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# Reference for `ultralytics/cfg/__init__.py`

Note

This file is available at https://github.com/ultralytics/ultralytics/blob/main/ultralytics/cfg/__init__.py. If you spot a problem please help fix it by contributing a Pull Request 🛠️. Thank you 🙏!

## `` ultralytics.cfg.cfg2dict

    cfg2dict(cfg: str | Path | dict | SimpleNamespace) -> dict

Convert a configuration object to a dictionary.

Parameters:

Name | Type | Description | Default
--- | --- | --- | ---
`cfg` | `str | Path | dict | SimpleNamespace` | Configuration object to be converted. Can be a file path, a string, a dictionary, or a SimpleNamespace object. | required

Returns:

Type | Description
--- | ---
`dict` | Configuration object in dictionary format.

Examples:

Convert a YAML file path to a dictionary:

    >>> config_dict = cfg2dict("config.yaml")

Convert a SimpleNamespace to a dictionary:

    >>> from types import SimpleNamespace
    >>> config_sn = SimpleNamespace(param1="value1", param2="value2")
    >>> config_dict = cfg2dict(config_sn)

Pass through an already existing dictionary:

    >>> config_dict = cfg2dict({"param1": "value1", "param2": "value2"})

Notes

- If cfg is a path or string, it's loaded as YAML and converted to a dictionary.
- If cfg is a SimpleNamespace object, it's converted to a dictionary using vars().
- If cfg is already a dictionary, it's returned unchanged.

Source code in `ultralytics/cfg/__init__.py`

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    def cfg2dict(cfg: str | Path | dict | SimpleNamespace) -> dict:
        """
        Convert a configuration object to a dictionary.

        Args:
            cfg (str | Path | dict | SimpleNamespace): Configuration object to be converted. Can be a file path,
                a string, a dictionary, or a SimpleNamespace object.

        Returns:
            (dict): Configuration object in dictionary format.

        Examples:
            Convert a YAML file path to a dictionary:
            >>> config_dict = cfg2dict("config.yaml")

            Convert a SimpleNamespace to a dictionary:
            >>> from types import SimpleNamespace
            >>> config_sn = SimpleNamespace(param1="value1", param2="value2")
            >>> config_dict = cfg2dict(config_sn)

            Pass through an already existing dictionary:
            >>> config_dict = cfg2dict({"param1": "value1", "param2": "value2"})

        Notes:
            - If cfg is a path or string, it's loaded as YAML and converted to a dictionary.
            - If cfg is a SimpleNamespace object, it's converted to a dictionary using vars().
            - If cfg is already a dictionary, it's returned unchanged.
        """
        if isinstance(cfg, STR_OR_PATH):
            cfg = YAML.load(cfg)  # load dict
        elif isinstance(cfg, SimpleNamespace):
            cfg = vars(cfg)  # convert to dict
        return cfg

## `` ultralytics.cfg.get_cfg

    get_cfg(
        cfg: str | Path | dict | SimpleNamespace = DEFAULT_CFG_DICT,
        overrides: dict = None,
    ) -> SimpleNamespace

Load and merge configuration data from a file or dictionary, with optional overrides.

Parameters:

Name | Type | Description | Default
--- | --- | --- | ---
`cfg` | `str | Path | dict | SimpleNamespace` | Configuration data source. Can be a file path, dictionary, or SimpleNamespace object. | `DEFAULT_CFG_DICT`
`overrides` | `dict | None` | Dictionary containing key-value pairs to override the base configuration. | `None`

Returns:

Type | Description
--- | ---
`SimpleNamespace` | Namespace containing the merged configuration arguments.

Examples:

    >>> from ultralytics.cfg import get_cfg
    >>> config = get_cfg()  # Load default configuration
    >>> config_with_overrides = get_cfg("path/to/config.yaml", overrides={"epochs": 50, "batch_size": 16})

Notes

- If both `cfg` and `overrides` are provided, the values in `overrides` will take precedence.
- Special handling ensures alignment and correctness of the configuration, such as converting numeric `project` and `name` to strings and validating configuration keys and values.
- The function performs type and value checks on the configuration data.

Source code in `ultralytics/cfg/__init__.py`

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    def get_cfg(cfg: str | Path | dict | SimpleNamespace = DEFAULT_CFG_DICT, overrides: dict = None) -> SimpleNamespace:
        """
        Load and merge configuration data from a file or dictionary, with optional overrides.

        Args:
            cfg (str | Path | dict | SimpleNamespace): Configuration data source. Can be a file path, dictionary, or
                SimpleNamespace object.
            overrides (dict | None): Dictionary containing key-value pairs to override the base configuration.

        Returns:
            (SimpleNamespace): Namespace containing the merged configuration arguments.

        Examples:
            >>> from ultralytics.cfg import get_cfg
            >>> config = get_cfg()  # Load default configuration
            >>> config_with_overrides = get_cfg("path/to/config.yaml", overrides={"epochs": 50, "batch_size": 16})

        Notes:
            - If both `cfg` and `overrides` are provided, the values in `overrides` will take precedence.
            - Special handling ensures alignment and correctness of the configuration, such as converting numeric
              `project` and `name` to strings and validating configuration keys and values.
            - The function performs type and value checks on the configuration data.
        """
        cfg = cfg2dict(cfg)

        # Merge overrides
        if overrides:
            overrides = cfg2dict(overrides)
            if "save_dir" not in cfg:
                overrides.pop("save_dir", None)  # special override keys to ignore
            check_dict_alignment(cfg, overrides)
            cfg = {**cfg, **overrides}  # merge cfg and overrides dicts (prefer overrides)

        # Special handling for numeric project/name
        for k in "project", "name":
            if k in cfg and isinstance(cfg[k], FLOAT_OR_INT):
                cfg[k] = str(cfg[k])
        if cfg.get("name") == "model":  # assign model to 'name' arg
            cfg["name"] = str(cfg.get("model", "")).partition(".")[0]
            LOGGER.warning(f"'name=model' automatically updated to 'name={cfg['name']}'.")

