add vertex visualization option

hoho/vis.py

@@ -41,7 +41,7 @@ def line(p1, p2, c=(255,0,0), resolution=10, radius=0.05):
          
     return mesh
 
-def show_wf(row, radius=10):
+def show_wf(row, radius=10, show_vertices=False):
     EDGE_CLASSES = ['eave',
                     'ridge',
                     'step_flashing',
@@ -51,14 +51,18 @@ def show_wf(row, radius=10):
                     'valley',
                     'hip',
                     'transition_line']
+    out_meshes = []
+    if show_vertices:
+        out_meshes.extend([trimesh.primitives.Sphere(radius=radius+5, center = center, color=(255,0,0)) for center in row['wf_vertices']])
     if 'edge_semantics' not in row:
         print ("Warning: edge semantics is not here, skipping")
-        return [line(a,b, radius=radius, c=(214, 251, 248)) for a,b in np.stack([*row['wf_vertices']])[np.stack(row['wf_edges'])]]
+        out_meshes.extend([line(a,b, radius=radius, c=(214, 251, 248)) for a,b in np.stack([*row['wf_vertices']])[np.stack(row['wf_edges'])]])
     elif len(np.stack(row['wf_edges'])) ==  len(row['edge_semantics']):
-        return [line(a,b, radius=radius, c=color_mappings.gestalt_color_mapping[EDGE_CLASSES[cls_id]]) for (a,b), cls_id in zip(np.stack([*row['wf_vertices']])[np.stack(row['wf_edges'])], row['edge_semantics'])]
+        out_meshes.extend([line(a,b, radius=radius, c=color_mappings.gestalt_color_mapping[EDGE_CLASSES[cls_id]]) for (a,b), cls_id in zip(np.stack([*row['wf_vertices']])[np.stack(row['wf_edges'])], row['edge_semantics'])])
     else:
         print ("Warning: edge semantics has different length compared to edges, skipping semantics")
-        return [line(a,b, radius=radius, c=(214, 251, 248)) for a,b in np.stack([*row['wf_vertices']])[np.stack(row['wf_edges'])]]
+        out_meshes.extend([line(a,b, radius=radius, c=(214, 251, 248)) for a,b in np.stack([*row['wf_vertices']])[np.stack(row['wf_edges'])]])
+    return out_meshes
     # return [line(a,b, radius=radius, c=color_mappings.edge_colors[cls_id]) for (a,b), cls_id in zip(np.stack([*row['wf_vertices']])[np.stack(row['wf_edges'])], row['edge_semantics'])]