vis_label -> vis_semantic_segmentation

chainercv/visualizations/__init__.py

@@ -1,4 +1,4 @@
 from chainercv.visualizations.vis_bbox import vis_bbox  # NOQA
 from chainercv.visualizations.vis_image import vis_image  # NOQA
 from chainercv.visualizations.vis_keypoint import vis_keypoint  # NOQA
-from chainercv.visualizations.vis_label import vis_label  # NOQA
+from chainercv.visualizations.vis_semantic_segmentation import vis_semantic_segmentation  # NOQA

chainercv/visualizations/vis_label.py → chainercv/visualizations/vis_semantic_segmentation.py

@@ -18,11 +18,11 @@ def _default_cmap(label):
     return r, g, b
 
 
-def vis_label(
+def vis_semantic_segmentation(
         label, label_names=None,
         label_colors=None, ignore_label_color=(0, 0, 0), alpha=1,
         all_label_names_in_legend=False, ax=None):
-    """Visualize a label for semantic segmentation.
+    """Visualize a semantic segmentation.
 
     Example:
 
@@ -32,12 +32,12 @@ def vis_label(
         >>> from chainercv.datasets \
         ...     import voc_semantic_segmentation_label_names
         >>> from chainercv.visualizations import vis_image
-        >>> from chainercv.visualizations import vis_label
+        >>> from chainercv.visualizations import vis_semantic_segmentation
         >>> import matplotlib.pyplot as plot
         >>> dataset = VOCSemanticSegmentationDataset()
         >>> img, label = dataset[60]
         >>> ax = vis_image(img)
-        >>> _, legend_handles = vis_label(
+        >>> _, legend_handles = vis_semantic_segmentation(
         ...     label,
         ...     label_names=voc_semantic_segmentation_label_names,
         ...     label_colors=voc_semantic_segmentation_label_colors,

docs/source/reference/visualizations.rst

@@ -16,6 +16,6 @@ vis_keypoint
 ~~~~~~~~~~~~
 .. autofunction:: vis_keypoint
 
-vis_label
-~~~~~~~~~
-.. autofunction:: vis_label
+vis_semantic_segmentation
+~~~~~~~~~~~~~~~~~~~~~~~~~
+.. autofunction:: vis_semantic_segmentation

examples/segnet/demo.py

@@ -8,7 +8,7 @@
 from chainercv.links import SegNetBasic
 from chainercv import utils
 from chainercv.visualizations import vis_image
-from chainercv.visualizations import vis_label
+from chainercv.visualizations import vis_semantic_segmentation
 
 
 def main():
@@ -36,7 +36,8 @@ def main():
     ax1 = fig.add_subplot(1, 2, 1)
     vis_image(img, ax=ax1)
     ax2 = fig.add_subplot(1, 2, 2)
-    vis_label(label, camvid_label_names, camvid_label_colors, ax=ax2)
+    vis_semantic_segmentation(
+        label, camvid_label_names, camvid_label_colors, ax=ax2)
     plot.show()
 
 

tests/visualizations_tests/test_vis_label.py → tests/visualizations_tests/test_vis_semantic_segmentation.py

@@ -3,7 +3,7 @@
 
 from chainer import testing
 
-from chainercv.visualizations import vis_label
+from chainercv.visualizations import vis_semantic_segmentation
 
 try:
     import matplotlib  # NOQA
@@ -17,15 +17,15 @@
     'label_colors': [None, ((255, 0, 0), (0, 255, 0), (0, 0, 255))],
     'all_label_names_in_legend': [False, True],
 }))
-class TestVisLabel(unittest.TestCase):
+class TestVisSemanticSegmentation(unittest.TestCase):
 
     def setUp(self):
         self.label = np.random.randint(
             -1, 3, size=(48, 64)).astype(np.int32)
 
-    def test_vis_label(self):
+    def test_vis_semantic_segmentation(self):
         if optional_modules:
-            ax, legend_handles = vis_label(
+            ax, legend_handles = vis_semantic_segmentation(
                 self.label,
                 label_names=self.label_names, label_colors=self.label_colors,
                 all_label_names_in_legend=self.all_label_names_in_legend)
@@ -35,24 +35,24 @@ def test_vis_label(self):
                 self.assertIsInstance(handle, matplotlib.patches.Patch)
 
 
-class TestVisLabelInvalidArguments(unittest.TestCase):
+class TestVisSemanticSegmentationInvalidArguments(unittest.TestCase):
 
-    def test_vis_label_mismatch_names_and_colors(self):
+    def test_vis_semantic_segmentation_mismatch_names_and_colors(self):
         label = np.random.randint(-1, 2, size=(48, 64)).astype(np.int32)
 
         if optional_modules:
             with self.assertRaises(ValueError):
-                vis_label(
+                vis_semantic_segmentation(
                     label,
                     label_names=('class0', 'class1', 'class2'),
                     label_colors=((255, 0, 0), (0, 255, 0)))
 
-    def test_vis_label_exceed_value(self):
+    def test_vis_semantic_segmentation_exceed_value(self):
         label = np.random.randint(10, 20, size=(48, 64)).astype(np.int32)
 
         if optional_modules:
             with self.assertRaises(ValueError):
-                vis_label(
+                vis_semantic_segmentation(
                     label,
                     label_names=('class0', 'class1', 'class2'))