        # Type and Value checks
        check_cfg(cfg)

        # Return instance
        return IterableSimpleNamespace(**cfg)

## `` ultralytics.cfg.check_cfg

    check_cfg(cfg: dict, hard: bool = True) -> None

Check configuration argument types and values for the Ultralytics library.

This function validates the types and values of configuration arguments, ensuring correctness and converting them if necessary. It checks for specific key types defined in global variables such as `CFG_FLOAT_KEYS`, `CFG_FRACTION_KEYS`, `CFG_INT_KEYS`, and `CFG_BOOL_KEYS`.

Parameters:

Name | Type | Description | Default
--- | --- | --- | ---
`cfg` | `dict` | Configuration dictionary to validate. | required
`hard` | `bool` | If True, raises exceptions for invalid types and values; if False, attempts to convert them. | `True`

Examples:

    >>> config = {
    ...     "epochs": 50,  # valid integer
    ...     "lr0": 0.01,  # valid float
    ...     "momentum": 1.2,  # invalid float (out of 0.0-1.0 range)
    ...     "save": "true",  # invalid bool
    ... }
    >>> check_cfg(config, hard=False)
    >>> print(config)
    {'epochs': 50, 'lr0': 0.01, 'momentum': 1.2, 'save': False}  # corrected 'save' key

Notes

- The function modifies the input dictionary in-place.
- None values are ignored as they may be from optional arguments.
- Fraction keys are checked to be within the range [0.0, 1.0].

Source code in `ultralytics/cfg/__init__.py`

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    def check_cfg(cfg: dict, hard: bool = True) -> None:
        """
        Check configuration argument types and values for the Ultralytics library.

        This function validates the types and values of configuration arguments, ensuring correctness and converting
        them if necessary. It checks for specific key types defined in global variables such as `CFG_FLOAT_KEYS`,
        `CFG_FRACTION_KEYS`, `CFG_INT_KEYS`, and `CFG_BOOL_KEYS`.

        Args:
            cfg (dict): Configuration dictionary to validate.
            hard (bool): If True, raises exceptions for invalid types and values; if False, attempts to convert them.

        Examples:
            >>> config = {
            ...     "epochs": 50,  # valid integer
            ...     "lr0": 0.01,  # valid float
            ...     "momentum": 1.2,  # invalid float (out of 0.0-1.0 range)
            ...     "save": "true",  # invalid bool
            ... }
            >>> check_cfg(config, hard=False)
            >>> print(config)
            {'epochs': 50, 'lr0': 0.01, 'momentum': 1.2, 'save': False}  # corrected 'save' key

        Notes:
            - The function modifies the input dictionary in-place.
            - None values are ignored as they may be from optional arguments.
            - Fraction keys are checked to be within the range [0.0, 1.0].
        """
        for k, v in cfg.items():
            if v is not None:  # None values may be from optional args
                if k in CFG_FLOAT_KEYS and not isinstance(v, FLOAT_OR_INT):
                    if hard:
                        raise TypeError(
                            f"'{k}={v}' is of invalid type {type(v).__name__}. "
                            f"Valid '{k}' types are int (i.e. '{k}=0') or float (i.e. '{k}=0.5')"
                        )
                    cfg[k] = float(v)
                elif k in CFG_FRACTION_KEYS:
                    if not isinstance(v, FLOAT_OR_INT):
                        if hard:
                            raise TypeError(
                                f"'{k}={v}' is of invalid type {type(v).__name__}. "
                                f"Valid '{k}' types are int (i.e. '{k}=0') or float (i.e. '{k}=0.5')"
                            )
                        cfg[k] = v = float(v)
                    if not (0.0 <= v <= 1.0):
                        raise ValueError(f"'{k}={v}' is an invalid value. Valid '{k}' values are between 0.0 and 1.0.")
                elif k in CFG_INT_KEYS and not isinstance(v, int):
                    if hard:
                        raise TypeError(
                            f"'{k}={v}' is of invalid type {type(v).__name__}. '{k}' must be an int (i.e. '{k}=8')"
                        )
                    cfg[k] = int(v)
                elif k in CFG_BOOL_KEYS and not isinstance(v, bool):
                    if hard:
                        raise TypeError(
                            f"'{k}={v}' is of invalid type {type(v).__name__}. "
                            f"'{k}' must be a bool (i.e. '{k}=True' or '{k}=False')"
                        )
                    cfg[k] = bool(v)

## `` ultralytics.cfg.get_save_dir

    get_save_dir(args: SimpleNamespace, name: str = None) -> Path

Return the directory path for saving outputs, derived from arguments or default settings.

Parameters:

Name | Type | Description | Default
--- | --- | --- | ---
`args` | `SimpleNamespace` | Namespace object containing configurations such as 'project', 'name', 'task', 'mode', and 'save_dir'. | required
`name` | `str | None` | Optional name for the output directory. If not provided, it defaults to 'args.name' or the 'args.mode'. | `None`

Returns:

Type | Description
--- | ---
`Path` | Directory path where outputs should be saved.

Examples:

    >>> from types import SimpleNamespace
    >>> args = SimpleNamespace(project="my_project", task="detect", mode="train", exist_ok=True)
    >>> save_dir = get_save_dir(args)
    >>> print(save_dir)
    my_project/detect/train

Source code in `ultralytics/cfg/__init__.py`

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    def get_save_dir(args: SimpleNamespace, name: str = None) -> Path:
        """
        Return the directory path for saving outputs, derived from arguments or default settings.

        Args:
            args (SimpleNamespace): Namespace object containing configurations such as 'project', 'name', 'task',
                'mode', and 'save_dir'.
            name (str | None): Optional name for the output directory. If not provided, it defaults to 'args.name'
                or the 'args.mode'.

        Returns:
            (Path): Directory path where outputs should be saved.

