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