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README.md

build_engine

The build_engine tool takes the YOLOv5 model expressed in ONNX form, and creates a TensorRT engine based on it. This TensorRT engine is optimized for the specific hardware being used, and can be used repeadetly for object detection. Note that you can export your trained YOLOv5 model to ONNX using the official YOLOv5 guide.

Basic usage:

./build_engine --model ONNX_MODEL --output OUTPUT_ENGINE

Arguments:

  • --model: path to the input ONNX model
  • --output: path at which the output engine should be written
  • --precision: (optional) the precision that should be used for the engine. The available options are "fp32" and "fp16". This argument is optional, and if it is not specified, the default "fp32" is used

Example Usage

Assuming that your YOLOv5 model is yolov5s.onnx (i.e. the S variant of YOLOv5), you can build an engine with FP16 inference as following:

./build_engine --model yolov5s.onnx --output yolov5s.engine --precision fp16

The resulting engine will be stored to disk as yolov5s.engine. After this, you may perform inference using one of the other tools, such as process_image.