X-Git-Url: http://git.euphorik.ch/?p=master-thesis.git;a=blobdiff_plain;f=Parasitemia%2FParasitemia%2FImgTools.fs;h=cee21c77d5c60fa26c8e25f4c2afa34c15056543;hp=7253390b31813230a69e47926db113f3eba9bd53;hb=d0c85068bb98a7999ed994f02669befa70edd5f9;hpb=10afa9a402eb88c8e073fe8b0d607faa25230eef diff --git a/Parasitemia/Parasitemia/ImgTools.fs b/Parasitemia/Parasitemia/ImgTools.fs index 7253390..cee21c7 100644 --- a/Parasitemia/Parasitemia/ImgTools.fs +++ b/Parasitemia/Parasitemia/ImgTools.fs @@ -3,11 +3,13 @@ open System open System.Drawing open System.Collections.Generic +open System.Linq open Emgu.CV open Emgu.CV.Structure open Utils +open Heap // Normalize image values between 0uy and 255uy. let normalizeAndConvert (img: Image) : Image = @@ -18,10 +20,651 @@ let normalizeAndConvert (img: Image) : Image = img.MinMax(min, max, minLocation, maxLocation) ((img - (!min).[0]) / ((!max).[0] - (!min).[0]) * 255.0).Convert() + +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 filepath + + +let suppressMConnections (img: Matrix) = + let w = img.Width + let h = img.Height + for i in 1 .. h - 2 do + for j in 1 .. w - 2 do + if img.[i, j] > 0uy && img.Data.[i + 1, j] > 0uy && (img.Data.[i, j - 1] > 0uy && img.Data.[i - 1, j + 1] = 0uy || img.Data.[i, j + 1] > 0uy && img.Data.[i - 1, j - 1] = 0uy) + then + img.[i, j] <- 0uy + for i in 1 .. h - 2 do + for j in 1 .. w - 2 do + if img.[i, j] > 0uy && img.Data.[i - 1, j] > 0uy && (img.Data.[i, j - 1] > 0uy && img.Data.[i + 1, j + 1] = 0uy || img.Data.[i, j + 1] > 0uy && img.Data.[i + 1, j - 1] = 0uy) + then + img.[i, j] <- 0uy + +let findEdges (img: Image) : Matrix * Image * Image = + let w = img.Width + let h = img.Height + + use sobelKernel = + new ConvolutionKernelF(array2D [[ 1.0f; 0.0f; -1.0f ] + [ 2.0f; 0.0f; -2.0f ] + [ 1.0f; 0.0f; -1.0f ]], Point(1, 1)) + + let xGradient = img.Convolution(sobelKernel).Convert() + let yGradient = img.Convolution(sobelKernel.Transpose()).Convert() + + let xGradientData = xGradient.Data + let yGradientData = yGradient.Data + for r in 0 .. h - 1 do + xGradientData.[r, 0, 0] <- 0.0 + xGradientData.[r, w - 1, 0] <- 0.0 + yGradientData.[r, 0, 0] <- 0.0 + yGradientData.[r, w - 1, 0] <- 0.0 + + for c in 0 .. w - 1 do + xGradientData.[0, c, 0] <- 0.0 + xGradientData.[h - 1, c, 0] <- 0.0 + yGradientData.[0, c, 0] <- 0.0 + yGradientData.[h - 1, c, 0] <- 0.0 + + use magnitudes = new Matrix(xGradient.Size) + use angles = new Matrix(xGradient.Size) + CvInvoke.CartToPolar(xGradient, yGradient, magnitudes, angles) // Compute the magnitudes (without angles). + + let thresholdHigh, thresholdLow = + let sensibility = 0.1 + use magnitudesByte = magnitudes.Convert() + let threshold = CvInvoke.Threshold(magnitudesByte, magnitudesByte, 0.0, 1.0, CvEnum.ThresholdType.Otsu ||| CvEnum.ThresholdType.Binary) + threshold + (sensibility * threshold), threshold - (sensibility * threshold) + + // Non-maximum suppression. + use nms = new Matrix(xGradient.Size) + + for i in 0 .. h - 1 do + nms.Data.[i, 0] <- 0uy + nms.Data.[i, w - 1] <- 0uy + + for j in 0 .. w - 1 do + nms.Data.[0, j] <- 0uy + nms.Data.[h - 1, j] <- 0uy + + for i in 1 .. h - 2 do + for j in 1 .. w - 2 do + let vx = xGradient.Data.[i, j, 0] + let vy = yGradient.Data.[i, j, 0] + if vx <> 0. || vy <> 0. + then + let angle = angles.