X-Git-Url: http://git.euphorik.ch/?p=master-thesis.git;a=blobdiff_plain;f=Parasitemia%2FParasitemiaCore%2FKMedians.fs;h=b2ac7382a16b98ecdb44f0efcf5218a56b33a27a;hp=5819a669ebea52ef18e897fb5cae6f2e57d653e5;hb=2d712781def419c9acc98368f7102b19b064f16d;hpb=4bfa3cbdc6145e6944f02e24829ab2ef3a851ac1

diff --git a/Parasitemia/ParasitemiaCore/KMedians.fs b/Parasitemia/ParasitemiaCore/KMedians.fs
index 5819a66..b2ac738 100644
--- a/Parasitemia/ParasitemiaCore/KMedians.fs
+++ b/Parasitemia/ParasitemiaCore/KMedians.fs
@@ -6,46 +6,49 @@ open System.Drawing
 open Emgu.CV
 open Emgu.CV.Structure
 
-type Result = {
-    fg: Image<Gray, byte>
-    median_bg: float
-    median_fg: float
-    d_fg: Image<Gray, float32> } // Euclidean distances of the foreground to median_fg.
-
-let kmedians (img: Image<Gray, float32>) : Result =
+type Result =
+    {
+        fg : Image<Gray, byte>
+        median_bg : float
+        median_fg : float
+        d_fg : Image<Gray, float32> // Euclidean distances of the foreground to median_fg.
+    }
+
+let kmedians (img : Image<Gray, float32>) : Result =
     let nbIteration = 4
     let w = img.Width
     let h = img.Height
 
     let min = ref [| 0.0 |]
-    let minLocation = ref <| [| Point() |]
+    let minLocation = ref <| [| Point () |]
     let max = ref [| 0.0 |]
-    let maxLocation = ref <| [| Point() |]
-    img.MinMax(min, max, minLocation, maxLocation)
+    let maxLocation = ref <| [| Point () |]
+    img.MinMax (min, max, minLocation, maxLocation)
 
     let mutable median_bg = (!max).[0] - ((!max).[0] - (!min).[0]) / 4.0
     let mutable median_fg = (!min).[0] + ((!max).[0] - (!min).[0]) / 4.0
-    use mutable d_bg = new Image<Gray, float32>(img.Size)
-    let mutable d_fg = new Image<Gray, float32>(img.Size)
-    let mutable fg = new Image<Gray, byte>(img.Size)
+    use mutable d_bg = new Image<Gray, float32> (img.Size)
+    let mutable d_fg = new Image<Gray, float32> (img.Size)
+    let mutable fg = new Image<Gray, byte> (img.Size)
 
-    for i in 1 .. nbIteration do
-        d_bg <- img.AbsDiff(Gray(median_bg))
-        d_fg <- img.AbsDiff(Gray(median_fg))
+    for i = 1 to nbIteration do
+        d_bg <- img.AbsDiff (Gray median_bg)
+        d_fg <- img.AbsDiff (Gray median_fg)
 
-        CvInvoke.Compare(d_fg, d_bg, fg, CvEnum.CmpType.LessThan)
+        CvInvoke.Compare (d_fg, d_bg, fg, CvEnum.CmpType.LessThan)
 
-        let bg_values = List<float>()
-        let fg_values = List<float>()
+        let bg_values = List<float> ()
+        let fg_values = List<float> ()
 
-        for i in 0 .. h - 1 do
-            for j in 0 .. w - 1 do
-                if fg.Data.[i, j, 0] > 0uy
-                then fg_values.Add(float img.Data.[i, j, 0])
-                else bg_values.Add(float img.Data.[i, j, 0])
+        for i = 0 to h - 1 do
+            for j = 0 to w - 1 do
+                if fg.Data.[i, j, 0] > 0uy then
+                    fg_values.Add (float img.Data.[i, j, 0])
+                else
+                    bg_values.Add (float img.Data.[i, j, 0])
 
-        median_bg <- MathNet.Numerics.Statistics.Statistics.Median(bg_values)
-        median_fg <- MathNet.Numerics.Statistics.Statistics.Median(fg_values)
+        median_bg <- MathNet.Numerics.Statistics.Statistics.Median bg_values
+        median_fg <- MathNet.Numerics.Statistics.Statistics.Median fg_values
 
     { fg = fg; median_bg = median_bg; median_fg = median_fg; d_fg = d_fg }