diff --git a/ultralytics/__init__.py b/ultralytics/__init__.py index f03064e..fc6f2a4 100644 --- a/ultralytics/__init__.py +++ b/ultralytics/__init__.py @@ -1,6 +1,6 @@ # Ultralytics YOLO 🚀, GPL-3.0 license -__version__ = '8.0.44' +__version__ = '8.0.45' from ultralytics.yolo.engine.model import YOLO from ultralytics.yolo.utils.checks import check_yolo as checks diff --git a/ultralytics/yolo/cfg/__init__.py b/ultralytics/yolo/cfg/__init__.py index 5fdf8a3..12e6c0c 100644 --- a/ultralytics/yolo/cfg/__init__.py +++ b/ultralytics/yolo/cfg/__init__.py @@ -48,19 +48,21 @@ CLI_HELP_MSG = \ """ # Define keys for arg type checks -CFG_FLOAT_KEYS = {'warmup_epochs', 'box', 'cls', 'dfl', 'degrees', 'shear', 'fl_gamma'} -CFG_FRACTION_KEYS = { - 'dropout', 'iou', 'lr0', 'lrf', 'momentum', 'weight_decay', 'warmup_momentum', 'warmup_bias_lr', 'label_smoothing', - 'hsv_h', 'hsv_s', 'hsv_v', 'translate', 'scale', 'perspective', 'flipud', 'fliplr', 'mosaic', 'mixup', 'copy_paste', - 'conf', 'iou'} # fractional floats limited to 0.0 - 1.0 -CFG_INT_KEYS = { - 'epochs', 'patience', 'batch', 'workers', 'seed', 'close_mosaic', 'mask_ratio', 'max_det', 'vid_stride', - 'line_thickness', 'workspace', 'nbs', 'save_period'} -CFG_BOOL_KEYS = { - 'save', 'exist_ok', 'pretrained', 'verbose', 'deterministic', 'single_cls', 'image_weights', 'rect', 'cos_lr', - 'overlap_mask', 'val', 'save_json', 'save_hybrid', 'half', 'dnn', 'plots', 'show', 'save_txt', 'save_conf', - 'save_crop', 'hide_labels', 'hide_conf', 'visualize', 'augment', 'agnostic_nms', 'retina_masks', 'boxes', 'keras', - 'optimize', 'int8', 'dynamic', 'simplify', 'nms', 'v5loader'} +CFG_FLOAT_KEYS = 'warmup_epochs', 'box', 'cls', 'dfl', 'degrees', 'shear', 'fl_gamma' +CFG_FRACTION_KEYS = ('dropout', 'iou', 'lr0', 'lrf', 'momentum', 'weight_decay', 'warmup_momentum', 'warmup_bias_lr', + 'label_smoothing', 'hsv_h', 'hsv_s', 'hsv_v', 'translate', 'scale', 'perspective', 'flipud', + 'fliplr', 'mosaic', 'mixup', 'copy_paste', 'conf', 'iou') # fractional floats limited to 0.0 - 1.0 +CFG_INT_KEYS = ('epochs', 'patience', 'batch', 'workers', 'seed', 'close_mosaic', 'mask_ratio', 'max_det', 'vid_stride', + 'line_thickness', 'workspace', 'nbs', 'save_period') +CFG_BOOL_KEYS = ('save', 'exist_ok', 'pretrained', 'verbose', 'deterministic', 'single_cls', 'image_weights', 'rect', + 'cos_lr', 'overlap_mask', 'val', 'save_json', 'save_hybrid', 'half', 'dnn', 'plots', 'show', + 'save_txt', 'save_conf', 'save_crop', 'hide_labels', 'hide_conf', 'visualize', 'augment', + 'agnostic_nms', 'retina_masks', 'boxes', 'keras', 'optimize', 'int8', 'dynamic', 'simplify', 'nms', + 'v5loader') + +# Define valid tasks and modes +TASKS = 'detect', 'segment', 'classify' +MODES = 'train', 'val', 'predict', 'export', 'track', 'benchmark' def cfg2dict(cfg): @@ -196,9 +198,6 @@ def entrypoint(debug=''): LOGGER.info(CLI_HELP_MSG) return - # Define tasks and modes - tasks = 'detect', 'segment', 'classify' - modes = 'train', 'val', 'predict', 'export', 'track', 'benchmark' special = { 'help': lambda: LOGGER.info(CLI_HELP_MSG), 'checks': checks.check_yolo, @@ -206,7 +205,7 @@ def entrypoint(debug=''): 'settings': lambda: yaml_print(USER_CONFIG_DIR / 'settings.yaml'), 'cfg': lambda: yaml_print(DEFAULT_CFG_PATH), 'copy-cfg': copy_default_cfg} - full_args_dict = {**DEFAULT_CFG_DICT, **{k: None for k in tasks}, **{k: None for k in modes}, **special} + full_args_dict = {**DEFAULT_CFG_DICT, **{k: None for k in TASKS}, **{k: None for k in MODES}, **special} # Define common mis-uses of special commands, i.e. -h, -help, --help special.update({k[0]: v for k, v in special.items()}) # singular @@ -240,9 +239,9 @@ def entrypoint(debug=''): except (NameError, SyntaxError, ValueError, AssertionError) as e: check_cfg_mismatch(full_args_dict, {a: ''}, e) - elif a in tasks: + elif a in TASKS: overrides['task'] = a - elif a in modes: + elif a in MODES: overrides['mode'] = a elif a in special: special[a]() @@ -262,10 +261,10 @@ def entrypoint(debug=''): mode = overrides.get('mode', None) if mode is None: mode = DEFAULT_CFG.mode or 'predict' - LOGGER.warning(f"WARNING ⚠️ 'mode' is missing. Valid modes are {modes}. Using default 'mode={mode}'.") - elif mode not in modes: + LOGGER.warning(f"WARNING ⚠️ 'mode' is missing. Valid modes are {MODES}. Using default 'mode={mode}'.") + elif mode not in MODES: if mode not in ('checks', checks): - raise ValueError(f"Invalid 'mode={mode}'. Valid modes are {modes}.