Welcome to YOLOX’s documentation!

Quick Run

• Get Started
  • 1.Installation
  • 2.Demo
  • 3.Reproduce our results on COCO
  • 4.Evaluation
• Model Zoo
  • Standard Models.
  • Light Models.

Tutorials

• Train Custom Data
  • 0. Before you start
  • 1. Create your own dataset
  • 2. Create your Exp file to control everything
  • 3. Train
  • 4. Tips for Best Training Results

Demployment

• YOLOX-TensorRT in Python
  • Install TensorRT Toolkit
  • Convert model
  • Demo
• YOLOX-TensorRT in C++
  • Step 1: Prepare serialized engine file
  • Step 2: build the demo
• YOLOX-CPP-MegEngine
  • Tutorial
  • Bechmark
  • Acknowledgement
• YOLOX-Python-MegEngine
  • Tutorial
• YOLOX-Android-ncnn
  • Tutorial
  • Reference
• YOLOX-CPP-ncnn
  • Tutorial
  • Acknowledgement
• YOLOX-ONNXRuntime in Python
  • Download ONNX models.
  • Convert Your Model to ONNX
  • ONNXRuntime Demo
• YOLOX-OpenVINO in Python
  • Download OpenVINO models.
  • Install OpenVINO Toolkit
  • Set up the Environment
  • Convert model
  • Demo
• YOLOX-OpenVINO in C++
  • Download OpenVINO models.
  • Install OpenVINO Toolkit
  • Set up the Environment
  • Convert model
  • Build
  • Demo