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Error code: DatasetGenerationError
Exception: ValueError
Message: Invalid string class label Moon_Detection_Dataset_for_YOLOv8@7ccf23a5a42677a9ca670c4e2539dffd294d2ccd
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 Moon_Detection_Dataset_for_YOLOv8@7ccf23a5a42677a9ca670c4e2539dffd294d2ccd
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.
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Moon Detection Dataset for YOLOv8
This dataset was developed as part of the CubeRT-02 project, a CubeSat mission aimed at testing AI-powered vision systems in aerospace contexts. It consists of 7500+ annotated images for object detection of the Moon, optimized for use with the YOLOv8 architecture.
📸 Dataset Collection & Annotation
Initial set: ~400 web-sourced images used for theoretical model exploration.
Main dataset: 7500+ images captured over 6 months using smartphones and amateur camera devices, reflecting real-world scales, perspectives, and conditions.
Cleaning: Manual filtering of blurry, low-quality, or irrelevant images.
Annotation: Performed via Roboflow platform with bounding boxes for YOLOv8.
Augmentation: Basic augmentations applied during preparation; none used during final training due to negative effects on performance.
📁 Dataset Structure
This dataset follows the YOLOv8 format. A Python script and a YAML configuration file are included to help you easily train or test the dataset using Ultralytics' YOLOv8 implementation.
Authors
Luis Adrian Cabrera | https://github.com/LuisAdrian5519
Jesse Banda Chaidez | https://github.com/Jessebnda
Contributors
José Alejandro Padilla Pérez | https://github.com/PadillaPepe777
Erick Blanco Nakashima
Juan Pablo Riojas Pesqueira
Guillermo Villegas
Juan Adrian Astorga
Julio Castañeda
Juan Pablo Aboytes
Maximo Millán Cabrera
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