Datasets:
The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 246, in _split_generators
raise ValueError(
"`file_name`, `*_file_name`, `file_names` or `*_file_names` must be present as dictionary key in metadata files"
)
ValueError: `file_name`, `*_file_name`, `file_names` or `*_file_names` must be present as dictionary key in metadata files
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/split_names.py", line 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
PG 26038 - Coffee Leaf Disease Sample Bank
Expert-scanned coffee (Coffea arabica) leaves with pixel-level lesion masks, a demonstration subset from the PG 26038 thesis project (EARTH University, Costa Rica)
- Roya (coffee leaf rust, Hemileia vastatrix): 20 leaves (40 images, both sides)
- Ojo de gallo (American leaf spot, Mycena citricolor): 20 leaves (40 images), grades G1-G3
- Healthy: 10 negative-control leaves (20 images)
All images are flatbed scans (background removed, transparent PNG, alpha = leaf); diseased leaves include binary lesion masks. Samples are drawn exclusively from the project's validation split: no deployed model was trained on these leaves, and the project's held-out test set remains unpublished pending peer review.
Live demo: pg.carlychery.com
Layout
images/{roya,ojo,healthy}/<leaf_id>__<side>.png RGBA scan cutouts (alpha = leaf)
masks/{roya,ojo}/<leaf_id>__<side>.png binary lesion masks (255 = lesion)
metadata.csv file, category, grade, leaf_id, orig_split, has_mask
Sides of the same leaf_id (__abaxial / __adaxial) are repeated measures, not
independent samples.
Citation
Chery, C. (2026). Automated severity grading of coffee leaf diseases (PG 26038). Licenciatura thesis, EARTH University. Dataset: CC BY 4.0.
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