o V h@s@ddlZddlZddlZddlmZddlmZddlmZm Z m Z m Z ddl Z ddl mZddlmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZm Z m!Z!m"Z"m#Z#ddd d d d d ddddddd Z$e%hdZ&e%hdZ'ddddddZ(ddddd dZ)d!d"d#d$d!dZ*e%d%d&e'DZ+ej,pd'd'gZ-d(e.d)ge-d*dd+e/e$0dd,d-Z1d(e.d)ge-d*dd.e'd/e&d0e/e$0d*d,d1 Z2e%hd2Z3e%hd3Z4e%hd4Z5e%hd5Z6d6e e.ee efd7e fd8d9Z7edfd6e e.ee efd:e d7efd;d<Z8dbd6e d>e9d7dfd?d@Z:dcdAedBe.d7efdCdDZ;dEe d7e fdFdGZdAe e.d7e e.fdLdMZ?dAe e.d7dfdNdOZ@dAe e.d7dfdPdQZAdAe e.d7dfdRdSZBdddUe.d7eCfdVdWZDdXe.d7efdYdZZEded[e.d7dfd\d]ZFdfd^d_ZGeHd`kreFd'dadSdS)gN)Path)SimpleNamespace)AnyDictListUnion) __version__)ASSETS DEFAULT_CFGDEFAULT_CFG_DICTDEFAULT_CFG_PATHDEFAULT_SOL_DICT IS_VSCODELOGGERRANKROOTRUNS_DIRSETTINGS SETTINGS_FILE TESTS_RUNNINGIterableSimpleNamespacecheckscolorstrdeprecation_warn vscode_msg yaml_load yaml_print ObjectCounter ObjectCropper ObjectBlurrerAIGymHeatmapInstanceSegmentation VisionEyeSpeedEstimator QueueManager Analytics Inference TrackZone) countcropblurworkoutheatmapisegment visioneyespeedqueue analytics inference trackzonehelp>valtracktrainexportpredict benchmark>obbposedetectsegmentclassifyz coco8.yamlzcoco8-seg.yaml imagenet10zcoco8-pose.yamlz dota8.yaml)r>r?r@r=r< yolo11n.ptzyolo11n-seg.ptzyolo11n-cls.ptzyolo11n-pose.ptzyolo11n-obb.ptzmetrics/mAP50-95(B)zmetrics/mAP50-95(M)zmetrics/accuracy_top1zmetrics/mAP50-95(P)cCsh|]}t|qS) TASK2MODEL).0taskrCrCL/var/www/vscode/kcb/lib/python3.10/site-packages/ultralytics/cfg/__init__.py MsrHz Arguments received: yoloz. Ultralytics 'yolo solutions' usage overview: yolo solutions SOLUTION ARGS Where SOLUTION (optional) is one of a. ARGS (optional) are any number of custom 'arg=value' pairs like 'show_in=True' that override defaults at https://docs.ultralytics.com/usage/cfg 1. Call object counting solution yolo solutions count source="path/to/video.mp4" region="[(20, 400), (1080, 400), (1080, 360), (20, 360)]" 2. Call heatmaps solution yolo solutions heatmap colormap=cv2.COLORMAP_PARULA model=yolo11n.pt 3. Call queue management solution yolo solutions queue region="[(20, 400), (1080, 400), (1080, 360), (20, 360)]" model=yolo11n.pt 4. Call workouts monitoring solution for push-ups yolo solutions workout model=yolo11n-pose.pt kpts=[6, 8, 10] 5. Generate analytical graphs yolo solutions analytics analytics_type="pie" 6. Track objects within specific zones yolo solutions trackzone source="path/to/video.mp4" region="[(150, 150), (1130, 150), (1130, 570), (150, 570)]" 7. Streamlit real-time webcam inference GUI yolo streamlit-predict z. Ultralytics 'yolo' commands use the following syntax: yolo TASK MODE ARGS Where TASK (optional) is one of z+ MODE (required) is one of a ARGS (optional) are any number of custom 'arg=value' pairs like 'imgsz=320' that override defaults. See all ARGS at https://docs.ultralytics.com/usage/cfg or with 'yolo cfg' 1. Train a detection model for 10 epochs with an initial learning_rate of 0.01 yolo train data=coco8.yaml model=yolo11n.pt epochs=10 lr0=0.01 2. Predict a YouTube video using a pretrained segmentation model at image size 320: yolo predict model=yolo11n-seg.pt source='https://youtu.be/LNwODJXcvt4' imgsz=320 3. Val