diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index 596f3e5f..c2aca220 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -34,7 +34,7 @@ jobs: uses: actions/checkout@v4 with: repository: ${{ github.event.pull_request.head.repo.full_name || github.repository }} - token: ${{ secrets.GITHUB_TOKEN }} + token: ${{ secrets.PERSONAL_ACCESS_TOKEN || secrets.GITHUB_TOKEN }} ref: ${{ github.head_ref || github.ref }} fetch-depth: 0 - name: Set up Python diff --git a/docs/en/guides/streamlit-live-inference.md b/docs/en/guides/streamlit-live-inference.md index 9220ab51..69de0996 100644 --- a/docs/en/guides/streamlit-live-inference.md +++ b/docs/en/guides/streamlit-live-inference.md @@ -10,6 +10,17 @@ keywords: Streamlit, YOLOv8, Real-time Object Detection, Streamlit Application, Streamlit makes it simple to build and deploy interactive web applications. Combining this with Ultralytics YOLOv8 allows for real-time object detection and analysis directly in your browser. YOLOv8 high accuracy and speed ensure seamless performance for live video streams, making it ideal for applications in security, retail, and beyond. +

+
+ +
+ Watch: How to Use Streamlit with Ultralytics for Real-Time Computer Vision in Your Browser +

+ | Aquaculture | Animals husbandry | | :---------------------------------------------------------------------------------------------------------------------------------------------: | :------------------------------------------------------------------------------------------------------------------------------------------------: | | ![Fish Detection using Ultralytics YOLOv8](https://github.com/RizwanMunawar/RizwanMunawar/assets/62513924/ea6d7ece-cded-4db7-b810-1f8433df2c96) | ![Animals Detection using Ultralytics YOLOv8](https://github.com/RizwanMunawar/RizwanMunawar/assets/62513924/2e1f4781-60ab-4e72-b3e4-726c10cd223c) |