[i, j] + + let vx', vy' = abs vx, abs vy + let ratio2 = if vx' > vy' then vy' / vx' else vx' / vy' + let ratio1 = 1. - ratio2 + + let mNeigbors (sign: int) : float = + if angle < Math.PI / 4. + then + ratio1 * magnitudes.Data.[i, j + sign] + ratio2 * magnitudes.Data.[i + sign, j + sign] + elif angle < Math.PI / 2. + then + ratio2 * magnitudes.Data.[i + sign, j + sign] + ratio1 * magnitudes.Data.[i + sign, j] + elif angle < 3.0 * Math.PI / 4. + then + ratio1 * magnitudes.Data.[i + sign, j] + ratio2 * magnitudes.Data.[i + sign, j - sign] + elif angle < Math.PI + then + ratio2 * magnitudes.Data.[i + sign, j - sign] + ratio1 * magnitudes.Data.[i, j - sign] + elif angle < 5. * Math.PI / 4. + then + ratio1 * magnitudes.Data.[i, j - sign] + ratio2 * magnitudes.Data.[i - sign, j - sign] + elif angle < 3. * Math.PI / 2. + then + ratio2 * magnitudes.Data.[i - sign, j - sign] + ratio1 * magnitudes.Data.[i - sign, j] + elif angle < 7. * Math.PI / 4. + then + ratio1 * magnitudes.Data.[i - sign, j] + ratio2 * magnitudes.Data.[i - sign, j + sign] + else + ratio2 * magnitudes.Data.[i - sign, j + sign] + ratio1 * magnitudes.Data.[i, j + sign] + + let m = magnitudes.Data.[i, j] + if m >= thresholdLow && m > mNeigbors 1 && m > mNeigbors -1 + then + nms.Data.[i, j] <- 1uy + + // suppressMConnections nms // It's not helpful for the rest of the process (ellipse detection). + + let edges = new Matrix(xGradient.Size) + + // Histeresis thresholding. + let toVisit = Stack() + for i in 0 .. h - 1 do + for j in 0 .. w - 1 do + if nms.Data.[i, j] = 1uy && magnitudes.Data.[i, j] >= thresholdHigh + then + nms.Data.[i, j] <- 0uy + toVisit.Push(Point(j, i)) + while toVisit.Count > 0 do + let p = toVisit.Pop() + edges.Data.[p.Y, p.X] <- 1uy + for i' in -1 .. 1 do + for j' in -1 .. 1 do + if i' <> 0 || j' <> 0 + then + let ni = p.Y + i' + let nj = p.X + j' + if ni >= 0 && ni < h && nj >= 0 && nj < w && nms.Data.[ni, nj] = 1uy + then + nms.Data.[ni, nj] <- 0uy + toVisit.Push(Point(nj, ni)) + + edges, xGradient, yGradient + + 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) + +type Points = HashSet + +let drawPoints (img: Image) (points: Points) (intensity: 'TDepth) = + for p in points do + img.Data.[p.Y, p.X, 0] <- intensity + +type ExtremumType = + | Maxima = 1 + | Minima = 2 + +let findExtremum (img: Image) (extremumType: ExtremumType) : IEnumerable = + let w = img.Width + let h = img.Height + let se = [| -1, 0; 0, -1; 1, 0; 0, 1 |] + + let imgData = img.Data + let suppress: bool[,] = Array2D.zeroCreate h w + + let result = List>() + + let flood (start: Point) : List> = + let sameLevelToCheck = Stack() + let betterLevelToCheck = Stack() + betterLevelToCheck.Push(start) + + let result' = List>() + + while betterLevelToCheck.Count > 0 do + let p = betterLevelToCheck.Pop() + if not suppress.[p.Y, p.X] + then + suppress.[p.Y, p.X] <- true + sameLevelToCheck.Push(p) + let current = List() + + let mutable betterExists = false + + while sameLevelToCheck.Count > 0 do + let p' = sameLevelToCheck.Pop() + let currentLevel = imgData.[p'.Y, p'.X, 0] + current.Add(p') |> ignore + for i, j in se do + let ni = i + p'.Y + let nj = j + p'.X + if ni >= 0 && ni < h && nj >= 0 && nj < w + then + let level = imgData.[ni, nj, 0] + let notSuppressed = not suppress.[ni, nj] + + if level = currentLevel && notSuppressed + then + suppress.