Update LICENSE to AGPL-3.0 (#2031)

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Glenn Jocher 2 years ago committed by GitHub
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      LICENSE
  13. 4
      README.md
  14. 4
      README.zh-CN.md
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  24. 2
      ultralytics/__init__.py
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      ultralytics/datasets/Argoverse.yaml
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      ultralytics/datasets/coco-pose.yaml
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      ultralytics/hub/__init__.py
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      ultralytics/models/v3/yolov3-spp.yaml
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      ultralytics/models/v5/yolov5.yaml
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      ultralytics/models/v8/yolov8-cls.yaml
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      ultralytics/models/v8/yolov8-p2.yaml
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      ultralytics/models/v8/yolov8-pose-p6.yaml
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      ultralytics/models/v8/yolov8-pose.yaml
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      ultralytics/nn/autoshape.py
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      ultralytics/tracker/trackers/bot_sort.py
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      ultralytics/tracker/utils/gmc.py
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      ultralytics/tracker/utils/kalman_filter.py
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      ultralytics/yolo/cfg/__init__.py
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      ultralytics/yolo/data/dataloaders/v5augmentations.py
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      ultralytics/yolo/data/dataloaders/v5loader.py
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      ultralytics/yolo/data/dataset.py
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      ultralytics/yolo/data/dataset_wrappers.py
  83. 2
      ultralytics/yolo/data/scripts/download_weights.sh
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      ultralytics/yolo/data/scripts/get_coco.sh
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      ultralytics/yolo/data/scripts/get_imagenet.sh
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      ultralytics/yolo/engine/model.py
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      ultralytics/yolo/engine/validator.py
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      ultralytics/yolo/utils/__init__.py
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      ultralytics/yolo/utils/autobatch.py
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      ultralytics/yolo/utils/benchmarks.py
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      ultralytics/yolo/utils/callbacks/base.py
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      ultralytics/yolo/utils/callbacks/clearml.py
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      ultralytics/yolo/utils/callbacks/comet.py
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      ultralytics/yolo/utils/callbacks/hub.py
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@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# README translation action to translate README.md to Chinese as README.zh-CN.md on any change to README.md # README translation action to translate README.md to Chinese as README.zh-CN.md on any change to README.md
name: Translate README name: Translate README

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLO Continuous Integration (CI) GitHub Actions tests # YOLO Continuous Integration (CI) GitHub Actions tests
name: Ultralytics CI name: Ultralytics CI

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
name: CLA Assistant name: CLA Assistant
on: on:

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Builds ultralytics/ultralytics:latest images on DockerHub https://hub.docker.com/r/ultralytics # Builds ultralytics/ultralytics:latest images on DockerHub https://hub.docker.com/r/ultralytics
name: Publish Docker Images name: Publish Docker Images

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
name: Greetings name: Greetings

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLO Continuous Integration (CI) GitHub Actions tests # YOLO Continuous Integration (CI) GitHub Actions tests
name: Check Broken links name: Check Broken links

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Publish pip package to PyPI https://pypi.org/project/ultralytics/ and Docs to https://docs.ultralytics.com # Publish pip package to PyPI https://pypi.org/project/ultralytics/ and Docs to https://docs.ultralytics.com
name: Publish to PyPI and Deploy Docs name: Publish to PyPI and Deploy Docs

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
name: Close stale issues name: Close stale issues
on: on:

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Pre-commit hooks. For more information see https://github.com/pre-commit/pre-commit-hooks/blob/main/README.md # Pre-commit hooks. For more information see https://github.com/pre-commit/pre-commit-hooks/blob/main/README.md
exclude: 'docs/' exclude: 'docs/'

@ -16,5 +16,5 @@ preferred-citation:
version: 8.0.0 version: 8.0.0
# doi: 10.5281/zenodo.3908559 # TODO # doi: 10.5281/zenodo.3908559 # TODO
date-released: 2023-1-10 date-released: 2023-1-10
license: GPL-3.0 license: AGPL-3.0
url: "https://github.com/ultralytics/ultralytics" url: "https://github.com/ultralytics/ultralytics"

