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Improvements (#142)
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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@ -73,7 +73,7 @@ from ultralytics.yolo.data.dataloaders.stream_loaders import LoadImages
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from ultralytics.yolo.data.utils import check_dataset
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from ultralytics.yolo.utils import DEFAULT_CONFIG, LOGGER, callbacks, colorstr, get_default_args, yaml_save
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from ultralytics.yolo.utils.checks import check_imgsz, check_requirements, check_version, check_yaml
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from ultralytics.yolo.utils.files import file_size, increment_path
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from ultralytics.yolo.utils.files import file_size
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from ultralytics.yolo.utils.ops import Profile
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from ultralytics.yolo.utils.torch_utils import guess_task_from_head, select_device, smart_inference_mode
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@ -138,10 +138,6 @@ class Exporter:
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if overrides is None:
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overrides = {}
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self.args = get_config(config, overrides)
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project = self.args.project or f"runs/{self.args.task}"
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name = self.args.name or "exp" # hardcode mode as export doesn't require it
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self.save_dir = increment_path(Path(project) / name, exist_ok=self.args.exist_ok)
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self.save_dir.mkdir(parents=True, exist_ok=True)
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self.callbacks = defaultdict(list, {k: [v] for k, v in callbacks.default_callbacks.items()}) # add callbacks
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callbacks.add_integration_callbacks(self)
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@ -35,7 +35,7 @@ from ultralytics.nn.autobackend import AutoBackend
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from ultralytics.yolo.configs import get_config
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from ultralytics.yolo.data.dataloaders.stream_loaders import LoadImages, LoadScreenshots, LoadStreams
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from ultralytics.yolo.data.utils import IMG_FORMATS, VID_FORMATS
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from ultralytics.yolo.utils import DEFAULT_CONFIG, LOGGER, callbacks, colorstr, ops
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from ultralytics.yolo.utils import DEFAULT_CONFIG, LOGGER, SETTINGS, callbacks, colorstr, ops
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from ultralytics.yolo.utils.checks import check_file, check_imgsz, check_imshow
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from ultralytics.yolo.utils.files import increment_path
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from ultralytics.yolo.utils.torch_utils import select_device, smart_inference_mode
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@ -73,7 +73,7 @@ class BasePredictor:
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if overrides is None:
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overrides = {}
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self.args = get_config(config, overrides)
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project = self.args.project or f"runs/{self.args.task}"
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project = self.args.project or Path(SETTINGS['runs_dir']) / self.args.task
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name = self.args.name or f"{self.args.mode}"
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self.save_dir = increment_path(Path(project) / name, exist_ok=self.args.exist_ok)
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(self.save_dir / 'labels' if self.args.save_txt else self.save_dir).mkdir(parents=True, exist_ok=True)
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@ -25,7 +25,8 @@ import ultralytics.yolo.utils as utils
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from ultralytics import __version__
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from ultralytics.yolo.configs import get_config
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from ultralytics.yolo.data.utils import check_dataset, check_dataset_yaml
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from ultralytics.yolo.utils import DEFAULT_CONFIG, LOGGER, RANK, TQDM_BAR_FORMAT, callbacks, colorstr, yaml_save
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from ultralytics.yolo.utils import (DEFAULT_CONFIG, LOGGER, RANK, SETTINGS, TQDM_BAR_FORMAT, callbacks, colorstr,
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yaml_save)
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from ultralytics.yolo.utils.checks import check_file, print_args
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from ultralytics.yolo.utils.dist import ddp_cleanup, generate_ddp_command
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from ultralytics.yolo.utils.files import get_latest_run, increment_path
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@ -88,7 +89,7 @@ class BaseTrainer:
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init_seeds(self.args.seed + 1 + RANK, deterministic=self.args.deterministic)
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# Dirs
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project = self.args.project or f"runs/{self.args.task}"
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project = self.args.project or Path(SETTINGS['runs_dir']) / self.args.task
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name = self.args.name or f"{self.args.mode}"
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self.save_dir = Path(
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self.args.get(
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@ -8,7 +8,7 @@ from tqdm import tqdm
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from ultralytics.nn.autobackend import AutoBackend
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from ultralytics.yolo.data.utils import check_dataset, check_dataset_yaml
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from ultralytics.yolo.utils import DEFAULT_CONFIG, LOGGER, RANK, TQDM_BAR_FORMAT, callbacks
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from ultralytics.yolo.utils import DEFAULT_CONFIG, LOGGER, RANK, SETTINGS, TQDM_BAR_FORMAT, callbacks
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from ultralytics.yolo.utils.checks import check_imgsz
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from ultralytics.yolo.utils.files import increment_path
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from ultralytics.yolo.utils.ops import Profile
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@ -59,7 +59,7 @@ class BaseValidator:
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self.speed = None
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self.jdict = None
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project = self.args.project or f"runs/{self.args.task}"
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project = self.args.project or Path(SETTINGS['runs_dir']) / self.args.task
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name = self.args.name or f"{self.args.mode}"
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self.save_dir = save_dir or increment_path(Path(project) / name,
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exist_ok=self.args.exist_ok if RANK in {-1, 0} else True)
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@ -18,7 +18,6 @@ FILE = Path(__file__).resolve()
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ROOT = FILE.parents[2] # YOLO
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DEFAULT_CONFIG = ROOT / "yolo/configs/default.yaml"
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RANK = int(os.getenv('RANK', -1))
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DATASETS_DIR = Path(os.getenv('YOLOv5_DATASETS_DIR', ROOT.parent / 'datasets')) # global datasets directory
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NUM_THREADS = min(8, max(1, os.cpu_count() - 1)) # number of YOLOv5 multiprocessing threads
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AUTOINSTALL = str(os.getenv('YOLOv5_AUTOINSTALL', True)).lower() == 'true' # global auto-install mode
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FONT = 'Arial.ttf' # https://ultralytics.com/assets/Arial.ttf
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@ -119,6 +118,41 @@ def is_docker() -> bool:
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return 'docker' in f.read()
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def is_git_directory() -> bool:
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"""
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Check if the current working directory is inside a git repository.