[ni, nj] <- true + sameLevelToCheck.Push(Point(nj, ni)) + elif if extremumType = ExtremumType.Maxima then level > currentLevel else level < currentLevel + then + betterExists <- true + if notSuppressed + then + betterLevelToCheck.Push(Point(nj, ni)) + + if not betterExists + then + result'.Add(current) + result' + + for i in 0 .. h - 1 do + for j in 0 .. w - 1 do + let maxima = flood (Point(j, i)) + if maxima.Count > 0 + then + result.AddRange(maxima) + + result.Select(fun l -> Points(l)) + + +let findMaxima (img: Image) : IEnumerable = + findExtremum img ExtremumType.Maxima + + +let findMinima (img: Image) : IEnumerable = + findExtremum img ExtremumType.Minima + + +type PriorityQueue () = + let size = 256 + let q: Points[] = Array.init size (fun i -> Points()) + let mutable highest = -1 // Value of the first elements of 'q'. + let mutable lowest = size + + member this.NextMax () : byte * Point = + if this.IsEmpty + then + invalidOp "Queue is empty" + else + let l = q.[highest] + let next = l.First() + l.Remove(next) |> ignore + let value = byte highest + + if l.Count = 0 + then + highest <- highest - 1 + while highest > lowest && q.[highest].Count = 0 do + highest <- highest - 1 + if highest = lowest + then + highest <- -1 + lowest <- size + + value, next + + member this.NextMin () : byte * Point = + if this.IsEmpty + then + invalidOp "Queue is empty" + else + let l = q.[lowest + 1] + let next = l.First() + l.Remove(next) |> ignore + let value = byte (lowest + 1) + + if l.Count = 0 + then + lowest <- lowest + 1 + while lowest < highest && q.[lowest + 1].Count = 0 do + lowest <- lowest + 1 + if highest = lowest + then + highest <- -1 + lowest <- size + + value, next + + member this.Max = + highest |> byte + + member this.Min = + lowest + 1 |> byte + + member this.Add (value: byte) (p: Point) = + let vi = int value + + if vi > highest + then + highest <- vi + if vi <= lowest + then + lowest <- vi - 1 + + q.[vi].Add(p) |> ignore + + member this.Remove (value: byte) (p: Point) = + let vi = int value + if q.[vi].Remove(p) && q.[vi].Count = 0 + then + if vi = highest + then + highest <- highest - 1 + while highest > lowest && q.[highest].Count = 0 do + highest <- highest - 1 + elif vi - 1 = lowest + then + lowest <- lowest + 1 + while lowest < highest && q.[lowest + 1].Count = 0 do + lowest <- lowest + 1 + + if highest = lowest // The queue is now empty. + then + highest <- -1 + lowest <- size + + member this.IsEmpty = + highest = -1 + + member this.Clear () = + while highest > lowest do + q.[highest].Clear() + highest <- highest - 1 + highest <- -1 + lowest <- size + + +type private AreaState = + | Removed = 1 + | Unprocessed = 2 + | Validated = 3 + +type private AreaOperation = + | Opening = 1 + | Closing = 2 + +[] +type private Area (elements: Points) = + member this.Elements = elements + member val Intensity = None with get, set + member val State = AreaState.Unprocessed with get, set + +let private areaOperation (img: Image) (area: int) (op: AreaOperation) = + let w = img.Width + let h = img.Height + let imgData = img.Data + let se = [| -1, 0; 0, -1; 1, 0; 0, 1 |] + + let areas = List((if op = AreaOperation.Opening then findMaxima img else findMinima img) |> Seq.map Area) + + let pixels: Area[,] = Array2D.create h w null + for m in areas do + for e in m.Elements do + pixels.