Ejemplo n.º 1
0
 def on_file_open(self, event):
     dlg = wx.FileDialog(self.frame, style=wx.FD_OPEN)
     if dlg.ShowModal() == wx.ID_OK:
         img = pil_to_array(
             PILImage.open(
                 os.path.join(dlg.GetDirectory(), dlg.GetFilename())))
         if img.ndim == 3:
             img = img[:, :, 0] + img[:, :, 1] + img[:, :, 2]
         img = stretch(img.astype(float))
         lt = self.frame.MenuBar.Menus[0][0].MenuItems[7].IsChecked()
         if lt:
             limg, d = log_transform(img)
         else:
             limg = img
         self.frame.subplot_imshow_grayscale(0, 0, limg)
         limg = limg.flatten()
         menu_items = self.frame.MenuBar.Menus[0][0].MenuItems
         if menu_items[2].IsChecked():
             t1 = t2 = otsu(limg)
         elif menu_items[3].IsChecked():
             t1 = t2 = entropy(limg)
         elif menu_items[4].IsChecked():
             t1, t2 = otsu3slow(limg)
         elif menu_items[5].IsChecked():
             t1, t2 = entropy3(limg)
         else:
             t1, t2 = otsu3(limg)
         if lt:
             t1, t2 = inverse_log_transform(np.array([t1, t2]), d)
         m1 = img < t1
         m2 = np.logical_and(img >= t1, img < t2)
         m3 = img > t2
         cimg = np.zeros((m1.shape[0], m1.shape[1], 3))
         cimg[:, :, 0][m1] = img[m1]
         cimg[:, :, 1][m2] = img[m2]
         cimg[:, :, 2][m3] = img[m3]
         self.frame.subplot_imshow(1,
                                   0,
                                   cimg,
                                   sharex=self.frame.subplot(0, 0),
                                   sharey=self.frame.subplot(0, 0))
         self.frame.Refresh()
         wx.MessageBox("Low threshold = %f, high threshold = %f" %
                       (t1, t2),
                       parent=self.frame)
Ejemplo n.º 2
0
 def test_05_02_otsu_entropy(self):
     '''Test the entropy version of Otsu'''
     np.random.seed(0)
     image = np.hstack((np.random.exponential(1.5,size=600),
                        np.random.poisson(15,size=300)))
     image.shape=(30,30)
     image = stretch(image)
     limage, d = T.log_transform(image)
     threshold = entropy(limage)
     threshold = T.inverse_log_transform(threshold, d)
     expected = image > threshold
     workspace, module = self.make_workspace(image)
     module.binary.value = A.BINARY
     module.threshold_method.value = T.TM_OTSU_GLOBAL
     module.use_weighted_variance.value = I.O_ENTROPY
     module.two_class_otsu.value = I.O_TWO_CLASS
     module.run(workspace)
     output = workspace.image_set.get_image(OUTPUT_IMAGE_NAME)
     self.assertTrue(np.all(output.pixel_data == expected))
Ejemplo n.º 3
0
 def test_05_02_otsu_entropy(self):
     '''Test the entropy version of Otsu'''
     np.random.seed(0)
     image = np.hstack((np.random.exponential(1.5,size=600),
                        np.random.poisson(15,size=300)))
     image.shape=(30,30)
     image = stretch(image)
     limage, d = T.log_transform(image)
     threshold = entropy(limage)
     threshold = T.inverse_log_transform(threshold, d)
     expected = image > threshold
     workspace, module = self.make_workspace(image)
     module.binary.value = A.BINARY
     module.threshold_method.value = T.TM_OTSU_GLOBAL
     module.use_weighted_variance.value = I.O_ENTROPY
     module.two_class_otsu.value = I.O_TWO_CLASS
     module.run(workspace)
     output = workspace.image_set.get_image(OUTPUT_IMAGE_NAME)
     self.assertTrue(np.all(output.pixel_data == expected))
Ejemplo n.º 4
0
 def test_05_06_otsu3_entropy_high(self):
     '''Test the three-class otsu, entropy, middle = background'''
     np.random.seed(0)
     image = np.hstack((np.random.exponential(1.5,size=300),
                        np.random.poisson(15,size=300),
                        np.random.poisson(30,size=300)))
     image.shape=(30,30)
     image = stretch(image)
     limage, d = T.log_transform(image)
     t1,t2 = entropy3(limage)
     threshold = T.inverse_log_transform(t1, d)
     expected = image > threshold
     workspace, module = self.make_workspace(image)
     module.binary.value = A.BINARY
     module.threshold_method.value = T.TM_OTSU_GLOBAL
     module.use_weighted_variance.value = I.O_ENTROPY
     module.two_class_otsu.value = I.O_THREE_CLASS
     module.assign_middle_to_foreground.value = I.O_FOREGROUND
     module.run(workspace)
     output = workspace.image_set.get_image(OUTPUT_IMAGE_NAME)
     self.assertTrue(np.all(output.pixel_data == expected))
Ejemplo n.º 5
0
 def test_05_06_otsu3_entropy_high(self):
     '''Test the three-class otsu, entropy, middle = background'''
     np.random.seed(0)
