ultralytics 8.0.53 DDP AMP and Edge TPU fixes (ultralytics#1362)

Co-authored-by: Richard Aljaste <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Vuong Kha Sieu <[email protected]>

.github/workflows/ci.yaml

@@ -103,7 +103,7 @@ jobs:
         shell: python
         run: |
           from ultralytics.yolo.utils.benchmarks import benchmark
-          benchmark(model='${{ matrix.model }}-cls.pt', imgsz=160, half=False, hard_fail=0.60)
+          benchmark(model='${{ matrix.model }}-cls.pt', imgsz=160, half=False, hard_fail=0.61)
       - name: Benchmark Summary
         run: cat benchmarks.log
 

.github/workflows/publish.yml

@@ -61,7 +61,9 @@ jobs:
       - name: Deploy Docs
         continue-on-error: true
         if: (github.event_name == 'push' && steps.check_pypi.outputs.increment == 'True') || github.event.inputs.docs == 'true'
+        env:
+          PERSONAL_ACCESS_TOKEN: ${{ secrets.PERSONAL_ACCESS_TOKEN }}
         run: |
           mkdocs gh-deploy || true
           git checkout gh-pages
-          git push https://${{ secrets.PERSONAL_ACCESS_TOKEN }}@github.com/ultralytics/docs gh-pages --force
+          git push https://[email protected]/ultralytics/docs gh-pages --force

README.md

@@ -240,7 +240,7 @@ on your experience. Thank you 🙏 to all our contributors!
 <!-- SVG image from https://opencollective.com/ultralytics/contributors.svg?width=990 -->
 
 <a href="https://github.com/ultralytics/yolov5/graphs/contributors">
-<img src="https://github.com/ultralytics/assets/raw/main/im/image-contributors.png" /></a>
+<img width="100%" src="https://github.com/ultralytics/assets/raw/main/im/image-contributors.png"></a>
 
 ## <div align="center">License</div>
 

README.zh-CN.md

@@ -219,7 +219,7 @@ Ultralytics [发布页](https://github.com/ultralytics/ultralytics/releases) 自
 <!-- SVG image from https://opencollective.com/ultralytics/contributors.svg?width=990 -->
 
 <a href="https://github.com/ultralytics/yolov5/graphs/contributors">
-<img src="https://github.com/ultralytics/assets/raw/main/im/image-contributors.png" /></a>
+<img width="100%" src="https://github.com/ultralytics/assets/raw/main/im/image-contributors.png"></a>
 
 ## <div align="center">License</div>
 

docs/app.md

@@ -3,7 +3,6 @@
 <a href="https://bit.ly/ultralytics_hub" target="_blank">
 <img width="100%" src="https://github.com/ultralytics/assets/raw/main/im/ultralytics-hub.png"></a>
 <br>
-<br>
 <div align="center">
   <a href="https://github.com/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="2%" alt="" /></a>
@@ -27,26 +26,26 @@
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-instagram.png" width="2%" alt="" /></a>
   <br>
   <br>
-  <a href="https://github.com/ultralytics/hub/actions/workflows/ci.yaml">
-    <img src="https://github.com/ultralytics/hub/actions/workflows/ci.yaml/badge.svg" alt="CI CPU"></a>
-  <a href="https://colab.research.google.com/github/ultralytics/hub/blob/master/hub.ipynb">
-    <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> 
+  <a href="https://play.google.com/store/apps/details?id=com.ultralytics.ultralytics_app" style="text-decoration:none;">
+    <img src="https://raw.githubusercontent.com/ultralytics/assets/master/app/google-play.svg" width="15%" alt="" /></a>&nbsp;
+  <a href="https://apps.apple.com/xk/app/ultralytics/id1583935240" style="text-decoration:none;">
+    <img src="https://raw.githubusercontent.com/ultralytics/assets/master/app/app-store.svg" width="15%" alt="" /></a>
 </div>
-<br>
 
-Welcome to the Ultralytics HUB app for demonstrating YOLOv5 and YOLOv8 models! In this app, available on the [Apple App
-Store](https://apps.apple.com/xk/app/ultralytics/id1583935240) and the
-[Google Play Store](https://play.google.com/store/apps/details?id=com.ultralytics.ultralytics_app), you will be able
-to see the power and capabilities of YOLOv5, a state-of-the-art object detection model developed by Ultralytics.
+Welcome to the Ultralytics HUB app, which is designed to demonstrate the power and capabilities of the YOLOv5 and YOLOv8
+models. This app is available for download on
+the [Apple App Store](https://apps.apple.com/xk/app/ultralytics/id1583935240) and
+the [Google Play Store](https://play.google.com/store/apps/details?id=com.ultralytics.ultralytics_app).
 
-**To install simply scan the QR code above**. The App currently features YOLOv5 models, with YOLOv8 models coming soon.
+**To install the app, simply scan the QR code provided above**. At the moment, the app features YOLOv5 models, with
+YOLOv8 models set to be available soon.
 
-With YOLOv5, you can detect and classify objects in images and videos with high accuracy and speed. The model has been
-trained on a large dataset and is able to detect a wide range of objects, including cars, pedestrians, and traffic
-signs.
+With the YOLOv5 model, you can easily detect and classify objects in images and videos with high accuracy and speed. The
+model has been trained on a vast dataset and can recognize a wide range of objects, including pedestrians, traffic
+signs, and cars.
 
-In this app, you will be able to try out YOLOv5 on your own images and videos, and see the model in action. You can also
-learn more about how YOLOv5 works and how it can be used in real-world applications.
+Using this app, you can try out YOLOv5 on your images and videos, and observe how the model works in real-time.
+Additionally, you can learn more about YOLOv5's functionality and how it can be integrated into real-world applications.
 
-We hope you enjoy using YOLOv5 and seeing its capabilities firsthand. Thank you for choosing Ultralytics for your object
-detection needs!
+We are confident that you will enjoy using YOLOv5 and be amazed at its capabilities. Thank you for choosing Ultralytics
+for your AI solutions.