X-Git-Url: http://git.tomasm.cz/imago.git/blobdiff_plain/ecc0929cb0e011db2825e79d7495d7ef7b113e1e..ffbceafad3b67b48c3206a232a99065bc4d00a81:/imago_pack/filters.py

diff --git a/imago_pack/filters.py b/imago_pack/filters.py
index c53b6e8..3a64039 100644
--- a/imago_pack/filters.py
+++ b/imago_pack/filters.py
@@ -2,12 +2,40 @@ from PIL import Image, ImageFilter
 
 import pcf
 
+def color_enhance(image):
+    image_l = image.load()
+    min_r, min_g, min_b = 999, 999, 999
+    max_r, max_g, max_b = -1, -1, -1
+
+    for x in xrange(image.size[0]):
+        for y in xrange(image.size[1]):
+            min_r = min(min_r, image_l[x, y][0])
+            max_r = max(max_r, image_l[x, y][0])
+            min_g = min(min_g, image_l[x, y][1])
+            max_g = max(max_g, image_l[x, y][1])
+            min_b = min(min_b, image_l[x, y][2])
+            max_b = max(max_b, image_l[x, y][2])
+
+    new_image = Image.new('RGB', image.size)
+    new_image_l = new_image.load()
+    for x in xrange(image.size[0]):
+        for y in xrange(image.size[1]):
+            r, g, b = image_l[x, y]
+            r = (r - min_r) * 255 / (max_r - min_r)
+            g = (g - min_g) * 255 / (max_g - min_g)
+            b = (b - min_b) * 255 / (max_b - min_b)
+            new_image_l[x, y] = (r, g, b)
+           # print min_r, max_r, r, g, b
+
+    return new_image
+
 def edge_detection(image):
-    image = image.filter(ImageFilter.GaussianBlur())
+    new_image = image.filter(ImageFilter.GaussianBlur())
     # GaussianBlur is undocumented class, it might not work in future versions
     # of PIL
-    image = Image.fromstring('L', image.size, pcf.edge(image.size, image.tostring()))
-    return image
+    new_image = Image.fromstring('L', image.size,
+                             pcf.edge(image.size, image.tostring()))
+    return new_image
 
 def peaks(image):
     image_l = image.load()
@@ -147,5 +175,4 @@ def components2(image):
                 c += 1
             new_image_l[int(round(float(x_c)/c)), int(round(float(y_c)/c))] = 255
 
-
     return new_image