        Examples:
            >>> from types import SimpleNamespace
            >>> args = SimpleNamespace(project="my_project", task="detect", mode="train", exist_ok=True)
            >>> save_dir = get_save_dir(args)
            >>> print(save_dir)
            my_project/detect/train
        """
        if getattr(args, "save_dir", None):
            save_dir = args.save_dir
        else:
            from ultralytics.utils.files import increment_path

            project = args.project or (ROOT.parent / "tests/tmp/runs" if TESTS_RUNNING else RUNS_DIR) / args.task
            name = name or args.name or f"{args.mode}"
            save_dir = increment_path(Path(project) / name, exist_ok=args.exist_ok if RANK in {-1, 0} else True)

        return Path(save_dir).resolve()  # resolve to display full path in console

## `` ultralytics.cfg._handle_deprecation

    _handle_deprecation(custom: dict) -> dict

Handle deprecated configuration keys by mapping them to current equivalents with deprecation warnings.

Parameters:

Name | Type | Description | Default
--- | --- | --- | ---
`custom` | `dict` | Configuration dictionary potentially containing deprecated keys. | required

Returns:

Type | Description
--- | ---
`dict` | Updated configuration dictionary with deprecated keys replaced.

Examples:

    >>> custom_config = {"boxes": True, "hide_labels": "False", "line_thickness": 2}
    >>> _handle_deprecation(custom_config)
    >>> print(custom_config)
    {'show_boxes': True, 'show_labels': True, 'line_width': 2}

Notes

This function modifies the input dictionary in-place, replacing deprecated keys with their current equivalents. It also handles value conversions where necessary, such as inverting boolean values for 'hide_labels' and 'hide_conf'.

Source code in `ultralytics/cfg/__init__.py`

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    def _handle_deprecation(custom: dict) -> dict:
        """
        Handle deprecated configuration keys by mapping them to current equivalents with deprecation warnings.

        Args:
            custom (dict): Configuration dictionary potentially containing deprecated keys.

        Returns:
            (dict): Updated configuration dictionary with deprecated keys replaced.

        Examples:
            >>> custom_config = {"boxes": True, "hide_labels": "False", "line_thickness": 2}
            >>> _handle_deprecation(custom_config)
            >>> print(custom_config)
            {'show_boxes': True, 'show_labels': True, 'line_width': 2}

        Notes:
            This function modifies the input dictionary in-place, replacing deprecated keys with their current
            equivalents. It also handles value conversions where necessary, such as inverting boolean values for
            'hide_labels' and 'hide_conf'.
        """
        deprecated_mappings = {
            "boxes": ("show_boxes", lambda v: v),
            "hide_labels": ("show_labels", lambda v: not bool(v)),
            "hide_conf": ("show_conf", lambda v: not bool(v)),
            "line_thickness": ("line_width", lambda v: v),
        }
        removed_keys = {"label_smoothing", "save_hybrid", "crop_fraction"}

        for old_key, (new_key, transform) in deprecated_mappings.items():
            if old_key not in custom:
                continue
            deprecation_warn(old_key, new_key)
            custom[new_key] = transform(custom.pop(old_key))

        for key in removed_keys:
            if key not in custom:
                continue
            deprecation_warn(key)
            custom.pop(key)

        return custom

## `` ultralytics.cfg.check_dict_alignment

    check_dict_alignment(base: dict, custom: dict, e: Exception = None) -> None

Check alignment between custom and base configuration dictionaries, handling deprecated keys and providing error messages for mismatched keys.

Parameters:

Name | Type | Description | Default
--- | --- | --- | ---
`base` | `dict` | The base configuration dictionary containing valid keys. | required
`custom` | `dict` | The custom configuration dictionary to be checked for alignment. | required
`e` | `Exception | None` | Optional error instance passed by the calling function. | `None`

Raises:

Type | Description
--- | ---
`SystemExit` | If mismatched keys are found between the custom and base dictionaries.

Examples:

    >>> base_cfg = {"epochs": 50, "lr0": 0.01, "batch_size": 16}
    >>> custom_cfg = {"epoch": 100, "lr": 0.02, "batch_size": 32}
    >>> try:
    ...     check_dict_alignment(base_cfg, custom_cfg)
    ... except SystemExit:
    ...     print("Mismatched keys found")

Notes

- Suggests corrections for mismatched keys based on similarity to valid keys.
- Automatically replaces deprecated keys in the custom configuration with updated equivalents.
- Prints detailed error messages for each mismatched key to help users correct their configurations.

Source code in `ultralytics/cfg/__init__.py`

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    def check_dict_alignment(base: dict, custom: dict, e: Exception = None) -> None:
        """
        Check alignment between custom and base configuration dictionaries, handling deprecated keys and providing error
        messages for mismatched keys.

        Args:
            base (dict): The base configuration dictionary containing valid keys.
            custom (dict): The custom configuration dictionary to be checked for alignment.
            e (Exception | None): Optional error instance passed by the calling function.

        Raises:
            SystemExit: If mismatched keys are found between the custom and base dictionaries.

        Examples:
            >>> base_cfg = {"epochs": 50, "lr0": 0.01, "batch_size": 16}
            >>> custom_cfg = {"epoch": 100, "lr": 0.02, "batch_size": 32}
            >>> try:
            ...     check_dict_alignment(base_cfg, custom_cfg)
            ... except SystemExit:
            ...     print("Mismatched keys found")

        Notes:
            - Suggests corrections for mismatched keys based on similarity to valid keys.
            - Automatically replaces deprecated keys in the custom configuration with updated equivalents.
            - Prints detailed error messages for each mismatched key to help users correct their configurations.
        """
        custom = _handle_deprecation(custom)
        base_keys, custom_keys = (frozenset(x.keys()) for x in (base, custom))
        if mismatched := [k for k in custom_keys if k not in base_keys]:
            from difflib import get_close_matches

            string = ""
            for x in mismatched:
                matches = get_close_matches(x, base_keys)  # key list
                matches = [f"{k}={base[k]}" if base.get(k) is not None else k for k in matches]
                match_str = f"Similar arguments are i.e. {matches}." if matches else ""
                string += f"'{colorstr('red', 'bold', x)}' is not a valid YOLO argument. {match_str}\n"
            raise SyntaxError(string + CLI_HELP_MSG) from e

## `` ultralytics.cfg.merge_equals_args

    merge_equals_args(args: list[str]) -> list[str]

Merge arguments around isolated '=' in a list of strings and join fragments with brackets.

