quality-classification
task1283_hrngo_quality_classification
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task1283_hrngo_quality_classification
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks}… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task1283_hrngo_quality_classification.tomato_quality_classification
Tomato Quality Classification
A dataset for quality classification of Tomatoes. The dataset contains raw and augmented versions.The raw dataset contains 1,986 images.Images per class:
Fresh: 1,350
Rotten: 636
The augmented dataset contains 6,000 images.Images per class:
Fresh: 3,000
Rotten: 3,000
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{khatun2023extensive,
title={An extensive real-world… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/tomato_quality_classification.FruitNet_quality_classification
Fruitnet Quality Classification
A dataset for image classification of Fruitnet Quality Classification. The dataset contains 19,526 images across 3 classes: Bad, Good, Mixed.Images per class:
Bad: 6,788
Good: 11,664
Mixed: 1,074
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{meshram2022fruitnet,
title={FruitNet: Indian fruits image dataset with quality for machine learning applications}… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/FruitNet_quality_classification.FruitVision_quality_classification
FruitVision Quality Classification
A dataset for quality classification of apples, bananas, mangoes, grapes, and oranges. The dataset contains raw and augmented versions.The raw dataset contains 10,154 images.Images per class:
Formalin-mixed: 3,176
Fresh: 3,800
Rotten: 3,178
The augmented dataset contains 73,389 images.Images per class:
Formalin-mixed: 22,228
Fresh: 30,400
Rotten: 20,761
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/FruitVision_quality_classification.Luffa_quality_classification
Luffa Quality Classification
This dataset provides real RGB images of luffa plants captured in a field environment in Bangladesh using a handheld smartphone. Collected during October 2023, the images depict natural variations in luffa quality relevant to agricultural disease classification. It serves as a practical resource for developing computer vision models in agricultural quality assessment under real-world field conditions. The dataset contains 343 images across 2 classes:… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/Luffa_quality_classification.german-webtext-quality-classification-dataset
Dataset Card for Dataset Name
Train and (manually annotated) test data of Paper:
Bootstrapping a Sentence-Level Corpus Quality Classifier for Web Text using Active Learning (RANLP25)
Dataset Details
see: https://aclanthology.org/2025.globalnlp-1.12/