Roadwork_Cones_Dataset

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Cannot get the split names for the config 'default' of the dataset.

Exception:    HfHubHTTPError
Message:      (Request ID: Root=1-6a6733ae-22a63e9d0abfb9bb422c9d83;a35ec9b3-2f70-45d7-8600-3740331712c6)

429 Too Many Requests: you have reached your 'api' rate limit.
Retry after 122 seconds (0/500 requests remaining in current 300s window).
Url: https://huggingface.co/api/datasets/Robbin123/Roadwork_Cones_Dataset/tree/2ed38487279a0e71b9a7e4cfebbfd2f08bd0313c/data?recursive=true&expand=false.
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Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 71, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ~~~~~~~~~~~~~~~~~~~~~~~^
                      path=dataset,
                      ^^^^^^^^^^^^^
                      config_name=config,
                      ^^^^^^^^^^^^^^^^^^^
                      token=hf_token,
                      ^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 268, in get_dataset_config_info
                  builder = load_dataset_builder(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/src/services/worker/src/worker/utils.py", line 390, in safe_load_dataset_builder
                  dataset_module = dataset_module_factory(
                      repo_dir,
                      revision=revision,
                      download_config=download_config,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 1217, in dataset_module_factory
                  raise e1 from None
                File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 1192, in dataset_module_factory
                  ).get_module()
                    ~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 648, in get_module
                  patterns = get_data_patterns(base_path, download_config=self.download_config)
                File "/usr/local/lib/python3.14/site-packages/datasets/data_files.py", line 493, in get_data_patterns
                  return _get_data_files_patterns(resolver)
                File "/usr/local/lib/python3.14/site-packages/datasets/data_files.py", line 268, in _get_data_files_patterns
                  data_files = pattern_resolver(pattern)
                File "/usr/local/lib/python3.14/site-packages/datasets/data_files.py", line 372, in resolve_pattern
                  for filepath, info in fs.glob(fs_pattern, detail=True, **glob_kwargs).items():
                                        ~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_file_system.py", line 728, in glob
                  return super().glob(path, maxdepth=maxdepth, **kwargs)
                         ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/fsspec/spec.py", line 611, in glob
                  allpaths = self.find(root, maxdepth=depth, withdirs=True, detail=True, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_file_system.py", line 767, in find
                  out = self._ls_tree(path, recursive=True, refresh=refresh, maxdepth=maxdepth, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_file_system.py", line 612, in _ls_tree
                  for path_info in tree:
                                   ^^^^
                File "/usr/local/lib/python3.14/site-packages/huggingface_hub/hf_api.py", line 3922, in list_repo_tree
                  for path_info in paginate(path=tree_url, headers=headers, params={"recursive": recursive, "expand": expand}):
                                   ~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/huggingface_hub/utils/_pagination.py", line 36, in paginate
                  hf_raise_for_status(r)
                  ~~~~~~~~~~~~~~~~~~~^^^
                File "/usr/local/lib/python3.14/site-packages/huggingface_hub/utils/_http.py", line 868, in hf_raise_for_status
                  raise _format(HfHubHTTPError, message, response) from e
              huggingface_hub.errors.HfHubHTTPError: (Request ID: Root=1-6a6733ae-22a63e9d0abfb9bb422c9d83;a35ec9b3-2f70-45d7-8600-3740331712c6)
              
              429 Too Many Requests: you have reached your 'api' rate limit.
              Retry after 122 seconds (0/500 requests remaining in current 300s window).
              Url: https://huggingface.co/api/datasets/Robbin123/Roadwork_Cones_Dataset/tree/2ed38487279a0e71b9a7e4cfebbfd2f08bd0313c/data?recursive=true&expand=false.
              We had to rate limit your IP (100.60.123.83). To continue using our service, create a HF account or login to your existing account, and make sure you pass a HF_TOKEN if you're using the API.

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Check out the documentation for more information.

Roadwork Cones Dataset

This dataset is designed for detecting roadwork-zone objects in autonomous driving scenarios. It contains three classes - traffic cones, roadworks signs, and vertical guide panels (delineators) - captured from four vehicle-mounted cameras across 39 driving sessions in urban and suburban roads.

Classes (3)

Class	Count	Description
cone	11,520	Standard traffic cone
roadworks	2,813	Roadwork zone sign / panel
vertical_pannel	17,069	Vertical guide panel (delineator)

Data Fields

Field	Type	Description
bbox_msg_id	VARCHAR	UUID linking to the original bounding box message
object_id	BIGINT	Unique object tracking ID
label	VARCHAR	Object class (`cone`, `roadworks`, `vertical_pannel`)
bbox_coords	DOUBLE[4]	Bounding box [x, y, width, height] in pixel coordinates
timestamp_ns	BIGINT	ROS bag timestamp (nanoseconds)
image_path	VARCHAR	Relative path to JPEG in `train/` or `test/`

Data Splits

Split	Rows	Images
train	22,841	2,871
test	8,561	1,803

Dataset Structure

roadwork_cones_dataset/
├── annotations.parquet   # All annotations (31,402 rows)
├── train/
│   ├── camera_1C0FAF5250E2/   # 854 images
│   ├── camera_1C0FAF57D6F8/   # 1,415 images
│   ├── camera_1C0FAF5CA7B6/   # 494 images
│   └── camera_1C0FAF5CC14D/   # 108 images
└── test/
    ├── camera_1C0FAF5250E2/   # 570 images
    ├── camera_1C0FAF57D6F8/   # 1,193 images
    ├── camera_1C0FAF5CA7B6/   # 40 images
    └── camera_1C0FAF5CC14D/   # 0 images

Usage

import pandas as pd

df = pd.read_parquet("annotations.parquet")
print(f"{len(df)} annotations, {df.image_path.nunique()} unique images")

Downloads last month: 29

Source:

Fleet of autonomous vehicles, urban and suburban roads

Sensor:

4x LUCID TRI054S-CC cameras (2880×1860), front/side facing

Coverage:

~31K bounding box annotations, ~4.7K unique images, 3 classes

Splits:

Train 70% (22,841 rows, 2,871 images), Test 30% (8,561 rows, 1,803 images) - split by driving session to prevent temporal leakage