This function handles the following cases

1. ['arg', '=', 'val'] becomes ['arg=val']
2. ['arg=', 'val'] becomes ['arg=val']
3. ['arg', '=val'] becomes ['arg=val']
4. Joins fragments with brackets, e.g., ['imgsz=[3,', '640,', '640]'] becomes ['imgsz=[3,640,640]']

Parameters:

Name | Type | Description | Default
--- | --- | --- | ---
`args` | `list[str]` | A list of strings where each element represents an argument or fragment. | required

Returns:

Type | Description
--- | ---
`list[str]` | A list of strings where the arguments around isolated '=' are merged and fragments with brackets are joined.

Examples:

    >>> args = ["arg1", "=", "value", "arg2=", "value2", "arg3", "=value3", "imgsz=[3,", "640,", "640]"]
    >>> merge_equals_args(args)
    ['arg1=value', 'arg2=value2', 'arg3=value3', 'imgsz=[3,640,640]']

Source code in `ultralytics/cfg/__init__.py`

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    def merge_equals_args(args: list[str]) -> list[str]:
        """
        Merge arguments around isolated '=' in a list of strings and join fragments with brackets.

        This function handles the following cases:
            1. ['arg', '=', 'val'] becomes ['arg=val']
            2. ['arg=', 'val'] becomes ['arg=val']
            3. ['arg', '=val'] becomes ['arg=val']
            4. Joins fragments with brackets, e.g., ['imgsz=[3,', '640,', '640]'] becomes ['imgsz=[3,640,640]']

        Args:
            args (list[str]): A list of strings where each element represents an argument or fragment.

        Returns:
            (list[str]): A list of strings where the arguments around isolated '=' are merged and fragments with brackets are joined.

        Examples:
            >>> args = ["arg1", "=", "value", "arg2=", "value2", "arg3", "=value3", "imgsz=[3,", "640,", "640]"]
            >>> merge_equals_args(args)
            ['arg1=value', 'arg2=value2', 'arg3=value3', 'imgsz=[3,640,640]']
        """
        new_args = []
        current = ""
        depth = 0

        i = 0
        while i < len(args):
            arg = args[i]

            # Handle equals sign merging
            if arg == "=" and 0 < i < len(args) - 1:  # merge ['arg', '=', 'val']
                new_args[-1] += f"={args[i + 1]}"
                i += 2
                continue
            elif arg.endswith("=") and i < len(args) - 1 and "=" not in args[i + 1]:  # merge ['arg=', 'val']
                new_args.append(f"{arg}{args[i + 1]}")
                i += 2
                continue
            elif arg.startswith("=") and i > 0:  # merge ['arg', '=val']
                new_args[-1] += arg
                i += 1
                continue

            # Handle bracket joining
            depth += arg.count("[") - arg.count("]")
            current += arg
            if depth == 0:
                new_args.append(current)
                current = ""

            i += 1

        # Append any remaining current string
        if current:
            new_args.append(current)

        return new_args

## `` ultralytics.cfg.handle_yolo_hub

    handle_yolo_hub(args: list[str]) -> None

Handle Ultralytics HUB command-line interface (CLI) commands for authentication.

This function processes Ultralytics HUB CLI commands such as login and logout. It should be called when executing a script with arguments related to HUB authentication.

Parameters:

Name | Type | Description | Default
--- | --- | --- | ---
`args` | `list[str]` | A list of command line arguments. The first argument should be either 'login' or 'logout'. For 'login', an optional second argument can be the API key. | required

Examples:

$ yolo login YOUR_API_KEY

Notes

- The function imports the 'hub' module from ultralytics to perform login and logout operations.
- For the 'login' command, if no API key is provided, an empty string is passed to the login function.
- The 'logout' command does not require any additional arguments.

Source code in `ultralytics/cfg/__init__.py`

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    def handle_yolo_hub(args: list[str]) -> None:
        """
        Handle Ultralytics HUB command-line interface (CLI) commands for authentication.

        This function processes Ultralytics HUB CLI commands such as login and logout. It should be called when executing a
        script with arguments related to HUB authentication.

        Args:
            args (list[str]): A list of command line arguments. The first argument should be either 'login'
                or 'logout'. For 'login', an optional second argument can be the API key.

        Examples:
            $ yolo login YOUR_API_KEY

        Notes:
            - The function imports the 'hub' module from ultralytics to perform login and logout operations.
            - For the 'login' command, if no API key is provided, an empty string is passed to the login function.
            - The 'logout' command does not require any additional arguments.
        """
        from ultralytics import hub

        if args[0] == "login":
            key = args[1] if len(args) > 1 else ""
            # Log in to Ultralytics HUB using the provided API key
            hub.login(key)
        elif args[0] == "logout":
            # Log out from Ultralytics HUB
            hub.logout()

## `` ultralytics.cfg.handle_yolo_settings

    handle_yolo_settings(args: list[str]) -> None

Handle YOLO settings command-line interface (CLI) commands.

This function processes YOLO settings CLI commands such as reset and updating individual settings. It should be called when executing a script with arguments related to YOLO settings management.

Parameters:

Name | Type | Description | Default
--- | --- | --- | ---
`args` | `list[str]` | A list of command line arguments for YOLO settings management. | required

Examples:

    >>> handle_yolo_settings(["reset"])  # Reset YOLO settings
    >>> handle_yolo_settings(["default_cfg_path=yolo11n.yaml"])  # Update a specific setting

Notes

- If no arguments are provided, the function will display the current settings.
- The 'reset' command will delete the existing settings file and create new default settings.
- Other arguments are treated as key-value pairs to update specific settings.
- The function will check for alignment between the provided settings and the existing ones.
- After processing, the updated settings will be displayed.
- For more information on handling YOLO settings, visit: https://docs.ultralytics.com/quickstart/#ultralytics-settings

Source code in `ultralytics/cfg/__init__.py`

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    def handle_yolo_settings(args: list[str]) -> None:
        """
        Handle YOLO settings command-line interface (CLI) commands.

