Docs update for new YOLOv5 URLs (#11409)

* Update YOLOv5 Docs Tutorials * Update YOLOv5 Docs Tutorials * Update actions * Update actions * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update actions * Update actions * Update actions * Update actions * Update actions * Update actions --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
ultralytics · Apr 21, 2023 · fb1e746 · fb1e746
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diff --git a/.github/workflows/greetings.yml b/.github/workflows/greetings.yml
@@ -23,11 +23,11 @@ jobs:
             - ✅ Reduce changes to the absolute **minimum** required for your bug fix or feature addition. _"It is not daily increase but daily decrease, hack away the unessential. The closer to the source, the less wastage there is."_  — Bruce Lee
 
           issue-message: |
-            👋 Hello @${{ github.actor }}, thank you for your interest in YOLOv5 🚀! Please visit our ⭐️ [Tutorials](https://docs.ultralytics.com/yolov5/#tutorials) to get started, where you can find quickstart guides for simple tasks like [Custom Data Training](https://docs.ultralytics.com/yolov5/train_custom_data/) all the way to advanced concepts like [Hyperparameter Evolution](https://docs.ultralytics.com/yolov5/hyp_evolution/).
+            👋 Hello @${{ github.actor }}, thank you for your interest in YOLOv5 🚀! Please visit our ⭐️ [Tutorials](https://docs.ultralytics.com/yolov5/) to get started, where you can find quickstart guides for simple tasks like [Custom Data Training](https://docs.ultralytics.com/yolov5/tutorials/train_custom_data/) all the way to advanced concepts like [Hyperparameter Evolution](https://docs.ultralytics.com/yolov5/tutorials/hyperparameter_evolution/).
 
             If this is a 🐛 Bug Report, please provide a **minimum reproducible example** to help us debug it.
 
-            If this is a custom training ❓ Question, please provide as much information as possible, including dataset image examples and training logs, and verify you are following our [Tips for Best Training Results](https://github.com/ultralytics/yolov5/wiki/Tips-for-Best-Training-Results).
+            If this is a custom training ❓ Question, please provide as much information as possible, including dataset image examples and training logs, and verify you are following our [Tips for Best Training Results](https://docs.ultralytics.com/yolov5/tutorials/tips_for_best_training_results/).
 
             ## Requirements
 
@@ -43,15 +43,15 @@ jobs:
             YOLOv5 may be run in any of the following up-to-date verified environments (with all dependencies including [CUDA](https://developer.nvidia.com/cuda)/[CUDNN](https://developer.nvidia.com/cudnn), [Python](https://www.python.org/) and [PyTorch](https://pytorch.org/) preinstalled):
 
             - **Notebooks** with free GPU: <a href="https://bit.ly/yolov5-paperspace-notebook"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Run on Gradient"></a> <a href="https://colab.research.google.com/github/ultralytics/yolov5/blob/master/tutorial.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> <a href="https://www.kaggle.com/ultralytics/yolov5"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a>
-            - **Google Cloud** Deep Learning VM. See [GCP Quickstart Guide](https://github.com/ultralytics/yolov5/wiki/GCP-Quickstart)
-            - **Amazon** Deep Learning AMI. See [AWS Quickstart Guide](https://github.com/ultralytics/yolov5/wiki/AWS-Quickstart)
-            - **Docker Image**. See [Docker Quickstart Guide](https://github.com/ultralytics/yolov5/wiki/Docker-Quickstart) <a href="https://hub.docker.com/r/ultralytics/yolov5"><img src="https://img.shields.io/docker/pulls/ultralytics/yolov5?logo=docker" alt="Docker Pulls"></a>
+            - **Google Cloud** Deep Learning VM. See [GCP Quickstart Guide](https://docs.ultralytics.com/yolov5/environments/google_cloud_quickstart_tutorial/)
+            - **Amazon** Deep Learning AMI. See [AWS Quickstart Guide](https://docs.ultralytics.com/aws_quickstart_tutorial/)
+            - **Docker Image**. See [Docker Quickstart Guide](https://docs.ultralytics.com/yolov5/environments/docker_image_quickstart_tutorial/) <a href="https://hub.docker.com/r/ultralytics/yolov5"><img src="https://img.shields.io/docker/pulls/ultralytics/yolov5?logo=docker" alt="Docker Pulls"></a>
 
