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FastDeploy C++ API Summary

Runtime

FastDeploy Runtime can be used as an inference engine with the same code, we can deploy Paddle/ONNX model on different device by different backends.
Currently, FastDeploy supported backends listed as below,

Backend Hardware Support Model Format Platform
Paddle Inference CPU/Nvidia GPU Paddle Windows(x64)/Linux(x64)
ONNX Runtime CPU/Nvidia GPU Paddle/ONNX Windows(x64)/Linux(x64/aarch64)/Mac(x86/arm64)
TensorRT Nvidia GPU Paddle/ONNX Windows(x64)/Linux(x64)/Jetson
OpenVINO CPU Paddle/ONNX Windows(x64)/Linux(x64)/Mac(x86)
Poros CPU/Nvidia GPU TorchScript Linux(x64)

Example code

Related APIs

Vision Models

Task Model API Example
object detection PaddleDetection/PPYOLOE fastdeploy::vision::detection::PPYOLOE C++/Python
image classification PaddleClassification serials fastdeploy::vision::classification::PaddleClasModel C++/Python
semantic segmentation PaddleSegmentation serials fastdeploy::vision::classification::PaddleSegModel C++/Python