a pretrained detection model at batch-size 1 and image size 640: yolo val model=yolo11n.pt data=coco8.yaml batch=1 imgsz=640 4. Export a YOLO11n classification model to ONNX format at image size 224 by 128 (no TASK required) yolo export model=yolo11n-cls.pt format=onnx imgsz=224,128 5. Ultralytics solutions usage yolo solutions count or in a source="path/to/video.mp4" 6. Run special commands: yolo help yolo checks yolo version yolo settings yolo copy-cfg yolo cfg yolo solutions help Docs: https://docs.ultralytics.com Solutions: https://docs.ultralytics.com/solutions/ Community: https://community.ultralytics.com GitHub: https://github.com/ultralytics/ultralytics > boxclsdfltimebatchsheardegrees workspace warmup_epochs>bgrioulr0lrfconfhsv_hhsv_shsv_vmixupscalefliplrflipudmosaicdropoutfractionmomentum translate copy_paste perspective weight_decaywarmup_bias_lrwarmup_momentum> nbsseedepochsmax_detworkerspatience line_width mask_ratio vid_stride save_period close_mosaic>!dnnnmsr6halfint8rectsaveshowkerasplotscos_lraugmentdynamicprofileverboseexist_okoptimizesave_txtsimplify save_conf save_crop save_json show_conf visualize show_boxes single_cls multi_scale save_frames show_labels agnostic_nms overlap_mask retina_masks deterministiccfgreturncCs0t|ttfr t|}|St|trt|}|S)a Converts 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. ) isinstancestrrrrvarsrrCrCrGcfg2dicts  r overridescCst|}|rt|}d|vr|ddt||i||}dD]}||vr8t||ttfr8t||||<q!|ddkrZt|dddd|d<t d |dd t |t d i|S) a@ 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. save_dirN)projectnamermodelrI.rz,'name=model' automatically updated to 'name='.rC) rpopcheck_dict_alignmentrintfloatrgetsplitrwarning check_cfgr)rrkrCrCrGget_cfgs    rThardcCs|D]\}}|dur|tvr:t|ttfs:|r3td|d|dt|jd|d|d|d t|||<q|tvrt|ttfsi|ratd|d|dt|jd|d|d|d t|||<}d |krsd ksnt d|d|d |d q|t vrt|ts|rtd|d|dt|jd |d|d t|||<q|t vrt|t s|rtd|d|dt|jd |d|d|d t |||<qdS)a Checks 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]. N'=z' is of invalid type z . Valid 'z' types are int (i.e. 'z=0') or float (i.e. 'z=0.5')gg?z' is an invalid value. Valid 'z!' values are between 0.0 and 1.0.z. 'z' must be an int (i.e. 'z=8')z' must be a bool (i.e. 'z =True' or 'z=False')) itemsCFG_FLOAT_KEYSrrr TypeErrortype__name__CFG_FRACTION_KEYS ValueError CFG_INT_KEYS CFG_BOOL_KEYSbool)rrrvrCrCrGrGsd( rargsrcCst|ddr |j}t |Sddlm}|jp!trtjdnt|j }|p*|j p*|j }|t ||t dvr8|jndd}t |S) a Returns 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 rNr)increment_pathztests/tmp/runs>rrLT)r)getattrrultralytics.utils.filesrrrrparentrrFrmoderrr)rrrrrrCrCrG get_save_dirs  "rcustomcCsdddfdddfdddfdd dfd }hd }|D]\}\}}||vr*qt|||||||<q|D]}||vrBq;t|||q;|S) a Handles deprecated configuration keys by mapping them to current equivalents with deprecation warnings. Args: custom (dict): Configuration dictionary potentially containing deprecated keys. 