dev(narugo): update doc generate svgs for these 2 models

import random

from benchmark import BaseBenchmark, create_plot_cli

from imgutils.detect import detect_hands

from imgutils.detect.hand import detect_hands, _REPO_ID

from imgutils.generic.yolo import _open_models_for_repo_id

_MODELS = _open_models_for_repo_id(_REPO_ID).model_names

class HandDetectBenchmark(BaseBenchmark):

    def __init__(self, version, level):

    def __init__(self, model_name: str):

        BaseBenchmark.__init__(self)

        self.version = version

        self.level = level

        self.model_name = model_name

    def load(self):

        from imgutils.detect.hand import _open_hand_detect_model

        _ = _open_hand_detect_model(version=self.version, level=self.level)

        from imgutils.generic.yolo import _open_models_for_repo_id

        _ = _open_models_for_repo_id(_REPO_ID)._open_model(self.model_name)

    def unload(self):

        from imgutils.detect.hand import _open_hand_detect_model

        _open_hand_detect_model.cache_clear()

        from imgutils.generic.yolo import _open_models_for_repo_id

        _open_models_for_repo_id.cache_clear()

    def run(self):

        image_file = random.choice(self.all_images)

        _ = detect_hands(image_file, version=self.version, level=self.level)

        _ = detect_hands(image_file, model_name=self.model_name)

if __name__ == '__main__':

    create_plot_cli(

        [

            ('hand v0.8 (yolov8s)', HandDetectBenchmark('v0.8', 's')),

            ('hand v1.0 (yolov8s)', HandDetectBenchmark('v1.0', 's')),

            ('hand v1.0 (yolov8n)', HandDetectBenchmark('v1.0', 'n')),

            (model_name, HandDetectBenchmark(model_name))

            for model_name in _MODELS

        ],

        title='Benchmark for Anime Hand Detections',

        run_times=10,

import random

from benchmark import BaseBenchmark, create_plot_cli

from imgutils.detect import detect_person

from imgutils.detect.person import detect_person, _REPO_ID

from imgutils.generic.yolo import _open_models_for_repo_id

_MODELS = _open_models_for_repo_id(_REPO_ID).model_names

class PersonDetectBenchmark(BaseBenchmark):

    def __init__(self, level, version):

    def __init__(self, model_name: str):

        BaseBenchmark.__init__(self)

        self.level = level

        self.version = version

        self.model_name = model_name

    def load(self):

        from imgutils.detect.person import _open_person_detect_model

        _ = _open_person_detect_model(level=self.level, version=self.version)

        from imgutils.generic.yolo import _open_models_for_repo_id

        _ = _open_models_for_repo_id(_REPO_ID)._open_model(self.model_name)

    def unload(self):

        from imgutils.detect.person import _open_person_detect_model

        _open_person_detect_model.cache_clear()

        from imgutils.generic.yolo import _open_models_for_repo_id

        _open_models_for_repo_id.cache_clear()

    def run(self):

        image_file = random.choice(self.all_images)

        _ = detect_person(image_file, level=self.level, version=self.version)

        _ = detect_person(image_file, model_name=self.model_name)

if __name__ == '__main__':

    create_plot_cli(

        [

            ('person v1.1 (yolov8m)', PersonDetectBenchmark('m', 'v1.1')),

            ('person v1.1 (yolov8s)', PersonDetectBenchmark('s', 'v1.1')),

            ('person v1.1 (yolov8n)', PersonDetectBenchmark('n', 'v1.1')),

            ('person v1 (yolov8m)', PersonDetectBenchmark('m', 'v1')),

            ('person v0 (yolov8s)', PersonDetectBenchmark('s', 'v0')),

            ('person v0 (yolov8m)', PersonDetectBenchmark('m', 'v0')),

            ('person v0 (yolov8x)', PersonDetectBenchmark('x', 'v0')),

            (model_name, PersonDetectBenchmark(model_name))

            for model_name in _MODELS

        ],

        title='Benchmark for Anime Person Detections',

        run_times=10,