fix problem with python3 and extractor features

src/extraction/feature_extraction.py

@@ -173,10 +173,7 @@ class FeatureExtractor(object):
             raise IException("Image %s is possibly corrupt" % filepath)
 
         if len(self.data) > 0:
-            if sys.version_info >= (3, 0):
-                values = list(zip(*([extractor().run(image) for extractor in self.extractors])))
-            else:
-                values = list(itertools.chain.from_iterable(zip(*([extractor().run(image) for extractor in self.extractors]))[2]))
+            values = list(itertools.chain.from_iterable(zip(*([extractor().run(image)[2] for extractor in self.extractors]))))
 	    
             self.data.append(values + [cl if cl in classes else classes[0]])
 
@@ -258,19 +255,19 @@ class FeatureExtractor(object):
         """
 
         arff = open(output_file, 'wb')
-        arff.write(bytes(str("%s %s\n\n" % ('@relation', relation)), 'utf-8'))
+        arff.write(str("%s %s\n\n" % ('@relation', relation)).encode('utf-8'))
 
         for label, t in zip(labels, types):
-            arff.write(bytes(str("%s %s %s\n" % ('@attribute', label, t)), 'utf-8'))
+            arff.write(str("%s %s %s\n" % ('@attribute', label, t)).encode('utf-8'))
         
-        arff.write(bytes(str("%s %s {%s}\n\n" % ('@attribute', 'classe', ', '.join(classes))), 'utf-8'))
-
-        arff.write(bytes(str('@data\n\n'), 'utf-8'))
+        arff.write(str("%s %s {%s}\n\n" % ('@attribute', 'classe', ', '.join(classes))).encode( 'utf-8'))
 
+        arff.write(str('@data\n\n').encode( 'utf-8'))
+        #print(data)
         for instance in data:
             instance = map(str, instance)
             line = ",".join(instance)
-            arff.write(bytes(str(line + "\n"), 'utf-8'))
+            arff.write(str(line + "\n").encode( 'utf-8'))
 
         arff.close()
 

src/extraction/image_moments.py

@@ -43,22 +43,26 @@ class RawCentralMoments(Extractor):
         """
         #raw_moments = moments(image)
 
-
+		
         image_binary = ImageUtils.image_binary(image, bgr = True)
-        
+		
         m = measure.moments(image_binary)
-        
+        m=np.nan_to_num(m)
+		
         values_m = [m[p, q] for (p, q) in self._moments_order]
-        labels_m = [M+str(p)+str(q) for M,(p,q) in zip(['M_'] * len(self._moments_order), self._moments_order)]
         
+        labels_m = [M+str(p)+str(q) for M,(p,q) in zip(['M_'] * len(self._moments_order), self._moments_order)]
         row = m[0, 1] / m[0, 0]
         col = m[1, 0] / m[0, 0]
-	
+		
         mu = measure.moments_central(image_binary, center=(row, col), order=3)
-        
+        mu=np.nan_to_num(mu)
+		
         values_mu = [mu[p, q] for (p, q) in self._moments_order]
+				
+		
         labels_mu = [M+str(p)+str(q) for M,(p,q) in zip(['Mu_'] * len(self._moments_order), self._moments_order)]
-        #print(values_mu)
+		
         labels = labels_m + labels_mu
         types = [Extractor.NUMERIC] * len(labels)
         values = values_m + values_mu