Reference for ultralytics/cfg/__init__.py
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Summary
function ultralytics.cfg.cfg2dict
def cfg2dict(cfg: str | Path | dict | SimpleNamespace) -> dict
Convert a configuration object to a dictionary.
Args
| 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
View on GitHubdef 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
function ultralytics.cfg.get_cfg
def get_cfg(
cfg: str | Path | dict | SimpleNamespace = DEFAULT_CFG_DICT, overrides: dict | None = None
) -> SimpleNamespace
Load and merge configuration data from a file or dictionary, with optional overrides.
Args
| 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
cfgandoverridesare provided, the values inoverrideswill take precedence. - Special handling ensures alignment and correctness of the configuration, such as converting numeric
projectandnameto 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
View on GitHubdef get_cfg(
cfg: str | Path | dict | SimpleNamespace = DEFAULT_CFG_DICT, overrides: dict | None = 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)
function ultralytics.cfg.check_cfg
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
| 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
View on GitHubdef 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)
function ultralytics.cfg.get_save_dir
def get_save_dir(args: SimpleNamespace, name: str | None = None) -> Path
Return the directory path for saving outputs, derived from arguments or default settings.
Args
| 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
View on GitHubdef get_save_dir(args: SimpleNamespace, name: str | None = 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
function ultralytics.cfg._handle_deprecation
def _handle_deprecation(custom: dict) -> dict
Handle deprecated configuration keys by mapping them to current equivalents with deprecation warnings.
Args
| 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
View on GitHubdef _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
function ultralytics.cfg.check_dict_alignment
def check_dict_alignment(
base: dict, custom: dict, e: Exception | None = None, allowed_custom_keys: set | None = None
) -> None
Check alignment between custom and base configuration dictionaries, handling deprecated keys and providing error
messages for mismatched keys.
Args
| 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 |
allowed_custom_keys | set | None | Optional set of additional keys that are allowed in the custom dictionary. | None |
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.
Raises
| Type | Description |
|---|---|
SystemExit | If mismatched keys are found between the custom and base dictionaries. |
Source code in ultralytics/cfg/__init__.py
View on GitHubdef check_dict_alignment(
base: dict, custom: dict, e: Exception | None = None, allowed_custom_keys: set | None = 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.
allowed_custom_keys (set | None): Optional set of additional keys that are allowed in the custom dictionary.
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))
# Allow 'augmentations' as a valid custom parameter for custom Albumentations transforms
if allowed_custom_keys is None:
allowed_custom_keys = {"augmentations"}
if mismatched := [k for k in custom_keys if k not in base_keys and k not in allowed_custom_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
function ultralytics.cfg.merge_equals_args
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
| 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 |
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
View on GitHubdef 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
function ultralytics.cfg.handle_yolo_hub
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
| 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
View on GitHubdef 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()
function ultralytics.cfg.handle_yolo_settings
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
| 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
View on GitHubdef 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.")
function ultralytics.cfg.handle_yolo_solutions
def handle_yolo_solutions(args: list[str]) -> None
Process YOLO solutions arguments and run the specified computer vision solutions pipeline.
Args
| Name | Type | Description | Default |
|---|---|---|---|
args | list[str] | Command-line arguments for configuring and running the Ultralytics YOLO solutions. | 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
View on GitHubdef 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.
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()
function ultralytics.cfg.parse_key_value_pair
def parse_key_value_pair(pair: str = "key=value") -> tuple
Parse a key-value pair string into separate key and value components.
Args
| Name | Type | Description | Default |
|---|---|---|---|
pair | str | A string containing a key-value pair in the format "key=value". | "key=value" |
Returns
| Type | Description |
|---|---|
key (str) | The parsed key. |
value (str) | The parsed value. |
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.
Raises
| Type | Description |
|---|---|
AssertionError | If the value is missing or empty. |
Source code in ultralytics/cfg/__init__.py
View on GitHubdef 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)
function ultralytics.cfg.smart_value
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
| 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 |
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 ast.literal_eval() function for safe evaluation.
- If no conversion is possible, the original string is returned.
Source code in ultralytics/cfg/__init__.py
View on GitHubdef 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 ast.literal_eval() function for safe evaluation.
- 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 ast.literal_eval(v)
except Exception:
return v
function ultralytics.cfg.entrypoint
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
| 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
View on GitHubdef 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())
function ultralytics.cfg.copy_default_cfg
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.
Source code in ultralytics/cfg/__init__.py
View on GitHubdef 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"
)