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'. rcS|SNrCrrCrCrGz%_handle_deprecation..rcS t| SrrrrCrCrGr rcSrrrrrCrCrGrrrrcSrrrCrrCrCrGrr)boxes hide_labels hide_confline_thickness> save_hybrid crop_fractionlabel_smoothing)rrr)rdeprecated_mappings removed_keysold_keynew_key transformkeyrCrCrG_handle_deprecations"      rbaseec st|}dd|fD\}fdd|D}rUddlm}d}|D])}||}fdd|D}|r>> 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. css|] }t|VqdSr) frozensetkeysrExrCrCrG sz'check_dict_alignment..csg|]}|vr|qSrCrCrEr) base_keysrCrG sz(check_dict_alignment..r)get_close_matchesrIcs0g|]}|dur|d|n|qS)Nr)rr)rrCrGrs0zSimilar arguments are i.e. rrredboldz ' is not a valid YOLO argument.  N)rdifflibrr SyntaxError CLI_HELP_MSG) rrr custom_keys mismatchedrstringrmatches match_strrC)rrrGrs   rcCsJg}d}d}d}|t|kr||}|dkr:d|kr$t|dkr:nn|dd||d7<|d7}q|dra|t|dkrad||dvra||||d|d7}q|drw|dkrw|d|7<|d7}q||d|d7}||7}|dkr||d}|d7}|t|ks|r|||S) a{ Merges arguments around isolated '=' in a list of strings and joins 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]'] rIrrrKrL[])lenendswithappend startswithr))rnew_argscurrentdepthiargrCrCrGmerge_equals_argss8 (*   rcCsZddlm}|ddkrt|dkr|dnd}||dS|ddkr+|dSdS)a5 Handles 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. r)hubloginrKrIlogoutN) ultralyticsrrrr)rrrrCrCrGhandle_yolo_hub1s    rc Csd}z;t|r.|ddkrtttdntdd|D}tt|t |tttd|Wd St y\}zt d|d |d WYd }~d Sd }~ww) a{ Handles 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 z=https://docs.ultralytics.com/quickstart/#ultralytics-settingsrresetzSettings reset successfullycss|]}t|VqdSr)parse_key_value_pair)rEarCrCrGrnsz'handle_yolo_settings..u.💡 Learn more about Ultralytics Settings at zsettings error: 'z'. Please see z for help.N) anyrunlinkrrrinfodictrupdate Exceptionr)rurlnewrrCrCrGhandle_yolo_settingsOs      &rc sittdddd}i}t|D]I}|dd}d|vrKz t|\}}|||<Wqtttt fyJ}zt ||di|WYd }~qd }~ww||vr[t | |t r[d ||<qt |||sktd d g}|d dkrxttd S|d tvr|d }ntd|d ddttd ddd }|dkrtdtdtddttddd|ddgd Sd dlm}t|t|d0dd i|} t !| j"d |d!kr fd"d#t j#t j$t j%fD\} } } |d$krd%\} } t&t'd&d'd(d)} | j(d d*t )t| |d+t j*d,| | | f}z\d }+rh,\}}|s2n=|d$kr@| ||d-}n| |}|d!krO|-|j.t /d-d.@t0d/kr\n+s(W1d SW1d SW1d SW1d S1w)1a Processes YOLO solutions arguments and runs 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: - Default configurations are merged from DEFAULT_SOL_DICT and DEFAULT_CFG_DICT - 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. g?)rzcropped-detections) blur_ratio vision_pointcrop_dir-,rrINTzMNo solution name provided. i.e `yolo solutions count`. Defaulting to 'count'.r)rr5u❌ 'uQ' is not a valid solution. 💡 Defaulting to 'count'. 🚀 Available solutions: z, rLrr3zstreamlit>=1.29.0,<1.44.0u.💡 Loading Ultralytics live inference app... streamlitrunz solutions/streamlit_inference.pyz--server.headlesstruerrB) solutionsis_clisourcer*c3s|] }t|VqdSr)rrrcaprCrGrs z(handle_yolo_solutions..r2)iizruns/solutionsexpF)rrr)parentsz.avimp4vrKqrC)2r r rlstriprstripr NameErrorrrAssertionErrorrrrrrrrSOLUTIONS_HELP_MSG SOLUTION_MAPrjoinlistrrcheck_requirements subprocessrrrrrrcv2 VideoCaptureCFGCAP_PROP_FRAME_WIDTHCAP_PROP_FRAME_HEIGHT CAP_PROP_FPSrrmkdir VideoWriterVideoWriter_fourccisOpenedreadwriteplot_imwaitKeyordrelease)rfull_args_dictrrrrr solution_namersolutionwhfpsrvwf_nsuccessframeresultsrCrrGhandle_yolo_solutionsxs                    (  $     rG key=valuepaircCsB|dd\}}||}}|sJd|d|t|fS)aw Parses 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. rrKz