The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: ReadError
Message: unexpected end of data
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
return get_rows(
File "/src/libs/libcommon/src/libcommon/utils.py", line 271, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2266, in __iter__
for key, example in ex_iterable:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1866, in __iter__
for key, example in self.ex_iterable:
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 222, in __iter__
for key_example in islice(self.generate_examples_fn(**gen_kwags), shard_example_idx_start, None):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 122, in _generate_examples
for example_idx, example in enumerate(self._get_pipeline_from_tar(tar_path, tar_iterator)):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 44, in _get_pipeline_from_tar
current_example[field_name.lower()] = f.read()
File "/usr/local/lib/python3.9/tarfile.py", line 690, in read
raise ReadError("unexpected end of data")
tarfile.ReadError: unexpected end of dataNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Turin 3D Dataset
Description
The Turin 3D dataset is a collection of LiDAR point cloud data acquired within the city of Turin, Italy on January 2022 and collected in LAS 1.4 format. It's designed for use in 3D semantic segmentation tasks. This dataset offers a detailed 3D representation of the urban environment, enabling the development and evaluation of semantic segmentation models for urban scenes.
Purpose
This dataset is intended for researchers and practitioners interested in studying 3D semantic segmentation of urban environments using LiDAR data. It can be used for:
- Development and evaluation of 3D semantic segmentation algorithms.
- Analysis and understanding of urban scenes.
- Applications in autonomous vehicles, robotics, and urban planning.
Dataset Content
It contains almost 70M points divided among 57 blocks covering around 25k m^2 each. Data is compressed with gzip, you can extract it using
cat dataset.tar.*.gz.part > dataset.tar.gz
tar -xvzf dataset.tar.gz
Class Taxonomy
The dataset utilizes a taxonomy of 6 semantic classes:
- Undefined
- Soil
- Terrain
- Vegetation
- Building
- Street element
- Water
Dataset Splits
- Train: Provided with soft labels (class probabilities).
- Validation: Precise annotations (hard labels) for model evaluation.
- Test: Precise annotations (hard labels) for final model evaluation.
Annotation
- Train: Annotations generated automatically using deep learning models, providing soft labels.
- Validation and Test: Manual annotations.
Dataset Card Authors
Luca Barco, Giacomo Blanco, Gaetano Chiriaco, Fabrizio Dominici
Dataset Card Contact
[email protected], [email protected], [email protected], [email protected]
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