How to Change Model Inference Backend

FastDeploy supports various backends, including

OpenVINO (supports Paddle/ONNX formats, CPU inference only )
ONNX Runtime (supports Paddle/ONNX formats, inference on CPU/GPU)
TensorRT (supports Paddle/ONNX formats, GPU inference only）
Paddle Inference (supports Paddle format, inference on CPU/GPU)

All models can backend via RuntimeOption

Python

import fastdeploy as fd
option = fd.RuntimeOption()

# Change CPU/GPU
option.use_cpu()
option.use_gpu()

# Change the Backend
option.use_paddle_backend() # Paddle Inference
option.use_trt_backend() # TensorRT
option.use_openvino_backend() # OpenVINO
option.use_ort_backend() # ONNX Runtime

C++

fastdeploy::RuntimeOption option;

// Change CPU/GPU
option.UseCpu();
option.UseGpu();

// Change the Backend
option.UsePaddleBackend(); // Paddle Inference
option.UseTrtBackend(); // TensorRT
option.UseOpenVINOBackend(); // OpenVINO
option.UseOrtBackend(); // ONNX Runtime

For more specific demos, please refer to python or c++ inference code for different models under FastDeploy/examples/vision

For more deployment methods, please refer to FastDeploy API tutorials.