HPSv2

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HPSv2 is an AI Agents & Automation tool that provides a solid benchmark for evaluating human preferences of text-to-image synthesis. It includes a large-scale dataset and a preference prediction model for comparing generative AI models.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is HPSv2?

HPSv2 is a comprehensive benchmark designed for evaluating human preferences in text-to-image synthesis. It features the Human Preference Dataset v2 (HPD v2), a large-scale dataset comprising 798k preference choices across 430k images, and the Human Preference Score v2 (HPS v2), a preference prediction model trained on HPD v2. This tool allows users to compare images generated with the same prompt and provides a fair, stable, and easy-to-use set of evaluation prompts. It supports benchmarking models across various styles like Animation, Concept-art, Painting, and Photo, and offers functionalities for custom model evaluation and preference model assessment.

Best used for

Ideal for data scientists and developers who need to rigorously evaluate the quality of text-to-image generative models, compare their performance against established benchmarks, and train custom preference predictors. Especially valuable for researchers and practitioners in AI image generation seeking a robust and human-aligned evaluation framework.

Common actions

evaluate AI models

benchmark image generation

compare text-to-image models

predict human preferences

collaborationopen-sourceautomated workflowdeepfakelow-code/no-code"AI Agents"workflowsgithub copilotface swapping

Capabilities

Key features

Human Preference Dataset v2
Human Preference Score v2
Image comparison
Benchmark reproduction
Custom model evaluation
Preference model evaluation

Target Audience

data scientistdeveloper

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What is the difference between HPS v2.0 and HPS v2.1?

HPS v2.1 is an updated model trained on higher quality datasets compared to v2.0. While both predict human preferences, their scores are not directly comparable, and v2.1 generally offers improved performance and accuracy in evaluations.

Can I use HPSv2 to evaluate my own text-to-image generative model?

Yes, HPSv2 provides functionality for custom evaluation. You can generate images using the benchmark prompts provided by HPSv2, save them, and then use the `hpsv2.evaluate()` function to assess your model's performance.

What kind of data is included in the Human Preference Dataset v2 (HPD v2)?

HPD v2 is a large-scale dataset containing 798k human preference choices across 430k images and 107k prompts. It includes images generated by various text-to-image models, with prompts sourced from DiffusionDB and MSCOCO Captions.

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