             ## Status
 
             <a href="https://github.com/ultralytics/yolov5/actions/workflows/ci-testing.yml"><img src="https://github.com/ultralytics/yolov5/actions/workflows/ci-testing.yml/badge.svg" alt="YOLOv5 CI"></a>
 
-            If this badge is green, all [YOLOv5 GitHub Actions](https://github.com/ultralytics/yolov5/actions) Continuous Integration (CI) tests are currently passing. CI tests verify correct operation of YOLOv5 [training](https://github.com/ultralytics/yolov5/blob/master/train.py), [validation](https://github.com/ultralytics/yolov5/blob/master/val.py), [inference](https://github.com/ultralytics/yolov5/blob/master/detect.py), [export](https://github.com/ultralytics/yolov5/blob/master/export.py) and [benchmarks](https://github.com/ultralytics/yolov5/blob/master/benchmarks.py) on MacOS, Windows, and Ubuntu every 24 hours and on every commit.
+            If this badge is green, all [YOLOv5 GitHub Actions](https://github.com/ultralytics/yolov5/actions) Continuous Integration (CI) tests are currently passing. CI tests verify correct operation of YOLOv5 [training](https://github.com/ultralytics/yolov5/blob/master/train.py), [validation](https://github.com/ultralytics/yolov5/blob/master/val.py), [inference](https://github.com/ultralytics/yolov5/blob/master/detect.py), [export](https://github.com/ultralytics/yolov5/blob/master/export.py) and [benchmarks](https://github.com/ultralytics/yolov5/blob/master/benchmarks.py) on macOS, Windows, and Ubuntu every 24 hours and on every commit.
 
             ## Introducing YOLOv8 🚀
 

diff --git a/.github/workflows/links.yml b/.github/workflows/links.yml
@@ -0,0 +1,38 @@
+# Ultralytics YOLO 🚀, AGPL-3.0 license
+# YOLO Continuous Integration (CI) GitHub Actions tests
+
+name: Check Broken links
+
+on:
+  push:
+    branches: [master]
+  pull_request:
+    branches: [master]
+  workflow_dispatch:
+  schedule:
+    - cron: '0 0 * * *'  # runs at 00:00 UTC every day
+
+jobs:
+  Links:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+
+      - name: Test Markdown and HTML links
+        uses: lycheeverse/lychee-action@v1.6.1
+        with:
+          fail: true
+          # accept 429(Instagram, 'too many requests'), 999(LinkedIn, 'unknown status code'), Timeout(Twitter)
+          args: --accept 429,999 --exclude-loopback --exclude twitter.com --exclude-mail './**/*.md' './**/*.html'
+        env:
+          GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}}
+
+      - name: Test Markdown, HTML, YAML, Python and Notebook links
+        if: github.event_name == 'workflow_dispatch'
+        uses: lycheeverse/lychee-action@v1.6.1
+        with:
+          fail: true
+          # accept 429(Instagram, 'too many requests'), 999(LinkedIn, 'unknown status code'), Timeout(Twitter)
+          args: --accept 429,999 --exclude-loopback --exclude twitter.com,url.com --exclude-mail './**/*.md' './**/*.html' './**/*.yml' './**/*.yaml' './**/*.py' './**/*.ipynb'
+        env:
+          GITHUB_TOKEN: ${{secrets.GITHUB_TOKEN}}
diff --git a/.github/workflows/stale.yml b/.github/workflows/stale.yml
@@ -12,26 +12,33 @@ jobs:
       - uses: actions/stale@v8
         with:
           repo-token: ${{ secrets.GITHUB_TOKEN }}
+
           stale-issue-message: |
-            👋 Hello, this issue has been automatically marked as stale because it has not had recent activity. Please note it will be closed if no further activity occurs.
+            👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.
 
-            Access additional [YOLOv5](https://ultralytics.com/yolov5) 🚀 resources:
-            - **Wiki** – https://github.com/ultralytics/yolov5/wiki
-            - **Tutorials** – https://github.com/ultralytics/yolov5#tutorials
-            - **Docs** – https://docs.ultralytics.com
+            For additional resources and information, please see the links below:
 
-            Access additional [Ultralytics](https://ultralytics.com) ⚡ resources:
-            - **Ultralytics HUB** – https://ultralytics.com/hub
-            - **Vision API** – https://ultralytics.com/yolov5
-            - **About Us** – https://ultralytics.com/about
-            - **Join Our Team** – https://ultralytics.com/work
-            - **Contact Us** – https://ultralytics.com/contact
+            - **Docs**: https://docs.ultralytics.com
+            - **HUB**: https://hub.ultralytics.com
+            - **Community**: https://community.ultralytics.com
 
             Feel free to inform us of any other **issues** you discover or **feature requests** that come to mind in the future. Pull Requests (PRs) are also always welcomed!
 
