imgutils.validate.real

Overview:

A model for classifying anime real images into 2 classes (anime, real).

The following are sample images for testing.

../../_images/real.plot.py.svg

This is an overall benchmark of all the real classification models:

../../_images/real_benchmark.plot.py.svg

The models are hosted on huggingface - deepghs/anime_real_cls.

anime_real_score

imgutils.validate.real.anime_real_score(image: str | PathLike | bytes | bytearray | BinaryIO | Image, model_name: str = 'mobilenetv3_v1.4_dist') → Dict[str, float][source]

Get the scores for different types in an anime real.

Parameters:

  • image (ImageTyping) – The input image.

  • model_name (str) – The model name. Default is ‘mobilenetv3_v1.2_dist’.

Returns:

A dictionary with type scores.

Return type:

Dict[str, float]

Examples::
>>> from imgutils.validate import anime_real_score
>>>
>>> anime_real_score('real/anime/1.jpg')
{'anime': 0.9999716281890869, 'real': 2.8398366339388303e-05}
>>> anime_real_score('real/anime/2.jpg')
{'anime': 0.9992202520370483, 'real': 0.0007797438884153962}
>>> anime_real_score('real/anime/3.jpg')
{'anime': 0.9999709129333496, 'real': 2.905452492996119e-05}
>>> anime_real_score('real/anime/4.jpg')
{'anime': 0.9999765157699585, 'real': 2.3499671442550607e-05}
>>> anime_real_score('real/anime/5.jpg')
{'anime': 0.9994087219238281, 'real': 0.0005913018831051886}
>>> anime_real_score('real/anime/6.jpg')
{'anime': 0.9999759197235107, 'real': 2.4061362637439743e-05}
>>> anime_real_score('real/anime/7.jpg')
{'anime': 0.9999052286148071, 'real': 9.475799015490338e-05}
>>> anime_real_score('real/anime/8.jpg')
{'anime': 0.9999759197235107, 'real': 2.403173675702419e-05}
>>> anime_real_score('real/real/9.jpg')
{'anime': 1.5848207794988411e-06, 'real': 0.9999984502792358}
>>> anime_real_score('real/real/10.jpg')
{'anime': 0.0010207017185166478, 'real': 0.9989792704582214}
>>> anime_real_score('real/real/11.jpg')
{'anime': 2.2124368115328252e-06, 'real': 0.9999977350234985}
>>> anime_real_score('real/real/12.jpg')
{'anime': 1.6512358342879452e-05, 'real': 0.9999834299087524}
>>> anime_real_score('real/real/13.jpg')
{'anime': 6.359853614412714e-06, 'real': 0.9999936819076538}
>>> anime_real_score('real/real/14.jpg')
{'anime': 1.600314317329321e-05, 'real': 0.9999840259552002}
>>> anime_real_score('real/real/15.jpg')
{'anime': 1.5589323083986528e-05, 'real': 0.9999843835830688}
>>> anime_real_score('real/real/16.jpg')
{'anime': 1.5513256585109048e-05, 'real': 0.9999845027923584}

anime_real

imgutils.validate.real.anime_real(image: str | PathLike | bytes | bytearray | BinaryIO | Image, model_name: str = 'mobilenetv3_v1.4_dist') → Tuple[str, float][source]

Get the primary anime real type and its score.

Parameters:

  • image (ImageTyping) – The input image.

  • model_name (str) – The model name. Default is ‘mobilenetv3_v1.2_dist’.

Returns:

A tuple with the primary type and its score.

Return type:

Tuple[str, float]

Examples::
>>> from imgutils.validate import anime_real
>>>
>>> anime_real('real/anime/1.jpg')
('anime', 0.9999716281890869)
>>> anime_real('real/anime/2.jpg')
('anime', 0.9992202520370483)
>>> anime_real('real/anime/3.jpg')
('anime', 0.9999709129333496)
>>> anime_real('real/anime/4.jpg')
('anime', 0.9999765157699585)
>>> anime_real('real/anime/5.jpg')
('anime', 0.9994087219238281)
>>> anime_real('real/anime/6.jpg')
('anime', 0.9999759197235107)
>>> anime_real('real/anime/7.jpg')
('anime', 0.9999052286148071)
>>> anime_real('real/anime/8.jpg')
('anime', 0.9999759197235107)
>>> anime_real('real/real/9.jpg')
('real', 0.9999984502792358)
>>> anime_real('real/real/10.jpg')
('real', 0.9989792704582214)
>>> anime_real('real/real/11.jpg')
('real', 0.9999977350234985)
>>> anime_real('real/real/12.jpg')
('real', 0.9999834299087524)
>>> anime_real('real/real/13.jpg')
('real', 0.9999936819076538)
>>> anime_real('real/real/14.jpg')
('real', 0.9999840259552002)
>>> anime_real('real/real/15.jpg')
('real', 0.9999843835830688)
>>> anime_real('real/real/16.jpg')
('real', 0.9999845027923584)