        This function processes YOLO settings CLI commands such as reset and updating individual settings. It should be
        called when executing a script with arguments related to YOLO settings management.

        Args:
            args (list[str]): A list of command line arguments for YOLO settings management.

        Examples:
            >>> handle_yolo_settings(["reset"])  # Reset YOLO settings
            >>> handle_yolo_settings(["default_cfg_path=yolo11n.yaml"])  # Update a specific setting

        Notes:
            - If no arguments are provided, the function will display the current settings.
            - The 'reset' command will delete the existing settings file and create new default settings.
            - Other arguments are treated as key-value pairs to update specific settings.
            - The function will check for alignment between the provided settings and the existing ones.
            - After processing, the updated settings will be displayed.
            - For more information on handling YOLO settings, visit:
              https://docs.ultralytics.com/quickstart/#ultralytics-settings
        """
        url = "https://docs.ultralytics.com/quickstart/#ultralytics-settings"  # help URL
        try:
            if any(args):
                if args[0] == "reset":
                    SETTINGS_FILE.unlink()  # delete the settings file
                    SETTINGS.reset()  # create new settings
                    LOGGER.info("Settings reset successfully")  # inform the user that settings have been reset
                else:  # save a new setting
                    new = dict(parse_key_value_pair(a) for a in args)
                    check_dict_alignment(SETTINGS, new)
                    SETTINGS.update(new)
                    for k, v in new.items():
                        LOGGER.info(f"✅ Updated '{k}={v}'")

            LOGGER.info(SETTINGS)  # print the current settings
            LOGGER.info(f"💡 Learn more about Ultralytics Settings at {url}")
        except Exception as e:
            LOGGER.warning(f"settings error: '{e}'. Please see {url} for help.")

## `` ultralytics.cfg.handle_yolo_solutions

    handle_yolo_solutions(args: list[str]) -> None

Process YOLO solutions arguments and run the specified computer vision solutions pipeline.

Parameters:

Name | Type | Description | Default
--- | --- | --- | ---
`args` | `list[str]` | Command-line arguments for configuring and running the Ultralytics YOLO solutions: https://docs.ultralytics.com/solutions/, It can include solution name, source, and other configuration parameters. | required

Examples:

Run people counting solution with default settings:

    >>> handle_yolo_solutions(["count"])

Run analytics with custom configuration:

    >>> handle_yolo_solutions(["analytics", "conf=0.25", "source=path/to/video.mp4"])

Run inference with custom configuration, requires Streamlit version 1.29.0 or higher.

    >>> handle_yolo_solutions(["inference", "model=yolo11n.pt"])

Notes

- Arguments can be provided in the format 'key=value' or as boolean flags
- Available solutions are defined in SOLUTION_MAP with their respective classes and methods
- If an invalid solution is provided, defaults to 'count' solution
- Output videos are saved in 'runs/solution/{solution_name}' directory
- For 'analytics' solution, frame numbers are tracked for generating analytical graphs
- Video processing can be interrupted by pressing 'q'
- Processes video frames sequentially and saves output in .avi format
- If no source is specified, downloads and uses a default sample video
- The inference solution will be launched using the 'streamlit run' command.
- The Streamlit app file is located in the Ultralytics package directory.

Source code in `ultralytics/cfg/__init__.py`

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    def handle_yolo_solutions(args: list[str]) -> None:
        """
        Process YOLO solutions arguments and run the specified computer vision solutions pipeline.

        Args:
            args (list[str]): Command-line arguments for configuring and running the Ultralytics YOLO
                solutions: https://docs.ultralytics.com/solutions/, It can include solution name, source,
                and other configuration parameters.

        Examples:
            Run people counting solution with default settings:
            >>> handle_yolo_solutions(["count"])

            Run analytics with custom configuration:
            >>> handle_yolo_solutions(["analytics", "conf=0.25", "source=path/to/video.mp4"])

            Run inference with custom configuration, requires Streamlit version 1.29.0 or higher.
            >>> handle_yolo_solutions(["inference", "model=yolo11n.pt"])

        Notes:
            - Arguments can be provided in the format 'key=value' or as boolean flags
            - Available solutions are defined in SOLUTION_MAP with their respective classes and methods
            - If an invalid solution is provided, defaults to 'count' solution
            - Output videos are saved in 'runs/solution/{solution_name}' directory
            - For 'analytics' solution, frame numbers are tracked for generating analytical graphs
            - Video processing can be interrupted by pressing 'q'
            - Processes video frames sequentially and saves output in .avi format
            - If no source is specified, downloads and uses a default sample video
            - The inference solution will be launched using the 'streamlit run' command.
            - The Streamlit app file is located in the Ultralytics package directory.
        """
        from ultralytics.solutions.config import SolutionConfig

        full_args_dict = vars(SolutionConfig())  # arguments dictionary
        overrides = {}

        # check dictionary alignment
        for arg in merge_equals_args(args):
            arg = arg.lstrip("-").rstrip(",")
            if "=" in arg:
                try:
                    k, v = parse_key_value_pair(arg)
                    overrides[k] = v
                except (NameError, SyntaxError, ValueError, AssertionError) as e:
                    check_dict_alignment(full_args_dict, {arg: ""}, e)
            elif arg in full_args_dict and isinstance(full_args_dict.get(arg), bool):
                overrides[arg] = True
        check_dict_alignment(full_args_dict, overrides)  # dict alignment