-            Thank you for your contributions to YOLOv5 🚀 and Vision AI ⭐!
+            Thank you for your contributions to YOLO 🚀 and Vision AI ⭐
+
+          stale-pr-message: |
+            👋 Hello there! We wanted to let you know that we've decided to close this pull request due to inactivity. We appreciate the effort you put into contributing to our project, but unfortunately, not all contributions are suitable or aligned with our product roadmap.
+
+            We hope you understand our decision, and please don't let it discourage you from contributing to open source projects in the future. We value all of our community members and their contributions, and we encourage you to keep exploring new projects and ways to get involved.
+
+            For additional resources and information, please see the links below:
+
+            - **Docs**: https://docs.ultralytics.com
+            - **HUB**: https://hub.ultralytics.com
+            - **Community**: https://community.ultralytics.com
+
+            Thank you for your contributions to YOLO 🚀 and Vision AI ⭐
 
-          stale-pr-message: 'This pull request has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions YOLOv5 🚀 and Vision AI ⭐.'
           days-before-issue-stale: 30
           days-before-issue-close: 10
           days-before-pr-stale: 90

diff --git a/README.md b/README.md
@@ -153,22 +153,22 @@ python train.py --data coco.yaml --epochs 300 --weights '' --cfg yolov5n.yaml  -
 <details open>
 <summary>Tutorials</summary>
 
-- [Train Custom Data](https://docs.ultralytics.com/yolov5/train_custom_data) 🚀 RECOMMENDED
-- [Tips for Best Training Results](https://docs.ultralytics.com/yolov5/tips_for_best_training_results) ☘️ RECOMMENDED
-- [Multi-GPU Training](https://docs.ultralytics.com/yolov5/multi_gpu_training)
-- [PyTorch Hub](https://docs.ultralytics.com/yolov5/pytorch_hub) 🌟 NEW
-- [TFLite, ONNX, CoreML, TensorRT Export](https://docs.ultralytics.com/yolov5/export) 🚀
-- [NVIDIA Jetson platform Deployment](https://docs.ultralytics.com/yolov5/jetson_nano) 🌟 NEW
-- [Test-Time Augmentation (TTA)](https://docs.ultralytics.com/yolov5/tta)
-- [Model Ensembling](https://docs.ultralytics.com/yolov5/ensemble)
-- [Model Pruning/Sparsity](https://docs.ultralytics.com/yolov5/pruning_sparsity)
-- [Hyperparameter Evolution](https://docs.ultralytics.com/yolov5/hyp_evolution)
-- [Transfer Learning with Frozen Layers](https://docs.ultralytics.com/yolov5/transfer_learn_frozen)
-- [Architecture Summary](https://docs.ultralytics.com/yolov5/architecture) 🌟 NEW
-- [Roboflow for Datasets](https://docs.ultralytics.com/yolov5/roboflow)
-- [ClearML Logging](https://docs.ultralytics.com/yolov5/clearml) 🌟 NEW
-- [YOLOv5 with Neural Magic's Deepsparse](https://docs.ultralytics.com/yolov5/neural_magic) 🌟 NEW
-- [Comet Logging](https://docs.ultralytics.com/yolov5/comet) 🌟 NEW
+- [Train Custom Data](https://docs.ultralytics.com/yolov5/tutorials/train_custom_data) 🚀 RECOMMENDED
+- [Tips for Best Training Results](https://docs.ultralytics.com/yolov5/tutorials/tips_for_best_training_results) ☘️
+- [Multi-GPU Training](https://docs.ultralytics.com/yolov5/tutorials/multi_gpu_training)
+- [PyTorch Hub](https://docs.ultralytics.com/yolov5/tutorials/pytorch_hub_model_loading) 🌟 NEW
+- [TFLite, ONNX, CoreML, TensorRT Export](https://docs.ultralytics.com/yolov5/tutorials/model_export) 🚀
+- [NVIDIA Jetson platform Deployment](https://docs.ultralytics.com/yolov5/tutorials/running_on_jetson_nano) 🌟 NEW
+- [Test-Time Augmentation (TTA)](https://docs.ultralytics.com/yolov5/tutorials/test_time_augmentation)
+- [Model Ensembling](https://docs.ultralytics.com/yolov5/tutorials/model_ensembling)
+- [Model Pruning/Sparsity](https://docs.ultralytics.com/yolov5/tutorials/model_pruning_and_sparsity)
+- [Hyperparameter Evolution](https://docs.ultralytics.com/yolov5/tutorials/hyperparameter_evolution)
+- [Transfer Learning with Frozen Layers](https://docs.ultralytics.com/yolov5/tutorials/transfer_learning_with_frozen_layers)
+- [Architecture Summary](https://docs.ultralytics.com/yolov5/tutorials/architecture_description) 🌟 NEW
+- [Roboflow for Datasets, Labeling, and Active Learning](https://docs.ultralytics.com/yolov5/tutorials/roboflow_datasets_integration)
+- [ClearML Logging](https://docs.ultralytics.com/yolov5/tutorials/clearml_logging_integration) 🌟 NEW
+- [YOLOv5 with Neural Magic's Deepsparse](https://docs.ultralytics.com/yolov5/tutorials/neural_magic_pruning_quantization) 🌟 NEW
+- [Comet Logging](https://docs.ultralytics.com/yolov5/tutorials/comet_logging_integration) 🌟 NEW
 