[e.Y, e.X] <- m + + let queue = PriorityQueue() + + let addEdgeToQueue (elements: Points) = + for p in elements do + for i, j in se do + let ni = i + p.Y + let nj = j + p.X + let p' = Point(nj, ni) + if ni >= 0 && ni < h && nj >= 0 && nj < w && not (elements.Contains(p')) + then + queue.Add (imgData.[ni, nj, 0]) p' + + // Reverse order is quicker. + for i in areas.Count - 1 .. -1 .. 0 do + let m = areas.[i] + if m.Elements.Count <= area && m.State <> AreaState.Removed + then + queue.Clear() + addEdgeToQueue m.Elements + + let mutable intensity = if op = AreaOperation.Opening then queue.Max else queue.Min + let nextElements = Points() + + let mutable stop = false + while not stop do + let intensity', p = if op = AreaOperation.Opening then queue.NextMax () else queue.NextMin () + let mutable merged = false + + if intensity' = intensity // The intensity doesn't change. + then + if m.Elements.Count + nextElements.Count + 1 > area + then + m.State <- AreaState.Validated + m.Intensity <- Some intensity + stop <- true + else + nextElements.Add(p) |> ignore + + elif if op = AreaOperation.Opening then intensity' < intensity else intensity' > intensity + then + m.Elements.UnionWith(nextElements) + for e in nextElements do + pixels.[e.Y, e.X] <- m + + if m.Elements.Count = area + then + m.State <- AreaState.Validated + m.Intensity <- Some (intensity') + stop <- true + else + intensity <- intensity' + nextElements.Clear() + nextElements.Add(p) |> ignore + + else + let m' = pixels.[p.Y, p.X] + if m' <> null + then + if m'.Elements.Count + m.Elements.Count <= area + then + m'.State <- AreaState.Removed + for e in m'.Elements do + pixels.[e.Y, e.X] <- m + queue.Remove imgData.[e.Y, e.X, 0] e + addEdgeToQueue m'.Elements + m.Elements.UnionWith(m'.Elements) + let intensityMax = if op = AreaOperation.Opening then queue.Max else queue.Min + if intensityMax <> intensity + then + intensity <- intensityMax + nextElements.Clear() + merged <- true + + if not merged + then + m.State <- AreaState.Validated + m.Intensity <- Some (intensity) + stop <- true + + if not stop && not merged + then + for i, j in se do + let ni = i + p.Y + let nj = j + p.X + let p' = Point(nj, ni) + if ni < 0 || ni >= h || nj < 0 || nj >= w + then + m.State <- AreaState.Validated + m.Intensity <- Some (intensity) + stop <- true + elif not (m.Elements.Contains(p')) && not (nextElements.Contains(p')) + then + queue.Add (imgData.[ni, nj, 0]) p' + + if queue.IsEmpty + then + if m.Elements.Count + nextElements.Count <= area + then + m.State <- AreaState.Validated + m.Intensity <- Some intensity' + m.Elements.UnionWith(nextElements) + stop <- true + + for m in areas do + if m.State = AreaState.Validated + then + match m.Intensity with + | Some i -> + for p in m.Elements do + imgData.[p.Y, p.X, 0] <- i + | _ -> () + () + + +let areaOpen (img: Image) (area: int) = + areaOperation img area AreaOperation.Opening + +let areaClose (img: Image) (area: int) = + areaOperation img area AreaOperation.Closing + +[] +type Island (cmp: IComparer) = + member val Shore = Heap.Heap(cmp) with get + member val Level = 0.f with get, set + member val Surface = 0 with get, set + + +let private areaOperationF (img: Image) (area: int) (op: AreaOperation) = + let w = img.Width + let h = img.Height + let earth = img.Data + let se = [| -1, 0; 0, -1; 1, 0; 0, 1 |] + + let comparer = if op = AreaOperation.Opening + then { new IComparer with member this.Compare(v1, v2) = v1.CompareTo(v2) } + else { new IComparer with member this.Compare(v1, v2) = v2.CompareTo(v1) } + + let ownership: Island[,] = Array2D.create h w null + + // Initialize islands with their shore. + let islands = List() + let extremum = img |> if op = AreaOperation.Opening then findMaxima else findMinima + for e in extremum do + let island = + let p = e.First() + Island(comparer, Level = earth.