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import contextlib
import logging.config
import os
import platform
import sys
import threading
from pathlib import Path
import cv2
import IPython
import pandas as pd
# Constants
FILE = Path(__file__).resolve()
ROOT = FILE.parents[2] # YOLO
RANK = int(os.getenv('RANK', -1))
DATASETS_DIR = Path(os.getenv('YOLOv5_DATASETS_DIR', ROOT.parent / 'datasets')) # global datasets directory
NUM_THREADS = min(8, max(1, os.cpu_count() - 1)) # number of YOLOv5 multiprocessing threads
AUTOINSTALL = str(os.getenv('YOLOv5_AUTOINSTALL', True)).lower() == 'true' # global auto-install mode
FONT = 'Arial.ttf' # https://ultralytics.com/assets/Arial.ttf
VERBOSE = str(os.getenv('YOLOv5_VERBOSE', True)).lower() == 'true' # global verbose mode
TQDM_BAR_FORMAT = '{l_bar}{bar:10}{r_bar}' # tqdm bar format
LOGGING_NAME = 'yolov5'
# Settings
# torch.set_printoptions(linewidth=320, precision=5, profile='long')
# np.set_printoptions(linewidth=320, formatter={'float_kind': '{:11.5g}'.format}) # format short g, %precision=5
pd.options.display.max_columns = 10
cv2.setNumThreads(0) # prevent OpenCV from multithreading (incompatible with PyTorch DataLoader)
os.environ['NUMEXPR_MAX_THREADS'] = str(NUM_THREADS) # NumExpr max threads
os.environ['OMP_NUM_THREADS'] = '1' if platform.system() == 'darwin' else str(NUM_THREADS) # OpenMP (PyTorch and SciPy)
def is_colab():
# Is environment a Google Colab instance?
return 'google.colab' in sys.modules
def is_kaggle():
# Is environment a Kaggle Notebook?
return os.environ.get('PWD') == '/kaggle/working' and os.environ.get('KAGGLE_URL_BASE') == 'https://www.kaggle.com'
def is_notebook():
# Is environment a Jupyter notebook? Verified on Colab, Jupyterlab, Kaggle, Paperspace
ipython_type = str(type(IPython.get_ipython()))
return 'colab' in ipython_type or 'zmqshell' in ipython_type
def is_docker() -> bool:
"""Check if the process runs inside a docker container."""
if Path("/.dockerenv").exists():
return True
try: # check if docker is in control groups
with open("/proc/self/cgroup") as file:
return any("docker" in line for line in file)
except OSError:
return False
def is_writeable(dir, test=False):
# Return True if directory has write permissions, test opening a file with write permissions if test=True
if not test:
return os.access(dir, os.W_OK) # possible issues on Windows
file = Path(dir) / 'tmp.txt'
try:
with open(file, 'w'): # open file with write permissions
pass
file.unlink() # remove file
return True
except OSError:
return False
def user_config_dir(dir='Ultralytics', env_var='YOLOV5_CONFIG_DIR'):
# Return path of user configuration directory. Prefer environment variable if exists. Make dir if required.
env = os.getenv(env_var)
if env:
path = Path(env) # use environment variable
else:
cfg = {'Windows': 'AppData/Roaming', 'Linux': '.config', 'Darwin': 'Library/Application Support'} # 3 OS dirs
path = Path.home() / cfg.get(platform.system(), '') # OS-specific config dir
path = (path if is_writeable(path) else Path('/tmp')) / dir # GCP and AWS lambda fix, only /tmp is writeable
path.mkdir(exist_ok=True) # make if required
return path
USER_CONFIG_DIR = user_config_dir() # Ultralytics settings dir
def emojis(str=''):
# Return platform-dependent emoji-safe version of string
return str.encode().decode('ascii', 'ignore') if platform.system() == 'Windows' else str
def colorstr(*input):
# Colors a string https://en.wikipedia.org/wiki/ANSI_escape_code, i.e. colorstr('blue', 'hello world')
*args, string = input if len(input) > 1 else ("blue", "bold", input[0]) # color arguments, string
colors = {
"black": "\033[30m", # basic colors
"red": "\033[31m",
"green": "\033[32m",
"yellow": "\033[33m",
"blue": "\033[34m",
"magenta": "\033[35m",
"cyan": "\033[36m",
"white": "\033[37m",
"bright_black": "\033[90m", # bright colors
"bright_red": "\033[91m",
"bright_green": "\033[92m",
"bright_yellow": "\033[93m",
"bright_blue": "\033[94m",
"bright_magenta": "\033[95m",
"bright_cyan": "\033[96m",
"bright_white": "\033[97m",
"end": "\033[0m", # misc
"bold": "\033[1m",
"underline": "\033[4m",}
return "".join(colors[x] for x in args) + f"{string}" + colors["end"]
def set_logging(name=LOGGING_NAME, verbose=True):
# sets up logging for the given name
rank = int(os.getenv('RANK', -1)) # rank in world for Multi-GPU trainings
level = logging.INFO if verbose and rank in {-1, 0} else logging.ERROR
logging.config.dictConfig({
"version": 1,
"disable_existing_loggers": False,
"formatters": {
name: {
"format": "%(message)s"}},
"handlers": {
name: {
"class": "logging.StreamHandler",
"formatter": name,
"level": level,}},
"loggers": {
name: {
"level": level,
"handlers": [name],
"propagate": False,}}})
set_logging(LOGGING_NAME) # run before defining LOGGER
LOGGER = logging.getLogger(LOGGING_NAME) # define globally (used in train.py, val.py, detect.py, etc.)
if platform.system() == 'Windows':
for fn in LOGGER.info, LOGGER.warning:
setattr(LOGGER, fn.__name__, lambda x: fn(emojis(x))) # emoji safe logging
class TryExcept(contextlib.ContextDecorator):
# YOLOv5 TryExcept class. Usage: @TryExcept() decorator or 'with TryExcept():' context manager
def __init__(self, msg=''):
self.msg = msg
def __enter__(self):
pass
def __exit__(self, exc_type, value, traceback):
if value:
print(emojis(f"{self.msg}{': ' if self.msg else ''}{value}"))
return True
def threaded(func):
# Multi-threads a target function and returns thread. Usage: @threaded decorator
def wrapper(*args, **kwargs):
thread = threading.Thread(target=func, args=args, kwargs=kwargs, daemon=True)
thread.start()
return thread
return wrapper