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MichalPelka
/
MandeyeMappingLoopClosure

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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
device: string
dtype: string
fpa_temp_c: double
frame: int64
frame_counter: int64
height: int64
housing_temp_c: double
timestamp_ns: int64
uptime_ms: int64
width: int64
SCALER_CROP: string
EXPOSURE_TIME: string
COLOUR_CORRECTION_MATRIX: string
DIGITAL_GAIN: string
FRAME_WALL_CLOCK: string
COLOUR_TEMPERATURE: string
ANALOGUE_GAIN: string
COLOUR_GAINS: string
FRAME_DURATION: string
FOCUS_FO_M: string
SENSOR_BLACK_LEVELS: string
AE_STATE: string
SENSOR_TIMESTAMP: string
LUX: string
to
{'AE_STATE': Value('string'), 'ANALOGUE_GAIN': Value('string'), 'COLOUR_CORRECTION_MATRIX': Value('string'), 'COLOUR_GAINS': Value('string'), 'COLOUR_TEMPERATURE': Value('string'), 'DIGITAL_GAIN': Value('string'), 'EXPOSURE_TIME': Value('string'), 'FOCUS_FO_M': Value('string'), 'FRAME_DURATION': Value('string'), 'FRAME_WALL_CLOCK': Value('string'), 'LUX': Value('string'), 'SCALER_CROP': Value('string'), 'SENSOR_BLACK_LEVELS': Value('string'), 'SENSOR_TIMESTAMP': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              device: string
              dtype: string
              fpa_temp_c: double
              frame: int64
              frame_counter: int64
              height: int64
              housing_temp_c: double
              timestamp_ns: int64
              uptime_ms: int64
              width: int64
              SCALER_CROP: string
              EXPOSURE_TIME: string
              COLOUR_CORRECTION_MATRIX: string
              DIGITAL_GAIN: string
              FRAME_WALL_CLOCK: string
              COLOUR_TEMPERATURE: string
              ANALOGUE_GAIN: string
              COLOUR_GAINS: string
              FRAME_DURATION: string
              FOCUS_FO_M: string
              SENSOR_BLACK_LEVELS: string
              AE_STATE: string
              SENSOR_TIMESTAMP: string
              LUX: string
              to
              {'AE_STATE': Value('string'), 'ANALOGUE_GAIN': Value('string'), 'COLOUR_CORRECTION_MATRIX': Value('string'), 'COLOUR_GAINS': Value('string'), 'COLOUR_TEMPERATURE': Value('string'), 'DIGITAL_GAIN': Value('string'), 'EXPOSURE_TIME': Value('string'), 'FOCUS_FO_M': Value('string'), 'FRAME_DURATION': Value('string'), 'FRAME_WALL_CLOCK': Value('string'), 'LUX': Value('string'), 'SCALER_CROP': Value('string'), 'SENSOR_BLACK_LEVELS': Value('string'), 'SENSOR_TIMESTAMP': Value('string')}
              because column names don't match
              
              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 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, 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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AE_STATE
string
ANALOGUE_GAIN
string
COLOUR_CORRECTION_MATRIX
string
COLOUR_GAINS
string
COLOUR_TEMPERATURE
string
DIGITAL_GAIN
string
EXPOSURE_TIME
string
FOCUS_FO_M
string
FRAME_DURATION
string
FRAME_WALL_CLOCK
string
LUX
string
SCALER_CROP
string
SENSOR_BLACK_LEVELS
string
SENSOR_TIMESTAMP
string
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[ 1.985759, 1.745461 ]
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[ 4096, 4096, 4096, 4096 ]
97299848000
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1.000000
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[ 1.977509, 1.752644 ]
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(0, 0)/4656x3496
[ 4096, 4096, 4096, 4096 ]
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1.000000
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[ 1.972177, 1.757294 ]
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3645.930664
(0, 0)/4656x3496
[ 4096, 4096, 4096, 4096 ]
98410604000
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1.000000
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[ 1.968050, 1.760892 ]
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(0, 0)/4656x3496
[ 4096, 4096, 4096, 4096 ]
98965982000
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1.000000
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[ 1.949743, 1.777562 ]
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[ 4096, 4096, 4096, 4096 ]
99521361000
2
1.186558
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100632116000
End of preview.

Mandeye Mapping – Loop Closure dataset

Handheld LiDAR + IMU + camera dataset recorded with a Mandeye scanner in an urban courtyard, with a loop in the trajectory. It comes with LiDAR-inertial odometry results from HDMapping (v0.104.0) and a LiDAR–camera calibration, so you can colorize the point cloud from the camera images.

Colored point cloud and camera trajectory in HDMapping's Trajectory Viewer

▶️ Video: https://youtu.be/jxjWX8dq30Y

Contents

Path Description
lidar*.laz, lidar*.sn Raw LiDAR chunks (point clouds + serial numbers)
imu*.csv IMU data (gyro, accelerometer, timestamps)
status*.json Scanner status snapshots
CAMERA_0_blurred/ Camera images (cam0_<timestamp>.jpg), faces/plates blurred
extrinsics.json Camera intrinsics (fx, fy, cx, cy, distortion) and T_lidar_to_camera_4x4 extrinsics
lio_result_0/ HDMapping LiDAR-inertial odometry output: scan_lio_*.laz, trajectory_lio_*.csv, session.mjs, params .toml

Usage

  1. Download the dataset:
    git lfs install
git clone https://huggingface.co/datasets/MichalPelka/MandeyeMappingLoopClosure
  2. Get HDMapping (releases).
  3. (Optional) Re-run LiDAR odometry on the raw data with HDMapping's lidar_odometry_step_1, or use the provided lio_result_0/.
  4. Open the Trajectory Viewer and in the side panel:
    • Session → LIO result directory: ./lio_result_0, leave CAMERA_0 directory empty (auto-detects CAMERA_0_blurred) → Load session → Load cloud
    • Calibration → Calibration JSON: extrinsics.json → Load calibration
    • Export → Export colored LAZ / Export colored E57

Links

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