[p.Y, p.X, 0], Surface = e.Count) + islands.Add(island) + let shorePoints = Points() + for p in e do + ownership.[p.Y, p.X] <- island + for i, j in se do + let ni = i + p.Y + let nj = j + p.X + let neighbor = Point(nj, ni) + if ni >= 0 && ni < h && nj >= 0 && nj < w && ownership.[ni, nj] = null && not (shorePoints.Contains(neighbor)) + then + shorePoints.Add(neighbor) |> ignore + island.Shore.Add earth.[ni, nj, 0] neighbor + + for island in islands do + let mutable stop = island.Shore.IsEmpty + + // 'true' if 'p' is owned or adjacent to 'island'. + let ownedOrAdjacent (p: Point) : bool = + ownership.[p.Y, p.X] = island || + (p.Y > 0 && ownership.[p.Y - 1, p.X] = island) || + (p.Y < h - 1 && ownership.[p.Y + 1, p.X] = island) || + (p.X > 0 && ownership.[p.Y, p.X - 1] = island) || + (p.X < w - 1 && ownership.[p.Y, p.X + 1] = island) + + while not stop && island.Surface < area do + let level, next = island.Shore.Max + let other = ownership.[next.Y, next.X] + if other = island // During merging, some points on the shore may be owned by the island itself -> ignored. + then + island.Shore.RemoveNext () + else + if other <> null + then // We touching another island. + if island.Surface + other.Surface >= area + then + stop <- true + else // We can merge 'other' into 'surface'. + island.Surface <- island.Surface + other.Surface + island.Level <- if comparer.Compare(island.Level, other.Level) > 0 then island.Level else other.Level + for l, p in other.Shore do + let mutable currentY = p.Y + 1 + while currentY < h && ownership.[currentY, p.X] = other do + ownership.[currentY, p.X] <- island + currentY <- currentY + 1 + island.Shore.Add l p + other.Shore.Clear() + + elif comparer.Compare(level, island.Level) > 0 + then + stop <- true + else + island.Shore.RemoveNext () + for i, j in se do + let ni = i + next.Y + let nj = j + next.X + if ni < 0 || ni >= h || nj < 0 || nj >= w + then + island.Surface <- Int32.MaxValue + stop <- true + else + let neighbor = Point(nj, ni) + if not <| ownedOrAdjacent neighbor + then + island.Shore.Add earth.[ni, nj, 0] neighbor + if not stop + then + ownership.[next.Y, next.X] <- island + island.Level <- level + island.Surface <- island.Surface + 1 + + for i in 0 .. h - 1 do + for j in 0 .. w - 1 do + let island = ownership.[i, j] + if island <> null + then + earth.[i, j, 0] <- island.Level + () + + +let areaOpenF (img: Image) (area: int) = + areaOperationF img area AreaOperation.Opening + +let areaCloseF (img: Image) (area: int) = + areaOperationF img area AreaOperation.Closing + +// A simpler algorithm than 'areaOpen' but slower. +let areaOpen2 (img: Image) (area: int) = + let w = img.Width + let h = img.Height + let imgData = img.Data + let se = [| -1, 0; 0, -1; 1, 0; 0, 1 |] + + let histogram = Array.zeroCreate 256 + for i in 0 .. h - 1 do + for j in 0 .. w - 1 do + let v = imgData.[i, j, 0] |> int + histogram.[v] <- histogram.