Notebook reproduction
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Thank you for the amazing work
I was running the superpoint_transformer_tutorial.ipynb with data downloaded from the https://webtransfer.vancouver.ca/opendata/2022LiDAR/482000_5455000.zip as mentioned in the instruction.
I couldnt get past intensity based evaluation and also visualize model output.
in the visualization i get
data.show(center=[425, 282, 15], radius=30, keys=['intensity'], class_names=VANCOUVER_CLASS_NAMES, class_colors=VANCOUVER_CLASS_COLORS)
>>> 343 void_classes = [num_classes] if num_classes else []
345 # Draw a trace for position-colored 3D point cloud
--> 346 mini = data_0.pos.min(dim=0).values
347 maxi = data_0.pos.max(dim=0).values
348 colors = (data_0.pos - mini) / (maxi - mini + 1e-6)
IndexError: min(): Expected reduction dim 0 to have non-zero size.
and visualizing transformations
nag.show(class_names=VANCOUVER_CLASS_NAMES, class_colors=VANCOUVER_CLASS_COLORS, center=[485, 505, 0], radius=20, keys=nag[0].keys, centroids=True, h_edge=True)
>>> File ~/superpoint_transformer/src/utils/sparse.py:17, in indices_to_pointers(indices)
15 device = indices.device
16 assert len(indices.shape) == 1, "Only 1D indices are accepted."
---> 17 assert indices.shape[0] >= 1, "At least one group index is required."
18 assert is_dense(indices), "Indices must be dense"
20 # Sort indices if need be
AssertionError: At least one group index is required.
what am i doing wrong ? if this is related to the data should i download specific one?
Hi @IsraelAbebe, thanks for your interest in the project !
The error you are seeing suggests you are visualizing an empty Data
object (ie with 0 points). I can think of 2 ways this could have happened to you:
- you introduced some additional modifications on the
Data
object (ie have you made any modification to the notebook so far ?) - the Vancouver dataset tile you are using is not the same as the one I used in the tutorial. In which case, it is likely the
center
used for visualization is simply outside the range of your cloud's point coordinates. To adjust this, run the previous cell:
data.show(class_names=VANCOUVER_CLASS_NAMES, class_colors=VANCOUVER_CLASS_COLORS)
and find newcenter
coordinates better suited to your tile by mouse hovering over points
PS: If you ❤️ or use this project, don't forget to give it a ⭐, it means a lot to us !