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Returns:
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bool: True if the current working directory is inside a git repository, False otherwise.
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"""
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from git import Repo
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try:
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# Check if the current working directory is a git repository
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Repo(search_parent_directories=True)
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return True
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except Exception:
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return False
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def is_pip_package(filepath: str = __name__) -> bool:
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"""
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Determines if the file at the given filepath is part of a pip package.
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Args:
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filepath (str): The filepath to check.
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Returns:
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bool: True if the file is part of a pip package, False otherwise.
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"""
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import importlib.util
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# Get the spec for the module
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spec = importlib.util.find_spec(filepath)
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# Return whether the spec is not None and the origin is not None (indicating it is a package)
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return spec is not None and spec.origin is not None
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def is_dir_writeable(dir_path: str) -> bool:
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"""
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Check if a directory is writeable.
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@ -305,10 +339,11 @@ def get_settings(file=USER_CONFIG_DIR / 'settings.yaml'):
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"""
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from ultralytics.yolo.utils.torch_utils import torch_distributed_zero_first
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git_install = not is_pip_package()
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defaults = {
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'datasets_dir': None, # default datasets directory. If None, current working directory is used.
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'weights_dir': None, # default weights directory. If None, current working directory is used.
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'runs_dir': None, # default runs directory. If None, current working directory is used.
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'datasets_dir': str(ROOT / 'datasets') if git_install else 'datasets', # default datasets directory.
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'weights_dir': str(ROOT / 'weights') if git_install else 'weights', # default weights directory.
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'runs_dir': str(ROOT / 'runs') if git_install else 'runs', # default runs directory.
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'sync': True, # sync analytics to help with YOLO development
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'uuid': uuid.getnode(), # device UUID to align analytics
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'yaml_file': str(file)} # setting YAML file path
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@ -336,6 +371,7 @@ if platform.system() == 'Windows':
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# Check first-install steps
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SETTINGS = get_settings()
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DATASETS_DIR = Path(SETTINGS['datasets_dir']) # global datasets directory
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def set_settings(kwargs, file=USER_CONFIG_DIR / 'settings.yaml'):
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@ -1,5 +1,6 @@
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import glob
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import inspect
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import math
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import platform
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import urllib
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from pathlib import Path
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@ -13,71 +14,141 @@ import torch
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from ultralytics.yolo.utils import (AUTOINSTALL, FONT, LOGGER, ROOT, USER_CONFIG_DIR, TryExcept, colorstr, emojis,
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is_docker, is_jupyter_notebook)
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from ultralytics.yolo.utils.ops import make_divisible
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def is_ascii(s=''):
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# Is string composed of all ASCII (no UTF) characters? (note str().isascii() introduced in python 3.7)
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s = str(s) # convert list, tuple, None, etc. to str
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return len(s.encode().decode('ascii', 'ignore')) == len(s)
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def is_ascii(s) -> bool:
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"""
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Check if a string is composed of only ASCII characters.
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Args:
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s (str): String to be checked.
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Returns:
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bool: True if the string is composed only of ASCII characters, False otherwise.
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"""
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# Convert list, tuple, None, etc. to string
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s = str(s)
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# Check if the string is composed of only ASCII characters
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return all(ord(c) < 128 for c in s)
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def check_imgsz(imgsz, stride=32, min_dim=1, floor=0):
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# Verify image size is a multiple of stride s in each dimension
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"""
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Verify image size is a multiple of the given stride in each dimension. If the image size is not a multiple of the
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stride, update it to the nearest multiple of the stride that is greater than or equal to the given floor value.