@ -112,4 +112,4 @@ understand and diagnose your problem.
## License ## License
By contributing, you agree that your contributions will be licensed under By contributing, you agree that your contributions will be licensed under
the [GPL-3.0 license](https://choosealicense.com/licenses/gpl-3.0/) the [AGPL-3.0 license](https://choosealicense.com/licenses/agpl-3.0/)

@ -1,5 +1,5 @@
GNU GENERAL PUBLIC LICENSE GNU AFFERO GENERAL PUBLIC LICENSE
Version 3, 29 June 2007 Version 3, 19 November 2007
Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/> Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
Everyone is permitted to copy and distribute verbatim copies Everyone is permitted to copy and distribute verbatim copies
@ -7,17 +7,15 @@
Preamble Preamble
The GNU General Public License is a free, copyleft license for The GNU Affero General Public License is a free, copyleft license for
software and other kinds of works. software and other kinds of works, specifically designed to ensure
cooperation with the community in the case of network server software.
The licenses for most software and other practical works are designed The licenses for most software and other practical works are designed
to take away your freedom to share and change the works. By contrast, to take away your freedom to share and change the works. By contrast,
the GNU General Public License is intended to guarantee your freedom to our General Public Licenses are intended to guarantee your freedom to
share and change all versions of a program--to make sure it remains free share and change all versions of a program--to make sure it remains free
software for all its users. We, the Free Software Foundation, use the software for all its users.
GNU General Public License for most of our software; it applies also to
any other work released this way by its authors. You can apply it to
your programs, too.
When we speak of free software, we are referring to freedom, not When we speak of free software, we are referring to freedom, not
price. Our General Public Licenses are designed to make sure that you price. Our General Public Licenses are designed to make sure that you
@ -26,44 +24,34 @@ them if you wish), that you receive source code or can get it if you
want it, that you can change the software or use pieces of it in new want it, that you can change the software or use pieces of it in new
free programs, and that you know you can do these things. free programs, and that you know you can do these things.
To protect your rights, we need to prevent others from denying you Developers that use our General Public Licenses protect your rights
these rights or asking you to surrender the rights. Therefore, you have with two steps: (1) assert copyright on the software, and (2) offer
certain responsibilities if you distribute copies of the software, or if you this License which gives you legal permission to copy, distribute
you modify it: responsibilities to respect the freedom of others. and/or modify the software.
For example, if you distribute copies of such a program, whether A secondary benefit of defending all users' freedom is that
gratis or for a fee, you must pass on to the recipients the same improvements made in alternate versions of the program, if they
freedoms that you received. You must make sure that they, too, receive receive widespread use, become available for other developers to
or can get the source code. And you must show them these terms so they incorporate. Many developers of free software are heartened and
know their rights. encouraged by the resulting cooperation. However, in the case of
software used on network servers, this result may fail to come about.
Developers that use the GNU GPL protect your rights with two steps: The GNU General Public License permits making a modified version and
(1) assert copyright on the software, and (2) offer you this License letting the public access it on a server without ever releasing its
giving you legal permission to copy, distribute and/or modify it. source code to the public.
For the developers' and authors' protection, the GPL clearly explains The GNU Affero General Public License is designed specifically to
that there is no warranty for this free software. For both users' and ensure that, in such cases, the modified source code becomes available
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a publicly accessible server, gives the public access to the source
Some devices are designed to deny users access to install or run code of the modified version.
modified versions of the software inside them, although the manufacturer
can do so. This is fundamentally incompatible with the aim of An older license, called the Affero General Public License and
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pattern of such abuse occurs in the area of products for individuals to a different license, not a version of the Affero GPL, but Affero has
use, which is precisely where it is most unacceptable. Therefore, we released a new version of the Affero GPL which permits relicensing under
have designed this version of the GPL to prohibit the practice for those this license.
products. If such problems arise substantially in other domains, we
stand ready to extend this provision to those domains in future versions
of the GPL, as needed to protect the freedom of users.
Finally, every program is threatened constantly by software patents.
States should not allow patents to restrict development and use of
software on general-purpose computers, but in those that do, we wish to
avoid the special danger that patents applied to a free program could
make it effectively proprietary. To prevent this, the GPL assures that
patents cannot be used to render the program non-free.
The precise terms and conditions for copying, distribution and The precise terms and conditions for copying, distribution and
modification follow. modification follow.
@ -72,7 +60,7 @@ modification follow.
0. Definitions. 0. Definitions.
"This License" refers to version 3 of the GNU General Public License. "This License" refers to version 3 of the GNU Affero General Public License.
"Copyright" also means copyright-like laws that apply to other kinds of "Copyright" also means copyright-like laws that apply to other kinds of
works, such as semiconductor masks. works, such as semiconductor masks.
@ -549,35 +537,45 @@ to collect a royalty for further conveying from those to whom you convey
the Program, the only way you could satisfy both those terms and this the Program, the only way you could satisfy both those terms and this
License would be to refrain entirely from conveying the Program. License would be to refrain entirely from conveying the Program.
13. Use with the GNU Affero General Public License. 13. Remote Network Interaction; Use with the GNU General Public License.
