ajustes e testes da versão com Python3 e Python2

.idea/inspectionProfiles/Project_Default.xml

@@ -64,6 +64,10 @@
           <option value="E501" />
           <option value="W29" />
           <option value="E501" />
+          <option value="W29" />
+          <option value="E501" />
+          <option value="W29" />
+          <option value="E501" />
         </list>
       </option>
     </inspection_tool>

INSTALL.sh

@@ -6,6 +6,8 @@ YELLOW='\033[0;33m'
 NC='\033[0m'
 
 echo "[PYNOVISAO INSTALLER] Installing PYNOVISAO... Please wait!"
+export OMP_NUM_THREADS=4
+export KMP_AFFINITY="verbose,explicit,proclist=[0,3,5,9],granularity=core"
 
 #check if is root
 if [ "$EUID" -ne 0 ]

README.md

@@ -242,6 +242,7 @@ Se você deseja as funcionalidades gráficas você precisa instalar matplotlib t
 - http://pythonhosted.org/python-weka-wrapper/troubleshooting.html
 
 
+
 ### Como instalar o caffe ( Opcional )
 
 #### Ubuntu / Windows
@@ -352,3 +353,8 @@ Após a implementação de seu classificador, você deve configurá-lo no pynovi
 Caso você necessite de classes utilitárias, os arquivos delas devem ser criados no diretório  src/util/. Além disso, as classes utilitárias devem ser registradas como módulos no arquivo src/util/__init__.py
 
 
+Caso dê problema relacionado ao número de processos, adicione as duas váriaveis de ambiente,
+sendo que deve adicionar no número de threads que o seu processador permite:
+
+export OMP_NUM_THREADS=8
+export KMP_AFFINITY="verbose,explicit,proclist=[0,3,5,9,12,15,18,21],granularity=core"

src/extraction/feature_extraction.py

@@ -103,9 +103,7 @@ class FeatureExtractor(object):
         with tqdm(total=len(self.threads)) as pbar:
             for  t in self.threads:
                  t.start()
-                 if(len(multiprocessing.active_children())>10):
-                     t.join()
-                     gc.collect()
+
                  pbar.update(1)
             pbar.close()
 
@@ -113,13 +111,13 @@ class FeatureExtractor(object):
         with tqdm(total=len(self.threads)) as ppbar:
             for t in self.threads:
                 t.join()
-                del t
+
                 ppbar.update(1)
             ppbar.close()
         self.print_console("The process was completed with "+str(len(self.threads))+" images!")
         if len(self.data) == 0:
             raise IException("There are no images in dataset: %s" % dataset)
-
+        del self.threads
         # Save the output file in ARFF format
         # self._save_output(File.get_filename(dataset), classes, self.labels, self.types, self.data, output_file)
         self._save_output(File.get_filename(dataset), classes, self.labels[0], self.types[0], self.data, output_file)
@@ -138,7 +136,7 @@ class FeatureExtractor(object):
                 continue
             #th = threading.Thread(target=self.sub_job_extractor,args=(item, dataset, cl, classes))
             th = multiprocessing.Process(target=self.sub_job_extractor,args=(item, dataset, cl, classes))
-
+            multiprocessing.
             self.threads.append(th)
 
 

src/extraction/image_moments.py

@@ -58,7 +58,7 @@ class RawCentralMoments(Extractor):
         
         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)
+        #print(values_mu)
         labels = labels_m + labels_mu
         types = [Extractor.NUMERIC] * len(labels)
         values = values_m + values_mu

src/interface/tk/tk_canvas.py

@@ -161,7 +161,8 @@ class Image(object):
             self._toolbar.configure(background='white', borderwidth=0)
             for child in self._toolbar.winfo_children():
                 if sys.version_info[0] < 3:
-                    child.configure(background='white', foreground='black')
+                    #child.configure(background='white', foreground='black')
+                    child.configure(background='white')
                 else:
                     child.configure(background='white')
             #self._toolbar.update()