        # Get solution name
        if not args:
            LOGGER.warning("No solution name provided. i.e `yolo solutions count`. Defaulting to 'count'.")
            args = ["count"]
        if args[0] == "help":
            LOGGER.info(SOLUTIONS_HELP_MSG)
            return  # Early return for 'help' case
        elif args[0] in SOLUTION_MAP:
            solution_name = args.pop(0)  # Extract the solution name directly
        else:
            LOGGER.warning(
                f"❌ '{args[0]}' is not a valid solution. 💡 Defaulting to 'count'.\n"
                f"🚀 Available solutions: {', '.join(list(SOLUTION_MAP.keys())[:-1])}\n"
            )
            solution_name = "count"  # Default for invalid solution

        if solution_name == "inference":
            checks.check_requirements("streamlit>=1.29.0")
            LOGGER.info("💡 Loading Ultralytics live inference app...")
            subprocess.run(
                [  # Run subprocess with Streamlit custom argument
                    "streamlit",
                    "run",
                    str(ROOT / "solutions/streamlit_inference.py"),
                    "--server.headless",
                    "true",
                    overrides.pop("model", "yolo11n.pt"),
                ]
            )
        else:
            import cv2  # Only needed for cap and vw functionality

            from ultralytics import solutions

            solution = getattr(solutions, SOLUTION_MAP[solution_name])(is_cli=True, **overrides)  # class i.e ObjectCounter

            cap = cv2.VideoCapture(solution.CFG["source"])  # read the video file
            if solution_name != "crop":
                # extract width, height and fps of the video file, create save directory and initialize video writer
                w, h, fps = (
                    int(cap.get(x)) for x in (cv2.CAP_PROP_FRAME_WIDTH, cv2.CAP_PROP_FRAME_HEIGHT, cv2.CAP_PROP_FPS)
                )
                if solution_name == "analytics":  # analytical graphs follow fixed shape for output i.e w=1920, h=1080
                    w, h = 1280, 720
                save_dir = get_save_dir(SimpleNamespace(project="runs/solutions", name="exp", exist_ok=False))
                save_dir.mkdir(parents=True)  # create the output directory i.e. runs/solutions/exp
                vw = cv2.VideoWriter(str(save_dir / f"{solution_name}.avi"), cv2.VideoWriter_fourcc(*"mp4v"), fps, (w, h))

            try:  # Process video frames
                f_n = 0  # frame number, required for analytical graphs
                while cap.isOpened():
                    success, frame = cap.read()
                    if not success:
                        break
                    results = solution(frame, f_n := f_n + 1) if solution_name == "analytics" else solution(frame)
                    if solution_name != "crop":
                        vw.write(results.plot_im)
                    if solution.CFG["show"] and cv2.waitKey(1) & 0xFF == ord("q"):
                        break
            finally:
                cap.release()

## `` ultralytics.cfg.parse_key_value_pair

    parse_key_value_pair(pair: str = 'key=value') -> tuple

Parse a key-value pair string into separate key and value components.

Parameters:

Name | Type | Description | Default
--- | --- | --- | ---
`pair` | `str` | A string containing a key-value pair in the format "key=value". | `'key=value'`

Returns:

Name | Type | Description
--- | --- | ---
`key` | `str` | The parsed key.
`value` | `str` | The parsed value.

Raises:

Type | Description
--- | ---
`AssertionError` | If the value is missing or empty.

Examples:

    >>> key, value = parse_key_value_pair("model=yolo11n.pt")
    >>> print(f"Key: {key}, Value: {value}")
    Key: model, Value: yolo11n.pt

    >>> key, value = parse_key_value_pair("epochs=100")
    >>> print(f"Key: {key}, Value: {value}")
    Key: epochs, Value: 100

Notes

- The function splits the input string on the first '=' character.
- Leading and trailing whitespace is removed from both key and value.
- An assertion error is raised if the value is empty after stripping.

Source code in `ultralytics/cfg/__init__.py`

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    def parse_key_value_pair(pair: str = "key=value") -> tuple:
        """
        Parse a key-value pair string into separate key and value components.

        Args:
            pair (str): A string containing a key-value pair in the format "key=value".

        Returns:
            key (str): The parsed key.
            value (str): The parsed value.

        Raises:
            AssertionError: If the value is missing or empty.

        Examples:
            >>> key, value = parse_key_value_pair("model=yolo11n.pt")
            >>> print(f"Key: {key}, Value: {value}")
            Key: model, Value: yolo11n.pt

            >>> key, value = parse_key_value_pair("epochs=100")
            >>> print(f"Key: {key}, Value: {value}")
            Key: epochs, Value: 100

        Notes:
            - The function splits the input string on the first '=' character.
            - Leading and trailing whitespace is removed from both key and value.
            - An assertion error is raised if the value is empty after stripping.
        """
        k, v = pair.split("=", 1)  # split on first '=' sign
        k, v = k.strip(), v.strip()  # remove spaces
        assert v, f"missing '{k}' value"
        return k, smart_value(v)

## `` ultralytics.cfg.smart_value

    smart_value(v: str) -> Any

Convert a string representation of a value to its appropriate Python type.

This function attempts to convert a given string into a Python object of the most appropriate type. It handles conversions to None, bool, int, float, and other types that can be evaluated safely.

Parameters:

Name | Type | Description | Default
--- | --- | --- | ---
`v` | `str` | The string representation of the value to be converted. | required

Returns:

Type | Description
--- | ---
`Any` | The converted value. The type can be None, bool, int, float, or the original string if no conversion is applicable.

Examples:

    >>> smart_value("42")
    42
    >>> smart_value("3.14")
    3.14
    >>> smart_value("True")
    True
    >>> smart_value("None")
    None
    >>> smart_value("some_string")
    'some_string'

Notes

- The function uses a case-insensitive comparison for boolean and None values.
- For other types, it attempts to use Python's eval() function, which can be unsafe if used on untrusted input.
- If no conversion is possible, the original string is returned.

Source code in `ultralytics/cfg/__init__.py`

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    def smart_value(v: str) -> Any:
        """
        Convert a string representation of a value to its appropriate Python type.

        This function attempts to convert a given string into a Python object of the most appropriate type. It handles
        conversions to None, bool, int, float, and other types that can be evaluated safely.

        Args:
            v (str): The string representation of the value to be converted.

        Returns:
            (Any): The converted value. The type can be None, bool, int, float, or the original string if no conversion
                is applicable.

