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ultralytics 8.0.51 add assets and CI actions (#1296)

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Paul Kehrer <paulhkehrer@gmail.com>
This commit is contained in:
Glenn Jocher
2023-03-07 20:25:10 +01:00
committed by GitHub
parent f0d8e4718b
commit 790f9c067c
21 changed files with 272 additions and 107 deletions
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2
ultralytics/yolo/cfg/__init__.py
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@ -327,4 +327,4 @@ def copy_default_cfg():
if __name__ == '__main__':
# entrypoint(debug='yolo predict model=yolov8n.pt')
entrypoint(debug='yolo train model=yolov8n-seg.pt')
entrypoint(debug='')

9
ultralytics/yolo/data/utils.py
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@ -210,8 +210,7 @@ def check_det_dataset(dataset, autodownload=True):
for k in 'train', 'val', 'names':
if k not in data:
raise SyntaxError(
emojis(f"{dataset} '{k}:' key missing ❌.\n"
f"'train', 'val' and 'names' are required in data.yaml files."))
emojis(f"{dataset} '{k}:' key missing ❌.\n'train', 'val' and 'names' are required in all data YAMLs."))
data['names'] = check_class_names(data['names'])
data['nc'] = len(data['names'])
@ -236,11 +235,11 @@ def check_det_dataset(dataset, autodownload=True):
if val:
val = [Path(x).resolve() for x in (val if isinstance(val, list) else [val])] # val path
if not all(x.exists() for x in val):
msg = f"\nDataset '{dataset}' not found ⚠️, missing paths %s" % [str(x) for x in val if not x.exists()]
m = f"\nDataset '{dataset}' images not found ⚠️, missing paths %s" % [str(x) for x in val if not x.exists()]
if s and autodownload:
LOGGER.warning(msg)
LOGGER.warning(m)
else:
raise FileNotFoundError(msg)
raise FileNotFoundError(m)
t = time.time()
if s.startswith('http') and s.endswith('.zip'): # URL
safe_download(url=s, dir=DATASETS_DIR, delete=True)

4
ultralytics/yolo/engine/exporter.py
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@ -69,7 +69,7 @@ from ultralytics.yolo.data.dataloaders.stream_loaders import LoadImages
from ultralytics.yolo.data.utils import IMAGENET_MEAN, IMAGENET_STD, check_det_dataset
from ultralytics.yolo.utils import (DEFAULT_CFG, LINUX, LOGGER, MACOS, __version__, callbacks, colorstr,
get_default_args, yaml_save)
from ultralytics.yolo.utils.checks import check_imgsz, check_requirements, check_version, check_yaml
from ultralytics.yolo.utils.checks import check_imgsz, check_requirements, check_version
from ultralytics.yolo.utils.files import file_size
from ultralytics.yolo.utils.ops import Profile
from ultralytics.yolo.utils.torch_utils import get_latest_opset, select_device, smart_inference_mode
@ -601,7 +601,7 @@ class Exporter:
if n >= n_images:
break
dataset = LoadImages(check_det_dataset(check_yaml(self.args.data))['train'], imgsz=imgsz, auto=False)
dataset = LoadImages(check_det_dataset(self.args.data)['train'], imgsz=imgsz, auto=False)
converter.representative_dataset = lambda: representative_dataset_gen(dataset, n_images=100)
converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS_INT8]
converter.target_spec.supported_types = []

4
ultralytics/yolo/engine/model.py
View File

@ -10,7 +10,7 @@ from ultralytics.yolo.cfg import get_cfg
from ultralytics.yolo.engine.exporter import Exporter
from ultralytics.yolo.utils import (DEFAULT_CFG, DEFAULT_CFG_DICT, DEFAULT_CFG_KEYS, LOGGER, ONLINE, RANK, ROOT,
callbacks, is_git_dir, is_pip_package, yaml_load)
from ultralytics.yolo.utils.checks import check_file, check_imgsz, check_pip_update, check_yaml
from ultralytics.yolo.utils.checks import check_file, check_imgsz, check_pip_update_available, check_yaml
from ultralytics.yolo.utils.downloads import GITHUB_ASSET_STEMS
from ultralytics.yolo.utils.torch_utils import smart_inference_mode
@ -158,7 +158,7 @@ class YOLO:
Inform user of ultralytics package update availability
"""
if ONLINE and is_pip_package():
check_pip_update()
check_pip_update_available()
def reset(self):
"""

