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ultralytics 8.0.169TQDM, INTERP_LINEAR and RTDETR load_image() updates (#4704)

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Co-authored-by: Rustem Galiullin <rustemgal@gmail.com>
Co-authored-by: Rustem Galiullin <rustem.galiullin@bayanat.ai>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
This commit is contained in:
Glenn Jocher 2023-09-02 20:01:57 +02:00 • committed by GitHub
parent a4fabfdacf
commit 187b504d68
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23 changed files with 101 additions and 120 deletions
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19
ultralytics/utils/__init__.py
View file

@ -20,6 +20,7 @@ import matplotlib.pyplot as plt
import numpy as np
import torch
import yaml
from tqdm import tqdm as tqdm_original
from ultralytics import __version__
@ -35,7 +36,7 @@ DEFAULT_CFG_PATH = ROOT / 'cfg/default.yaml'
NUM_THREADS = min(8, max(1, os.cpu_count() - 1)) # number of YOLOv5 multiprocessing threads
AUTOINSTALL = str(os.getenv('YOLO_AUTOINSTALL', True)).lower() == 'true' # global auto-install mode
VERBOSE = str(os.getenv('YOLO_VERBOSE', True)).lower() == 'true' # global verbose mode
TQDM_BAR_FORMAT = '{l_bar}{bar:10}{r_bar}' # tqdm bar format
TQDM_BAR_FORMAT = '{l_bar}{bar:10}{r_bar}' if VERBOSE else None # tqdm bar format
LOGGING_NAME = 'ultralytics'
MACOS, LINUX, WINDOWS = (platform.system() == x for x in ['Darwin', 'Linux', 'Windows']) # environment booleans
ARM64 = platform.machine() in ('arm64', 'aarch64') # ARM64 booleans
@ -106,6 +107,22 @@ os.environ['CUBLAS_WORKSPACE_CONFIG'] = ':4096:8' # for deterministic training
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # suppress verbose TF compiler warnings in Colab
class TQDM(tqdm_original):
"""
Custom Ultralytics tqdm class with different default arguments.
Args:
(*args): Positional arguments passed to original tqdm.
(**kwargs): Keyword arguments, with custom defaults applied.
"""
def __init__(self, *args, **kwargs):
# Set new default values (these can still be overridden when calling TQDM)
kwargs['disable'] = not VERBOSE or kwargs.get('disable', False) # logical 'and' with default value if passed
kwargs.setdefault('bar_format', TQDM_BAR_FORMAT) # override default value if passed
super().__init__(*args, **kwargs)
class SimpleClass:
"""
Ultralytics SimpleClass is a base class providing helpful string representation, error reporting, and attribute

7
ultralytics/utils/benchmarks.py
View file

@ -32,12 +32,11 @@ from pathlib import Path
import numpy as np
import torch.cuda
from tqdm import tqdm
from ultralytics import YOLO
from ultralytics.cfg import TASK2DATA, TASK2METRIC
from ultralytics.engine.exporter import export_formats
from ultralytics.utils import ASSETS, LINUX, LOGGER, MACOS, SETTINGS
from ultralytics.utils import ASSETS, LINUX, LOGGER, MACOS, SETTINGS, TQDM
from ultralytics.utils.checks import check_requirements, check_yolo
from ultralytics.utils.files import file_size
from ultralytics.utils.torch_utils import select_device
@ -285,7 +284,7 @@ class ProfileModels:
# Timed runs
run_times = []
for _ in tqdm(range(num_runs), desc=engine_file):
for _ in TQDM(range(num_runs), desc=engine_file):
results = model(input_data, imgsz=self.imgsz, verbose=False)
run_times.append(results[0].speed['inference']) # Convert to milliseconds
@ -336,7 +335,7 @@ class ProfileModels:
# Timed runs
run_times = []
for _ in tqdm(range(num_runs), desc=onnx_file):
for _ in TQDM(range(num_runs), desc=onnx_file):
start_time = time.time()
sess.run([output_name], {input_name: input_data})
run_times.append((time.time() - start_time) * 1000) # Convert to milliseconds

1
ultralytics/utils/callbacks/clearml.py
View file

@ -9,6 +9,7 @@ try:
from clearml import Task
from clearml.binding.frameworks.pytorch_bind import PatchPyTorchModelIO
from clearml.binding.matplotlib_bind import PatchedMatplotlib
assert hasattr(clearml, '__version__') # verify package is not directory
except (ImportError, AssertionError):

1
ultralytics/utils/callbacks/mlflow.py
View file

@ -6,6 +6,7 @@ try:
assert not TESTS_RUNNING # do not log pytest
assert SETTINGS['mlflow'] is True # verify integration is enabled
import mlflow
assert hasattr(mlflow, '__version__') # verify package is not directory
import os

20
ultralytics/utils/downloads.py
View file

@ -11,9 +11,8 @@ from urllib import parse, request
import requests
import torch
from tqdm import tqdm
from ultralytics.utils import LOGGER, TQDM_BAR_FORMAT, checks, clean_url, emojis, is_online, url2file
from ultralytics.utils import LOGGER, TQDM, checks, clean_url, emojis, is_online, url2file
# Define Ultralytics GitHub assets maintained at https://github.com/ultralytics/assets
GITHUB_ASSETS_REPO = 'ultralytics/assets'
@ -101,11 +100,7 @@ def zip_directory(directory, compress=True, exclude=('.DS_Store', '__MACOSX'), p
zip_file = directory.with_suffix('.zip')
compression = ZIP_DEFLATED if compress else ZIP_STORED
with ZipFile(zip_file, 'w', compression) as f:
for file in tqdm(files_to_zip,
desc=f'Zipping {directory} to {zip_file}...',
unit='file',
disable=not progress,
bar_format=TQDM_BAR_FORMAT):
for file in TQDM(files_to_zip, desc=f'Zipping {directory} to {zip_file}...', unit='file', disable=not progress):
f.write(file, file.relative_to(directory))
return zip_file # return path to zip file
@ -163,11 +158,7 @@ def unzip_file(file, path=None, exclude=('.DS_Store', '__MACOSX'), exist_ok=Fals
LOGGER.warning(f'WARNING ⚠️ Skipping {file} unzip as destination directory {path} is not empty.')
return path
for f in tqdm(files,
desc=f'Unzipping {file} to {Path(path).resolve()}...',
unit='file',
disable=not progress,
bar_format=TQDM_BAR_FORMAT):
for f in TQDM(files, desc=f'Unzipping {file} to {Path(path).resolve()}...', unit='file', disable=not progress):
zipObj.extract(f, path=extract_path)
return path # return unzip dir
@ -297,13 +288,12 @@ def safe_download(url,
if method == 'torch':
torch.hub.download_url_to_file(url, f, progress=progress)
else:
with request.urlopen(url) as response, tqdm(total=int(response.getheader('Content-Length', 0)),
with request.urlopen(url) as response, TQDM(total=int(response.getheader('Content-Length', 0)),
desc=desc,
disable=not progress,
unit='B',
unit_scale=True,
unit_divisor=1024,
bar_format=TQDM_BAR_FORMAT) as pbar:
unit_divisor=1024) as pbar:
with open(f, 'wb') as f_opened:
for data in response:
f_opened.write(data)