Evaluation for stable diffusion model training
You can simply install it with pip
command line from the official PyPI site.
pip install sdeval
If your operating environment includes a available GPU, you can use the following installation command to achieve higher performance:
pip install sdeval[gpu]
For more information about installation, you can refer to Installation.
from sdeval.fidelity import CCIPMetrics
ccip = CCIPMetrics(images='/path/of/character/dataset')
# ccip score of one image
print(ccip.score('/path/of/one/image'))
# ccip score of a directory of images
print(ccip.score('/directory/of/images'))
from sdeval.controllability import BikiniPlusMetrics
# build bikini plus score metrics
bp = BikiniPlusMetrics(
tag_blacklist=[
'bangs', 'long_hair', 'blue_eyes', 'animal_ears', 'sleeveless',
'breasts', 'grey_hair', 'medium_breasts'
]
)
# bp score of one image
# the image should contain a1111 webui's metadata of prompts
print(bp.score('/path/of/one/image'))
# bp score of a directory of images
# the images should contain a1111 webui's metadata of prompts
print(bp.score('/directory/of/images'))
from sdeval.corrupt import AICorruptMetrics
# build metrics
metrics = AICorruptMetrics()
# get ai corrupt score for one image file
print(metrics.score('/path/of/one/image'))
# get ai corrupt score of a directory of image files
print(metrics.score('/directory/of/images'))
# get ai corrupt score of list of images
print(metrics.score(['image1.png', 'image2.png']))