datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
synthetic-dataset-1m-dalle3-high-quality-captions
Dataset Card for Dalle3 1 Million+ High Quality Captions
Alt name: Human Preference Synthetic Dataset
Example grids for landscapes, cats, creatures, and fantasy are also available.
Description:
This dataset comprises of AI-generated images sourced from various websites and individuals, primarily focusing on Dalle 3 content, along with contributions from other AI systems of sufficient quality like Stable Diffusion and Midjourney (MJ v5 and above). As users typically… See the full description on the dataset page: https://huggingface.co/datasets/ProGamerGov/synthetic-dataset-1m-dalle3-high-quality-captions.lpbf-melt-pool-quality-dataset
LPBF 熔池监测与成形质量合成数据集
面向激光粉末床熔融（Laser Powder Bed Fusion, LPBF）金属增材制造过程质量控制的教学/算法验证数据集。
数据集将熔池图像、工艺参数与传感器时序三路数据以同一样本编号对齐，可用于成形质量分类、
致密度回归与过程异常检测等任务。
⚠️ 数据性质声明：本数据集为程序合成的模拟数据（synthetic），非真实实验或企业产线数据。
生成脚本为 generate_sample_data.py（配套课程设计项目），随机种子固定为 42，可完全复现。
如需真实工业数据，请使用 NIST AM-Bench 等公开基准数据集。
数据集背景
LPBF 过程以高功率激光逐层熔化金属粉末成形零件，熔池的温度、形貌与稳定性直接决定成形件的致密度与缺陷水平。
实际产线中，熔池图像由同轴高速相机采集，温度与氧含量由过程传感器逐层记录，而激光功率、扫描速度、
层厚与扫描间距是可调的工艺参数。本数据集按上述物理关系构造三路相互关联的数据，用于在没有产线条件… See the full description on the dataset page: https://huggingface.co/datasets/zoumingwu/lpbf-melt-pool-quality-dataset.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.vintage-photography-450k-high-quality-captionsThis is a 450k image datastet focused on photography from the 20th century, and their analog aspect. Many of the images are in high resolution. This dataset currently has 20k images captioned with InternVL2 26B, and is a work in progress (I plan to caption the entire dataset and also have short captions for all of the images, compute is an issue for now).
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.synthetic-dataset-1m-dalle3-high-quality-captions
Dataset Card for Dalle3 1 Million+ High Quality Captions
Alt name: Human Preference Synthetic Dataset
Example grids for landscapes, cats, creatures, and fantasy are also available.
Description:
This dataset comprises of AI-generated images sourced from various websites and individuals, primarily focusing on Dalle 3 content, along with contributions from other AI systems of sufficient quality like Stable Diffusion and Midjourney (MJ v5 and above). As users typically… See the full description on the dataset page: https://huggingface.co/datasets/lingcarzy/synthetic-dataset-1m-dalle3-high-quality-captions.banana_guava_quality_classification
Banana Guava Quality Classification
A dataset for quality classification of bananas and guavas. The dataset contains 1,748 images across 3 classes: Class_A, Class_B, Defect.Images per class:
Class_A: 671
Class_B: 469
Defect: 608
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{kumari2024banana,
title={Banana and Guava dataset for machine learning and deep learning-based quality classification}… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/banana_guava_quality_classification.pomegranate_quality_classification
Pomegranate Quality Classification
A dataset for classification of Pomegranate quality. The dataset contains 1,080 images across 3 classes: G1_Q1, G2_Q1, G3_Q1.Images per class:
G1_Q1: 360
G2_Q1: 360
G3_Q1: 360
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{kumar2021image,
title={Image dataset of pomegranate fruits (Punica granatum) for various machine vision applications},
author={Kumar, Arun… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/pomegranate_quality_classification.dragonfruit_quality_classification
Dragonfruit Quality Classification
A dataset for quality classification of dragonfruit. The dataset contains raw and augmented versions.The raw dataset contains 1,652 images.Images per class:
Defect Dragon Fruit: 754
Fresh Dragon Fruit: 898
The augmented dataset contains 5,000 images.Images per class:
Defect Dragon Fruit: 3,000
Fresh Dragon Fruit: 2,000
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/dragonfruit_quality_classification.VegNet_quality_classification
VegNet Quality Classification
A dataset for quality classification of various crops. The dataset contains 6,150 images across 5 classes: Damaged, Dried, Old, Ripe, Unripe.Images per class:
Damaged: 317
Dried: 1,389
Old: 2,044
Ripe: 1,787
Unripe: 613
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{suryawanshi2022vegnet,
title={VegNet: dataset of vegetable quality images for machine learning… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/VegNet_quality_classification.vintage-photography-450k-high-quality-captionsThis is a 450k image datastet focused on photography from the 20th century, and their analog aspect. Many of the images are in high resolution. This dataset currently has 20k images captioned with InternVL2 26B, and is a work in progress (I plan to caption the entire dataset and also have short captions for all of the images, compute is an issue for now).
coffee_bean_quality_classification
Coffee Bean Quality Classification
A dataset for quality classification of Coffee Beans. The dataset contains 464 images across 9 classes: A, AA, AAA, AB, Bits, Bulk, C, PB-I, PB-II.
Images per class:
A: 50
AA: 61
AAA: 50
AB: 50
Bits: 51
Bulk: 50
C: 51
PB-I: 51
PB-II: 50
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{bj2025cbd,
title={CBD: Coffee Beans Dataset},
author={BJ, Bipin Nair and KM… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/coffee_bean_quality_classification.bangumibase-face-quality-cls
deepghs-cv/bangumibase-face-quality-cls
A 4-class anime face drawing-quality classification dataset (88,000 single-character close-up frames, 818 anime shows), derived from deepghs/bangumibase-webp-4Mpixel_x. Labels are {poor, ok, good, excellent} from face_geo_mean = sqrt(face_w · face_h) after a strict single-face + single-head + face∩head-overlap consistency filter.
⚠ Scope. Every row is a frame from an anime TV-series broadcast. The dataset is intended for training/evaluating… See the full description on the dataset page: https://huggingface.co/datasets/deepghs-cv/bangumibase-face-quality-cls.autotrain-data-coffee-bean-quality
AutoTrain Dataset for project: coffee-bean-quality
Dataset Description
This dataset has been automatically processed by AutoTrain for project coffee-bean-quality.
Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"image": "<224x224 RGB PIL image>",
"feat_width": 224,
"feat_height": 224,
"target": 1,
"feat_xmin": 42… See the full description on the dataset page: https://huggingface.co/datasets/everycoffee/autotrain-data-coffee-bean-quality.Deepfake-Quality-20K
Deepfake-Quality-20K
Deepfake-Quality-20K is a Deepfake Quality Assessment model dataset designed to analyze the quality of deepfake images & videos. It evaluates whether a deepfake is of good or bad quality, where:
0 represents a bad-quality deepfake
1 represents a good-quality deepfake
This classification serves as the foundation for training models on deepfake quality assessment, helping improve deepfake detection and enhancement techniques.
Citation… See the full description on the dataset page: https://huggingface.co/datasets/prithivMLmods/Deepfake-Quality-20K.