Add docs for the fns candy demo (#1479)

microsoft · Jul 24, 2019 · 91d32c9 · 91d32c9
1 parent a8e9e18
commit 91d32c9
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Showing 5 changed files with 103 additions and 26 deletions.
diff --git a/samples/c_cxx/CMakeLists.txt b/samples/c_cxx/CMakeLists.txt
@@ -21,10 +21,22 @@ option(onnxruntime_USE_NGRAPH "Build with nGraph support" OFF)
 option(onnxruntime_USE_NUPHAR "Build with Nuphar" OFF)
 option(onnxruntime_USE_BRAINSLICE "Build with BrainSlice" OFF)
 option(onnxruntime_USE_TENSORRT "Build with TensorRT support" OFF)
+option(LIBPNG_ROOTDIR "libpng root dir")
 
 #if JPEG lib is available, we'll use it for image decoding, otherwise we'll use WIC
 find_package(JPEG)
-find_package(PNG)
+if(LIBPNG_ROOTDIR)
+  set(PNG_FOUND true)
+  if(WIN32)
+    set(PNG_LIBRARIES debug libpng16_d optimized libpng16)
+  else()
+    set(PNG_LIBRARIES png16)
+  endif()
+  set(PNG_INCLUDE_DIRS "${LIBPNG_ROOTDIR}/include")
+  set(PNG_LIBDIR "${LIBPNG_ROOTDIR}/lib")
+else()
+  find_package(PNG)
+endif()
 
 if(onnxruntime_USE_CUDA)
   add_definitions(-DUSE_CUDA)

diff --git a/samples/c_cxx/README.md b/samples/c_cxx/README.md
@@ -9,6 +9,9 @@ This directory contains a few C/C++ sample applications for demoing onnxruntime
 ## Prerequisites
 1. Visual Studio 2015/2017/2019
 2. cmake(version >=3.13)
+3. (optional) [libpng 1.6](http://www.libpng.org/pub/png/libpng.html)
+
+You may get a precompiled libpng library from [https://onnxruntimetestdata.blob.core.windows.net/models/libpng.zip](https://onnxruntimetestdata.blob.core.windows.net/models/libpng.zip)
 
 ## Install ONNX Runtime
 You may either get a prebuit onnxruntime from nuget.org, or build it from source by following the [BUILD.md document](../../../BUILD.md). 
@@ -26,8 +29,9 @@ When the solution is loaded, change the build configuration to "RelWithDebInfo"(
 Open cmd.exe, change your current directory to samples\c_cxx, then run
 ```bat
 mkdir build
-cmake .. -A x64 -T host=x64
+cmake .. -A x64 -T host=x64 -DLIBPNG_ROOTDIR=C:\path\to\your\libpng\binary
 ```
+You may omit the "-DLIBPNG_ROOTDIR=..." argument if you don't have the libpng library.     
 You may append "-Donnxruntime_USE_CUDA=ON" to the last command args if your onnxruntime binary was built with CUDA support.
 
 Then you can open the onnxruntime_samples.sln file in the "build" directory and build the solution.

diff --git a/samples/c_cxx/fns_candy_style_transfer/CMakeLists.txt b/samples/c_cxx/fns_candy_style_transfer/CMakeLists.txt
@@ -3,4 +3,7 @@
 
