From 95971f472293fb16079f63bd8a67d85cbcb29c43 Mon Sep 17 00:00:00 2001
From: Ultralytics Assistant
<135830346+UltralyticsAssistant@users.noreply.github.com>
Date: Sat, 5 Oct 2024 14:27:48 +0200
Subject: [PATCH] Ultralytics Code Refactor https://ultralytics.com/actions
(#2290)
Refactor code for speed and clarity
---
README.md | 22 +++++++++++-----------
README.zh-CN.md | 22 +++++++++++-----------
2 files changed, 22 insertions(+), 22 deletions(-)
diff --git a/README.md b/README.md
index f197aba42c..d5f8b3d43e 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
-YOLOv3 🚀 is the world's most loved vision AI, representing Ultralytics open-source research into future vision AI methods, incorporating lessons learned and best practices evolved over thousands of hours of research and development.
+YOLOv3 🚀 is the world's most loved vision AI, representing Ultralytics open-source research into future vision AI methods, incorporating lessons learned and best practices evolved over thousands of hours of research and development.
-We hope that the resources here will help you get the most out of YOLOv3. Please browse the YOLOv3 Docs for details, raise an issue on GitHub for support, and join our Discord community for questions and discussions!
+We hope that the resources here will help you get the most out of YOLOv3. Please browse the YOLOv3 Docs for details, raise an issue on GitHub for support, and join our Discord community for questions and discussions!
To request an Enterprise License please complete the form at [Ultralytics Licensing](https://www.ultralytics.com/license).
@@ -37,7 +37,7 @@ To request an Enterprise License please complete the form at [Ultralytics Licens
-
+
@@ -55,7 +55,7 @@ pip install ultralytics
```
@@ -161,7 +161,7 @@ python train.py --data coco.yaml --epochs 300 --weights '' --cfg yolov5n.yaml -
## Integrations
-
+
@@ -170,7 +170,7 @@ python train.py --data coco.yaml --epochs 300 --weights '' --cfg yolov5n.yaml -
-
+
@@ -188,7 +188,7 @@ python train.py --data coco.yaml --epochs 300 --weights '' --cfg yolov5n.yaml -
Experience seamless AI with [Ultralytics HUB](https://www.ultralytics.com/hub) ⭐, the all-in-one solution for data visualization, YOLO 🚀 model training and deployment, without any coding. Transform images into actionable insights and bring your AI visions to life with ease using our cutting-edge platform and user-friendly [Ultralytics App](https://www.ultralytics.com/app-install). Start your journey for **Free** now!
-
+
## Why YOLOv3
@@ -245,7 +245,7 @@ Our new YOLOv5 [release v7.0](https://github.com/ultralytics/yolov5/releases/v7.
Segmentation Checkpoints
@@ -461,7 +461,7 @@ For YOLOv3 bug reports and feature requests please visit [GitHub Issues](https:/
-
+
[tta]: https://docs.ultralytics.com/yolov5/tutorials/test_time_augmentation
diff --git a/README.zh-CN.md b/README.zh-CN.md
index 04c5d9b99d..d2bd6e0473 100644
--- a/README.zh-CN.md
+++ b/README.zh-CN.md
@@ -1,6 +1,6 @@
-YOLOv3 🚀 是世界上最受欢迎的视觉 AI,代表 Ultralytics 对未来视觉 AI 方法的开源研究,结合在数千小时的研究和开发中积累的经验教训和最佳实践。
+YOLOv3 🚀 是世界上最受欢迎的视觉 AI,代表 Ultralytics 对未来视觉 AI 方法的开源研究,结合在数千小时的研究和开发中积累的经验教训和最佳实践。
-我们希望这里的资源能帮助您充分利用 YOLOv3。请浏览 YOLOv3 文档 了解详细信息,在 GitHub 上提交问题以获得支持,并加入我们的 Discord 社区进行问题和讨论!
+我们希望这里的资源能帮助您充分利用 YOLOv3。请浏览 YOLOv3 文档 了解详细信息,在 GitHub 上提交问题以获得支持,并加入我们的 Discord 社区进行问题和讨论!
如需申请企业许可,请在 [Ultralytics Licensing](https://www.ultralytics.com/license) 处填写表格
@@ -38,7 +38,7 @@ YOLOv3 🚀 是世界上最受欢迎的视觉 AI,代表
-
+
@@ -55,7 +55,7 @@ pip install ultralytics
```
@@ -161,7 +161,7 @@ python train.py --data coco.yaml --epochs 300 --weights '' --cfg yolov5n.yaml -
## 模块集成
-
+
@@ -170,7 +170,7 @@ python train.py --data coco.yaml --epochs 300 --weights '' --cfg yolov5n.yaml -
-
+
@@ -188,7 +188,7 @@ python train.py --data coco.yaml --epochs 300 --weights '' --cfg yolov5n.yaml -
[Ultralytics HUB](https://www.ultralytics.com/hub) 是我们的⭐**新的**用于可视化数据集、训练 YOLOv3 🚀 模型并以无缝体验部署到现实世界的无代码解决方案。现在开始 **免费** 使用他!
-
+
## 为什么选择 YOLOv3
@@ -247,7 +247,7 @@ YOLOv3 超级容易上手,简单易学。我们优先考虑现实世界的结
@@ -462,7 +462,7 @@ Ultralytics 提供两种许可证选项以适应各种使用场景:
-
+
[tta]: https://docs.ultralytics.com/yolov5/tutorials/test_time_augmentation