fix typo + formatting

README.md

@@ -13,9 +13,9 @@ The repo consistst of the following parts:
 
 ## Solution description
 
-The solution is is simple. 
+The solution is simple. 
 
-1. Using provided (but noisy) semantic segmentation called `gestalt`, it taks the centroids of the vertex classes - `apex` and `eave_end_point` and projects them to 3D using provided (also noisy) monocular depth. 
+1. Using provided (but noisy) semantic segmentation called `gestalt`, it takes the centroids of the vertex classes - `apex` and `eave_end_point` and projects them to 3D using provided (also noisy) monocular depth. 
 2. The vertices are connected using the same segmentation, by checking for edges classes to be present - `['eave', 'ridge', 'rake', 'valley']`. 
 3. All the "per-image" vertex predictions are merged in 3D space if their distance is less than threshold.
 4. All vertices, which have zero connections, are removed. 

handcrafted_solution.py

@@ -238,6 +238,8 @@ def predict(entry, visualize=False) -> Tuple[np.ndarray, List[int]]:
         return (good_entry['__key__'], *empty_solution())
     if visualize:
         from hoho.viz3d import plot_estimate_and_gt
-        plot_estimate_and_gt(all_3d_vertices_clean, connections_3d_clean, good_entry['wf_vertices'],
-                            good_entry['wf_edges'])
-    return good_entry['__key__'], all_3d_vertices_clean, connections_3d_clean
+        plot_estimate_and_gt(   all_3d_vertices_clean, 
+                                connections_3d_clean, 
+                                good_entry['wf_vertices'],
+                                good_entry['wf_edges'])
+    return good_entry['__key__'], all_3d_vertices_clean, connections_3d_clean