, x] > 0uy + then + let dx, dy = c.center.X - c.elements.Width / 2, c.center.Y - c.elements.Height / 2 + let b = img.Data.[y + dy, x + dx, 0] |> int + let g = img.Data.[y + dy, x + dx, 1] |> int + let r = img.Data.[y + dy, x + dx, 2] |> int + img.Data.[y + dy, x + dx, 0] <- if b + colorB > 255 then 255uy else byte (b + colorB) + img.Data.[y + dy, x + dx, 1] <- if g + colorG > 255 then 255uy else byte (g + colorG) + img.Data.[y + dy, x + dx, 2] <- if r + colorR > 255 then 255uy else byte (r + colorR) + + let crossColor = match c.cellClass with + | Types.HealthyRBC -> Bgr(255.0, 0.0, 0.0) + | Types.InfectedRBC -> Bgr(0.0, 0.0, 255.0) + | Types.Peculiar -> Bgr(0.0, 0.0, 0.0) + + drawLine img crossColor (c.center.X - 3) c.center.Y (c.center.X + 3) c.center.Y + drawLine img crossColor c.center.X (c.center.Y - 3) c.center.X (c.center.Y + 3) + +let drawCells (img: Image) (drawCellContent: bool) (cells: Types.Cell list) = + List.iter (fun c -> drawCell img drawCellContent c) cells \ No newline at end of file