datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
text-to-image-promptsIf you have questions about this dataset , feel free to ask them on the fusion-discord : https://discord.gg/8TVHPf6Edn
This collection contains sets from the fusion-t2i-ai-generator on perchance.
This datset is used in this notebook: https://huggingface.co/datasets/codeShare/text-to-image-prompts/tree/main/Google%20Colab%20Notebooks
To see the full sets, please use the url "https://perchance.org/" + url
, where the urls are listed below:
_generator
gen_e621
fusion-t2i-e621-tags-1… See the full description on the dataset page: https://huggingface.co/datasets/codeShare/text-to-image-prompts.text-2-image-Rich-Human-Feedback
Building upon Google's research Rich Human Feedback for Text-to-Image Generation we have collected over 1.5 million responses from 152'684 individual humans using Rapidata via the Python API. Collection took roughly 5 days.
If you get value from this dataset and would like to see more in the future, please consider liking it.
Overview
We asked humans to evaluate AI-generated images in style, coherence and prompt alignment. For images that contained flaws, participants were… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/text-2-image-Rich-Human-Feedback.text-to-image-2M
text-to-image-2M: A High-Quality, Diverse Text-to-Image Training Dataset
Citation
@article{zou2026advancing,
title = {Advancing Aesthetic Image Generation via Composition Transfer},
author = {Zou, Kai and Zhao, Zhiwei and Liu, Bin and Yu, Nenghai},
journal = {International Journal of Computer Vision},
volume = {134},
pages = {252},
year = {2026},
doi = {10.1007/s11263-026-02862-8},
url = {https://doi.org/10.1007/s11263-026-02862-8}… See the full description on the dataset page: https://huggingface.co/datasets/jackyhate/text-to-image-2M.text-2-image-human-preferences-2m
Text-to-image human preferences: 2M votes across 30 models
This dataset contains the complete voting record behind the
Datapoint Image Bench
leaderboard: 2,161,160 validated pairwise votes — exactly 10 for each of
216,116 image pairs. The votes compare 30 text-to-image models in a complete
round-robin on 500 prompts, judged by annotators from over 200 countries.
Every vote includes the annotator's trust score at the time the vote was
cast.
Built on the Datapoint annotation… See the full description on the dataset page: https://huggingface.co/datasets/datapointai/text-2-image-human-preferences-2m.Textual-Image-Caption-Dataset
Update: OCT-2023
Add v2 with recent SoTA model swinV2 classifier for both soft/hard-label visual_caption_cosine_score_v2 with person label (0.2, 0.3 and 0.4)
Introduction
Modern image captaining relies heavily on extracting knowledge, from images such as objects,
to capture the concept of static story in the image. In this paper, we propose a textual visual context dataset
for captioning, where the publicly available dataset COCO caption (Lin et al., 2014) has been… See the full description on the dataset page: https://huggingface.co/datasets/AhmedSSabir/Textual-Image-Caption-Dataset.text-2-image-dpo-human-preferences-full
Text-2-Image DPO Human Preferences (Full)
The complete human preference dataset for text-to-image generation. 416,360 pairwise judgments from ~20,000 annotators comparing AI-generated images across two evaluation dimensions: prompt alignment and overall preference.
This is the full, unfiltered version with uniform vote weights. For quality-filtered subsets with calibrated annotator weighting, see:
datapointai/text-2-image-dpo-human-preferences (5,000 pairs, trust-weighted)… See the full description on the dataset page: https://huggingface.co/datasets/datapointai/text-2-image-dpo-human-preferences-full.text-to-image-2M
text-to-image-2M: A High-Quality, Diverse Text-to-Image Training Dataset
Overview
text-to-image-2M is a curated text-image pair dataset designed for fine-tuning text-to-image models. The dataset consists of approximately 2 million samples, carefully selected and enhanced to meet the high demands of text-to-image model training. The motivation behind creating this dataset stems from the observation that datasets with over 1 million samples tend to produce better… See the full description on the dataset page: https://huggingface.co/datasets/NovaBrown/text-to-image-2M.text-to-image-2M
text-to-image-2M: A High-Quality, Diverse Text-to-Image Training Dataset
Overview
text-to-image-2M is a curated text-image pair dataset designed for fine-tuning text-to-image models. The dataset consists of approximately 2 million samples, carefully selected and enhanced to meet the high demands of text-to-image model training. The motivation behind creating this dataset stems from the observation that datasets with over 1 million samples tend to produce better… See the full description on the dataset page: https://huggingface.co/datasets/rivisia/text-to-image-2M.text-2-image-dpo-human-preferences
Text-2-Image DPO Human Preferences
A large-scale, quality-controlled human preference dataset for text-to-image generation. 80,000 trust-weighted pairwise judgments from calibrated annotators comparing AI-generated images across two evaluation dimensions: prompt alignment and overall preference.
Built on the Datapoint annotation platform — purpose-built infrastructure for collecting high-quality human preference data at scale.
Overview
Metric
Value
Total… See the full description on the dataset page: https://huggingface.co/datasets/datapointai/text-2-image-dpo-human-preferences.socratis_image_text_emotion
SOCRATIS: A benchmark of diverse open-ended emotional reactions to image-caption pairs.
ICCV WECIA Workshop 2023 (oral)
Project Page, Paper
We release a benchmark which contains 18K diverse emotions and reasons for feeling them on 2K image-caption pairs.
Our current preliminary findings have shown that Humans prefer human-written emotional reactions over machine-generated by more than two times.
We also find that current metrics fail to correlate with human preference… See the full description on the dataset page: https://huggingface.co/datasets/array/socratis_image_text_emotion.text-to-image-promptsIf you have questions about this dataset , feel free to ask them on the fusion-discord : https://discord.gg/8TVHPf6Edn
This collection contains sets from the fusion-t2i-ai-generator on perchance.
This datset is used in this notebook: https://huggingface.co/datasets/codeShare/text-to-image-prompts/tree/main/Google%20Colab%20Notebooks
To see the full sets, please use the url "https://perchance.org/" + url
, where the urls are listed below:
_generator
gen_e621
fusion-t2i-e621-tags-1… See the full description on the dataset page: https://huggingface.co/datasets/bofbofai/text-to-image-prompts.text-2-image-dpo-human-preferences-small
Text-2-Image DPO Human Preferences (Small)
A quality-controlled human preference dataset for text-to-image generation. 40,000 trust-weighted pairwise judgments from calibrated annotators comparing AI-generated images across two evaluation dimensions: prompt alignment and overall preference.
This is the highest-annotator-quality subset. For the full 5,000-pair dataset, see datapointai/text-2-image-dpo-human-preferences.
Built on the Datapoint annotation platform — purpose-built… See the full description on the dataset page: https://huggingface.co/datasets/datapointai/text-2-image-dpo-human-preferences-small.text-to-image-2M
text-to-image-2M: A High-Quality, Diverse Text-to-Image Training Dataset
Overview
text-to-image-2M is a curated text-image pair dataset designed for fine-tuning text-to-image models. The dataset consists of approximately 2 million samples, carefully selected and enhanced to meet the high demands of text-to-image model training. The motivation behind creating this dataset stems from the observation that datasets with over 1 million samples tend to produce better… See the full description on the dataset page: https://huggingface.co/datasets/Junaid7188/text-to-image-2M.