[v] + 1 + + let flooded : bool[,] = Array2D.zeroCreate h w + + let pointsChecked = HashSet() + let pointsToCheck = Stack() + + for level in 255 .. -1 .. 0 do + let mutable n = histogram.[level] + if n > 0 + then + for i in 0 .. h - 1 do + for j in 0 .. w - 1 do + if not flooded.[i, j] && imgData.[i, j, 0] = byte level + then + let mutable maxNeighborValue = 0uy + pointsChecked.Clear() + pointsToCheck.Clear() + pointsToCheck.Push(Point(j, i)) + + while pointsToCheck.Count > 0 do + let next = pointsToCheck.Pop() + pointsChecked.Add(next) |> ignore + flooded.[next.Y, next.X] <- true + + for nx, ny in se do + let p = Point(next.X + nx, next.Y + ny) + if p.X >= 0 && p.X < w && p.Y >= 0 && p.Y < h + then + let v = imgData.[p.Y, p.X, 0] + if v = byte level + then + if not (pointsChecked.Contains(p)) + then + pointsToCheck.Push(p) + elif v > maxNeighborValue + then + maxNeighborValue <- v + + if int maxNeighborValue < level && pointsChecked.Count <= area + then + for p in pointsChecked do + imgData.[p.Y, p.X, 0] <- maxNeighborValue + + // Zhang and Suen algorithm. // Modify 'mat' in place. let thin (mat: Matrix) = @@ -73,11 +716,6 @@ let thin (mat: Matrix) = 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) = @@ -103,37 +741,37 @@ let removeArea (mat: Matrix) (areaSize: int) = for j in 0..w-1 do if data'.[i, j] = 1uy then - let neighborhood = List<(int*int)>() - let neighborsToCheck = List<(int*int)>() - neighborsToCheck.Add((i, j)) + let neighborhood = List() + let neighborsToCheck = Stack() + neighborsToCheck.Push(Point(j, i)) data'.[i, j] <- 0uy while neighborsToCheck.Count > 0 do - let (ci, cj) = pop neighborsToCheck - neighborhood.Add((ci, cj)) + let n = neighborsToCheck.Pop() + neighborhood.Add(n) for (ni, nj) in neighbors do - let pi = ci + ni - let pj = cj + nj + let pi = n.Y + ni + let pj = n.X + nj if pi >= 0 && pi < h && pj >= 0 && pj < w && data'.[pi, pj] = 1uy then - neighborsToCheck.Add((pi, pj)) + neighborsToCheck.Push(Point(pj, pi)) data'.[pi, pj] <- 0uy if neighborhood.Count <= areaSize then - for (ni, nj) in neighborhood do - data.[ni, nj] <- 0uy + for n in neighborhood do + data.[n.Y, n.X] <- 0uy let connectedComponents (img: Image) (startPoints: List) : List = let w = img.Width let h = img.Height - let pointChecked = HashSet() - let pointToCheck = List(startPoints); + let pointChecked = Points() + let pointToCheck = Stack(startPoints); let data = img.Data while pointToCheck.Count > 0 do - let next = pop pointToCheck + let next = pointToCheck.Pop() pointChecked.Add(next) |> ignore for ny in -1 .. 1 do for nx in -1 .. 1 do @@ -142,26 +780,19 @@ let connectedComponents (img: Image) (startPoints: List) : Li 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) + pointToCheck.Push(p) List(pointChecked) -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 filepath - let drawLine (img: Image<'TColor, 'TDepth>) (color: 'TColor) (x0: int) (y0: int) (x1: int) (y1: int) (thickness: int) = img.Draw(LineSegment2D(Point(x0, y0), Point(x1, y1)), color, thickness); + let drawLineF (img: Image<'TColor, 'TDepth>) (color: 'TColor) (x0: float) (y0: float) (x1: float) (y1: float) (thickness: int) = img.Draw(LineSegment2DF(PointF(float32 x0, float32 y0), PointF(float32 x1, float32 y1)), color, thickness, CvEnum.LineType.AntiAlias); + let drawEllipse (img: Image<'TColor, 'TDepth>) (e: Types.Ellipse) (color: 'TColor) (alpha: float) = if alpha >= 1.0