imgutils.validate.aicheck

Overview:

A model for detecting AI-created images.

The following are sample images for testing.

../../_images/aicheck.plot.py.svg

This is an overall benchmark of all the AI-check validation models:

../../_images/aicheck_benchmark.plot.py.svg

The models are hosted on huggingface - deepghs/anime_ai_check.

get_ai_created_score

imgutils.validate.aicheck.get_ai_created_score(image: str | PathLike | bytes | bytearray | BinaryIO | Image, model_name: str = 'mobilenetv3_sce_dist') → float[source]
Overview:

Predict if the given image is created by AI (mainly by stable diffusion), given a score.

Parameters:

  • image – Image to be predicted.

  • model_name – Name of the model. Default is mobilenetv3_sce_dist. If you need better accuracy, use caformer_s36_plus_sce. All the available values are listed on the benchmark graph.

Returns:

A float number which represent the score of AI-check.

Examples::
>>> from imgutils.validate import get_ai_created_score
>>>
>>> get_ai_created_score('aicheck/ai/1.jpg')
0.9996960163116455
>>> get_ai_created_score('aicheck/ai/2.jpg')
0.9999125003814697
>>> get_ai_created_score('aicheck/ai/3.jpg')
0.997803270816803
>>> get_ai_created_score('aicheck/ai/4.jpg')
0.9960069060325623
>>> get_ai_created_score('aicheck/ai/5.jpg')
0.9887709021568298
>>> get_ai_created_score('aicheck/ai/6.jpg')
0.9998629093170166
>>> get_ai_created_score('aicheck/human/7.jpg')
0.0013722758740186691
>>> get_ai_created_score('aicheck/human/8.jpg')
0.00020673229300882667
>>> get_ai_created_score('aicheck/human/9.jpg')
0.0001895089662866667
>>> get_ai_created_score('aicheck/human/10.jpg')
0.0008857478387653828
>>> get_ai_created_score('aicheck/human/11.jpg')
4.552320024231449e-05
>>> get_ai_created_score('aicheck/human/12.jpg')
0.001168627175502479

is_ai_created

imgutils.validate.aicheck.is_ai_created(image: str | PathLike | bytes | bytearray | BinaryIO | Image, model_name: str = 'mobilenetv3_sce_dist', threshold: float = 0.5) → bool[source]
Overview:

Predict if the given image is created by AI (mainly by stable diffusion).

Parameters:

  • image – Image to be predicted.

  • model_name – Name of the model. Default is mobilenetv3_sce_dist. If you need better accuracy, use caformer_s36_plus_sce. All the available values are listed on the benchmark graph.

  • threshold – Threshold of the score. When the score is no less than threshold, this image will be predicted as AI-created. Default is 0.5.

Returns:

This image is AI-created or not.

Examples::
>>> from imgutils.validate import is_ai_created
>>>
>>> is_ai_created('aicheck/ai/1.jpg')
True
>>> is_ai_created('aicheck/ai/2.jpg')
True
>>> is_ai_created('aicheck/ai/3.jpg')
True
>>> is_ai_created('aicheck/ai/4.jpg')
True
>>> is_ai_created('aicheck/ai/5.jpg')
True
>>> is_ai_created('aicheck/ai/6.jpg')
True
>>> is_ai_created('aicheck/human/7.jpg')
False
>>> is_ai_created('aicheck/human/8.jpg')
False
>>> is_ai_created('aicheck/human/9.jpg')
False
>>> is_ai_created('aicheck/human/10.jpg')
False
>>> is_ai_created('aicheck/human/11.jpg')
False
>>> is_ai_created('aicheck/human/12.jpg')
False