forked from ultralytics/yolov5
-
Notifications
You must be signed in to change notification settings - Fork 0
/
pyproject.toml
147 lines (133 loc) Β· 5.25 KB
/
pyproject.toml
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
# Ultralytics YOLOv5 π, AGPL-3.0 license
# Overview:
# This pyproject.toml file manages the build, packaging, and distribution of the Ultralytics library.
# It defines essential project metadata, dependencies, and settings used to develop and deploy the library.
# Key Sections:
# - [build-system]: Specifies the build requirements and backend (e.g., setuptools, wheel).
# - [project]: Includes details like name, version, description, authors, dependencies and more.
# - [project.optional-dependencies]: Provides additional, optional packages for extended features.
# - [tool.*]: Configures settings for various tools (pytest, yapf, etc.) used in the project.
# Installation:
# The Ultralytics library can be installed using the command: 'pip install ultralytics'
# For development purposes, you can install the package in editable mode with: 'pip install -e .'
# This approach allows for real-time code modifications without the need for re-installation.
# Documentation:
# For comprehensive documentation and usage instructions, visit: https://docs.ultralytics.com
[build-system]
requires = ["setuptools>=43.0.0", "wheel"]
build-backend = "setuptools.build_meta"
# Project settings -----------------------------------------------------------------------------------------------------
[project]
version = "7.0.0"
name = "YOLOv5"
description = "Ultralytics YOLOv5 for SOTA object detection, instance segmentation and image classification."
readme = "README.md"
requires-python = ">=3.8"
license = { "text" = "AGPL-3.0" }
keywords = ["machine-learning", "deep-learning", "computer-vision", "ML", "DL", "AI", "YOLO", "YOLOv3", "YOLOv5", "YOLOv8", "HUB", "Ultralytics"]
authors = [
{ name = "Glenn Jocher" },
{ name = "Ayush Chaurasia" },
{ name = "Jing Qiu" }
]
maintainers = [
{ name = "Glenn Jocher" },
{ name = "Ayush Chaurasia" },
{ name = "Jing Qiu" }
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"Intended Audience :: Education",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Topic :: Software Development",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
"Topic :: Scientific/Engineering :: Image Recognition",
"Operating System :: POSIX :: Linux",
"Operating System :: MacOS",
"Operating System :: Microsoft :: Windows",
]
# Required dependencies ------------------------------------------------------------------------------------------------
dependencies = [
"matplotlib>=3.3.0",
"numpy>=1.22.2",
"opencv-python>=4.6.0",
"pillow>=7.1.2",
"pyyaml>=5.3.1",
"requests>=2.23.0",
"scipy>=1.4.1",
"torch>=1.8.0",
"torchvision>=0.9.0",
"tqdm>=4.64.0", # progress bars
"psutil", # system utilization
"py-cpuinfo", # display CPU info
"thop>=0.1.1", # FLOPs computation
"pandas>=1.1.4",
"seaborn>=0.11.0", # plotting
"ultralytics>=8.1.47"
]
# Optional dependencies ------------------------------------------------------------------------------------------------
[project.optional-dependencies]
dev = [
"ipython",
"check-manifest",
"pre-commit",
"pytest",
"pytest-cov",
"coverage[toml]",
"mkdocs-material",
"mkdocstrings[python]",
"mkdocs-redirects", # for 301 redirects
"mkdocs-ultralytics-plugin>=0.0.34", # for meta descriptions and images, dates and authors
]
export = [
"onnx>=1.12.0", # ONNX export
"coremltools>=7.0; platform_system != 'Windows'", # CoreML only supported on macOS and Linux
"openvino-dev>=2023.0", # OpenVINO export
"tensorflow>=2.0.0", # TF bug https://github.com/ultralytics/ultralytics/issues/5161
"tensorflowjs>=3.9.0", # TF.js export, automatically installs tensorflow
]
# tensorflow>=2.4.1,<=2.13.1 # TF exports (-cpu, -aarch64, -macos)
# tflite-support # for TFLite model metadata
# scikit-learn==0.19.2 # CoreML quantization
# nvidia-pyindex # TensorRT export
# nvidia-tensorrt # TensorRT export
logging = [
"comet", # https://docs.ultralytics.com/integrations/comet/
"tensorboard>=2.13.0",
"dvclive>=2.12.0",
]
extra = [
"ipython", # interactive notebook
"albumentations>=1.0.3", # training augmentations
"pycocotools>=2.0.6", # COCO mAP
]
[project.urls]
"Bug Reports" = "https://github.com/ultralytics/yolov5/issues"
"Funding" = "https://ultralytics.com"
"Source" = "https://github.com/ultralytics/yolov5/"
# Tools settings -------------------------------------------------------------------------------------------------------
[tool.pytest]
norecursedirs = [".git", "dist", "build"]
addopts = "--doctest-modules --durations=30 --color=yes"
[tool.isort]
line_length = 120
multi_line_output = 0
[tool.ruff]
line-length = 120
[tool.docformatter]
wrap-summaries = 120
wrap-descriptions = 120
in-place = true
pre-summary-newline = true
close-quotes-on-newline = true
[tool.codespell]
ignore-words-list = "crate,nd,strack,dota,ane,segway,fo,gool,winn,commend"
skip = '*.csv,*venv*,docs/??/,docs/mkdocs_??.yml'