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# Ultralytics YOLO 🚀, GPL-3.0 license
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import argparse
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import shutil
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from pathlib import Path
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from ultralytics import __version__, yolo
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from ultralytics.yolo.utils import DEFAULT_CONFIG, LOGGER, PREFIX, checks, print_settings, yaml_load
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DIR = Path(__file__).parent
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CLI_HELP_MSG = \
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"""
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YOLOv8 CLI Usage examples:
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1. Install the ultralytics package:
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pip install ultralytics
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2. Train, Val, Predict and Export using 'yolo' commands of the form:
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yolo TASK MODE ARGS
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Where TASK (optional) is one of [detect, segment, classify]
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MODE (required) is one of [train, val, predict, export]
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ARGS (optional) are any number of custom 'arg=value' pairs like 'imgsz=320' that override defaults.
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For a full list of available ARGS see https://docs.ultralytics.com/config.
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Train a detection model for 10 epochs with an initial learning_rate of 0.01
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yolo detect train data=coco128.yaml model=yolov8n.pt epochs=10 lr0=0.01
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Predict a YouTube video using a pretrained segmentation model at image size 320:
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yolo segment predict model=yolov8n-seg.pt source=https://youtu.be/Zgi9g1ksQHc imgsz=320
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Validate a pretrained detection model at batch-size 1 and image size 640:
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yolo detect val model=yolov8n.pt data=coco128.yaml batch=1 imgsz=640
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Export a YOLOv8n classification model to ONNX format at image size 224 by 128 (no TASK required)
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yolo export model=yolov8n-cls.pt format=onnx imgsz=224,128
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3. Run special commands:
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yolo help
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yolo checks
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yolo version
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yolo settings
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yolo copy-config
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Docs: https://docs.ultralytics.com/cli
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Community: https://community.ultralytics.com
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GitHub: https://github.com/ultralytics/ultralytics
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"""
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def cli(cfg):
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"""
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Run a specified task and mode with the given configuration.
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Args:
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cfg (DictConfig): Configuration for the task and mode.
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"""
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# LOGGER.info(f"{colorstr(f'Ultralytics YOLO v{ultralytics.__version__}')}")
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from ultralytics.yolo.configs import get_config
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if cfg.cfg:
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LOGGER.info(f"{PREFIX}Overriding default config with {cfg.cfg}")
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cfg = get_config(cfg.cfg)
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task, mode = cfg.task.lower(), cfg.mode.lower()
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# Mapping from task to module
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tasks = {"detect": yolo.v8.detect, "segment": yolo.v8.segment, "classify": yolo.v8.classify}
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module = tasks.get(task)
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if not module:
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raise SyntaxError(f"yolo task={task} is invalid. Valid tasks are: {', '.join(tasks.keys())}\n{CLI_HELP_MSG}")
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# Mapping from mode to function
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modes = {"train": module.train, "val": module.val, "predict": module.predict, "export": yolo.engine.exporter.export}
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func = modes.get(mode)
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if not func:
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raise SyntaxError(f"yolo mode={mode} is invalid. Valid modes are: {', '.join(modes.keys())}\n{CLI_HELP_MSG}")
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func(cfg)
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def entrypoint():
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"""
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This function is the ultralytics package entrypoint, it's responsible for parsing the command line arguments passed
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to the package. It's a combination of argparse and hydra.
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This function allows for:
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- passing mandatory YOLO args as a list of strings
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- specifying the task to be performed, either 'detect', 'segment' or 'classify'
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- specifying the mode, either 'train', 'val', 'test', or 'predict'
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- running special modes like 'checks'
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- passing overrides to the package's configuration
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It uses the package's default config and initializes it using the passed overrides.
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Then it calls the CLI function with the composed config
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"""
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parser = argparse.ArgumentParser(description='YOLO parser')
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parser.add_argument('args', type=str, nargs='+', help='YOLO args')
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args = parser.parse_args().args
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tasks = 'detect', 'segment', 'classify'
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modes = 'train', 'val', 'predict', 'export'
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special_modes = {
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'help': lambda: LOGGER.info(CLI_HELP_MSG),
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'checks': checks.check_yolo,
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'version': lambda: LOGGER.info(__version__),
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'settings': print_settings,
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'copy-config': copy_default_config}
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overrides = [] # basic overrides, i.e. imgsz=320
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defaults = yaml_load(DEFAULT_CONFIG)
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for a in args:
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if '=' in a:
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overrides.append(a)
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elif a in tasks:
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overrides.append(f'task={a}')
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elif a in modes:
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overrides.append(f'mode={a}')
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elif a in special_modes:
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special_modes[a]()
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return
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elif a in defaults and defaults[a] is False:
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overrides.append(f'{a}=True') # auto-True for default False args, i.e. yolo show
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elif a in defaults:
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raise SyntaxError(f"'{a}' is a valid YOLO argument but is missing an '=' sign to set its value, "
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f"i.e. try '{a}={defaults[a]}'"
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f"\n{CLI_HELP_MSG}")
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else:
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raise SyntaxError(
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f"'{a}' is not a valid YOLO argument. For a full list of valid arguments see "
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f"https://github.com/ultralytics/ultralytics/blob/main/ultralytics/yolo/configs/default.yaml"
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f"\n{CLI_HELP_MSG}")
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from hydra import compose, initialize
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with initialize(version_base=None, config_path=str(DEFAULT_CONFIG.parent.relative_to(DIR)), job_name="YOLO"):
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cfg = compose(config_name=DEFAULT_CONFIG.name, overrides=overrides)
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cli(cfg)
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# Special modes --------------------------------------------------------------------------------------------------------
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def copy_default_config():
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new_file = Path.cwd() / DEFAULT_CONFIG.name.replace('.yaml', '_copy.yaml')
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shutil.copy2(DEFAULT_CONFIG, new_file)
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LOGGER.info(f"{PREFIX}{DEFAULT_CONFIG} copied to {new_file}\n"
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f"Usage for running YOLO with this new custom config:\nyolo cfg={new_file} args...")
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