mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-05-14 20:48:00 +00:00
cf19c3697d
### Description
Run clang-format in CI. Formatted all c/c++, objective-c/c++ files.
Excluded
```
'onnxruntime/core/mlas/**',
'onnxruntime/contrib_ops/cuda/bert/tensorrt_fused_multihead_attention/**',
```
because they contain assembly or is data heavy
### Motivation and Context
Coding style consistency
58 lines
No EOL
2 KiB
C++
58 lines
No EOL
2 KiB
C++
#include "winrt/Windows.Graphics.Imaging.h"
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#include "winrt/Windows.Graphics.h"
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#include "winrt/Windows.Media.h"
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#include "winrt/microsoft.ai.machinelearning.h"
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#include "winrt/windows.foundation.collections.h"
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#include "winrt/windows.foundation.h"
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#include "winrt/windows.storage.h"
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#include <stdio.h>
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#include <windows.h>
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EXTERN_C IMAGE_DOS_HEADER __ImageBase;
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using namespace winrt::Microsoft::AI::MachineLearning;
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using namespace winrt::Windows::Storage;
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using namespace winrt::Windows::Media;
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using namespace winrt::Windows::Graphics::Imaging;
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std::wstring GetModulePath()
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{
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std::wstring val;
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wchar_t modulePath[MAX_PATH] = {0};
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GetModuleFileNameW((HINSTANCE)&__ImageBase, modulePath, _countof(modulePath));
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wchar_t drive[_MAX_DRIVE];
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wchar_t dir[_MAX_DIR];
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wchar_t filename[_MAX_FNAME];
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wchar_t ext[_MAX_EXT];
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_wsplitpath_s(modulePath, drive, _MAX_DRIVE, dir, _MAX_DIR, filename, _MAX_FNAME, ext, _MAX_EXT);
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val = drive;
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val += dir;
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return val;
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}
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int main()
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{
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printf("Load squeezenet.onnx.\n");
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auto model = LearningModel::LoadFromFilePath(L"squeezenet.onnx");
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printf("Load kitten_224.png as StorageFile.\n");
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auto name = GetModulePath() + L"kitten_224.png";
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auto image = StorageFile::GetFileFromPathAsync(name).get();
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printf("Load StorageFile into Stream.\n");
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auto stream = image.OpenAsync(FileAccessMode::Read).get();
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printf("Create SoftwareBitmap from decoded Stream.\n");
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auto softwareBitmap = BitmapDecoder::CreateAsync(stream).get().GetSoftwareBitmapAsync().get();
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printf("Create VideoFrame.\n");
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auto frame = VideoFrame::CreateWithSoftwareBitmap(softwareBitmap);
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printf("Create LearningModelSession.\n");
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auto session = LearningModelSession(model);
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printf("Create LearningModelBinding.\n");
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auto binding = LearningModelBinding(session);
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printf("Bind data_0.\n");
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binding.Bind(L"data_0", frame);
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printf("Evaluate.\n");
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auto results = session.Evaluate(binding, L"");
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printf("Success!\n");
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return 0;
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} |