\n{CLI_HELP_MSG}") + raise ValueError(f"Invalid 'mode={mode}'. Valid modes are {MODES}.\n{CLI_HELP_MSG}") LOGGER.warning("WARNING ⚠️ 'yolo mode=checks' is deprecated. Use 'yolo checks' instead.") checks.check_yolo() return @@ -280,11 +279,11 @@ def entrypoint(debug=''): model = YOLO(model) # Task - # if task and task != model.task: - # LOGGER.warning(f"WARNING ⚠️ 'task={task}' conflicts with {model.task} model {overrides['model']}. " - # f"Inheriting 'task={model.task}' from {overrides['model']} and ignoring 'task={task}'.") - overrides['task'] = overrides.get('task', model.task) - model.task = overrides['task'] + task = overrides.get('task', None) + if task is not None and task not in TASKS: + raise ValueError(f"Invalid 'task={task}'. Valid tasks are {TASKS}.\n{CLI_HELP_MSG}") + else: + model.task = task # Mode if mode in {'predict', 'track'} and 'source' not in overrides: diff --git a/ultralytics/yolo/engine/exporter.py b/ultralytics/yolo/engine/exporter.py index 242cecd..5eaf9a9 100644 --- a/ultralytics/yolo/engine/exporter.py +++ b/ultralytics/yolo/engine/exporter.py @@ -292,7 +292,10 @@ class Exporter: @try_export def _export_onnx(self, prefix=colorstr('ONNX:')): # YOLOv8 ONNX export - check_requirements('onnx>=1.12.0') + requirements = ['onnx>=1.12.0'] + if self.args.simplify: + requirements += ['onnxsim', 'onnxruntime-gpu' if torch.cuda.is_available() else 'onnxruntime'] + check_requirements(requirements) import onnx # noqa LOGGER.info(f'\n{prefix} starting export with onnx {onnx.__version__}...') @@ -326,7 +329,6 @@ class Exporter: # Simplify if self.args.simplify: try: - check_requirements(('onnxsim', 'onnxruntime-gpu' if torch.cuda.is_available() else 'onnxruntime')) import onnxsim LOGGER.info(f'{prefix} simplifying with onnxsim {onnxsim.__version__}...') @@ -508,9 +510,8 @@ class Exporter: try: import tensorflow as tf # noqa except ImportError: - check_requirements( - f"tensorflow{'-macos' if MACOS else '-aarch64' if ARM64 else '' if torch.cuda.is_available() else '-cpu'}" - ) + cuda = torch.cuda.is_available() + check_requirements(f"tensorflow{'-macos' if MACOS else '-aarch64' if ARM64 else '' if cuda else '-cpu'}") import tensorflow as tf # noqa check_requirements(('onnx', 'onnx2tf', 'sng4onnx', 'onnxsim', 'onnx_graphsurgeon', 'tflite_support', 'onnxruntime-gpu' if torch.cuda.is_available() else 'onnxruntime'), diff --git a/ultralytics/yolo/engine/model.py b/ultralytics/yolo/engine/model.py index c9620dc..585133c 100644 --- a/ultralytics/yolo/engine/model.py +++ b/ultralytics/yolo/engine/model.py @@ -64,7 +64,7 @@ class YOLO: Performs prediction using the YOLO model. Returns: - list[ultralytics.yolo.engine.results.Results]: The prediction results. + list(ultralytics.yolo.engine.results.Results): The prediction results. """ def __init__(self, model='yolov8n.pt') -> None: diff --git a/ultralytics/yolo/engine/results.py b/ultralytics/yolo/engine/results.py index 12ed3f3..0d77b05 100644 --- a/ultralytics/yolo/engine/results.py +++ b/ultralytics/yolo/engine/results.py @@ -111,14 +111,14 @@ class Results: Args: show_conf (bool): Whether to show the detection confidence score. - line_width (float, optional): The line width of the bounding boxes. If None, it is automatically scaled to the image size. - font_size (float, optional): The font size of the text. If None, it is automatically scaled to the image size. + line_width (float, optional): The