1 Star 0 Fork 3

kesionli / easycv

forked from Gitee 极速下载 / easycv 
加入 Gitee
与超过 1200万 开发者一起发现、参与优秀开源项目,私有仓库也完全免费 :)
免费加入
克隆/下载
贡献代码
同步代码
取消
提示: 由于 Git 不支持空文件夾,创建文件夹后会生成空的 .keep 文件
Loading...
README
Apache-2.0

PyPI Documentation Status license open issues GitHub pull-requests GitHub latest commit

EasyCV

English | 简体中文

简介

EasyCV是一个涵盖多个领域的基于Pytorch的计算机视觉工具箱,聚焦自监督学习和视觉transformer关键技术,覆盖主流的视觉建模任务例如图像分类,度量学习,目标检测,关键点检测等。

核心特性

  • SOTA 自监督算法

    EasyCV提供了state-of-the-art的自监督算法,有基于对比学习的算法例如 SimCLR,MoCO V2,Swav, Moby,DINO,也有基于掩码图像建模的MAE算法,除此之外我们还提供了标准的benchmark工具用来进行自监督算法模型的效果评估。

  • 视觉Transformers

    EasyCV聚焦视觉transformer技术,希望通过一种简洁的方式让用户方便地使用各种SOTA的、基于自监督预训练和imagenet预训练的视觉transformer模型,例如ViT,Swin-Transformer,Shuffle Transformer,未来也会加入更多相关模型。此外,我们还支持所有timm仓库中的预训练模型.

  • 易用性和可扩展性

    除了自监督学习,EasyCV还支持图像分类、目标检测,度量学习,关键点检测等领域,同时未来也会支持更多任务领域。 尽管横跨多个任务领域,EasyCV保持了统一的架构,整体框架划分为数据集、模型、回调模块,非常容易增加新的算法、功能,以及基于现有模块进行扩展。

    推理方面,EasyCV提供了端到端的简单易用的推理接口,支持上述多个领域。 此外所有的模型都支持使用PAI-EAS进行在线部署,支持自动伸缩和服务监控。

  • 高性能

    EasyCV支持多机多卡训练,同时支持TorchAccelerator和fp16进行训练加速。在数据读取和预处理方面,EasyCV使用DALI进行加速。对于模型推理优化,EasyCV支持使用jit script导出模型,使用PAI-Blade进行模型优化。

最新进展

[🔥 Latest News] 近期我们开源了YOLOX-PAI,在40-50mAP(推理速度小于1ms)范围内达到了业界的SOTA水平。同时EasyCV提供了一套简洁高效的模型导出和预测接口,供用户快速完成端到端的图像检测任务。如果你想快速了解YOLOX-PAI, 点击 这里!

  • 31/08/2022 EasyCV v0.6.0 版本发布。
    • 发布YOLOX-PAI,在轻量级模型中取得SOTA效果
    • 增加检测算法DINO, COCO mAP 58.5
    • 增加Mask2Former算法
    • Datahub新增imagenet1k, imagenet22k, coco, lvis, voc2012 数据的百度网盘链接,加速下载

更多版本的详细信息请参考变更记录

技术文章

我们有一系列关于EasyCV功能的技术文章。

安装

请参考快速开始教程中的安装章节。

快速开始

请参考快速开始教程 快速开始。我们也提供了更多的教程方便你的学习和使用。

模型库

模型
自监督学习 图像分类 目标检测 分割 3D目标检测
实例分割 语义分割 全景分割

不同领域的模型仓库和benchmark指标如下

开源许可证

本项目使用 Apache 2.0 开源许可证. 项目内含有一些第三方依赖库源码,部分实现借鉴其他开源仓库,仓库名称和开源许可证说明请参考NOTICE文件

Contact

本项目由阿里云机器学习平台PAI-CV团队维护,你可以通过如下方式联系我们:

钉钉群号: 41783266 邮箱: easycv@list.alibaba-inc.com

企业级服务

如果你需要针对EasyCV提供企业级服务,或者购买云产品服务,你可以通过加入钉钉群联系我们。

dingding_qrcode

Copyright 2020-2022 Alibaba PAI. All rights reserved. Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. "Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. "Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. "You" (or "Your") shall mean an individual or Legal Entity exercising permissions granted by this License. "Source" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. "Object" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types. "Work" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below). "Derivative Works" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof. "Contribution" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. For the purposes of this definition, "submitted" means any form of electronic, verbal, or written communication sent to the Licensor or its representatives, including but not limited to communication on electronic mailing lists, source code control systems, and issue tracking systems that are managed by, or on behalf of, the Licensor for the purpose of discussing and improving the Work, but excluding communication that is conspicuously marked or otherwise designated in writing by the copyright owner as "Not a Contribution." "Contributor" shall mean Licensor and any individual or Legal Entity on behalf of whom a Contribution has been received by Licensor and subsequently incorporated within the Work. 2. Grant of Copyright License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. 3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed. 4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions: (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and (b) You must cause any modified files to carry prominent notices stating that You changed the files; and (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and (d) If the Work includes a "NOTICE" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License. You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License. 5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions. 6. Trademarks. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Work and reproducing the content of the NOTICE file. 7. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Work (and each Contributor provides its Contributions) on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are solely responsible for determining the appropriateness of using or redistributing the Work and assume any risks associated with Your exercise of permissions under this License. 8. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages. 9. Accepting Warranty or Additional Liability. While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability. END OF TERMS AND CONDITIONS APPENDIX: How to apply the Apache License to your work. To apply the Apache License to your work, attach the following boilerplate notice, with the fields enclosed by brackets "[]" replaced with your own identifying information. (Don't include the brackets!) The text should be enclosed in the appropriate comment syntax for the file format. We also recommend that a file or class name and description of purpose be included on the same "printed page" as the copyright notice for easier identification within third-party archives. Copyright 2020-2022 Alibaba PAI. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

简介

EasyCV 是基于 PyTorch 的一体化计算机视觉工具箱,主要专注于自监督学习、基于 Transformer 的模型,以及主要的 CV 任务,包括图像分类、度量学习、目标检测 展开 收起
Python
Apache-2.0
取消

发行版

暂无发行版

贡献者

全部

近期动态

加载更多
不能加载更多了
Python
1
https://gitee.com/lgsg/easycv.git
git@gitee.com:lgsg/easycv.git
lgsg
easycv
easycv
master

搜索帮助

14c37bed 8189591 565d56ea 8189591