 </details>
 
@@ -436,10 +436,10 @@ Get started in seconds with our verified environments. Click each icon below for
   <a href="https://hub.docker.com/r/ultralytics/yolov5">
     <img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-docker-small.png" width="10%" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="5%" alt="" />
-  <a href="https://github.com/ultralytics/yolov5/wiki/AWS-Quickstart">
+  <a href="https://docs.ultralytics.com/yolov5/environments/aws_quickstart_tutorial/">
     <img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-aws-small.png" width="10%" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="5%" alt="" />
-  <a href="https://github.com/ultralytics/yolov5/wiki/GCP-Quickstart">
+  <a href="https://docs.ultralytics.com/yolov5/environments/google_cloud_quickstart_tutorial/">
     <img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-gcp-small.png" width="10%" /></a>
 </div>
 

diff --git a/README.zh-CN.md b/README.zh-CN.md
@@ -147,22 +147,22 @@ python train.py --data coco.yaml --epochs 300 --weights '' --cfg yolov5n.yaml  -
 <details open>
 <summary>教程</summary>
 
-- [训练自定义数据](https://docs.ultralytics.com/yolov5/train_custom_data) 🚀 推荐
-- [获得最佳训练结果的技巧](https://docs.ultralytics.com/yolov5/tips_for_best_training_results) ☘️ 推荐
-- [多 GPU 训练](https://docs.ultralytics.com/yolov5/multi_gpu_training)
-- [PyTorch Hub](https://docs.ultralytics.com/yolov5/pytorch_hub) 🌟 新
-- [TFLite, ONNX, CoreML, TensorRT 导出](https://docs.ultralytics.com/yolov5/export) 🚀
-- [NVIDIA Jetson 平台部署](https://docs.ultralytics.com/yolov5/jetson_nano) 🌟 新
-- [测试时增强（TTA）](https://docs.ultralytics.com/yolov5/tta)
-- [模型集成](https://docs.ultralytics.com/yolov5/ensemble)
-- [模型剪枝/稀疏性](https://docs.ultralytics.com/yolov5/pruning_sparsity)
-- [超参数进化](https://docs.ultralytics.com/yolov5/hyp_evolution)
-- [冻结层的迁移学习](https://docs.ultralytics.com/yolov5/transfer_learn_frozen)
-- [架构概述](https://docs.ultralytics.com/yolov5/architecture) 🌟 新
-- [Roboflow](https://docs.ultralytics.com/yolov5/roboflow)
-- [ClearML 日志记录](https://docs.ultralytics.com/yolov5/clearml) 🌟 新
-- [YOLOv5 与 Neural Magic 的 Deepsparse](https://docs.ultralytics.com/yolov5/neural_magic) 🌟 新
-- [Comet 日志记录](https://docs.ultralytics.com/yolov5/comet) 🌟 新
+- [训练自定义数据](https://docs.ultralytics.com/yolov5/tutorials/train_custom_data) 🚀 推荐
+- [获得最佳训练结果的技巧](https://docs.ultralytics.com/yolov5/tutorials/tips_for_best_training_results) ☘️
+- [多GPU训练](https://docs.ultralytics.com/yolov5/tutorials/multi_gpu_training)
+- [PyTorch Hub](https://docs.ultralytics.com/yolov5/tutorials/pytorch_hub_model_loading) 🌟 新
+- [TFLite，ONNX，CoreML，TensorRT导出](https://docs.ultralytics.com/yolov5/tutorials/model_export) 🚀
+- [NVIDIA Jetson平台部署](https://docs.ultralytics.com/yolov5/tutorials/running_on_jetson_nano) 🌟 新
+- [测试时增强 (TTA)](https://docs.ultralytics.com/yolov5/tutorials/test_time_augmentation)
+- [模型集成](https://docs.ultralytics.com/yolov5/tutorials/model_ensembling)
+- [模型剪枝/稀疏](https://docs.ultralytics.com/yolov5/tutorials/model_pruning_and_sparsity)
+- [超参数进化](https://docs.ultralytics.com/yolov5/tutorials/hyperparameter_evolution)
+- [冻结层的迁移学习](https://docs.ultralytics.com/yolov5/tutorials/transfer_learning_with_frozen_layers)
+- [架构概述](https://docs.ultralytics.com/yolov5/tutorials/architecture_description) 🌟 新
+- [Roboflow用于数据集、标注和主动学习](https://docs.ultralytics.com/yolov5/tutorials/roboflow_datasets_integration)
+- [ClearML日志记录](https://docs.ultralytics.com/yolov5/tutorials/clearml_logging_integration) 🌟 新
+- [使用Neural Magic的Deepsparse的YOLOv5](https://docs.ultralytics.com/yolov5/tutorials/neural_magic_pruning_quantization) 🌟 新
+- [Comet日志记录](https://docs.ultralytics.com/yolov5/tutorials/comet_logging_integration) 🌟 新
 