        Examples:
            >>> smart_value("42")
            42
            >>> smart_value("3.14")
            3.14
            >>> smart_value("True")
            True
            >>> smart_value("None")
            None
            >>> smart_value("some_string")
            'some_string'

        Notes:
            - The function uses a case-insensitive comparison for boolean and None values.
            - For other types, it attempts to use Python's eval() function, which can be unsafe if used on untrusted input.
            - If no conversion is possible, the original string is returned.
        """
        v_lower = v.lower()
        if v_lower == "none":
            return None
        elif v_lower == "true":
            return True
        elif v_lower == "false":
            return False
        else:
            try:
                return eval(v)
            except Exception:
                return v

## `` ultralytics.cfg.entrypoint

    entrypoint(debug: str = '') -> None

Ultralytics entrypoint function for parsing and executing command-line arguments.

This function serves as the main entry point for the Ultralytics CLI, parsing command-line arguments and executing the corresponding tasks such as training, validation, prediction, exporting models, and more.

Parameters:

Name | Type | Description | Default
--- | --- | --- | ---
`debug` | `str` | Space-separated string of command-line arguments for debugging purposes. | `''`

Examples:

Train a detection model for 10 epochs with an initial learning_rate of 0.01:

    >>> entrypoint("train data=coco8.yaml model=yolo11n.pt epochs=10 lr0=0.01")

Predict a YouTube video using a pretrained segmentation model at image size 320:

    >>> entrypoint("predict model=yolo11n-seg.pt source='https://youtu.be/LNwODJXcvt4' imgsz=320")

Validate a pretrained detection model at batch-size 1 and image size 640:

    >>> entrypoint("val model=yolo11n.pt data=coco8.yaml batch=1 imgsz=640")

Notes

- If no arguments are passed, the function will display the usage help message.
- For a list of all available commands and their arguments, see the provided help messages and the Ultralytics documentation at https://docs.ultralytics.com.

Source code in `ultralytics/cfg/__init__.py`

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    def entrypoint(debug: str = "") -> None:
        """
        Ultralytics entrypoint function for parsing and executing command-line arguments.

        This function serves as the main entry point for the Ultralytics CLI, parsing command-line arguments and
        executing the corresponding tasks such as training, validation, prediction, exporting models, and more.

        Args:
            debug (str): Space-separated string of command-line arguments for debugging purposes.

        Examples:
            Train a detection model for 10 epochs with an initial learning_rate of 0.01:
            >>> entrypoint("train data=coco8.yaml model=yolo11n.pt epochs=10 lr0=0.01")

            Predict a YouTube video using a pretrained segmentation model at image size 320:
            >>> entrypoint("predict model=yolo11n-seg.pt source='https://youtu.be/LNwODJXcvt4' imgsz=320")

            Validate a pretrained detection model at batch-size 1 and image size 640:
            >>> entrypoint("val model=yolo11n.pt data=coco8.yaml batch=1 imgsz=640")

        Notes:
            - If no arguments are passed, the function will display the usage help message.
            - For a list of all available commands and their arguments, see the provided help messages and the
              Ultralytics documentation at https://docs.ultralytics.com.
        """
        args = (debug.split(" ") if debug else ARGV)[1:]
        if not args:  # no arguments passed
            LOGGER.info(CLI_HELP_MSG)
            return

        special = {
            "checks": checks.collect_system_info,
            "version": lambda: LOGGER.info(__version__),
            "settings": lambda: handle_yolo_settings(args[1:]),
            "cfg": lambda: YAML.print(DEFAULT_CFG_PATH),
            "hub": lambda: handle_yolo_hub(args[1:]),
            "login": lambda: handle_yolo_hub(args),
            "logout": lambda: handle_yolo_hub(args),
            "copy-cfg": copy_default_cfg,
            "solutions": lambda: handle_yolo_solutions(args[1:]),
            "help": lambda: LOGGER.info(CLI_HELP_MSG),  # help below hub for -h flag precedence
        }
        full_args_dict = {**DEFAULT_CFG_DICT, **{k: None for k in TASKS}, **{k: None for k in MODES}, **special}

        # Define common misuses of special commands, i.e. -h, -help, --help
        special.update({k[0]: v for k, v in special.items()})  # singular
        special.update({k[:-1]: v for k, v in special.items() if len(k) > 1 and k.endswith("s")})  # singular
        special = {**special, **{f"-{k}": v for k, v in special.items()}, **{f"--{k}": v for k, v in special.items()}}

        overrides = {}  # basic overrides, i.e. imgsz=320
        for a in merge_equals_args(args):  # merge spaces around '=' sign
            if a.startswith("--"):
                LOGGER.warning(f"argument '{a}' does not require leading dashes '--', updating to '{a[2:]}'.")
                a = a[2:]
            if a.endswith(","):
                LOGGER.warning(f"argument '{a}' does not require trailing comma ',', updating to '{a[:-1]}'.")
                a = a[:-1]
            if "=" in a:
                try:
                    k, v = parse_key_value_pair(a)
                    if k == "cfg" and v is not None:  # custom.yaml passed
                        LOGGER.info(f"Overriding {DEFAULT_CFG_PATH} with {v}")
                        overrides = {k: val for k, val in YAML.load(checks.check_yaml(v)).items() if k != "cfg"}
                    else:
                        overrides[k] = v
                except (NameError, SyntaxError, ValueError, AssertionError) as e:
                    check_dict_alignment(full_args_dict, {a: ""}, e)

            elif a in TASKS:
                overrides["task"] = a
            elif a in MODES:
                overrides["mode"] = a
            elif a.lower() in special:
                special[a.lower()]()
                return
            elif a in DEFAULT_CFG_DICT and isinstance(DEFAULT_CFG_DICT[a], bool):
                overrides[a] = True  # auto-True for default bool args, i.e. 'yolo show' sets show=True
            elif a in DEFAULT_CFG_DICT:
                raise SyntaxError(
                    f"'{colorstr('red', 'bold', a)}' is a valid YOLO argument but is missing an '=' sign "
                    f"to set its value, i.e. try '{a}={DEFAULT_CFG_DICT[a]}'\n{CLI_HELP_MSG}"
                )
            else:
                check_dict_alignment(full_args_dict, {a: ""})