Notwithstanding any other provision of this License, if you modify the
Program, your modified version must prominently offer all users
interacting with it remotely through a computer network (if your version
supports such interaction) an opportunity to receive the Corresponding
Source of your version by providing access to the Corresponding Source
from a network server at no charge, through some standard or customary
means of facilitating copying of software. This Corresponding Source
shall include the Corresponding Source for any work covered by version 3
of the GNU General Public License that is incorporated pursuant to the
following paragraph.
Notwithstanding any other provision of this License, you have Notwithstanding any other provision of this License, you have
permission to link or combine any covered work with a work licensed permission to link or combine any covered work with a work licensed
under version 3 of the GNU Affero General Public License into a single under version 3 of the GNU General Public License into a single
combined work, and to convey the resulting work. The terms of this combined work, and to convey the resulting work. The terms of this
License will continue to apply to the part which is the covered work, License will continue to apply to the part which is the covered work,
but the special requirements of the GNU Affero General Public License, but the work with which it is combined will remain governed by version
section 13, concerning interaction through a network will apply to the 3 of the GNU General Public License.
combination as such.
14. Revised Versions of this License. 14. Revised Versions of this License.
The Free Software Foundation may publish revised and/or new versions of The Free Software Foundation may publish revised and/or new versions of
the GNU General Public License from time to time. Such new versions will the GNU Affero General Public License from time to time. Such new versions
be similar in spirit to the present version, but may differ in detail to will be similar in spirit to the present version, but may differ in detail to
address new problems or concerns. address new problems or concerns.
Each version is given a distinguishing version number. If the Each version is given a distinguishing version number. If the
Program specifies that a certain numbered version of the GNU General Program specifies that a certain numbered version of the GNU Affero General
Public License "or any later version" applies to it, you have the Public License "or any later version" applies to it, you have the
option of following the terms and conditions either of that numbered option of following the terms and conditions either of that numbered
version or of any later version published by the Free Software version or of any later version published by the Free Software
Foundation. If the Program does not specify a version number of the Foundation. If the Program does not specify a version number of the
GNU General Public License, you may choose any version ever published GNU Affero General Public License, you may choose any version ever published
by the Free Software Foundation. by the Free Software Foundation.
If the Program specifies that a proxy can decide which future If the Program specifies that a proxy can decide which future
versions of the GNU General Public License can be used, that proxy's versions of the GNU Affero General Public License can be used, that proxy's
public statement of acceptance of a version permanently authorizes you public statement of acceptance of a version permanently authorizes you
to choose that version for the Program. to choose that version for the Program.
@ -635,40 +633,29 @@ the "copyright" line and a pointer to where the full notice is found.
Copyright (C) <year> <name of author> Copyright (C) <year> <name of author>
This program is free software: you can redistribute it and/or modify This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by it under the terms of the GNU Affero General Public License as published by
the Free Software Foundation, either version 3 of the License, or the Free Software Foundation, either version 3 of the License, or
(at your option) any later version. (at your option) any later version.
This program is distributed in the hope that it will be useful, This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details. GNU Affero General Public License for more details.
You should have received a copy of the GNU General Public License You should have received a copy of the GNU Affero General Public License
along with this program. If not, see <https://www.gnu.org/licenses/>. along with this program. If not, see <https://www.gnu.org/licenses/>.
Also add information on how to contact you by electronic and paper mail. Also add information on how to contact you by electronic and paper mail.
If the program does terminal interaction, make it output a short If your software can interact with users remotely through a computer
notice like this when it starts in an interactive mode: network, you should also make sure that it provides a way for users to
get its source. For example, if your program is a web application, its
<program> Copyright (C) <year> <name of author> interface could display a "Source" link that leads users to an archive
This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. of the code. There are many ways you could offer source, and different
This is free software, and you are welcome to redistribute it solutions will be better for different programs; see section 13 for the
under certain conditions; type `show c' for details. specific requirements.
The hypothetical commands `show w' and `show c' should show the appropriate
parts of the General Public License. Of course, your program's commands
might be different; for a GUI interface, you would use an "about box".
You should also get your employer (if you work as a programmer) or school, You should also get your employer (if you work as a programmer) or school,
if any, to sign a "copyright disclaimer" for the program, if necessary. if any, to sign a "copyright disclaimer" for the program, if necessary.
For more information on this, and how to apply and follow the GNU GPL, see For more information on this, and how to apply and follow the GNU AGPL, see
<https://www.gnu.org/licenses/>. <https://www.gnu.org/licenses/>.
The GNU General Public License does not permit incorporating your program
into proprietary programs. If your program is a subroutine library, you
may consider it more useful to permit linking proprietary applications with
the library. If this is what you want to do, use the GNU Lesser General
Public License instead of this License. But first, please read
<https://www.gnu.org/licenses/why-not-lgpl.html>.

