Merge pull request #104 from deepghs/dev/nudenet

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imgutils.detect.nudenet

==========================

.. currentmodule:: imgutils.detect.nudenet

.. automodule:: imgutils.detect.nudenet

detect_with_nudenet

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.. autofunction:: detect_with_nudenet

import random

from benchmark import BaseBenchmark, create_plot_cli

from imgutils.detect import detect_with_nudenet

class NudenetDetectBenchmark(BaseBenchmark):

    def __init__(self):

        BaseBenchmark.__init__(self)

    def load(self):

        from imgutils.detect.nudenet import _open_nudenet_yolo, _open_nudenet_nms

        _ = _open_nudenet_yolo()

        _ = _open_nudenet_nms()

    def unload(self):

        from imgutils.detect.nudenet import _open_nudenet_yolo, _open_nudenet_nms

        _open_nudenet_yolo.cache_clear()

        _open_nudenet_nms.cache_clear()

    def run(self):

        image_file = random.choice(self.all_images)

        _ = detect_with_nudenet(image_file)

if __name__ == '__main__':

    create_plot_cli(

        [

            ('Nudenet', NudenetDetectBenchmark()),

        ],

        title='Benchmark for Anime NudeNet Detections',

        run_times=10,

        try_times=20,

    )()

from imgutils.detect.nudenet import _LABELS, detect_with_nudenet

from imgutils.detect.visual import detection_visualize

from plot import image_plot

def _detect(img, **kwargs):

    return detection_visualize(img, detect_with_nudenet(img, **kwargs), _LABELS)

if __name__ == '__main__':

    image_plot(

        (_detect('censor/nude_girl.png'), 'simple nude'),

        (_detect('censor/simple_sex.jpg'), 'simple sex'),

        (_detect('censor/complex_pose.jpg'), 'complex pose'),

        (_detect('censor/complex_sex.jpg'), 'complex sex'),

        columns=2,

        figsize=(9, 9),

        autocensor=False,

    )