dev(narugo): add hand detection

import os.path

from ultralytics import YOLO

from ..base import _TRAIN_DIR as _GLOBAL_TRAIN_DIR

_TRAIN_DIR = os.path.join(_GLOBAL_TRAIN_DIR, 'hand_detect')

def train(train_cfg: str, session_name: str, level: str = 's',

          max_epochs: int = 200, **kwargs):

    # Load a pretrained YOLO model (recommended for training)

    _last_pt = os.path.join(_TRAIN_DIR, session_name, 'weights', 'last.pt')

    if os.path.exists(_last_pt):

        model, resume = YOLO(_last_pt), True

    else:

        model, resume = YOLO(f'yolov8{level}.pt'), False

    # Train the model using the 'coco128.yaml' dataset for 3 epochs

    model.train(

        data=train_cfg, epochs=max_epochs,

        name=session_name, project=_TRAIN_DIR,

        save=True, plots=True,

        exist_ok=True, resume=resume,

        **kwargs

    )

import os.path

from functools import partial

from typing import List

import click

from huggingface_hub import hf_hub_download

from tqdm.auto import tqdm

from ultralytics import YOLO

from .detection.onnx import export_yolo_to_onnx

from .utils import GLOBAL_CONTEXT_SETTINGS

from .utils import print_version as _origin_print_version

print_version = partial(_origin_print_version, 'zoo.face_detect')

@click.group(context_settings={**GLOBAL_CONTEXT_SETTINGS})

@click.option('-v', '--version', is_flag=True,

              callback=print_version, expose_value=False, is_eager=True,

              help="Show version information.")

def cli():

    pass  # pragma: no cover

_KNOWN_CKPTS: List[str] = [

    'face_detect_best_s.pt',

    'face_detect_best_n.pt',

]

@cli.command('export', help='Export all models as onnx.',

             context_settings={**GLOBAL_CONTEXT_SETTINGS})

@click.option('--output_dir', '-O', 'output_dir', type=click.Path(file_okay=False), required=True,

              help='Output directory of all models.', show_default=True)

def export(output_dir: str):

    for ckpt in tqdm(_KNOWN_CKPTS):

        yolo = YOLO(hf_hub_download('deepghs/imgutils-models', f'face_detect/{ckpt}'))

        filebody, _ = os.path.splitext(ckpt)

        output_file = os.path.join(output_dir, f'{filebody}.onnx')

        export_yolo_to_onnx(yolo, output_file)

if __name__ == '__main__':

    cli()

import os.path

from functools import partial

from typing import List

import click

from huggingface_hub import hf_hub_download

from tqdm.auto import tqdm

from ultralytics import YOLO

from .detection.onnx import export_yolo_to_onnx

from .utils import GLOBAL_CONTEXT_SETTINGS

from .utils import print_version as _origin_print_version

print_version = partial(_origin_print_version, 'zoo.hand_detect')

@click.group(context_settings={**GLOBAL_CONTEXT_SETTINGS})

@click.option('-v', '--version', is_flag=True,

              callback=print_version, expose_value=False, is_eager=True,

              help="Show version information.")

def cli():

    pass  # pragma: no cover

_KNOWN_CKPTS: List[str] = [

    'hand_detect_best_s.pt',

    'hand_detect_best_n.pt',

]

@cli.command('export', help='Export all models as onnx.',

             context_settings={**GLOBAL_CONTEXT_SETTINGS})

@click.option('--output_dir', '-O', 'output_dir', type=click.Path(file_okay=False), required=True,

              help='Output directory of all models.', show_default=True)

def export(output_dir: str):

    for ckpt in tqdm(_KNOWN_CKPTS):

        yolo = YOLO(hf_hub_download('deepghs/imgutils-models', f'hand_detect/{ckpt}'))

        filebody, _ = os.path.splitext(ckpt)

        output_file = os.path.join(output_dir, f'{filebody}.onnx')

        export_yolo_to_onnx(yolo, output_file)

if __name__ == '__main__':

    cli()