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View guide →Evaluate text-to-video models with VQAScore-based metrics.
t2v_metrics is an open-source video project by linzhiqiu (linzhiqiu/t2v_metrics on GitHub). It has 603 GitHub stars and 75 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 5 June 2026.
Set up the evaluation code.
Gather generated images, videos, or 3D.
Score prompt alignment across your samples.
Benchmark against other models fairly.
Principled prompt-alignment scoring.
Image, video, and 3D evaluation.
Backed by an academic paper.
Fair numbers instead of cherry-picks.
Built for rigorous evaluation.
Open for the community.
Download the source and move into the project folder.
git clone https://github.com/linzhiqiu/t2v_metrics.git
cd t2v_metricsEvery project documents its own setup; start with install requirements.
cat README.md | head -60Follow the project's launch command — Docker, pip, npm, or a binary release.
# see README for the exact launch commandApache 2.0 licensed — free for research and commercial use.
A published metric for visual-question-answering-based alignment scoring.
Scoring models need compute — check the README.
Yes — point it at any model's outputs.
Human eyeballing does not scale; metrics do.
HandBrake's development repository
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