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  • Introduction
  • Contributing
  • Versions
  • v1.x.x
    • 🚀 Getting Started
      • 🛠️ Installation
      • 📂 Project Structure
    • Pipeless REST API
    • Stream Formats and Protocols
    • Inference Runtimes
    • Key Value Store
    • 🐋 Container images
    • Deploying your application
    • Ready to Use CV Models
      • Tensorflow
        • Multi-pose estimation Tensorflow Model
    • Export and monitor stream events
    • 🌟 Examples
      • Adding wattermarks
      • Passing data between hooks and stages
      • Detecting Cats on a Video
      • Pose detection with TensorFlow
      • Object detection - YOLOv8 Python lib
      • ONXX Runtime - Candy filter
      • ONNX Runtime - Object detection with YOLO
      • ONNX Runtime - PPE detection with YOLO-World
      • Play a piano with your eyes by looking to the notes
      • Object tracking - YOLO and Norfair
    • Benchmark
    • Version Notable Changes
    • Troubleshooting
    • Processing Restart Policy
  • v0.x.x
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v1.x.x
🌟 Examples

Examples 🌟

You can start by running some of the following application examples. They contain everything you need on each case so you can easily play with them:

  • Add Wattermark
  • Cats Recognition
  • Multipose detection with TensorFlow
  • YOLOv8 object detection
  • Object detection using the ONNX Runtime
  • PPE detection using the ONNX Runtime and YOLO-World
  • Candy filter with ONNX Runtime
  • Passing data between hooks and stages
  • Object tracking with Norfair
Export and monitor stream eventsAdding wattermarks

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