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#include "winrt/Windows.Graphics.Imaging.h"
#include "winrt/Windows.Graphics.h"
#include "winrt/Windows.Media.h"
#include "winrt/microsoft.ai.machinelearning.h"
#include "winrt/windows.foundation.collections.h"
#include "winrt/windows.foundation.h"
#include "winrt/windows.storage.h"
#include <stdio.h>
#include <windows.h>
EXTERN_C IMAGE_DOS_HEADER __ImageBase;
using namespace winrt::Microsoft::AI::MachineLearning;
using namespace winrt::Windows::Storage;
using namespace winrt::Windows::Media;
using namespace winrt::Windows::Graphics::Imaging;
std::wstring GetModulePath()
{
std::wstring val;
wchar_t modulePath[MAX_PATH] = {0};
GetModuleFileNameW((HINSTANCE)&__ImageBase, modulePath, _countof(modulePath));
wchar_t drive[_MAX_DRIVE];
wchar_t dir[_MAX_DIR];
wchar_t filename[_MAX_FNAME];
wchar_t ext[_MAX_EXT];
_wsplitpath_s(modulePath, drive, _MAX_DRIVE, dir, _MAX_DIR, filename, _MAX_FNAME, ext, _MAX_EXT);
val = drive;
val += dir;
return val;
}
int main()
{
printf("Load squeezenet.onnx.\n");
auto model = LearningModel::LoadFromFilePath(L"squeezenet.onnx");
printf("Load kitten_224.png as StorageFile.\n");
auto name = GetModulePath() + L"kitten_224.png";
auto image = StorageFile::GetFileFromPathAsync(name).get();
printf("Load StorageFile into Stream.\n");
auto stream = image.OpenAsync(FileAccessMode::Read).get();
printf("Create SoftwareBitmap from decoded Stream.\n");
auto softwareBitmap = BitmapDecoder::CreateAsync(stream).get().GetSoftwareBitmapAsync().get();
printf("Create VideoFrame.\n");
auto frame = VideoFrame::CreateWithSoftwareBitmap(softwareBitmap);
printf("Create LearningModelSession.\n");
auto session = LearningModelSession(model);
printf("Create LearningModelBinding.\n");
auto binding = LearningModelBinding(session);
printf("Bind data_0.\n");
binding.Bind(L"data_0", frame);
printf("Evaluate.\n");
auto results = session.Evaluate(binding, L"");
printf("Success!\n");
return 0;
}
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