     image = np.hstack(
         (np.random.exponential(1.5, size=300),
          np.random.poisson(15, size=300), np.random.poisson(30, size=300)))
     image.shape = (30, 30)
     image = stretch(image)
     limage, d = T.log_transform(image)
     t1, t2 = entropy3(limage)
     threshold = T.inverse_log_transform(t1, d)
     expected = image > threshold
     workspace, module = self.make_workspace(image)
     module.binary.value = A.BINARY
     module.threshold_method.value = T.TM_OTSU_GLOBAL
     module.use_weighted_variance.value = I.O_ENTROPY
     module.two_class_otsu.value = I.O_THREE_CLASS
     module.assign_middle_to_foreground.value = I.O_FOREGROUND
     module.run(workspace)
     output = workspace.image_set.get_image(OUTPUT_IMAGE_NAME)
     self.assertTrue(np.all(output.pixel_data == expected))
Ejemplo n.º 6
0
 def on_file_open(self, event):
     dlg = wx.FileDialog(self.frame,style=wx.FD_OPEN)
     if dlg.ShowModal() == wx.ID_OK:
         img = pil_to_array(PILImage.open(os.path.join(dlg.GetDirectory(),dlg.GetFilename())))
         if img.ndim == 3:
             img = img[:,:,0]+img[:,:,1]+img[:,:,2]
         img = stretch(img.astype(float))
         lt = self.frame.MenuBar.Menus[0][0].MenuItems[7].IsChecked()
         if lt:
             limg, d = log_transform(img)
         else:
             limg = img
         self.frame.subplot_imshow_grayscale(0, 0, limg)
         limg = limg.flatten()
         menu_items = self.frame.MenuBar.Menus[0][0].MenuItems
         if menu_items[2].IsChecked():
             t1 = t2 = otsu(limg)
         elif menu_items[3].IsChecked():
             t1 = t2 = entropy(limg)
         elif menu_items[4].IsChecked():
             t1, t2 = otsu3slow(limg)
         elif menu_items[5].IsChecked():
             t1, t2 = entropy3(limg)
         else:
             t1, t2 = otsu3(limg)
         if lt:
             t1,t2 = inverse_log_transform(np.array([t1,t2]), d)
         m1 = img < t1
         m2 = np.logical_and(img >= t1, img < t2)
         m3 = img > t2
         cimg = np.zeros((m1.shape[0],m1.shape[1],3))
         cimg[:,:,0][m1]=img[m1]
         cimg[:,:,1][m2]=img[m2]
         cimg[:,:,2][m3]=img[m3]
         self.frame.subplot_imshow(1, 0, cimg,
                                   sharex = self.frame.subplot(0,0),
                                   sharey = self.frame.subplot(0,0))
         self.frame.Refresh()
         wx.MessageBox("Low threshold = %f, high threshold = %f"%(t1,t2),
                       parent=self.frame)
Ejemplo n.º 7
0
 def test_05_04_otsu3_wv_high(self):
     '''Test the three-class otsu, weighted variance middle = foreground'''
     np.random.seed(0)
     image = np.hstack((np.random.exponential(1.5,size=300),
                        np.random.poisson(15,size=300),
                        np.random.poisson(30,size=300)))
     image.shape=(30,30)
     image = stretch(image)
     limage, d = T.log_transform(image)
     t1,t2 = otsu3(limage)
     threshold = T.inverse_log_transform(t1, d)
     workspace, module = self.make_workspace(image)
     module.binary.value = A.BINARY
     module.threshold_scope.value = I.TS_GLOBAL
     module.threshold_method.value = T.TM_OTSU
     module.use_weighted_variance.value = I.O_WEIGHTED_VARIANCE
     module.two_class_otsu.value = I.O_THREE_CLASS
     module.assign_middle_to_foreground.value = I.O_FOREGROUND
     module.run(workspace)
     m = workspace.measurements
     m_threshold = m[cpmeas.IMAGE, I.FF_ORIG_THRESHOLD % module.get_measurement_objects_name()]
     self.assertAlmostEqual(m_threshold, threshold)
Ejemplo n.º 8
0
 def test_05_05_otsu3_entropy_low(self):
     '''Test the three-class otsu, entropy, middle = background'''
     np.random.seed(0)
     image = np.hstack((np.random.exponential(1.5,size=300),
                        np.random.poisson(15,size=300),
                        np.random.poisson(30,size=300)))
     image.shape=(30,30)
     image = stretch(image)
     limage, d = T.log_transform(image)
     t1,t2 = entropy3(limage)
     threshold = T.inverse_log_transform(t2, d)
     workspace, module = self.make_workspace(image)
     module.binary.value = A.BINARY
     module.threshold_scope.value = I.TS_GLOBAL
     module.threshold_method.value = T.TM_OTSU
     module.use_weighted_variance.value = I.O_ENTROPY
     module.two_class_otsu.value = I.O_THREE_CLASS
     module.assign_middle_to_foreground.value = I.O_BACKGROUND
     module.run(workspace)
     output = workspace.image_set.get_image(OUTPUT_IMAGE_NAME)
     m = workspace.measurements
     m_threshold = m[cpmeas.IMAGE, I.FF_ORIG_THRESHOLD % module.get_measurement_objects_name()]
     self.assertAlmostEqual(m_threshold, threshold)