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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    ValueError
Message:      Object arrays cannot be loaded when allow_pickle=False
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1593, in _prepare_split_single
                  example = self.info.features.encode_example(record) if self.info.features is not None else record
                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2058, in encode_example
                  example = cast_to_python_objects(example)
                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 484, in cast_to_python_objects
                  return _cast_to_python_objects(
                         ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 413, in _cast_to_python_objects
                  casted_v, has_changed_v = _cast_to_python_objects(
                                            ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 412, in _cast_to_python_objects
                  for k, v in obj.items():
                              ^^^^^^^^^^^
                File "<frozen _collections_abc>", line 894, in __iter__
                File "/usr/local/lib/python3.12/site-packages/numpy/lib/_npyio_impl.py", line 257, in __getitem__
                  return format.read_array(
                         ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/numpy/lib/_format_impl.py", line 833, in read_array
                  raise ValueError("Object arrays cannot be loaded when "
              ValueError: Object arrays cannot be loaded when allow_pickle=False
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1342, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 907, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1438, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1617, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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20230705_10/perspective_2/left_images/20230705_100730
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20230705_10/perspective_2/left_images/20230705_103330
hf://datasets/jacoblin/cloud4d@ce1860cb3b989dd515d24f7a9ec4c9863c931de4/real_world/20230705_10.tar.gz
20230705_10/perspective_2/left_images/20230705_104350
hf://datasets/jacoblin/cloud4d@ce1860cb3b989dd515d24f7a9ec4c9863c931de4/real_world/20230705_10.tar.gz
20230705_10/perspective_2/left_images/20230705_105045
hf://datasets/jacoblin/cloud4d@ce1860cb3b989dd515d24f7a9ec4c9863c931de4/real_world/20230705_10.tar.gz
20230705_10/perspective_2/left_images/20230705_100805
hf://datasets/jacoblin/cloud4d@ce1860cb3b989dd515d24f7a9ec4c9863c931de4/real_world/20230705_10.tar.gz
20230705_10/perspective_2/left_images/20230705_102520
hf://datasets/jacoblin/cloud4d@ce1860cb3b989dd515d24f7a9ec4c9863c931de4/real_world/20230705_10.tar.gz
20230705_10/perspective_2/left_images/20230705_103600
hf://datasets/jacoblin/cloud4d@ce1860cb3b989dd515d24f7a9ec4c9863c931de4/real_world/20230705_10.tar.gz
20230705_10/perspective_2/left_images/20230705_104025
hf://datasets/jacoblin/cloud4d@ce1860cb3b989dd515d24f7a9ec4c9863c931de4/real_world/20230705_10.tar.gz
20230705_10/perspective_2/left_images/20230705_105015
hf://datasets/jacoblin/cloud4d@ce1860cb3b989dd515d24f7a9ec4c9863c931de4/real_world/20230705_10.tar.gz
End of preview.

Cloud4D Dataset

Dataset for "Cloud4D: Estimating Cloud Properties at a High Spatial and Temporal Resolution", NeurIPS 2025 (Spotlight)

Project Page: https://cloud4d.jacob-lin.com/

Dataset Structure

The dataset is organized into two main categories:

Cloud4D/
├── real_world/                    # Real-world stereo camera captures
│   ├── 20230705_10/               # Date-hour folders (YYYYMMDD_HH)
│   │   ├── perspective_1/
│   │   │   ├── left_images/       # Left camera images
│   │   │   ├── right_images/      # Right camera images
│   │   │   ├── camera_pair.npz    # Stereo calibration data
│   │   │   └── *.npy              # Camera intrinsics/extrinsics
│   │   ├── perspective_2/
│   │   └── perspective_3/
│   └── ...
└── synthetic/                     # Synthetic cloud renders
    ├── terragen/                  # Terragen renders
    │   ├── perspective_1/
    │   ├── perspective_2/
    │   └── perspective_3/
    └── large_eddy_simulations/    # LES-based renders
        ├── perspective_1/
        ├── perspective_2/
        ├── perspective_3/
        └── volumes/

Quick Start

Download and Extract

# Clone the dataset
hf download jacoblin/cloud4d --repo-type dataset --local-dir cloud4d
cd cloud4d

# Extract all archives
python unpack.py

# Or extract to a specific location
python unpack.py --output /path/to/cloud4d

Selective Extraction

# Extract only real-world data
python unpack.py --subset real_world

# Extract only synthetic data
python unpack.py --subset synthetic

# Extract a specific date
python unpack.py --filter 20230705

# List available archives without extracting
python unpack.py --list

Parallel Extraction (Faster)

# Use 4 parallel workers
python unpack.py --jobs 4

Citation

If you use this dataset in your research, please cite:

@inproceedings{
      lin2025cloudd,
      title={Cloud4D: Estimating Cloud Properties at a High Spatial and Temporal Resolution},
      author={Jacob Lin and Edward Gryspeerdt and Ronald Clark},
      booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems},
      year={2025},
      url={https://openreview.net/forum?id=g2AAvmBwkS}
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