Pynovisao - Otimizacoes e correcoes

src/interface/tk/tk_canvas.py

@@ -49,10 +49,7 @@ class Image(object):
     def toggle_toolbar(self):
         self._toolbar_visible = not self._toolbar_visible
         
-        if self._toolbar_visible == True:
-            self._show_toolbar()
-        else:
-            self._hide_toolbar()
+        self._show_toolbar() if self._toolbar_visible else self._hide_toolbar()
     
         
     def render(self, image, onclick = None):
@@ -82,6 +79,7 @@ class Image(object):
         if self._canvas is not None:
             self.parent.image = image
             self._im.set_data(self.parent.image)
+            
             self._fig.tight_layout()
             self._canvas.draw()
 
@@ -96,6 +94,12 @@ class Image(object):
             if self._toolbar is not None:
                 self._toolbar.pack_forget()
                 self._toolbar.destroy()
+
+            # The command plt.clf() is used to minimize the effects of follow warning:
+            # "RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface 
+            # (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory."
+            # However this part of code need to be refactored to prevent the memory leak!!!
+            plt.clf()
             
             self._im = None
             self._canvas = None

src/main.py

@@ -54,6 +54,7 @@ if __name__ == "__main__":
     tk.add_command("Choose segmenter", act.select_segmenter)
     tk.add_command("Configure", act.config_segmenter, 'g')
     tk.add_separator()
+    tk.add_command("Clean", act.clean_segmentation, 'l')
     tk.add_command("Execute", act.run_segmenter, 'S')
     
     tk.add_menu("Feature Extraction")

src/pynovisao.py

@@ -106,7 +106,7 @@ class Act(object):
         if self.tk.close_image():
             self.tk.write_log("Closing image...")
             self._const_image = None
-
+            self._image = None
 
     def add_class(self, dialog = True, name = None, color = None):
         n_classes = len(self.classes)
@@ -216,13 +216,18 @@ class Act(object):
         if self._const_image is None:
             raise IException("Image not found")
         
-        self.tk.write_log("Running %s,,,", self.segmenter.get_name())
+        self.tk.write_log("Running %s...", self.segmenter.get_name())
 
         self.tk.append_log("\nConfig: %s", str(self.segmenter.get_summary_config()))
         self._image, run_time = self.segmenter.run(self._const_image)
         self.tk.append_log("Time elapsed: %0.3f seconds", run_time)
         
         self.tk.refresh_image(self._image)
+        
+    def clean_segmentation(self):
+        if self._const_image is not None:
+            self.tk.write_log("Removing %s segmentation...", self.segmenter.get_name())
+            self.tk.refresh_image(self._const_image)
 
 
     def select_extractors(self):

src/segmentation/skimage_segmenter.py

@@ -23,6 +23,9 @@ class SkimageSegmenter(object):
     
     __metaclass__ = ABCMeta
     
+    # flag FORCE_OPT highly increases speed of method paint_segment_skimage but performs a flawed painting
+    FORCE_OPT = False
+    
     def __init__(self, border_color = 'Yellow', border_outline = 'No'):
         self.border_color = Config("Border Color", border_color, 'color')
         self.border_outline = Config("Border Outline", border_outline, str)
@@ -62,8 +65,7 @@ class SkimageSegmenter(object):
         end_time = TimeUtils.get_time()
         
         return segment, size_segment, idx_segment, (end_time - start_time)
-        
-        
+
     def paint_segment_skimage(self, image, color, px = 0, py = 0, idx_segment = None, border = True, clear = False):
         if self._segments is None:
             return image, 0
@@ -80,17 +82,18 @@ class SkimageSegmenter(object):
             
         class_color = np.zeros((height,width,3), np.uint8)
         class_color[:, :] = X11Colors.get_color(color)
-        if clear == False:
+        if SkimageSegmenter.FORCE_OPT == False:
             colored_image = cv2.addWeighted(self._original_image, 0.7, class_color, 0.3, 0)
         else:
-            colored_image = self._original_image
+            colored_image = cv2.addWeighted(image, 0.7, class_color, 0.3, 0)
         colored_image = cv2.bitwise_and(colored_image, colored_image, mask=mask_segment)
         
-        new_image = cv2.bitwise_and(image, image, mask=mask_inv)
+        new_image = image if clear == False else self._original_image
+        new_image = cv2.bitwise_and(new_image, new_image, mask=mask_inv)
         mask_segment[:] = 255
         new_image = cv2.bitwise_or(new_image, colored_image, mask=mask_segment)
 
-        if border == True:
+        if border == True and SkimageSegmenter.FORCE_OPT == False:
             color = X11Colors.get_color_zero_one(self.border_color.get_cast_val())
             outline_color = color if self.border_outline.value == 'Yes' else None