text2image
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.
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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-2-image-Rich-Human-Feedback-32k
Building upon Google's research Rich Human Feedback for Text-to-Image Generation, and the
smaller, previous version of this dataset, we have collected over 3.7 million responses from 307'415 individual humans for the open-image-preference-v1 dataset using Rapidata via the Python API. Collection took less than 2 weeks.
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… See the full description on the dataset page: https://huggingface.co/datasets/Rapidata/text-2-image-Rich-Human-Feedback-32k.text2image-multi-prompt
text2image multi-prompt(s): a dataset collection
collection of several text2image prompt datasets
data was cleaned/normalized with the goal of removing "model specific APIs" like the "--ar" for Midjourney and so on
data de-duplicated on a basic level: exactly duplicate prompts were dropped (after cleaning and normalization)
updates
Oct 2023: the default config has been updated with better deduplication. It was deduplicated with minhash (params: n-gram size set to 3… See the full description on the dataset page: https://huggingface.co/datasets/pszemraj/text2image-multi-prompt.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.Sampled_AIGCBench_text2image_ar_0.625
Description
This dataset is intended for the implementation of image-to-video generation evaluations in the paper of AdaptiveDiffusion, which is composed of the original text-image pairs collected from AIGCBench v1.0 and a text file listing the randomly selected samples.
Data Organization
The dataset is organized into the following files:
AIGCBench_t2i_aspect_ratio_625.zip: 2002 images named by the index and the text description, adjusted to an aspect ratio of 0.625.… See the full description on the dataset page: https://huggingface.co/datasets/HankYe/Sampled_AIGCBench_text2image_ar_0.625.atomic2023-small_text2image