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• The YOLOR deployment is based on the code of YOLOR and Pre-trained Model Based on COCO.

  • （1）The *.pt provided by Official Repository should Export the ONNX Model to complete the deployment. The *.pose model’s deployment is not supported；
  • （2）The ScaledYOLOv4 model trained by personal data should Export the ONNX Model. Please refer to Detailed Deployment Documents to complete the deployment.

Visit the official YOLOR github repository, follow the guidelines to download the yolor.pt model, and employ models/export.py to get the file in onnx format. If the exported onnx model has a substandard accuracy or other problems about data dimension, you can refer to yolor#32 for the solution.

# Download yolor model file
wget https://github.com/WongKinYiu/yolor/releases/download/weights/yolor-d6-paper-570.pt

# Export the file in onnx format
python models/export.py  --weights PATH/TO/yolor-xx-xx-xx.pt --img-size 640

For developers' testing, models exported by YOLOR are provided below. Developers can download them directly. (The accuracy in the following table is derived from the source official repository)

• Python Deployment
• C++ Deployment

• Document and code are based on YOLOR weights