 </details>
 
@@ -431,10 +431,10 @@ python export.py --weights yolov5s-cls.pt resnet50.pt efficientnet_b0.pt --inclu
   <a href="https://hub.docker.com/r/ultralytics/yolov5">
     <img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-docker-small.png" width="10%" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="5%" alt="" />
-  <a href="https://github.com/ultralytics/yolov5/wiki/AWS-Quickstart">
+  <a href="https://docs.ultralytics.com/yolov5/environments/aws_quickstart_tutorial/">
     <img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-aws-small.png" width="10%" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="5%" alt="" />
-  <a href="https://github.com/ultralytics/yolov5/wiki/GCP-Quickstart">
+  <a href="https://docs.ultralytics.com/yolov5/environments/google_cloud_quickstart_tutorial/">
     <img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-gcp-small.png" width="10%" /></a>
 </div>
 
@@ -456,7 +456,7 @@ YOLOv5 在两种不同的 License 下可用：
 
 ## <div align="center">联系我们</div>
 
-请访问 [GitHub Issues](https://github.com/ultralytics/yolov5/issues) 或 [Ultralytics Community Forum](https://community.ultralytis.com) 以报告 YOLOv5 错误和请求功能。
+请访问 [GitHub Issues](https://github.com/ultralytics/yolov5/issues) 或 [Ultralytics Community Forum](https://community.ultralytics.com) 以报告 YOLOv5 错误和请求功能。
 
 <br>
 <div align="center">

diff --git a/utils/loggers/comet/README.md b/utils/loggers/comet/README.md
@@ -164,7 +164,7 @@ env COMET_LOG_PER_CLASS_METRICS=true python train.py \
 
 If you would like to store your data using [Comet Artifacts](https://www.comet.com/docs/v2/guides/data-management/using-artifacts/#learn-more?utm_source=yolov5&utm_medium=partner&utm_campaign=partner_yolov5_2022&utm_content=github), you can do so using the `upload_dataset` flag.
 
-The dataset be organized in the way described in the [YOLOv5 documentation](https://docs.ultralytics.com/tutorials/train-custom-datasets/#3-organize-directories). The dataset config `yaml` file must follow the same format as that of the `coco128.yaml` file.
+The dataset be organized in the way described in the [YOLOv5 documentation](https://docs.ultralytics.com/yolov5/tutorials/train_custom_data/). The dataset config `yaml` file must follow the same format as that of the `coco128.yaml` file.
 
 ```shell
 python train.py \