Unverified Commit ab56db74 authored by narugo1992's avatar narugo1992 Committed by GitHub
Browse files

Merge pull request #26 from deepghs/dev/monochrome 

dev(narugo): use dist model for monochrome detect
parents 2696218e 466890d5

docs/source/api_doc/validate/monochrome_benchmark.plot.py

+2 −0
Original line number Diff line number Diff line
@@ -30,6 +30,8 @@ if __name__ == '__main__': 
            ('caformer_s36 (safe)', MonochromeBenchmark('caformer_s36', True)),

            ('mobilenetv3 (unsafe)', MonochromeBenchmark('mobilenetv3', False)),

            ('mobilenetv3 (safe)', MonochromeBenchmark('mobilenetv3', True)),

            ('mobilenetv3_dist (unsafe)', MonochromeBenchmark('mobilenetv3_dist', False)),

            ('mobilenetv3_dist (safe)', MonochromeBenchmark('mobilenetv3_dist', True)),

        ],

        title='Benchmark for Monochrome Check Models',

        run_times=10,

docs/source/api_doc/validate/monochrome_benchmark.plot.py.svg

+578 −350

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imgutils/validate/monochrome.py

+6 −4
Original line number Diff line number Diff line
@@ -35,6 +35,8 @@ _MODELS: Mapping[Tuple[str, bool], str] = { 
    ('caformer_s36', True): 'caformer_s36_plus_safe2',

    ('mobilenetv3', False): 'mobilenetv3_large_100',

    ('mobilenetv3', True): 'mobilenetv3_large_100_safe2',

    ('mobilenetv3_dist', False): 'mobilenetv3_large_100_dist',

    ('mobilenetv3_dist', True): 'mobilenetv3_large_100_dist_safe2',

}
@@ -60,13 +62,13 @@ def _2d_encode(image: Image.Image, size: Tuple[int, int] = (384, 384), 
    return data





def get_monochrome_score(image: ImageTyping, model: str = 'mobilenetv3', safe: bool = True) -> float:

def get_monochrome_score(image: ImageTyping, model: str = 'mobilenetv3_dist', safe: bool = True) -> float:

    """

    Overview:

        Get monochrome score of the given image.



    :param image: Image to predict, can be a ``PIL.Image`` object or the path of the image file.

    :param model: The model used for inference. The default value is ``mobilenetv3``,

    :param model: The model used for inference. The default value is ``mobilenetv3_dist``,

        which offers high runtime performance. If you need better accuracy, just use ``caformer_s36``.

    :param safe: Whether to enable the safe mode. When enabled, calculations will be performed using a model

        with higher precision but lower recall. The default value is ``True``.
@@ -112,7 +114,7 @@ def get_monochrome_score(image: ImageTyping, model: str = 'mobilenetv3', safe: b 




def is_monochrome(image: ImageTyping, threshold: float = 0.5,

                  model: str = 'mobilenetv3', safe: bool = True) -> bool:

                  model: str = 'mobilenetv3_dist', safe: bool = True) -> bool:

    """

    Overview:

        Predict if the image is monochrome.
@@ -120,7 +122,7 @@ def is_monochrome(image: ImageTyping, threshold: float = 0.5, 
    :param image: Image to predict, can be a ``PIL.Image`` object or the path of the image file.

    :param threshold: Threshold value during prediction. If the score is higher than the threshold,

        the image will be classified as monochrome.

    :param model: The model used for inference. The default value is ``mobilenetv3``,

    :param model: The model used for inference. The default value is ``mobilenetv3_dist``,

        which offers high runtime performance. If you need better accuracy, just use ``caformer_s36``.

    :param safe: Safe level, with optional values including ``0``, ``2``, and ``4``,

        corresponding to different levels of the model. The default value is 2.

test/validate/test_monochrome.py

+2 −0
Original line number Diff line number Diff line
@@ -41,6 +41,8 @@ class TestValidateMonochrome: 
            ('caformer_s36', True),

            ('mobilenetv3', False),

            ('mobilenetv3', True),

            ('mobilenetv3_dist', False),

            ('mobilenetv3_dist', True),

        ],

    }))

    def test_monochrome_test(self, type_: str, file: str, model: str, safe: bool):