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A pipeline to generate user-preferred photo-realistic avatars using stable-diffusion and bayesian-optimization.

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lukassteinwender/avatair

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AvatAIr



Installation:

pip install -r requirements.txt

Script:

python avatair.py

Config:

Name Description Default
initial Number of iterations that will run until the program is finished 5
scales 3 types of scales for other use-cases
1 = acceptance, likeability, empathy, anthropomorphism, trust
2 = openness, conscientiousness, extraversion, agreeableness, neuroticism
3 = efficiency
1
pictures The amount of pictures should be generated during one iteration (Int) 1
attention Possibility to add several attention-checks after x iterations (Array (e.g [1,2,3]), [-1] for no check)
[1,3]
stablediffusion Choose between Stable Diffusion ("sd") and Stable Diffusion XL ("xl") "xl"
model Use different types of SD-models "SG161222/RealVisXL_V3.0"
token HuggingFace login-token, just needed for some specific SD-models ""
promptmodel Generate prompt with defined or latent variables
("defined" or "latent")
defined = e.g. abstraction, haircolor, eyecolor, ...
latent= e.g. acceptance, likeability, ...
defined

Requirements:
requirements.txt

The pipeline works as following:



Paper:
Download the paper here.

License:
CC BY-NC-SA 4.0

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

CC BY-NC-SA 4.0

For non-commercial use only!

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A pipeline to generate user-preferred photo-realistic avatars using stable-diffusion and bayesian-optimization.

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