FUSU: A Multi-temporal-source Land Use Change Segmentation Dataset for Fine-grained Urban Semantic Understanding
Paper • 2405.19055 • Published
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The dataset generation failed
Error code: DatasetGenerationError
Exception: ValueError
Message: Invalid string class label FUSU-Fine_grained_Urban_Semantic_Understanding@5a4a1c6d98e2a6bc0de42f5c372d5d9a96b730f8
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 FUSU-Fine_grained_Urban_Semantic_Understanding@5a4a1c6d98e2a6bc0de42f5c372d5d9a96b730f8
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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End of preview.
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Check out the documentation for more information.
About:
FUSU dataset covers 5 whole urban areas, 847 km^2 located in the north and south of China, with 17 land use and land cover (LULC) classes and over 170K images and 30 billion pixels of annotations, supporting segmentation, change detection and domain adaptation tasks. This data comprises 2 parts:
Bi-temporal high-resolution satellite RGB images with fine-grained annotations.
Monthly revisited Sentinel-2 and Sentinel-1 images.
Details:
1. Resolution
The spatial resolution of high-resolution image is 0.2-0.5m, and the Sentinel image is 10m. The time resolution of high-resolution image is 2 years, and the Sentinel image is one month.
2. Construction
(Now this repo only contains high-resolution images and labels)
FUSU comprises 62,752 image patches, each containing 25 images collected from Sentinel, 2 images from Google Earth, and 2 corresponding annotations.
Example: T1: im1/6_255.png, im1_label/6_255.png T2: im2/6_255.png, im2_label/6_255.png Sentinel: A/{8-12}/6_255_A_{8-12}.png, B/{1-12}/6_255_B_{1-12}.png, C/{1-12}/6_255_C_{1-12}.png
{A,B,C} represents the year, and {1-12} represents the month.
Shape: T1 image (512 times 512 times 3), T2 image (512 times 512 times 3), T1 label (512 times 512 times 1), T2 label (512 times 512 times 1), Sentinel image (128 times 128 times 14).
14 bands of Sentinel images include 12 bands for Sentinel-2 and 2 bands (VV/VH) for Sentinel-1. Now they are concatenated, we will separate them into single .npy file in the future for easier usage.
3. Annotation
FUSU has 17 land use classes according to the Chinese Land Use Classification Criteria (GB/T21010-2017) Level-1 classification system.
FUSU_class = { '0':'background','1':'traffic land','2':'inland water','3':'residential land','4':'cropland','5':'agriculture construction','6':'blank', '7':'industrial land','8':'orchard','9':'park','10':'public management and service','11':'commercial land','12':'public construction', '13':'special','14':'forest','15':'storage','16':'wetland','17':'grass' }
PALETTE = {[255, 255, 255],[233, 133, 133],[8, 514, 230],[255, 0, 30],[126, 211, 33],[135, 126, 20],[94, 47, 4],[10, 82, 77], [184, 233, 134],[219, 170, 230],[255, 199, 2],[252, 232, 5],[245, 107, 0],[243, 229, 176],[3, 100, 0],[127, 123, 127],[52, 205, 249],[18, 227, 180] }
4. Citation
Yuan, S., Lin, G., Zhang, L., Dong, R., Zhang, J., Chen, S., ... & Fu, H. (2024). FUSU: A Multi-temporal-source Land Use Change Segmentation Dataset for Fine-grained Urban Semantic Understanding. arXiv preprint arXiv:2405.19055.
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