@ -225,8 +225,8 @@ We love your input! YOLOv5 and YOLOv8 would not be possible without help from ou
YOLOv8 is available under two different licenses: YOLOv8 is available under two different licenses:
- **GPL-3.0 License**: See [LICENSE](https://github.com/ultralytics/ultralytics/blob/main/LICENSE) file for details. - **AGPL-3.0 License**: See [LICENSE](https://github.com/ultralytics/ultralytics/blob/main/LICENSE) file for details.
- **Enterprise License**: Provides greater flexibility for commercial product development without the open-source requirements of GPL-3.0. Typical use cases are embedding Ultralytics software and AI models in commercial products and applications. Request an Enterprise License at [Ultralytics Licensing](https://ultralytics.com/license). - **Enterprise License**: Provides greater flexibility for commercial product development without the open-source requirements of AGPL-3.0. Typical use cases are embedding Ultralytics software and AI models in commercial products and applications. Request an Enterprise License at [Ultralytics Licensing](https://ultralytics.com/license).
## <div align="center">Contact</div> ## <div align="center">Contact</div>

@ -224,8 +224,8 @@ success = model.export(format="onnx") # 将模型导出为 ONNX 格式
YOLOv8 提供两种不同的许可证: YOLOv8 提供两种不同的许可证:
- **GPL-3.0 许可证**:详细信息请参阅 [LICENSE](https://github.com/ultralytics/ultralytics/blob/main/LICENSE) 文件。 - **AGPL-3.0 许可证**:详细信息请参阅 [LICENSE](https://github.com/ultralytics/ultralytics/blob/main/LICENSE) 文件。
- **企业许可证**:为商业产品开发提供更大的灵活性,无需遵循 GPL-3.0 的开源要求。典型的用例是将 Ultralytics 软件和 AI 模型嵌入商业产品和应用中。在 [Ultralytics 授权](https://ultralytics.com/license) 处申请企业许可证。 - **企业许可证**:为商业产品开发提供更大的灵活性,无需遵循 AGPL-3.0 的开源要求。典型的用例是将 Ultralytics 软件和 AI 模型嵌入商业产品和应用中。在 [Ultralytics 授权](https://ultralytics.com/license) 处申请企业许可证。
## <div align="center">联系方式</div> ## <div align="center">联系方式</div>

