8.0.60 new HUB training syntax (#1753)

Co-authored-by: Rafael Pierre <97888102+rafaelvp-db@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com>
Co-authored-by: Semih Demirel <85176438+semihhdemirel@users.noreply.github.com>

ultralytics/yolo/cfg/__init__.py

@@ -9,7 +9,8 @@ from types import SimpleNamespace
 from typing import Dict, List, Union
 
 from ultralytics.yolo.utils import (DEFAULT_CFG, DEFAULT_CFG_DICT, DEFAULT_CFG_PATH, LOGGER, ROOT, USER_CONFIG_DIR,
-                                    IterableSimpleNamespace, __version__, checks, colorstr, yaml_load, yaml_print)
+                                    IterableSimpleNamespace, __version__, checks, colorstr, get_settings, yaml_load,
+                                    yaml_print)
 
 # Define valid tasks and modes
 MODES = 'train', 'val', 'predict', 'export', 'track', 'benchmark'
@@ -187,6 +188,51 @@ def merge_equals_args(args: List[str]) -> List[str]:
     return new_args
 
 
+def handle_yolo_hub(args: List[str]) -> None:
+    """
+    Handle Ultralytics HUB command-line interface (CLI) commands.
+
+    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
+
+    Example:
+        python my_script.py hub login your_api_key
+    """
+    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()
+
+
+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.
+    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.
+
+    Example:
+        python my_script.py yolo settings reset
+    """
+    path = USER_CONFIG_DIR / 'settings.yaml'  # get SETTINGS YAML file path
+    if any(args) and args[0] == 'reset':
+        path.unlink()  # delete the settings file
+        get_settings()  # create new settings
+        LOGGER.info('Settings reset successfully')  # inform the user that settings have been reset
+    yaml_print(path)  # print the current settings
+
+
 def entrypoint(debug=''):
     """
     This function is the ultralytics package entrypoint, it's responsible for parsing the command line arguments passed
@@ -211,8 +257,10 @@ def entrypoint(debug=''):
         'help': lambda: LOGGER.info(CLI_HELP_MSG),
         'checks': checks.check_yolo,
         'version': lambda: LOGGER.info(__version__),
-        'settings': lambda: yaml_print(USER_CONFIG_DIR / 'settings.yaml'),
+        '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),
         'copy-cfg': copy_default_cfg}
     full_args_dict = {**DEFAULT_CFG_DICT, **{k: None for k in TASKS}, **{k: None for k in MODES}, **special}
 
@@ -255,8 +303,8 @@ def entrypoint(debug=''):
             overrides['task'] = a
         elif a in MODES:
             overrides['mode'] = a
-        elif a in special:
-            special[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

ultralytics/yolo/engine/model.py

@@ -68,12 +68,14 @@ class YOLO:
         list(ultralytics.yolo.engine.results.Results): The prediction results.
     """
 
-    def __init__(self, model: Union[str, Path] = 'yolov8n.pt', task=None, session=None) -> None:
+    def __init__(self, model: Union[str, Path] = 'yolov8n.pt', task=None) -> None:
         """
         Initializes the YOLO model.
 
         Args:
-            model (str, Path): model to load or create
+            model (Union[str, Path], optional): Path or name of the model to load or create. Defaults to 'yolov8n.pt'.
+            task (Any, optional): Task type for the YOLO model. Defaults to None.
+
         """
         self._reset_callbacks()
         self.predictor = None  # reuse predictor
@@ -85,10 +87,16 @@ class YOLO:
         self.ckpt_path = None
         self.overrides = {}  # overrides for trainer object
         self.metrics = None  # validation/training metrics
-        self.session = session  # HUB session
+        self.session = None  # HUB session
+        model = str(model).strip()  # strip spaces
+
+        # Check if Ultralytics HUB model from https://hub.ultralytics.com
+        if model.startswith('https://hub.ultralytics.com/models/'):
+            from ultralytics.hub import HUBTrainingSession
+            self.session = HUBTrainingSession(model)
+            model = self.session.model_file
 
