continue
elif torch.is_tensor(item) and item.size(0) == num_nodes and item.size(0) != 1:
data[key] = item[choice]
+
elif isinstance(item, np.ndarray) and item.shape[0] == num_nodes and item.shape[0] != 1:
+
data[key] = item[choice]
+
return data
@@ -399,9 +402,7 @@
Source code for myria3d.pctl.transforms.transforms
if points_to_drop.sum() > 0:
points_to_keep = torch.logical_not(points_to_drop)
data = subsample_data(data, num_nodes=data.num_nodes, choice=points_to_keep)
- # Here we also subsample these idx since we do not need to interpolate these points back
- if "idx_in_original_cloud" in data:
- data.idx_in_original_cloud = data.idx_in_original_cloud[points_to_keep]
+
return data