Loading imgutils/validate/__init__.py +1 −0 Original line number Diff line number Diff line Loading @@ -8,6 +8,7 @@ from .classify import * from .color import * from .completeness import * from .dbrating import * from .furry import * from .monochrome import * from .nsfw import * from .portrait import * Loading imgutils/validate/furry.py 0 → 100644 +57 −0 Original line number Diff line number Diff line """ Overview: A model for classifying anime furry images into 2 classes (``non_furry``, ``furry``). The following are sample images for testing. .. image:: furry.plot.py.svg :align: center This is an overall benchmark of all the furry classification models: .. image:: furry_benchmark.plot.py.svg :align: center The models are hosted on `huggingface - deepghs/anime_furry <https://huggingface.co/deepghs/anime_furry>`_. """ from typing import Tuple, Dict from ..data import ImageTyping from ..generic import classify_predict, classify_predict_score __all__ = [ 'anime_furry_score', 'anime_furry', ] _DEFAULT_MODEL_NAME = 'mobilenetv3_v0.1_dist' _REPO_ID = 'deepghs/anime_furry' def anime_furry_score(image: ImageTyping, model_name: str = _DEFAULT_MODEL_NAME) -> Dict[str, float]: """ Get the scores for different types in a furry anime image. :param image: The input image. :type image: ImageTyping :param model_name: The model name. Default is 'mobilenetv3_v0.1_dist'. :type model_name: str :return: A dictionary with type scores. :rtype: Dict[str, float] """ return classify_predict_score(image, _REPO_ID, model_name) def anime_furry(image: ImageTyping, model_name: str = _DEFAULT_MODEL_NAME) -> Tuple[str, float]: """ Get the primary furry type and its score. :param image: The input image. :type image: ImageTyping :param model_name: The model name. Default is 'mobilenetv3_v0.1_dist'. :type model_name: str :return: A tuple with the primary type and its score. :rtype: Tuple[str, float] """ return classify_predict(image, _REPO_ID, model_name) Loading
imgutils/validate/__init__.py +1 −0 Original line number Diff line number Diff line Loading @@ -8,6 +8,7 @@ from .classify import * from .color import * from .completeness import * from .dbrating import * from .furry import * from .monochrome import * from .nsfw import * from .portrait import * Loading
imgutils/validate/furry.py 0 → 100644 +57 −0 Original line number Diff line number Diff line """ Overview: A model for classifying anime furry images into 2 classes (``non_furry``, ``furry``). The following are sample images for testing. .. image:: furry.plot.py.svg :align: center This is an overall benchmark of all the furry classification models: .. image:: furry_benchmark.plot.py.svg :align: center The models are hosted on `huggingface - deepghs/anime_furry <https://huggingface.co/deepghs/anime_furry>`_. """ from typing import Tuple, Dict from ..data import ImageTyping from ..generic import classify_predict, classify_predict_score __all__ = [ 'anime_furry_score', 'anime_furry', ] _DEFAULT_MODEL_NAME = 'mobilenetv3_v0.1_dist' _REPO_ID = 'deepghs/anime_furry' def anime_furry_score(image: ImageTyping, model_name: str = _DEFAULT_MODEL_NAME) -> Dict[str, float]: """ Get the scores for different types in a furry anime image. :param image: The input image. :type image: ImageTyping :param model_name: The model name. Default is 'mobilenetv3_v0.1_dist'. :type model_name: str :return: A dictionary with type scores. :rtype: Dict[str, float] """ return classify_predict_score(image, _REPO_ID, model_name) def anime_furry(image: ImageTyping, model_name: str = _DEFAULT_MODEL_NAME) -> Tuple[str, float]: """ Get the primary furry type and its score. :param image: The input image. :type image: ImageTyping :param model_name: The model name. Default is 'mobilenetv3_v0.1_dist'. :type model_name: str :return: A tuple with the primary type and its score. :rtype: Tuple[str, float] """ return classify_predict(image, _REPO_ID, model_name)
