Parasitemia/ParasitemiaCore/ImgTools/Histogram.fs

   1 module ParasitemiaCore.Histogram
   2
   3 open System
   4 open System.Drawing
   5
   6 open Emgu.CV
   7 open Emgu.CV.Structure
   8
   9 type Histogram = {
  10     data: int[]
  11     total: int // Number of elements.
  12     sum: int // Sum of all intensity.
  13     min: float32
  14     max: float32 }
  15
  16 let histogramImg (img: Image<Gray, float32>) (nbSamples: int) : Histogram =
  17     let imgData = img.Data
  18
  19     let min, max =
  20         let min = ref [| 0.0 |]
  21         let minLocation = ref <| [| Point() |]
  22         let max = ref [| 0.0 |]
  23         let maxLocation = ref <| [| Point() |]
  24         img.MinMax(min, max, minLocation, maxLocation)
  25         float32 (!min).[0], float32 (!max).[0]
  26
  27     let inline bin (x: float32) : int =
  28         let p = int ((x - min) / (max - min) * float32 nbSamples)
  29         if p >= nbSamples then nbSamples - 1 else p
  30
  31     let data = Array.zeroCreate nbSamples
  32
  33     for i in 0 .. img.Height - 1 do
  34         for j in 0 .. img.Width - 1 do
  35             let p = bin imgData.[i, j, 0]
  36             data.[p] <- data.[p] + 1
  37
  38     { data = data; total = img.Height * img.Width; sum = Array.sum data; min = min; max = max }
  39
  40 let histogramMat (mat: Matrix<float32>) (nbSamples: int) : Histogram =
  41     let matData = mat.Data
  42
  43     let min, max =
  44         let min = ref 0.0
  45         let minLocation = ref <| Point()
  46         let max = ref 0.0
  47         let maxLocation = ref <| Point()
  48         mat.MinMax(min, max, minLocation, maxLocation)
  49         float32 !min, float32 !max
  50
  51     let inline bin (x: float32) : int =
  52         let p = int ((x - min) / (max - min) * float32 nbSamples)
  53         if p >= nbSamples then nbSamples - 1 else p
  54
  55     let data = Array.zeroCreate nbSamples
  56
  57     for i in 0 .. mat.Height - 1 do
  58         for j in 0 .. mat.Width - 1 do
  59             let p = bin matData.[i, j]
  60             data.[p] <- data.[p] + 1
  61
  62     { data = data; total = mat.Height * mat.Width; sum = Array.sum data; min = min; max = max }
  63
  64 let histogram (values: float32 seq) (nbSamples: int) : Histogram =
  65     let mutable min = Single.MaxValue
  66     let mutable max = Single.MinValue
  67     let mutable n = 0
  68
  69     for v in values do
  70         n <- n + 1
  71         if v < min then min <- v
  72         if v > max then max <- v
  73
  74     let inline bin (x: float32) : int =
  75         let p = int ((x - min) / (max - min) * float32 nbSamples)
  76         if p >= nbSamples then nbSamples - 1 else p
  77
  78     let data = Array.zeroCreate nbSamples
  79
  80     for v in values do
  81         let p = bin v
  82         data.[p] <- data.[p] + 1
  83
  84     { data = data; total = n; sum = Array.sum data; min = min; max = max }