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Builds ultralytics/ultralytics:latest image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics # Builds ultralytics/ultralytics:latest image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics
# Image is CUDA-optimized for YOLOv8 single/multi-GPU training and inference # Image is CUDA-optimized for YOLOv8 single/multi-GPU training and inference
@ -40,12 +40,12 @@ ENV DEBIAN_FRONTEND teletype
# Usage Examples ------------------------------------------------------------------------------------------------------- # Usage Examples -------------------------------------------------------------------------------------------------------
docker pull ultralytics/ultralytics:latest-hub-export-edgetpu-paddle
# Build and Push # Build and Push
# t=ultralytics/ultralytics:latest && sudo docker build -f docker/Dockerfile -t $t . && sudo docker push $t # t=ultralytics/ultralytics:latest && sudo docker build -f docker/Dockerfile -t $t . && sudo docker push $t
# Pull and Run # Pull and Run
# t=ultralytics/ultralytics:latest && sudo docker pull $t && sudo docker run -it --ipc=host --gpus all $t # t=ultralytics/ultralytics/ultralytics:latest-hub-export-edgetpu-paddle && sudo docker pull $t && sudo docker run -it --ipc=host $t
# Pull and Run with local directory access # Pull and Run with local directory access
# t=ultralytics/ultralytics:latest && sudo docker pull $t && sudo docker run -it --ipc=host --gpus all -v "$(pwd)"/datasets:/usr/src/datasets $t # t=ultralytics/ultralytics:latest && sudo docker pull $t && sudo docker run -it --ipc=host --gpus all -v "$(pwd)"/datasets:/usr/src/datasets $t

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Builds ultralytics/ultralytics:latest-arm64 image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics # Builds ultralytics/ultralytics:latest-arm64 image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics
# Image is aarch64-compatible for Apple M1 and other ARM architectures i.e. Jetson Nano and Raspberry Pi # Image is aarch64-compatible for Apple M1 and other ARM architectures i.e. Jetson Nano and Raspberry Pi

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Builds ultralytics/ultralytics:latest-cpu image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics # Builds ultralytics/ultralytics:latest-cpu image on DockerHub https://hub.docker.com/r/ultralytics/ultralytics
# Image is CPU-optimized for ONNX, OpenVINO and PyTorch YOLOv8 deployments # Image is CPU-optimized for ONNX, OpenVINO and PyTorch YOLOv8 deployments