         # Load or create new YOLO model
-        model = str(model).strip()  # strip spaces
         suffix = Path(model).suffix
         if not suffix and Path(model).stem in GITHUB_ASSET_STEMS:
             model, suffix = Path(model).with_suffix('.pt'), '.pt'  # add suffix, i.e. yolov8n -> yolov8n.pt
@@ -280,6 +288,7 @@ class YOLO:
         from ultralytics.yolo.utils.benchmarks import benchmark
         overrides = self.model.args.copy()
         overrides.update(kwargs)
+        overrides['mode'] = 'benchmark'
         overrides = {**DEFAULT_CFG_DICT, **overrides}  # fill in missing overrides keys with defaults
         return benchmark(model=self, imgsz=overrides['imgsz'], half=overrides['half'], device=overrides['device'])
 
@@ -293,6 +302,7 @@ class YOLO:
         self._check_is_pytorch_model()
         overrides = self.overrides.copy()
         overrides.update(kwargs)
+        overrides['mode'] = 'export'
         args = get_cfg(cfg=DEFAULT_CFG, overrides=overrides)
         args.task = self.task
         if args.imgsz == DEFAULT_CFG.imgsz:
@@ -309,6 +319,11 @@ class YOLO:
             **kwargs (Any): Any number of arguments representing the training configuration.
         """
         self._check_is_pytorch_model()
+        if self.session:  # Ultralytics HUB session
+            if any(kwargs):
+                LOGGER.warning('WARNING ⚠️ using HUB training arguments, ignoring local training arguments.')
+            kwargs = self.session.train_args
+            self.session.check_disk_space()
         check_pip_update_available()
         overrides = self.overrides.copy()
         overrides.update(kwargs)

ultralytics/yolo/engine/results.py

@@ -277,6 +277,8 @@ class Masks(SimpleClass):
         self.masks = masks  # N, h, w
         self.orig_shape = orig_shape
 
+    @property
+    @lru_cache(maxsize=1)
     def segments(self):
         # Segments-deprecated (normalized)
         LOGGER.warning("WARNING ⚠️ 'Masks.segments' is deprecated. Use 'Masks.xyn' for segments (normalized) and "

ultralytics/yolo/utils/__init__.py

@@ -321,10 +321,13 @@ def is_online() -> bool:
         bool: True if connection is successful, False otherwise.
     """
     import socket
-    with contextlib.suppress(Exception):
-        host = socket.gethostbyname('www.github.com')
-        socket.create_connection((host, 80), timeout=2)
-        return True
+
+    for server in '1.1.1.1', '8.8.8.8', '223.5.5.5':  # Cloudflare, Google, AliDNS:
+        try:
+            socket.create_connection((server, 53), timeout=2)  # connect to (server, port=53)
+            return True
+        except (socket.timeout, socket.gaierror, OSError):
+            continue
     return False
 
 
@@ -586,7 +589,7 @@ def set_sentry():
             logging.getLogger(logger).setLevel(logging.CRITICAL)
 
 
-def get_settings(file=USER_CONFIG_DIR / 'settings.yaml', version='0.0.2'):
+def get_settings(file=USER_CONFIG_DIR / 'settings.yaml', version='0.0.3'):
     """
     Loads a global Ultralytics settings YAML file or creates one with default values if it does not exist.
 
@@ -609,8 +612,9 @@ def get_settings(file=USER_CONFIG_DIR / 'settings.yaml', version='0.0.2'):
         'datasets_dir': str(datasets_root / 'datasets'),  # default datasets directory.
         'weights_dir': str(root / 'weights'),  # default weights directory.
         'runs_dir': str(root / 'runs'),  # default runs directory.
-        'sync': True,  # sync analytics to help with YOLO development
         'uuid': hashlib.sha256(str(uuid.getnode()).encode()).hexdigest(),  # anonymized uuid hash
+        'sync': True,  # sync analytics to help with YOLO development
+        'api_key': '',  # Ultralytics HUB API key (https://hub.ultralytics.com/)
         'settings_version': version}  # Ultralytics settings version
 
     with torch_distributed_zero_first(RANK):

ultralytics/yolo/utils/callbacks/mlflow.py

@@ -25,7 +25,7 @@ def on_pretrain_routine_end(trainer):
         mlflow_location = os.environ['MLFLOW_TRACKING_URI']  # "http://192.168.xxx.xxx:5000"
         mlflow.set_tracking_uri(mlflow_location)
 
