The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code:   ConfigNamesError
Exception:    BadZipFile
Message:      zipfiles that span multiple disks are not supported
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 79, in compute_config_names_response
                  config_names = get_dataset_config_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1910, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1885, in dataset_module_factory
                  return HubDatasetModuleFactoryWithoutScript(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1270, in get_module
                  module_name, default_builder_kwargs = infer_module_for_data_files(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 589, in infer_module_for_data_files
                  split_modules = {
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 590, in <dictcomp>
                  split: infer_module_for_data_files_list(data_files_list, download_config=download_config)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 531, in infer_module_for_data_files_list
                  return infer_module_for_data_files_list_in_archives(data_files_list, download_config=download_config)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 559, in infer_module_for_data_files_list_in_archives
                  for f in xglob(extracted, recursive=True, download_config=download_config)[
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 1291, in xglob
                  fs, *_ = url_to_fs(urlpath, **storage_options)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/core.py", line 395, in url_to_fs
                  fs = filesystem(protocol, **inkwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/registry.py", line 293, in filesystem
                  return cls(**storage_options)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 80, in __call__
                  obj = super().__call__(*args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/implementations/zip.py", line 62, in __init__
                  self.zip = zipfile.ZipFile(
                File "/usr/local/lib/python3.9/zipfile.py", line 1266, in __init__
                  self._RealGetContents()
                File "/usr/local/lib/python3.9/zipfile.py", line 1329, in _RealGetContents
                  endrec = _EndRecData(fp)
                File "/usr/local/lib/python3.9/zipfile.py", line 286, in _EndRecData
                  return _EndRecData64(fpin, -sizeEndCentDir, endrec)
                File "/usr/local/lib/python3.9/zipfile.py", line 232, in _EndRecData64
                  raise BadZipFile("zipfiles that span multiple disks are not supported")
              zipfile.BadZipFile: zipfiles that span multiple disks are not supported

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

This is 125,160 (out of 800,000) 3D models from AllenAI Objaverse 1.0.

These models have had their materials & normals removed, have been normalised in scale and origin recentered, and are all triangulated.

As a result each model is much smaller in size, every model is uniform and faster to process.

This dataset is great for training networks on shapes of 3D objects.

My suggested use of this dataset is to raytrace a point-cloud of 𝑥 density from the triangle faced meshes, this can then be used to train a neural network to produce point-cloud shapes which can then be re-meshed.

The filenames will match up with the Allen-AI Objaverse Metadata.

If you want an even smaller dataset then Plyverse-1.0 is the same pre-processing on 10,000 3D models and includes the original vertex normals.

Possible licenses of these models, as quoted from AllenAI:

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