@ -19,7 +19,7 @@ pip install -r requirements.txt # install
YOLOv5 has about 30 hyperparameters used for various training settings. These are defined in `*.yaml` files in the `/data/hyps` directory. Better initial guesses will produce better final results, so it is important to initialize these values properly before evolving. If in doubt, simply use the default values, which are optimized for YOLOv5 COCO training from scratch. YOLOv5 has about 30 hyperparameters used for various training settings. These are defined in `*.yaml` files in the `/data/hyps` directory. Better initial guesses will produce better final results, so it is important to initialize these values properly before evolving. If in doubt, simply use the default values, which are optimized for YOLOv5 COCO training from scratch.
```yaml ```yaml
# YOLOv5 🚀 by Ultralytics, GPL-3.0 license # YOLOv5 🚀 by Ultralytics, AGPL-3.0 license
# Hyperparameters for low-augmentation COCO training from scratch # Hyperparameters for low-augmentation COCO training from scratch
# python train.py --batch 64 --cfg yolov5n6.yaml --weights '' --data coco.yaml --img 640 --epochs 300 --linear # python train.py --batch 64 --cfg yolov5n6.yaml --weights '' --data coco.yaml --img 640 --epochs 300 --linear
# See tutorials for hyperparameter evolution https://github.com/ultralytics/yolov5#tutorials # See tutorials for hyperparameter evolution https://github.com/ultralytics/yolov5#tutorials

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
site_name: YOLOv8 Docs site_name: YOLOv8 Docs
repo_url: https://github.com/ultralytics/ultralytics repo_url: https://github.com/ultralytics/ultralytics

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import re import re
from pathlib import Path from pathlib import Path
@ -23,7 +23,7 @@ setup(
name='ultralytics', # name of pypi package name='ultralytics', # name of pypi package
version=get_version(), # version of pypi package version=get_version(), # version of pypi package
python_requires='>=3.7', python_requires='>=3.7',
license='GPL-3.0', license='AGPL-3.0',
description='Ultralytics YOLOv8', description='Ultralytics YOLOv8',
long_description=README, long_description=README,
long_description_content_type='text/markdown', long_description_content_type='text/markdown',

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import subprocess import subprocess
from pathlib import Path from pathlib import Path

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
from pathlib import Path from pathlib import Path

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
from pathlib import Path from pathlib import Path

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
__version__ = '8.0.77' __version__ = '8.0.77'

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Argoverse-HD dataset (ring-front-center camera) http://www.cs.cmu.edu/~mengtial/proj/streaming/ by Argo AI # Argoverse-HD dataset (ring-front-center camera) http://www.cs.cmu.edu/~mengtial/proj/streaming/ by Argo AI
# Example usage: yolo train data=Argoverse.yaml # Example usage: yolo train data=Argoverse.yaml
# parent # parent

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Global Wheat 2020 dataset http://www.global-wheat.com/ by University of Saskatchewan # Global Wheat 2020 dataset http://www.global-wheat.com/ by University of Saskatchewan
# Example usage: yolo train data=GlobalWheat2020.yaml # Example usage: yolo train data=GlobalWheat2020.yaml
# parent # parent

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# ImageNet-1k dataset https://www.image-net.org/index.php by Stanford University # ImageNet-1k dataset https://www.image-net.org/index.php by Stanford University
# Simplified class names from https://github.com/anishathalye/imagenet-simple-labels # Simplified class names from https://github.com/anishathalye/imagenet-simple-labels
# Example usage: yolo train task=classify data=imagenet # Example usage: yolo train task=classify data=imagenet

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Objects365 dataset https://www.objects365.org/ by Megvii # Objects365 dataset https://www.objects365.org/ by Megvii
# Example usage: yolo train data=Objects365.yaml # Example usage: yolo train data=Objects365.yaml
# parent # parent

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# SKU-110K retail items dataset https://github.com/eg4000/SKU110K_CVPR19 by Trax Retail # SKU-110K retail items dataset https://github.com/eg4000/SKU110K_CVPR19 by Trax Retail
# Example usage: yolo train data=SKU-110K.yaml # Example usage: yolo train data=SKU-110K.yaml
# parent # parent

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# PASCAL VOC dataset http://host.robots.ox.ac.uk/pascal/VOC by University of Oxford # PASCAL VOC dataset http://host.robots.ox.ac.uk/pascal/VOC by University of Oxford
# Example usage: yolo train data=VOC.yaml # Example usage: yolo train data=VOC.yaml
# parent # parent

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# VisDrone2019-DET dataset https://github.com/VisDrone/VisDrone-Dataset by Tianjin University # VisDrone2019-DET dataset https://github.com/VisDrone/VisDrone-Dataset by Tianjin University
# Example usage: yolo train data=VisDrone.yaml # Example usage: yolo train data=VisDrone.yaml
# parent # parent

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# COCO 2017 dataset http://cocodataset.org by Microsoft # COCO 2017 dataset http://cocodataset.org by Microsoft
# Example usage: yolo train data=coco-pose.yaml # Example usage: yolo train data=coco-pose.yaml
# parent # parent

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# COCO 2017 dataset http://cocodataset.org by Microsoft # COCO 2017 dataset http://cocodataset.org by Microsoft
# Example usage: yolo train data=coco.yaml # Example usage: yolo train data=coco.yaml
# parent # parent

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# COCO128-seg dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017) by Ultralytics # COCO128-seg dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017) by Ultralytics
# Example usage: yolo train data=coco128.yaml # Example usage: yolo train data=coco128.yaml
# parent # parent

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# COCO128 dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017) by Ultralytics # COCO128 dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017) by Ultralytics
# Example usage: yolo train data=coco128.yaml # Example usage: yolo train data=coco128.yaml
# parent # parent

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# COCO8-pose dataset (first 8 images from COCO train2017) by Ultralytics # COCO8-pose dataset (first 8 images from COCO train2017) by Ultralytics