        # Check keys
        check_dict_alignment(full_args_dict, overrides)

        # Mode
        mode = overrides.get("mode")
        if mode is None:
            mode = DEFAULT_CFG.mode or "predict"
            LOGGER.warning(f"'mode' argument is missing. Valid modes are {list(MODES)}. Using default 'mode={mode}'.")
        elif mode not in MODES:
            raise ValueError(f"Invalid 'mode={mode}'. Valid modes are {list(MODES)}.\n{CLI_HELP_MSG}")

        # Task
        task = overrides.pop("task", None)
        if task:
            if task not in TASKS:
                if task == "track":
                    LOGGER.warning(
                        f"invalid 'task=track', setting 'task=detect' and 'mode=track'. Valid tasks are {list(TASKS)}.\n{CLI_HELP_MSG}."
                    )
                    task, mode = "detect", "track"
                else:
                    raise ValueError(f"Invalid 'task={task}'. Valid tasks are {list(TASKS)}.\n{CLI_HELP_MSG}")
            if "model" not in overrides:
                overrides["model"] = TASK2MODEL[task]

        # Model
        model = overrides.pop("model", DEFAULT_CFG.model)
        if model is None:
            model = "yolo11n.pt"
            LOGGER.warning(f"'model' argument is missing. Using default 'model={model}'.")
        overrides["model"] = model
        stem = Path(model).stem.lower()
        if "rtdetr" in stem:  # guess architecture
            from ultralytics import RTDETR

            model = RTDETR(model)  # no task argument
        elif "fastsam" in stem:
            from ultralytics import FastSAM

            model = FastSAM(model)
        elif "sam_" in stem or "sam2_" in stem or "sam2.1_" in stem:
            from ultralytics import SAM

            model = SAM(model)
        else:
            from ultralytics import YOLO

            model = YOLO(model, task=task)
            if "yoloe" in stem or "world" in stem:
                cls_list = overrides.pop("classes", DEFAULT_CFG.classes)
                if cls_list is not None and isinstance(cls_list, str):
                    model.set_classes(cls_list.split(","))  # convert "person, bus" -> ['person', ' bus'].
        # Task Update
        if task != model.task:
            if task:
                LOGGER.warning(
                    f"conflicting 'task={task}' passed with 'task={model.task}' model. "
                    f"Ignoring 'task={task}' and updating to 'task={model.task}' to match model."
                )
            task = model.task

        # Mode
        if mode in {"predict", "track"} and "source" not in overrides:
            overrides["source"] = (
                "https://ultralytics.com/images/boats.jpg" if task == "obb" else DEFAULT_CFG.source or ASSETS
            )
            LOGGER.warning(f"'source' argument is missing. Using default 'source={overrides['source']}'.")
        elif mode in {"train", "val"}:
            if "data" not in overrides and "resume" not in overrides:
                overrides["data"] = DEFAULT_CFG.data or TASK2DATA.get(task or DEFAULT_CFG.task, DEFAULT_CFG.data)
                LOGGER.warning(f"'data' argument is missing. Using default 'data={overrides['data']}'.")
        elif mode == "export":
            if "format" not in overrides:
                overrides["format"] = DEFAULT_CFG.format or "torchscript"
                LOGGER.warning(f"'format' argument is missing. Using default 'format={overrides['format']}'.")

        # Run command in python
        getattr(model, mode)(**overrides)  # default args from model

        # Show help
        LOGGER.info(f"💡 Learn more at https://docs.ultralytics.com/modes/{mode}")

        # Recommend VS Code extension
        if IS_VSCODE and SETTINGS.get("vscode_msg", True):
            LOGGER.info(vscode_msg())

## `` ultralytics.cfg.copy_default_cfg

    copy_default_cfg() -> None

Copy the default configuration file and create a new one with '_copy' appended to its name.

This function duplicates the existing default configuration file (DEFAULT_CFG_PATH) and saves it with '_copy' appended to its name in the current working directory. It provides a convenient way to create a custom configuration file based on the default settings.

Examples:

    >>> copy_default_cfg()
    # Output: default.yaml copied to /path/to/current/directory/default_copy.yaml
    # Example YOLO command with this new custom cfg:
    #   yolo cfg='/path/to/current/directory/default_copy.yaml' imgsz=320 batch=8

Notes

- The new configuration file is created in the current working directory.
- After copying, the function prints a message with the new file's location and an example YOLO command demonstrating how to use the new configuration file.
- This function is useful for users who want to modify the default configuration without altering the original file.

Source code in `ultralytics/cfg/__init__.py`

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    def copy_default_cfg() -> None:
        """
        Copy the default configuration file and create a new one with '_copy' appended to its name.

        This function duplicates the existing default configuration file (DEFAULT_CFG_PATH) and saves it
        with '_copy' appended to its name in the current working directory. It provides a convenient way
        to create a custom configuration file based on the default settings.

        Examples:
            >>> copy_default_cfg()
            # Output: default.yaml copied to /path/to/current/directory/default_copy.yaml
            # Example YOLO command with this new custom cfg:
            #   yolo cfg='/path/to/current/directory/default_copy.yaml' imgsz=320 batch=8

        Notes:
            - The new configuration file is created in the current working directory.
            - After copying, the function prints a message with the new file's location and an example
              YOLO command demonstrating how to use the new configuration file.
            - This function is useful for users who want to modify the default configuration without
              altering the original file.
        """
        new_file = Path.cwd() / DEFAULT_CFG_PATH.name.replace(".yaml", "_copy.yaml")
        shutil.copy2(DEFAULT_CFG_PATH, new_file)
        LOGGER.info(
            f"{DEFAULT_CFG_PATH} copied to {new_file}\n"
            f"Example YOLO command with this new custom cfg:\n    yolo cfg='{new_file}' imgsz=320 batch=8"
        )

📅 Created 1 year ago ✏️ Updated 8 months ago