 add_executable(fns_candy_style_transfer "fns_candy_style_transfer.c")
 target_include_directories(fns_candy_style_transfer PRIVATE ${PROJECT_SOURCE_DIR}/include ${PNG_INCLUDE_DIRS})
-target_link_libraries(fns_candy_style_transfer PRIVATE onnxruntime ${PNG_LIBRARIES})
+target_link_libraries(fns_candy_style_transfer PRIVATE onnxruntime ${PNG_LIBRARIES})
+if(PNG_LIBDIR)
+  target_link_directories(fns_candy_style_transfer PRIVATE ${PNG_LIBDIR})
+endif()
diff --git a/samples/c_cxx/fns_candy_style_transfer/README.md b/samples/c_cxx/fns_candy_style_transfer/README.md
@@ -0,0 +1,19 @@
+# Build 
+See [../README.md](../README.md)
+
+# Prepare data
+Please download the model from (candy.onnx)[https://raw.githubusercontent.com/microsoft/Windows-Machine-Learning/master/Samples/FNSCandyStyleTransfer/UWP/cs/Assets/candy.onnx]
+
+Then prepare an image:
+1. In png format
+2. With dimension of 720x720
+
+# Run
+```
+fns_candy_style_transfer.exe <model_path> <input_image_path> <output_image_path>
+```
+
+
+
+
+
diff --git a/samples/c_cxx/fns_candy_style_transfer/fns_candy_style_transfer.c b/samples/c_cxx/fns_candy_style_transfer/fns_candy_style_transfer.c
@@ -5,8 +5,10 @@
 #include <stdio.h>
 #include <assert.h>
 #include <png.h>
-
-#define ORT_THROW_ON_ERROR(expr)                         \
+#ifdef _WIN32
+#include <objbase.h>
+#endif
+#define ORT_ABORT_ON_ERROR(expr)                         \
   do {                                                   \
     OrtStatus* onnx_status = (expr);                     \
     if (onnx_status != NULL) {                           \
@@ -94,21 +96,21 @@ static int read_png_file(const char* input_file, size_t* height, size_t* width,
  */
 static int write_tensor_to_png_file(OrtValue* tensor, const char* output_file) {
   struct OrtTensorTypeAndShapeInfo* shape_info;
-  ORT_THROW_ON_ERROR(OrtGetTensorTypeAndShape(tensor, &shape_info));
+  ORT_ABORT_ON_ERROR(OrtGetTensorTypeAndShape(tensor, &shape_info));
   size_t dim_count;
-  ORT_THROW_ON_ERROR(OrtGetDimensionsCount(shape_info, &dim_count));
+  ORT_ABORT_ON_ERROR(OrtGetDimensionsCount(shape_info, &dim_count));
   if (dim_count != 4) {
     printf("output tensor must have 4 dimensions");
     return -1;
   }
   int64_t dims[4];
-  ORT_THROW_ON_ERROR(OrtGetDimensions(shape_info, dims, sizeof(dims) / sizeof(dims[0])));
+  ORT_ABORT_ON_ERROR(OrtGetDimensions(shape_info, dims, sizeof(dims) / sizeof(dims[0])));
   if (dims[0] != 1 || dims[1] != 3) {
     printf("output tensor shape error");
     return -1;
   }
   float* f;
-  ORT_THROW_ON_ERROR(OrtGetTensorMutableData(tensor, (void**)&f));
+  ORT_ABORT_ON_ERROR(OrtGetTensorMutableData(tensor, (void**)&f));
   png_bytep model_output_bytes;
   png_image image;
   memset(&image, 0, (sizeof image));
@@ -129,12 +131,33 @@ static int write_tensor_to_png_file(OrtValue* tensor, const char* output_file) {
 
 static void usage() { printf("usage: <model_path> <input_file> <output_file> \n"); }
 
-int run_inference(OrtSession* session, const char* input_file, const char* output_file) {
+static char* convert_string(const wchar_t* input) {
+  size_t src_len = wcslen(input) + 1;
+  if (src_len > INT_MAX) {
+    printf("size overflow\n");
+    abort();
+  }
+  const int len = WideCharToMultiByte(CP_ACP, 0, input, (int)src_len, NULL, 0, NULL, NULL);
+  assert(len > 0);
+  char* ret = (char*)malloc(len);
+  assert(ret != NULL);
+  const int r = WideCharToMultiByte(CP_ACP, 0, input, (int)src_len, ret, len, NULL, NULL);
+  assert(len == r);
+  return ret;
+}
+
+int run_inference(OrtSession* session, const ORTCHAR_T* input_file, const ORTCHAR_T* output_file) {
   size_t input_height;
   size_t input_width;
   float* model_input;
   size_t model_input_ele_count;
-  if (read_png_file(input_file, &input_height, &input_width, &model_input, &model_input_ele_count) != 0) {
+#ifdef _WIN32
+  char* output_file_p = convert_string(output_file);
+  char* input_file_p = convert_string(input_file);
+#else
+  char* input_file_p = input_file;
+#endif
+  if (read_png_file(input_file_p, &input_height, &input_width, &model_input, &model_input_ele_count) != 0) {
     return -1;
   }
   if (input_height != 720 || input_width != 720) {
@@ -143,69 +166,82 @@ int run_inference(OrtSession* session, const char* input_file, const char* outpu
     return -1;
   }
   OrtAllocatorInfo* allocator_info;
-  ORT_THROW_ON_ERROR(OrtCreateCpuAllocatorInfo(OrtArenaAllocator, OrtMemTypeDefault, &allocator_info));
+  ORT_ABORT_ON_ERROR(OrtCreateCpuAllocatorInfo(OrtArenaAllocator, OrtMemTypeDefault, &allocator_info));
   const int64_t input_shape[] = {1, 3, 720, 720};
   const size_t input_shape_len = sizeof(input_shape) / sizeof(input_shape[0]);
   const size_t model_input_len = model_input_ele_count * sizeof(float);
 