# Example usage: yolo train data=coco8-pose.yaml # Example usage: yolo train data=coco8-pose.yaml
# parent # parent

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# COCO8-seg dataset (first 8 images from COCO train2017) by Ultralytics # COCO8-seg dataset (first 8 images from COCO train2017) by Ultralytics
# Example usage: yolo train data=coco8-seg.yaml # Example usage: yolo train data=coco8-seg.yaml
# parent # parent

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# COCO8 dataset (first 8 images from COCO train2017) by Ultralytics # COCO8 dataset (first 8 images from COCO train2017) by Ultralytics
# Example usage: yolo train data=coco8.yaml # Example usage: yolo train data=coco8.yaml
# parent # parent

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# DIUx xView 2018 Challenge https://challenge.xviewdataset.org by U.S. National Geospatial-Intelligence Agency (NGA) # DIUx xView 2018 Challenge https://challenge.xviewdataset.org by U.S. National Geospatial-Intelligence Agency (NGA)
# -------- DOWNLOAD DATA MANUALLY and jar xf val_images.zip to 'datasets/xView' before running train command! -------- # -------- DOWNLOAD DATA MANUALLY and jar xf val_images.zip to 'datasets/xView' before running train command! --------
# Example usage: yolo train data=xView.yaml # Example usage: yolo train data=xView.yaml

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import requests import requests

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import requests import requests

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import signal import signal
import sys import sys
from pathlib import Path from pathlib import Path

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import os import os
import platform import platform

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Parameters # Parameters
nc: 80 # number of classes nc: 80 # number of classes

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Parameters # Parameters
nc: 80 # number of classes nc: 80 # number of classes

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Parameters # Parameters
nc: 80 # number of classes nc: 80 # number of classes

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Parameters # Parameters
nc: 80 # number of classes nc: 80 # number of classes

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Parameters # Parameters
nc: 80 # number of classes nc: 80 # number of classes

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLOv8-cls image classification model. For Usage examples see https://docs.ultralytics.com/tasks/classify # YOLOv8-cls image classification model. For Usage examples see https://docs.ultralytics.com/tasks/classify
# Parameters # Parameters

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLOv8 object detection model with P2-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect # YOLOv8 object detection model with P2-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
# Parameters # Parameters

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLOv8 object detection model with P3-P6 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect # YOLOv8 object detection model with P3-P6 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
# Parameters # Parameters

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLOv8 object detection model with P3-P6 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect # YOLOv8 object detection model with P3-P6 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
# Parameters # Parameters

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLOv8-pose keypoints/pose estimation model. For Usage examples see https://docs.ultralytics.com/tasks/pose # YOLOv8-pose keypoints/pose estimation model. For Usage examples see https://docs.ultralytics.com/tasks/pose
# Parameters # Parameters

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLOv8-seg instance segmentation model. For Usage examples see https://docs.ultralytics.com/tasks/segment # YOLOv8-seg instance segmentation model. For Usage examples see https://docs.ultralytics.com/tasks/segment
# Parameters # Parameters

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# YOLOv8 object detection model with P3-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect # YOLOv8 object detection model with P3-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
# Parameters # Parameters

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import ast import ast
import contextlib import contextlib
import json import json

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
""" """
Common modules Common modules
""" """

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
""" """
Common modules Common modules
""" """

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import contextlib import contextlib
from copy import deepcopy from copy import deepcopy

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
from .track import register_tracker from .track import register_tracker
from .trackers import BOTSORT, BYTETracker from .trackers import BOTSORT, BYTETracker

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Default YOLO tracker settings for BoT-SORT tracker https://github.com/NirAharon/BoT-SORT # Default YOLO tracker settings for BoT-SORT tracker https://github.com/NirAharon/BoT-SORT
tracker_type: botsort # tracker type, ['botsort', 'bytetrack'] tracker_type: botsort # tracker type, ['botsort', 'bytetrack']

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Default YOLO tracker settings for ByteTrack tracker https://github.com/ifzhang/ByteTrack # Default YOLO tracker settings for ByteTrack tracker https://github.com/ifzhang/ByteTrack
tracker_type: bytetrack # tracker type, ['botsort', 'bytetrack'] tracker_type: bytetrack # tracker type, ['botsort', 'bytetrack']

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
from functools import partial from functools import partial

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
from .bot_sort import BOTSORT from .bot_sort import BOTSORT
from .byte_tracker import BYTETracker from .byte_tracker import BYTETracker

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
from collections import OrderedDict from collections import OrderedDict

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
from collections import deque from collections import deque

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import numpy as np import numpy as np

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import copy import copy

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import numpy as np import numpy as np
import scipy.linalg import scipy.linalg

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import numpy as np import numpy as np
