Added image normalization to performance measuring script.

src/test_performance.py

 #!/usr/bin/python
+from os import listdir
 from cPickle import load
 from sys import argv, exit
 from time import time
 
+from GrayscaleImage import GrayscaleImage
+from NormalizedCharacterImage import NormalizedCharacterImage
+from Character import Character
 from Classifier import Classifier
 
 if len(argv) < 4:
@@ -14,17 +18,37 @@ blur_scale = float(argv[2])
 count = int(argv[3])
 suffix = '_%s_%s' % (blur_scale, neighbours)
 
-chars_file = 'characters%s.dat' % suffix
+#chars_file = 'characters%s.dat' % suffix
 classifier_file = 'classifier%s.dat' % suffix
 
-print 'Loading characters...'
-chars = load(open(chars_file, 'r'))[:count]
-count = len(chars)
+#print 'Loading characters...'
+#chars = load(open(chars_file, 'r'))[:count]
+#count = len(chars)
+#
+#for char in chars:
+#    del char.feature
+#
+#print 'Read %d characters' % count
 
-for char in chars:
-    del char.feature
+print 'Loading %d characters...' % count
+chars = []
+i = 0
+br = False
+
+for value in sorted(listdir('../images/LearningSet')):
+    for image in sorted(listdir('../images/LearningSet/' + value)):
+        f = '../images/LearningSet/' + value + '/' + image
+        image = GrayscaleImage(f)
+        char = Character(value, [], image)
+        chars.append(char)
+        i += 1
+
+        if i == count:
+            br = True
+            break
 
-print 'Read %d characters' % count
+    if br:
+        break
 
 print 'Loading classifier...'
 classifier = Classifier(filename=classifier_file)
@@ -33,6 +57,8 @@ classifier.neighbours = neighbours
 start = time()
 
 for char in chars:
+    char.image = NormalizedCharacterImage(image, blur=blur_scale, height=42)
+    char.get_single_cell_feature_vector(neighbours)
     classifier.classify(char)
 
 elapsed = time() - start