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Args:
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imgsz (int or List[int]): Image size.
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stride (int): Stride value.
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min_dim (int): Minimum number of dimensions.
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floor (int): Minimum allowed value for image size.
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Returns:
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List[int]: Updated image size.
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"""
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# Convert stride to integer if it is a tensor
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stride = int(stride.max() if isinstance(stride, torch.Tensor) else stride)
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if isinstance(imgsz, int): # integer i.e. imgsz=640
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sz = max(make_divisible(imgsz, stride), floor)
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else: # list i.e. imgsz=[640, 480]
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imgsz = list(imgsz) # convert to list if tuple
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sz = [max(make_divisible(x, stride), floor) for x in imgsz]
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# Convert image size to list if it is an integer
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if isinstance(imgsz, int):
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imgsz = [imgsz]
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# Make image size a multiple of the stride
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sz = [max(math.ceil(x / stride) * stride, floor) for x in imgsz]
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# Print warning message if image size was updated
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if sz != imgsz:
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LOGGER.warning(f'WARNING ⚠️ --img-size {imgsz} must be multiple of max stride {stride}, updating to {sz}')
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# Check dims
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if min_dim == 2:
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if isinstance(imgsz, int):
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sz = [sz, sz]
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elif len(sz) == 1:
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sz = [sz[0], sz[0]]
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# Add missing dimensions if necessary
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if min_dim == 2 and len(sz) == 1:
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sz = [sz[0], sz[0]]
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return sz
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def check_version(current="0.0.0", minimum="0.0.0", name="version ", pinned=False, hard=False, verbose=False):
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# Check version vs. required version
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current, minimum = (pkg.parse_version(x) for x in (current, minimum))
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def check_version(current: str = "0.0.0",
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minimum: str = "0.0.0",
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name: str = "version ",
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pinned: bool = False,
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hard: bool = False,
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verbose: bool = False) -> bool:
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"""
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Check current version against the required minimum version.
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Args:
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current (str): Current version.
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minimum (str): Required minimum version.
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name (str): Name to be used in warning message.
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pinned (bool): If True, versions must match exactly. If False, minimum version must be satisfied.
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hard (bool): If True, raise an AssertionError if the minimum version is not met.
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verbose (bool): If True, print warning message if minimum version is not met.
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Returns:
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bool: True if minimum version is met, False otherwise.
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"""
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from pkg_resources import parse_version
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current, minimum = (parse_version(x) for x in (current, minimum))
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result = (current == minimum) if pinned else (current >= minimum) # bool
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s = f"WARNING ⚠️ {name}{minimum} is required by YOLOv5, but {name}{current} is currently installed" # string
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warning_message = f"WARNING ⚠️ {name}{minimum} is required by YOLOv5, but {name}{current} is currently installed"
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if hard:
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assert result, emojis(s) # assert min requirements met
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assert result, emojis(warning_message) # assert min requirements met
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if verbose and not result:
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LOGGER.warning(s)
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LOGGER.warning(warning_message)
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return result
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def check_font(font=FONT, progress=False):
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# Download font to CONFIG_DIR if necessary
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def check_font(font: str = FONT, progress: bool = False) -> None:
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"""
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Download font file to the user's configuration directory if it does not already exist.
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Args:
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font (str): Path to font file.
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progress (bool): If True, display a progress bar during the download.
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Returns:
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None
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"""
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font = Path(font)
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# Destination path for the font file
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file = USER_CONFIG_DIR / font.name
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# Check if font file exists at the source or destination path
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if not font.exists() and not file.exists():
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# Download font file
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url = f'https://ultralytics.com/assets/{font.name}'
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LOGGER.info(f'Downloading {url} to {file}...')
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torch.hub.download_url_to_file(url, str(file), progress=progress)
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def check_online():
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# Check internet connectivity
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def check_online() -> bool:
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"""
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Check internet connectivity by attempting to connect to a known online host.
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Returns:
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bool: True if connection is successful, False otherwise.
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"""
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import socket
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try:
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socket.create_connection(("1.1.1.1", 443), 5) # check host accessibility
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# Check host accessibility by attempting to establish a connection
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socket.create_connection(("1.1.1.1", 443), timeout=5)
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return True
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except OSError:
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return False
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def check_python(minimum='3.7.0'):
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# Check current python version vs. required python version
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def check_python(minimum: str = '3.7.0') -> bool:
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"""
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Check current python version against the required minimum version.
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Args:
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minimum (str): Required minimum version of python.
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Returns:
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None
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"""
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check_version(platform.python_version(), minimum, name='Python ', hard=True)
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