Datasets:
Tasks:
Other
Modalities:
Image
Size:
100K<n<1M
Tags:
IGN
Environement
Earth Observation
Aerial Lidar
Point Cloud Segmentation
3D Scene Understanding
License:
Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code: DatasetGenerationError
Exception: ValueError
Message: Invalid string class label train
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1537, in _prepare_split_single
example = self.info.features.encode_example(record) if self.info.features is not None else record
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 2162, in encode_example
return encode_nested_example(self, example)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1446, in encode_nested_example
{k: encode_nested_example(schema[k], obj.get(k), level=level + 1) for k in schema}
~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1469, in encode_nested_example
return schema.encode_example(obj) if obj is not None else None
~~~~~~~~~~~~~~~~~~~~~^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1144, in encode_example
example_data = self.str2int(example_data)
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1081, in str2int
output = [self._strval2int(value) for value in values]
~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/features/features.py", line 1102, in _strval2int
raise ValueError(f"Invalid string class label {value}")
ValueError: Invalid string class label train
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 1382, 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 1560, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
image image | label class label |
|---|---|
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 | |
000 |
End of preview.
This repo contains the orthoimageries used to colorize point clouds in the FRACTAL semantic segmentation dataset.
They are provided as is, in their original size (50 x 50 m), spatial resolution (0.2 m, i.e. 250 x 250 pixels) and band order (near-infrared, red, green, blue).
They might be used for quick visual inspections of the FRACTAL's point clouds, or for more advanced use such as multimodal (2D-3D) deep learning training.
Note:
- The files are ordered by filename. Inspecting a single zip archive is therefore not representative of the whole dataset.
- The band order does not play nice with standard image softwares. Consider reordering band order and disabling the use of transparency in a GIS software like QGis.
- Downloads last month
- 13