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/harbor/harbor.py", line 171, in _split_generators
raise DataFilesNotFoundError("No task.toml or instruction.md files found")
datasets.exceptions.DataFilesNotFoundError: No task.toml or instruction.md files found
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.
DPD-Small: Out-of-Distribution Plant Disease Identification
语言 / Language： English | 简体中文
Dataset Summary
DPD-Small is a reduced version of the Deep-Plant-Disease (DPD) dataset used for the COS30082 Applied Machine Learning project. It supports experiments in identifying crop–disease combinations, including combinations absent from the training split. The project explores compositional generalization by predicting crop and disease concepts and combining them into crop–disease pairs.
The dataset contains 11,448 images across three provided splits. These splits are intended for training and evaluating models on seen and unseen crop–disease combinations.
Dataset Structure
DPD_Small_train.csv
DPD_Small_test_seen.csv
DPD_Small_test_unseen.csv
DPD_Small_dataset/
<image files>
| Split | CSV file | Images | Description |
|---|---|---|---|
| Train | DPD_Small_train.csv |
8,000 | Training images from seen crop–disease combinations |
| Seen test | DPD_Small_test_seen.csv |
2,000 | Test images from combinations represented in training |
| Unseen test | DPD_Small_test_unseen.csv |
1,448 | Test images from 10 crop–disease combinations absent from training |
The project brief describes 55 crop categories, 175 disease categories, 323 seen crop–disease combinations, and 10 unseen combinations. Category indices start at zero.
CSV metadata
According to the assignment specification, each CSV contains seven columns in this order:
- Image filename
- Crop category label
- Disease category label
- Crop–disease composition label
- Crop name
- Disease name
- Crop–disease composition name
Note: The exact CSV header names and the relationship between image filenames and paths should be checked against the uploaded files. This card describes the provided specification rather than asserting unverified header names.
Intended Use
- Training crop and disease classifiers on seen combinations.
- Evaluating recognition of previously unseen crop–disease combinations.
- Comparing seen and unseen Top-1/Top-5 accuracy and their harmonic mean.
- Studying robustness to variation in real-world plant images.
The unseen test images should not be used for model training or hyperparameter tuning. The project protocol allows use of unseen combination names as semantic side information.
Download
This repository is intended to be downloaded as a regular Hugging Face dataset repository, preserving the original CSV and image files:
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="print1Username/COS30082-Machine-Learning-Project.dataset",
repo_type="dataset",
local_dir="data",
token=False,
)
Anonymous downloading requires the repository to be public and not gated.
Dataset Limitations
The dataset is designed for research and coursework, not for clinical or agricultural diagnostic decisions without independent validation. Performance on the provided splits does not by itself establish reliable performance across all crops, diseases, environments, or imaging conditions.
Source, Licensing, and Attribution
To be completed by the dataset uploader before public release:
- Original DPD dataset publication, authors, and source URL.
- License or redistribution permission for the images and metadata.
- Any required attribution and usage restrictions.
This card does not assert that the original data may be redistributed publicly. Do not assign a license without verifying the original dataset's terms.
Project Context
Prepared for COS30082 Applied Machine Learning, Out-of-Distribution Plant Disease Identification (2026). The course assignment specification is the source for the split counts and label descriptions in this card.
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