import scipy import scipy

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
from . import v8 from . import v8

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import contextlib import contextlib
import re import re
import shutil import shutil

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Default training settings and hyperparameters for medium-augmentation COCO training # Default training settings and hyperparameters for medium-augmentation COCO training
task: detect # YOLO task, i.e. detect, segment, classify, pose task: detect # YOLO task, i.e. detect, segment, classify, pose

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
from .base import BaseDataset from .base import BaseDataset
from .build import build_classification_dataloader, build_dataloader, load_inference_source from .build import build_classification_dataloader, build_dataloader, load_inference_source

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import math import math
import random import random

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import glob import glob
import math import math

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import os import os
import random import random

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import glob import glob
import math import math

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
""" """
Image augmentation functions Image augmentation functions
""" """

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
""" """
Dataloaders and dataset utils Dataloaders and dataset utils
""" """

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
from itertools import repeat from itertools import repeat
from multiprocessing.pool import ThreadPool from multiprocessing.pool import ThreadPool

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import collections import collections
from copy import deepcopy from copy import deepcopy

@ -1,5 +1,5 @@
#!/bin/bash #!/bin/bash
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Download latest models from https://github.com/ultralytics/assets/releases # Download latest models from https://github.com/ultralytics/assets/releases
# Example usage: bash ultralytics/yolo/data/scripts/download_weights.sh # Example usage: bash ultralytics/yolo/data/scripts/download_weights.sh
# parent # parent

@ -1,5 +1,5 @@
#!/bin/bash #!/bin/bash
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Download COCO 2017 dataset http://cocodataset.org # Download COCO 2017 dataset http://cocodataset.org
# Example usage: bash data/scripts/get_coco.sh # Example usage: bash data/scripts/get_coco.sh
# parent # parent

@ -1,5 +1,5 @@
#!/bin/bash #!/bin/bash
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Download COCO128 dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017) # Download COCO128 dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017)
# Example usage: bash data/scripts/get_coco128.sh # Example usage: bash data/scripts/get_coco128.sh
# parent # parent

@ -1,5 +1,5 @@
#!/bin/bash #!/bin/bash
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
# Download ILSVRC2012 ImageNet dataset https://image-net.org # Download ILSVRC2012 ImageNet dataset https://image-net.org
# Example usage: bash data/scripts/get_imagenet.sh # Example usage: bash data/scripts/get_imagenet.sh
# parent # parent

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import contextlib import contextlib
import hashlib import hashlib

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
""" """
Export a YOLOv8 PyTorch model to other formats. TensorFlow exports authored by https://github.com/zldrobit Export a YOLOv8 PyTorch model to other formats. TensorFlow exports authored by https://github.com/zldrobit
@ -213,7 +213,7 @@ class Exporter:
self.metadata = { self.metadata = {
'description': description, 'description': description,
'author': 'Ultralytics', 'author': 'Ultralytics',
'license': 'GPL-3.0 https://ultralytics.com/license', 'license': 'AGPL-3.0 https://ultralytics.com/license',
'version': __version__, 'version': __version__,
'stride': int(max(model.stride)), 'stride': int(max(model.stride)),
'task': model.task, 'task': model.task,

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import sys import sys
from pathlib import Path from pathlib import Path

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
""" """
Run prediction on images, videos, directories, globs, YouTube, webcam, streams, etc. Run prediction on images, videos, directories, globs, YouTube, webcam, streams, etc.

@ -1,4 +1,4 @@
# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
""" """
Ultralytics Results, Boxes and Masks classes for handling inference results Ultralytics Results, Boxes and Masks classes for handling inference results

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# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
""" """
Train a model on a dataset Train a model on a dataset

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# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
""" """
Check a model's accuracy on a test or val split of a dataset Check a model's accuracy on a test or val split of a dataset

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# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import contextlib import contextlib
import inspect import inspect

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# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
""" """
Functions for estimating the best YOLO batch size to use a fraction of the available CUDA memory in PyTorch. Functions for estimating the best YOLO batch size to use a fraction of the available CUDA memory in PyTorch.
""" """

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# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
""" """
Benchmark a YOLO model formats for speed and accuracy Benchmark a YOLO model formats for speed and accuracy

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# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
""" """
Base callbacks Base callbacks
""" """

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# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import re import re
import matplotlib.image as mpimg import matplotlib.image as mpimg

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# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import os import os
from pathlib import Path from pathlib import Path

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# Ultralytics YOLO 🚀, GPL-3.0 license # Ultralytics YOLO 🚀, AGPL-3.0 license
import json import json
from time import time from time import time

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