インストールと運用 - 3.5 日本語

tar -xzvf vitis_ai_2023.1-r3.5.0.tar.gz -C /

次に、voe-0.1.0-py3-none-any.whl と onnxruntime_vitisai-1.16.0-py3-none-any.whl をダウンロードします。デバイスがオンラインであることを確認し、これらをオンラインでインストールします。

pip3 install voe*.whl
pip3 install onnxruntime_vitisai*.whl

// ...
#include <experimental_onnxruntime_cxx_api.h>
// include user header files
// ...

auto onnx_model_path = "resnet50_pt.onnx"
Ort::Env env(ORT_LOGGING_LEVEL_WARNING, "resnet50_pt");
auto session_options = Ort::SessionOptions();

auto options = std::unorderd_map<std::string,std::string>({});
options["config_file"] = "/etc/vaip_config.json";
// optional, eg: cache path : /tmp/my_cache/abcdefg // Replace abcdefg with your model name, eg. onnx_model_md5
options["cacheDir"] = "/tmp/my_cache";
options["cacheKey"] = "abcdefg"; // Replace abcdefg with your model name, eg. onnx_model_md5

// Create an inference session using the Vitis AI execution provider
session_options.AppendExecutionProvider("VitisAI", options);

auto session = Ort::Experimental::Session(env, model_name, session_options);

auto input_shapes = session.GetInputShapes();
// preprocess input data
// ...

// Create input tensors and populate input data
std::vector<Ort::Value> input_tensors;
input_tensors.push_back(Ort::Experimental::Value::CreateTensor<float>(
input_data.data(), input_data.size(), input_shapes[0]));

auto output_tensors = session.Run(session.GetInputNames(), input_tensors,
session.GetOutputNames());
// postprocess output data
// ...

import onnxruntime

# Add other imports
# ...

# Load inputs and do preprocessing
# ...

# Create an inference session using the Vitis-AI execution provider

session = onnxruntime.InferenceSession(
'[model_file].onnx',
providers=["VitisAIExecutionProvider"],
provider_options=[{"config_file":"/etc/vaip_config.json"}])

input_shape = session.get_inputs()[0].shape
input_name = session.get_inputs()[0].name

# Load inputs and do preprocessing by input_shape
input_data = [...]
result = session.run([], {input_name: input_data})

result=0 && pkg-config --list-all | grep opencv4 && result=1
if [ $result -eq 1 ]; then
	OPENCV_FLAGS=$(pkg-config --cflags --libs-only-L opencv4)
else
	OPENCV_FLAGS=$(pkg-config --cflags --libs-only-L opencv)
fi

lib_x=" -lglog -lunilog -lvitis_ai_library-xnnpp -lvitis_ai_library-model_config -lprotobuf -lxrt_core -lvart-xrt-device-handle -lvaip-core -lxcompiler-core -labsl_city -labsl_low_level_hash -lvart-dpu-controller -lxir -lvart-util -ltarget-factory -ljson-c" 
lib_onnx=" -lonnxruntime" 
lib_opencv=" -lopencv_videoio -lopencv_imgcodecs -lopencv_highgui -lopencv_imgproc -lopencv_core " 
inc_x=" -I=/usr/include/onnxruntime -I=/install/Release/include/onnxruntime -I=/install/Release/include -I=/usr/include/xrt " 
link_x=" -L=/install/Release/lib" 

name=$(basename $PWD)

CXX=${CXX:-g++}
$CXX -O2 -fno-inline -I. \
 ${inc_x} \
 ${link_x} \
 -o ${name}_onnx -std=c++17 \
 $PWD/${name}_onnx.cpp \
 ${OPENCV_FLAGS} \
 ${lib_opencv} \
 ${lib_x} \
 ${lib_onnx} 

sh -x build.sh

./resnet50_onnx <Onnx model> <image>