missing 'z' value)rstrip smart_value)rIrrrCrCrGrs rrcCsN|}|dkr dS|dkrdS|dkrdSzt|WSty&|YSw)a3 Converts 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. noneNrTfalseF)lowerevalr )rv_lowerrCrCrGrK s  rKdebugc s|r|dntddsttdSddtjddfddddfd dfd dfd dtfd dd }itddt Dddt D|}| dd| D| dd| Di|dd| Ddd| D}i}t D]}|drtd|d|ddd|dd}|drtd|d|ddd|dd}d|vrz.t|\}}|dkr|durtdtd|d dtt| D}n|||<Wqttttfy}zt||d!i|WYd}~qd}~ww|t vr||d"<q|t vr%||d#<q||vr6||dS|tvrHtt|trHd$||<q|tvrctd%td&d'|d(|dt|d)tt||d!iqt|||d#}|durtj pd*}td+t d,|dn|t vrtd-|d.t d/t|!d"d} | r| t vr| d0krtd1d2\} }n td3| d4t d/td5|vrt"| |d5<|!d5tj#} | durd6} td7| d| |d5<t$| j%} d8| vrd9d:l&m'} | | } n6d;| vrd9d| vs%d?| vr0d9d@l&m)}|| } n d9dAl&m*}|| | dB} t|dCt+rL| ,|dC| | j-krl| ritdD| dE| j-dF| dG| j-dH | j-} |dIvrdJ|vr| dKkr}dLntj.pt/|dJ<tdM|dJdnI|dNvrdO|vrdP|vrtj0pt1| ptj-tj0|dO<tdQ|dOdn|dRkrdS|vrtj2pdT|dS<tdU|dSdt3| |dXi|tdV|t4rt5dWd$rtt6dSdSdS)Ya 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.  rKNcS ttSr)rrrrCrCrCrGrYrzentrypoint..cSrSr)rrrrCrCrCrGr[rctddSNrK)rrCrrCrGr\cSsttSr)rr rCrCrCrGr]crTrUrrCrVrCrGr^rWctSrrYrCrVrCrGr_rXcrZrrYrCrVrCrGr`rXcrTrU)rGrCrVrCrGrbrW) r5rversionsettingsrrrrzcopy-cfgrcSsi|]}|dqSrrCrrCrCrG dszentrypoint..cSsi|] \}}|d|qS)rrCrErrrCrCrGr]gscSs4i|]\}}t|dkr|dr|dd|qS)rKsNrL)rrr^rCrCrGr]hs4cSi|] \}}d||qS)rrCr^rCrCrGr]icSr`)--rCr^rCrCrGr]irarbz argument 'z5' does not require leading dashes '--', updating to 'rrrz4' does not require trailing comma ',', updating to 'rLrrz Overriding z with cSsi|] \}}|dkr||qSrrC)rErr6rCrCrGr]xsrIrFrTrrrzR' is a valid YOLO argument but is missing an '=' sign to set its value, i.e. try 'z' r:z,'mode' argument is missing. Valid modes are z. Using default 'mode=zInvalid 'mode=z'. Valid modes are z. r7zfinvalid 'task=track', setting 'task=detect' and 'mode=track'. Valid tasks are {TASKS}. {CLI_HELP_MSG}.)r>r7zInvalid 'task=z'. Valid tasks are rrBz2'model' argument is missing. Using default 'model=rtdetrr)RTDETRfastsam)FastSAMsam_sam2_zsam2.1_)SAM)YOLO)rF pretrainedzconflicting 'task=z' passed with 'task=z' model. Ignoring 'task=z' and updating to 'task=z' to match model.>r7r:rr<z(https://ultralytics.com/images/boats.jpgz4'source' argument is missing. Using default 'source=>r6r8dataresumez0'data' argument is missing. Using default 'data=r9format torchscriptz4'format' argument is missing. Using default 'format=u6💡 Learn more at https://docs.ultralytics.com/modes/rrC)7rARGVrrrrcollect_system_infocopy_default_cfgr TASKSMODESr rrrrrrr r check_yamlr$rrr%rrNrrrrr rrrDrrstemrrdrfrirjrloadrFrr rl TASK2DATArnrrrr)rQspecialr<rrrrrrrFrrvrdrfrirjrCrVrG entrypoint:s      ( ,                                       "  rzcCsBttjdd}tt|ttd|d|ddS)a# Copies the default configuration file and creates 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. z.yamlz _copy.yamlz copied to z> Example YOLO command with this new custom cfg: yolo cfg='z' imgsz=320 batch=8N) rcwdr rreplaceshutilcopy2rr)new_filerCrCrGrrs  rr__main__)rQ)Tr)rH)rI)rN)Ir}r+syspathlibrtypesrtypingrrrrr,rrultralytics.utilsr r r r r rrrrrrrrrrrrrrrr'rrtrsrxrD TASK2METRICMODELSargvrprr)rr&rrrrrrrrrrrr rrrrrGtuplerrKrzrrrrCrCrCrGs   X  ) '(#0> )(;)s"- -