-        experiment_name = trainer.args.project or 'YOLOv8'
+        experiment_name = trainer.args.project or '/Shared/YOLOv8'
         experiment = mlflow.get_experiment_by_name(experiment_name)
         if experiment is None:
             mlflow.create_experiment(experiment_name)
@@ -33,16 +33,15 @@ def on_pretrain_routine_end(trainer):
 
         prefix = colorstr('MLFlow: ')
         try:
-            run, active_run = mlflow, mlflow.start_run() if mlflow else None
-            if active_run is not None:
-                run_id = active_run.info.run_id
-                LOGGER.info(f'{prefix}Using run_id({run_id}) at {mlflow_location}')
+            run, active_run = mlflow, mlflow.active_run()
+            if not active_run:
+                active_run = mlflow.start_run(experiment_id=experiment.experiment_id)
+            run_id = active_run.info.run_id
+            LOGGER.info(f'{prefix}Using run_id({run_id}) at {mlflow_location}')
+            run.log_params(vars(trainer.model.args))
         except Exception as err:
             LOGGER.error(f'{prefix}Failing init - {repr(err)}')
             LOGGER.warning(f'{prefix}Continuing without Mlflow')
-            run = None
-
-        run.log_params(vars(trainer.model.args))
 
 
 def on_fit_epoch_end(trainer):

ultralytics/yolo/utils/checks.py

@@ -142,7 +142,7 @@ def check_pip_update_available():
         bool: True if an update is available, False otherwise.
     """
     if ONLINE and is_pip_package():
-        with contextlib.suppress(ConnectionError):
+        with contextlib.suppress(Exception):
             from ultralytics import __version__
             latest = check_latest_pypi_version()
             if pkg.parse_version(__version__) < pkg.parse_version(latest):  # update is available

ultralytics/yolo/utils/downloads.py

@@ -12,7 +12,7 @@ import requests
 import torch
 from tqdm import tqdm
 
-from ultralytics.yolo.utils import LOGGER, checks, is_online
+from ultralytics.yolo.utils import LOGGER, checks, emojis, is_online
 
 GITHUB_ASSET_NAMES = [f'yolov8{size}{suffix}.pt' for size in 'nsmlx' for suffix in ('', '6', '-cls', '-seg')] + \
                      [f'yolov5{size}u.pt' for size in 'nsmlx'] + \
@@ -113,9 +113,9 @@ def safe_download(url,
                     f.unlink()  # remove partial downloads
             except Exception as e:
                 if i == 0 and not is_online():
-                    raise ConnectionError(f'❌  Download failure for {url}. Environment is not online.') from e
+                    raise ConnectionError(emojis(f'❌  Download failure for {url}. Environment is not online.')) from e
                 elif i >= retry:
-                    raise ConnectionError(f'❌  Download failure for {url}. Retry limit reached.') from e
+                    raise ConnectionError(emojis(f'❌  Download failure for {url}. Retry limit reached.')) from e
                 LOGGER.warning(f'⚠️ Download failure, retrying {i + 1}/{retry} {url}...')
 
     if unzip and f.exists() and f.suffix in ('.zip', '.tar', '.gz'):

ultralytics/yolo/utils/plotting.py

@@ -114,7 +114,7 @@ class Annotator:
             self.im[:] = im_gpu.permute(1, 2, 0).contiguous().cpu().numpy() * 255
         if im_gpu.device != masks.device:
             im_gpu = im_gpu.to(masks.device)
-        colors = torch.tensor(colors, device=masks.device, dtype=torch.float32) / 255.0
+        colors = torch.tensor(colors, device=masks.device, dtype=torch.float32) / 255.0  # shape(n,3)
         colors = colors[:, None, None]  # shape(n,1,1,3)
         masks = masks.unsqueeze(3)  # shape(n,h,w,1)
         masks_color = masks * (colors * alpha)  # shape(n,h,w,3)

ultralytics/yolo/v8/segment/predict.py

@@ -78,7 +78,7 @@ class SegmentationPredictor(DetectionPredictor):
         for j, d in enumerate(reversed(det)):
             c, conf, id = int(d.cls), float(d.conf), None if d.id is None else int(d.id.item())
             if self.args.save_txt:  # Write to file
-                seg = mask.segments[len(det) - j - 1].copy().reshape(-1)  # reversed mask.segments, (n,2) to (n*2)
+                seg = mask.xyn[len(det) - j - 1].copy().reshape(-1)  # reversed mask.xyn, (n,2) to (n*2)
                 line = (c, *seg) + (conf, ) * self.args.save_conf + (() if id is None else (id, ))
                 with open(f'{self.txt_path}.txt', 'a') as f:
                     f.write(('%g ' * len(line)).rstrip() % line + '\n')