Datasets:

meddourimane
/

StereoGeo-CARLA

Error code:   StreamingRowsError
Exception:    ValueError
Message:      Invalid string class label left_images
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 272, 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 "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2240, in __iter__
                  example = _apply_feature_types_on_example(
                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2157, in _apply_feature_types_on_example
                  encoded_example = features.encode_example(example)
                                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2152, in encode_example
                  return encode_nested_example(self, example)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1437, in encode_nested_example
                  {k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1460, in encode_nested_example
                  return schema.encode_example(obj) if obj is not None else None
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1143, in encode_example
                  example_data = self.str2int(example_data)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1080, in str2int
                  output = [self._strval2int(value) for value in values]
                            ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1101, in _strval2int
                  raise ValueError(f"Invalid string class label {value}")
              ValueError: Invalid string class label left_images

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StereoGeo CARLA Dataset

StereoGeo: End-to-End Stereo Camera Calibration Method

Introduction

The StereoGeo CARLA Dataset is a large-scale stereo camera calibration dataset generated from the CARLA driving simulator. It provides ground-truth intrinsic and extrinsic camera parameters for training deep learning-based calibration methods.

This public release contains 12,220 stereo pairs from diverse urban driving scenarios with varying weather conditions and camera orientations.

Dataset Overview

12,220 stereo image pairs
Resolution: 640×640 pixels each
Baseline range: 0.20 - 0.70 m
Roll/Pitch: ±0.5°
Vertical FoV: 55° - 75°
Total size: ~12.2 GB
Source: CARLA Simulator
Scenarios: Urban driving, multiple weather conditions

Dataset Structure

StereoGeo-CARLA/
├── left_images/
│   ├── batch_1.zip     (4.073 images)
│   └── batch_2.zip     (4.073 images)
│   └── batch_3.zip     (4.074 images)    
├── right_images/
│   ├── batch_1.zip     (4.073 images)
│   └── batch_2.zip     (4.073 images)
│   └── batch_3.zip     (4.074 images)
├── left_images.csv     (metadata for left camera)
└── right_images.csv    (metadata for right camera)

Why Batches?

Images are organized into batches to comply with HuggingFace's file limits. Simply load images by their filenames from the CSV files - the batch organization is transparent to users.

Metadata Format

left_images.csv and right_images.csv contain the following columns:

Column	Type	Description
`image_name`	string	Filename
`roll`	float	Camera roll angle (radians)
`pitch`	float	Camera pitch angle (radians)
`vfov`	float	Vertical field of view (radians)
`height`	int	Image height (pixels)
`width`	int	Image width (pixels)
`R_00` to `R_22`	float	Relative rotation matrix (9 elements)
`t_0`, `t_1`, `t_2`	float	Relative translation vector (meters)

Citation

If you use the StereoGeo CARLA dataset, please cite:

@inproceedings{2026stereogeo,
  title={StereoGeo: End-to-End Stereo Camera Calibration Method},
  author={Imane and Andrea and Cedric},
  booktitle={EUSIPCO},
  year={2026}
}

Acknowledgments

CGP has benefited from French State aid managed by the Agence Nationale de la Recherche (ANR) under France 2030 program with the reference ANR-23-PEIA-005 (REDEEM project).
CARLA Simulator Team - For the photorealistic driving simulator.

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Total file size:

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