line width of the bounding boxes. If None, it is scaled to the image size. + font_size (float, optional): The font size of the text. If None, it is scaled to the image size. font (str): The font to use for the text. pil (bool): Whether to return the image as a PIL Image. - example (str): An example string to display in the plot. Useful for indicating the expected format of the output. + example (str): An example string to display. Useful for indicating the expected format of the output. Returns: - None or PIL Image: If `pil` is True, the image will be returned as a PIL Image. Otherwise, nothing is returned. + (None) or (PIL.Image): If `pil` is True, a PIL Image is returned. Otherwise, nothing is returned. """ img = deepcopy(self.orig_img) annotator = Annotator(img, line_width, font_size, font, pil, example) @@ -284,7 +284,7 @@ class Masks: orig_shape (tuple): Original image size, in the format (height, width). Properties: - segments (list): A list of segments which includes x, y, w, h, label, confidence, and mask of each detection masks. + segments (list): A list of segments which includes x, y, w, h, label, confidence, and mask of each detection. Methods: cpu(): Returns a copy of the masks tensor on CPU memory. diff --git a/ultralytics/yolo/engine/trainer.py b/ultralytics/yolo/engine/trainer.py index 1dc38ff..263750b 100644 --- a/ultralytics/yolo/engine/trainer.py +++ b/ultralytics/yolo/engine/trainer.py @@ -181,7 +181,7 @@ class BaseTrainer: LOGGER.info(f'Running DDP command {cmd}') subprocess.run(cmd, check=True) except Exception as e: - LOGGER.warning(e) + raise e finally: ddp_cleanup(self, str(file)) else: diff --git a/ultralytics/yolo/engine/validator.py b/ultralytics/yolo/engine/validator.py index 3f1a5ec..efc59e5 100644 --- a/ultralytics/yolo/engine/validator.py +++ b/ultralytics/yolo/engine/validator.py @@ -63,7 +63,6 @@ class BaseValidator: dataloader (torch.utils.data.DataLoader): Dataloader to be used for validation. save_dir (Path): Directory to save results. pbar (tqdm.tqdm): Progress bar for displaying progress. - logger (logging.Logger): Logger to log messages. args (SimpleNamespace): Configuration for the validator. """ self.dataloader = dataloader diff --git a/ultralytics/yolo/utils/dist.py b/ultralytics/yolo/utils/dist.py index 9c91540..47ad6f7 100644 --- a/ultralytics/yolo/utils/dist.py +++ b/ultralytics/yolo/utils/dist.py @@ -24,8 +24,6 @@ def find_free_network_port() -> int: def generate_ddp_file(trainer): import_path = '.'.join(str(trainer.__class__).split('.')[1:-1]) - if not trainer.resume: - shutil.rmtree(trainer.save_dir) # remove the save_dir content = f'''cfg = {vars(trainer.args)} \nif __name__ == "__main__": from ultralytics.{import_path} import {trainer.__class__.__name__} @@ -43,16 +41,17 @@ def generate_ddp_file(trainer): def generate_ddp_command(world_size, trainer): - import __main__ # noqa local import to avoid https://github.com/Lightning-AI/lightning/issues/15218 - - # Get file and args (do not use sys.argv due to security vulnerability) - exclude_args = ['save_dir'] - args = [f'{k}={v}' for k, v in vars(trainer.args).items() if k not in exclude_args] - file = generate_ddp_file(trainer) # if argv[0].endswith('yolo') else os.path.abspath(argv[0]) - - # Build command + import __main__ # local import to avoid https://github.com/Lightning-AI/lightning/issues/15218 + file = os.path.abspath(sys.argv[0]) + using_cli = not file.endswith('.py') + if not trainer.resume: + shutil.rmtree(trainer.save_dir) # remove the save_dir + if using_cli: + file = generate_ddp_file(trainer) dist_cmd = 'torch.distributed.run' if TORCH_1_9 else 'torch.distributed.launch' port = find_free_network_port() + exclude_args = ['save_dir'] + args = [f'{k}={v}' for k, v in vars(trainer.args).items() if k not in exclude_args] cmd = [sys.executable, '-m', dist_cmd, '--nproc_per_node', f'{world_size}', '--master_port', f'{port}', file] + args return cmd, file