Cleaning.

[master-thesis.git] / Parasitemia / ParasitemiaCore / ImgTools.fs

diff --git a/Parasitemia/ParasitemiaCore/ImgTools.fs b/Parasitemia/ParasitemiaCore/ImgTools.fs
index cc15af7..44a6c86 100644 (file)
--- a/Parasitemia/ParasitemiaCore/ImgTools.fs
+++ b/Parasitemia/ParasitemiaCore/ImgTools.fs
@@ -43,7 +43,7 @@ let histogramImg (img: Image<Gray, float32>) (nbSamples: int) : Histogram =
         img.MinMax(min, max, minLocation, maxLocation)
         float32 (!min).[0], float32 (!max).[0]
 
-    let bin (x: float32) : int =
+    let inline bin (x: float32) : int =
         let p = int ((x - min) / (max - min) * float32 nbSamples)
         if p >= nbSamples then nbSamples - 1 else p
 
@@ -67,7 +67,7 @@ let histogramMat (mat: Matrix<float32>) (nbSamples: int) : Histogram =
         mat.MinMax(min, max, minLocation, maxLocation)
         float32 !min, float32 !max
 
-    let bin (x: float32) : int =
+    let inline bin (x: float32) : int =
         let p = int ((x - min) / (max - min) * float32 nbSamples)
         if p >= nbSamples then nbSamples - 1 else p
 
@@ -90,7 +90,7 @@ let histogram (values: float32 seq) (nbSamples: int) : Histogram =
         if v < min then min <- v
         if v > max then max <- v
 
-    let bin (x: float32) : int =
+    let inline bin (x: float32) : int =
         let p = int ((x - min) / (max - min) * float32 nbSamples)
         if p >= nbSamples then nbSamples - 1 else p
 
@@ -201,7 +201,6 @@ let findEdges (img: Image<Gray, float32>) : Matrix<byte> * Image<Gray, float32>
     let thresholdHigh, thresholdLow =
         let sensibilityHigh = 0.1f
         let sensibilityLow = 0.0f
-        use magnitudesByte = magnitudes.Convert<byte>()
         let threshold, _, _ = otsu (histogramMat magnitudes 300)
         threshold + (sensibilityHigh * threshold), threshold - (sensibilityLow * threshold)