Pynovisao - Corrigindo verificacao de python-weka-wrapper

src/classification/__init__.py

 from .classifier import Classifier
-from .weka_classifiers import WekaClassifiers
 
 try:
     import weka.core.jvm as jvm
     jvm.start()
 
-    weka_is_defined = True
+    from .weka_classifiers import WekaClassifiers
 except:
-    weka_is_defined = False
+    WekaClassifiers = None
 
 __all__ = ["classifier",
            "weka_classifiers"]
@@ -18,8 +17,8 @@ from util.config import Config
 
 
 _classifier_list = OrderedDict( [ 
-                            ["weka_classifiers", Config(WekaClassifiers().get_name(), weka_is_defined, bool, meta=WekaClassifiers, hidden=not weka_is_defined)],
-                            ["invalid", Config("Invalid", True, bool, meta=None, hidden=True)]
+                            ["weka_classifiers", Config("Invalid" if WekaClassifiers is None else WekaClassifiers().get_name(),
+                                WekaClassifiers is not None, bool, meta=WekaClassifiers, hidden=WekaClassifiers is None)]
                         ] )
 
 def get_classifier_config():

src/pynovisao.py

@@ -281,7 +281,7 @@ class Act(object):
         self.tk.append_log("%s", '\n'.join([extraction._extractor_list[extractor].label for extractor in extraction._extractor_list
                                                 if extraction._extractor_list[extractor].value == True ]))
         
-        output_file, run_time = fextractor.extract_all(self.dataset, "trainning")
+        output_file, run_time = fextractor.extract_all(self.dataset, "training")
         self.tk.append_log("\nOutput file saved in %s", output_file)
         self.tk.append_log("Time elapsed: %0.3f seconds", run_time)
 
@@ -345,14 +345,14 @@ class Act(object):
             list_segments = self.segmenter.get_list_segments()
         
         if self.classifier.must_train():
-            self.tk.append_log("Creating trainning data... (%0.3f seconds)", (TimeUtils.get_time() - start_time))
+            self.tk.append_log("Creating training data... (%0.3f seconds)", (TimeUtils.get_time() - start_time))
             
             fextractor = FeatureExtractor(self.extractors)
-            output_file, run_time = fextractor.extract_all(self.dataset, "trainning", overwrite = False)
+            output_file, run_time = fextractor.extract_all(self.dataset, "training", overwrite = False)
         
             self.tk.append_log("Training classifier... (%0.3f seconds)", (TimeUtils.get_time() - start_time))
             
-            self.classifier.train(self.dataset, "trainning")
+            self.classifier.train(self.dataset, "training")
         
         self._image = self._const_image