   OrtValue* input_tensor = NULL;
-  ORT_THROW_ON_ERROR(OrtCreateTensorWithDataAsOrtValue(allocator_info, model_input, model_input_len, input_shape,
+  ORT_ABORT_ON_ERROR(OrtCreateTensorWithDataAsOrtValue(allocator_info, model_input, model_input_len, input_shape,
                                                        input_shape_len, ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT,
                                                        &input_tensor));
   assert(input_tensor != NULL);
   int is_tensor;
-  ORT_THROW_ON_ERROR(OrtIsTensor(input_tensor, &is_tensor));
+  ORT_ABORT_ON_ERROR(OrtIsTensor(input_tensor, &is_tensor));
   assert(is_tensor);
   OrtReleaseAllocatorInfo(allocator_info);
   const char* input_names[] = {"inputImage"};
   const char* output_names[] = {"outputImage"};
   OrtValue* output_tensor = NULL;
-  ORT_THROW_ON_ERROR(
+  ORT_ABORT_ON_ERROR(
       OrtRun(session, NULL, input_names, (const OrtValue* const*)&input_tensor, 1, output_names, 1, &output_tensor));
   assert(output_tensor != NULL);
-  ORT_THROW_ON_ERROR(OrtIsTensor(output_tensor, &is_tensor));
+  ORT_ABORT_ON_ERROR(OrtIsTensor(output_tensor, &is_tensor));
   assert(is_tensor);
   int ret = 0;
-  if (write_tensor_to_png_file(output_tensor, output_file) != 0) {
+  if (write_tensor_to_png_file(output_tensor, output_file_p) != 0) {
     ret = -1;
   }
   OrtReleaseValue(output_tensor);
   OrtReleaseValue(input_tensor);
   free(model_input);
+#ifdef _WIN32
+  free(input_file_p);
+  free(output_file_p);
+#endif  // _WIN32
   return ret;
 }
 
 void verify_input_output_count(OrtSession* session) {
   size_t count;
-  ORT_THROW_ON_ERROR(OrtSessionGetInputCount(session, &count));
+  ORT_ABORT_ON_ERROR(OrtSessionGetInputCount(session, &count));
   assert(count == 1);
-  ORT_THROW_ON_ERROR(OrtSessionGetOutputCount(session, &count));
+  ORT_ABORT_ON_ERROR(OrtSessionGetOutputCount(session, &count));
   assert(count == 1);
 }
 
 #ifdef USE_CUDA
 void enable_cuda(OrtSessionOptions* session_options) {
-  ORT_THROW_ON_ERROR(OrtSessionOptionsAppendExecutionProvider_CUDA(session_options, 0));
+  ORT_ABORT_ON_ERROR(OrtSessionOptionsAppendExecutionProvider_CUDA(session_options, 0));
 }
 #endif
 
+#ifdef _WIN32
+int wmain(int argc, wchar_t* argv[]) {
+#else
 int main(int argc, char* argv[]) {
+#endif
   if (argc < 4) {
     usage();
     return -1;
   }
-  char* model_path = argv[1];
-  char* input_file = argv[2];
-  char* output_file = argv[3];
+#ifdef _WIN32
+  //CoInitializeEx is only needed if Windows Image Component will be used in this program for image loading/saving.
+  HRESULT hr = CoInitializeEx(NULL, COINIT_MULTITHREADED);
+  if (!SUCCEEDED(hr)) return -1;
+#endif
+  ORTCHAR_T* model_path = argv[1];
+  ORTCHAR_T* input_file = argv[2];
+  ORTCHAR_T* output_file = argv[3];
   OrtEnv* env;
-  ORT_THROW_ON_ERROR(OrtCreateEnv(ORT_LOGGING_LEVEL_WARNING, "test", &env));
+  ORT_ABORT_ON_ERROR(OrtCreateEnv(ORT_LOGGING_LEVEL_WARNING, "test", &env));
   OrtSessionOptions* session_options;
-  ORT_THROW_ON_ERROR(OrtCreateSessionOptions(&session_options));
+  ORT_ABORT_ON_ERROR(OrtCreateSessionOptions(&session_options));
 #ifdef USE_CUDA
   enable_cuda(session_options);
 #endif
   OrtSession* session;
-  ORT_THROW_ON_ERROR(OrtCreateSession(env, model_path, session_options, &session));
+  ORT_ABORT_ON_ERROR(OrtCreateSession(env, model_path, session_options, &session));
   verify_input_output_count(session);
   int ret = run_inference(session, input_file, output_file);
   OrtReleaseSessionOptions(session_options);
@@ -214,5 +250,8 @@ int main(int argc, char* argv[]) {
   if (ret != 0) {
     fprintf(stderr, "fail\n");
   }
+#ifdef _WIN32
+  CoUninitialize();
+#endif
   return ret;
 }