# sdeval
[](https://pypi.org/project/sdeval/)
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[](https://github.com/deepghs/sdeval/actions?query=workflow%3A%22Package+Release%22)
[](https://codecov.io/gh/deepghs/sdeval)
[](https://github.com/deepghs/sdeval/stargazers)
[](https://github.com/deepghs/sdeval/network)
[](https://github.com/deepghs/sdeval/issues)
[](https://github.com/deepghs/sdeval/pulls)
[](https://github.com/deepghs/sdeval/graphs/contributors)
[](https://github.com/deepghs/sdeval/blob/master/LICENSE)
Evaluation for stable diffusion model training
## Installation
You can simply install it with `pip` command line from the official PyPI site.
```shell
pip install sdeval
```
If your operating environment includes a available GPU, you can use the following installation command to achieve higher
performance:
```shell
pip install sdeval[gpu]
```
For more information about installation, you can refer
to [Installation](https://deepghs.github.io/sdeval/main/tutorials/installation/index.html).
## Quick Start
### CCIP Metrics
```python
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'))
```
### Bikini Plus Metrics
```python
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'))
```
### AI Corrupt Metrics
```python
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']))
```
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"description": "# sdeval\n\n[](https://pypi.org/project/sdeval/)\n\n\n\n\n[](https://github.com/deepghs/sdeval/actions?query=workflow%3A%22Code+Test%22)\n[](https://github.com/deepghs/sdeval/actions?query=workflow%3A%22Package+Release%22)\n[](https://codecov.io/gh/deepghs/sdeval)\n\n\n[](https://github.com/deepghs/sdeval/stargazers)\n[](https://github.com/deepghs/sdeval/network)\n\n[](https://github.com/deepghs/sdeval/issues)\n[](https://github.com/deepghs/sdeval/pulls)\n[](https://github.com/deepghs/sdeval/graphs/contributors)\n[](https://github.com/deepghs/sdeval/blob/master/LICENSE)\n\nEvaluation for stable diffusion model training\n\n## Installation\n\nYou can simply install it with `pip` command line from the official PyPI site.\n\n```shell\npip install sdeval\n```\n\nIf your operating environment includes a available GPU, you can use the following installation command to achieve higher\nperformance:\n\n```shell\npip install sdeval[gpu]\n```\n\nFor more information about installation, you can refer\nto [Installation](https://deepghs.github.io/sdeval/main/tutorials/installation/index.html).\n\n## Quick Start\n\n### CCIP Metrics\n\n```python\nfrom sdeval.fidelity import CCIPMetrics\n\nccip = CCIPMetrics(images='/path/of/character/dataset')\n\n# ccip score of one image\nprint(ccip.score('/path/of/one/image'))\n\n# ccip score of a directory of images\nprint(ccip.score('/directory/of/images'))\n\n```\n\n### Bikini Plus Metrics\n\n```python\nfrom sdeval.controllability import BikiniPlusMetrics\n\n# build bikini plus score metrics\nbp = BikiniPlusMetrics(\n tag_blacklist=[\n 'bangs', 'long_hair', 'blue_eyes', 'animal_ears', 'sleeveless',\n 'breasts', 'grey_hair', 'medium_breasts'\n ]\n)\n\n# bp score of one image\n# the image should contain a1111 webui's metadata of prompts\nprint(bp.score('/path/of/one/image'))\n\n# bp score of a directory of images\n# the images should contain a1111 webui's metadata of prompts\nprint(bp.score('/directory/of/images'))\n\n```\n\n### AI Corrupt Metrics\n\n```python\nfrom sdeval.corrupt import AICorruptMetrics\n\n# build metrics\nmetrics = AICorruptMetrics()\n\n# get ai corrupt score for one image file\nprint(metrics.score('/path/of/one/image'))\n\n# get ai corrupt score of a directory of image files\nprint(metrics.score('/directory/of/images'))\n\n# get ai corrupt score of list of images\nprint(metrics.score(['image1.png', 'image2.png']))\n\n```\n",
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