14
ultralytics/yolo/engine/results.py
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@ -263,8 +263,11 @@ class Boxes:
return self.boxes.__str__()
def __repr__(self):
return (f'Ultralytics YOLO {self.__class__.__name__}\n' + f'type: {type(self.boxes)}\n' +
f'shape: {self.boxes.shape}\n' + f'dtype: {self.boxes.dtype}\n + {self.boxes.__repr__()}')
return (f'{self.__class__.__module__}.{self.__class__.__name__}\n'
f'type: {self.boxes.__class__.__module__}.{self.boxes.__class__.__name__}\n'
f'shape: {self.boxes.shape}\n'
f'dtype: {self.boxes.dtype}\n'
f'{self.boxes.__repr__()}')
def __getitem__(self, idx):
return Boxes(self.boxes[idx], self.orig_shape)
@ -339,8 +342,11 @@ class Masks:
return self.masks.__str__()
def __repr__(self):
return (f'Ultralytics YOLO {self.__class__.__name__}\n' + f'type: {type(self.masks)}\n' +
f'shape: {self.masks.shape}\n' + f'dtype: {self.masks.dtype}\n + {self.masks.__repr__()}')
return (f'{self.__class__.__module__}.{self.__class__.__name__}\n'
f'type: {self.masks.__class__.__module__}.{self.masks.__class__.__name__}\n'
f'shape: {self.masks.shape}\n'
f'dtype: {self.masks.dtype}\n'
f'{self.masks.__repr__()}')
def __getitem__(self, idx):
return Masks(self.masks[idx], self.orig_shape)

80
ultralytics/yolo/utils/__init__.py
View File

@ -126,6 +126,37 @@ class IterableSimpleNamespace(SimpleNamespace):
return getattr(self, key, default)
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 logger
set_logging(LOGGING_NAME, verbose=VERBOSE) # run before defining LOGGER
LOGGER = logging.getLogger(LOGGING_NAME) # define globally (used in train.py, val.py, detect.py, etc.)
if WINDOWS: # emoji-safe logging
info_fn, warning_fn = LOGGER.info, LOGGER.warning
setattr(LOGGER, info_fn.__name__, lambda x: info_fn(emojis(x)))
setattr(LOGGER, warning_fn.__name__, lambda x: warning_fn(emojis(x)))
def yaml_save(file='data.yaml', data=None):
"""
Save YAML data to a file.
@ -163,10 +194,13 @@ def yaml_load(file='data.yaml', append_filename=False):
dict: YAML data and file name.
"""
with open(file, errors='ignore', encoding='utf-8') as f:
# Add YAML filename to dict and return
s = f.read() # string
if not s.isprintable(): # remove special characters
# Remove special characters
if not s.isprintable():
s = re.sub(r'[^\x09\x0A\x0D\x20-\x7E\x85\xA0-\uD7FF\uE000-\uFFFD\U00010000-\U0010ffff]+', '', s)
# Add YAML filename to dict and return
return {**yaml.safe_load(s), 'yaml_file': str(file)} if append_filename else yaml.safe_load(s)
@ -448,41 +482,6 @@ def colorstr(*input):
return ''.join(colors[x] for x in args) + f'{string}' + colors['end']
def remove_ansi_codes(string):
"""
Remove ANSI escape sequences from a string.
Args:
string (str): The input string that may contain ANSI escape sequences.
Returns:
str: The input string with ANSI escape sequences removed.
"""
return re.sub(r'\x1B\[([0-9]{1,2}(;[0-9]{1,2})?)?[m|K]', '', string)
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}}})
class TryExcept(contextlib.ContextDecorator):
# YOLOv8 TryExcept class. Usage: @TryExcept() decorator or 'with TryExcept():' context manager
def __init__(self, msg='', verbose=True):
@ -609,13 +608,6 @@ def set_settings(kwargs, file=USER_CONFIG_DIR / 'settings.yaml'):
# Run below code on yolo/utils init ------------------------------------------------------------------------------------
# Set logger
set_logging(LOGGING_NAME, verbose=VERBOSE) # run before defining LOGGER
LOGGER = logging.getLogger(LOGGING_NAME) # define globally (used in train.py, val.py, detect.py, etc.)
if WINDOWS:
for fn in LOGGER.info, LOGGER.warning:
setattr(LOGGER, fn.__name__, lambda x: fn(emojis(x))) # emoji safe logging
# Check first-install steps
PREFIX = colorstr('Ultralytics: ')
SETTINGS = get_settings()

12
ultralytics/yolo/utils/checks.py
View File

@ -134,12 +134,20 @@ def check_latest_pypi_version(package_name='ultralytics'):
return None
def check_pip_update():
def check_pip_update_available():
"""
Checks if a new version of the ultralytics package is available on PyPI.
Returns:
bool: True if an update is available, False otherwise.
"""
from ultralytics import __version__
latest = check_latest_pypi_version()
if pkg.parse_version(__version__) < pkg.parse_version(latest):
if pkg.parse_version(__version__) < pkg.parse_version(latest): # update is available
LOGGER.info(f'New https://pypi.org/project/ultralytics/{latest} available 😃 '
f"Update with 'pip install -U ultralytics'")
return True
return False
def check_font(font='Arial.ttf'):

3
ultralytics/yolo/utils/plotting.py
View File

@ -9,7 +9,6 @@ import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sn
import torch
from PIL import Image, ImageDraw, ImageFont
from PIL import __version__ as pil_version
@ -161,6 +160,8 @@ class Annotator:
@TryExcept() # known issue https://github.com/ultralytics/yolov5/issues/5395
def plot_labels(boxes, cls, names=(), save_dir=Path('')):
import seaborn as sn
# plot dataset labels
LOGGER.info(f"Plotting labels to {save_dir / 'labels.jpg'}... ")
b = boxes.transpose() # classes, boxes