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PiperOrigin-RevId: 570745425
This commit is contained in:
Daniel Cheng 2023-10-04 11:03:17 -07:00 committed by Copybara-Service
parent 3b99f8d9dd
commit d2baba6dbb
162 changed files with 961 additions and 919 deletions
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7
mediapipe/calculators/core/bypass_calculator.cc
View File

@ -92,7 +92,7 @@ class BypassCalculator : public Node {
auto options = cc->Options<BypassCalculatorOptions>();
RET_CHECK_EQ(options.pass_input_stream().size(),
options.pass_output_stream().size());
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto pass_streams,
GetPassMap(options, *cc->Inputs().TagMap(), *cc->Outputs().TagMap()));
std::set<CollectionItemId> pass_out;
@ -121,8 +121,9 @@ class BypassCalculator : public Node {
// Saves the map of passthrough input and output stream ids.
absl::Status Open(CalculatorContext* cc) override {
auto options = cc->Options<BypassCalculatorOptions>();
ASSIGN_OR_RETURN(pass_streams_, GetPassMap(options, *cc->Inputs().TagMap(),
*cc->Outputs().TagMap()));
MP_ASSIGN_OR_RETURN(
pass_streams_,
GetPassMap(options, *cc->Inputs().TagMap(), *cc->Outputs().TagMap()));
return absl::OkStatus();
}

6
mediapipe/calculators/image/affine_transformation_runner_gl.cc
View File

@ -223,7 +223,7 @@ class GlTextureWarpAffineRunner
absl::StrCat(mediapipe::kMediaPipeFragmentShaderPreamble,
interpolation_def, kFragShader);
ASSIGN_OR_RETURN(program_, create_fn(vert_src, frag_src));
MP_ASSIGN_OR_RETURN(program_, create_fn(vert_src, frag_src));
auto create_custom_zero_fn = [&]() -> absl::StatusOr<Program> {
std::string custom_zero_border_mode_def = R"(
@ -236,10 +236,10 @@ class GlTextureWarpAffineRunner
};
#if GL_CLAMP_TO_BORDER_MAY_BE_SUPPORTED
if (!IsGlClampToBorderSupported(gl_helper_->GetGlContext())) {
ASSIGN_OR_RETURN(program_custom_zero_, create_custom_zero_fn());
MP_ASSIGN_OR_RETURN(program_custom_zero_, create_custom_zero_fn());
}
#else
ASSIGN_OR_RETURN(program_custom_zero_, create_custom_zero_fn());
MP_ASSIGN_OR_RETURN(program_custom_zero_, create_custom_zero_fn());
#endif // GL_CLAMP_TO_BORDER_MAY_BE_SUPPORTED
glGenFramebuffers(1, &framebuffer_);

6
mediapipe/calculators/image/image_file_properties_calculator.cc
View File

@ -92,7 +92,7 @@ absl::StatusOr<ImageFileProperties> GetImageFileProperites(
properties.set_focal_length_mm(result.FocalLength);
properties.set_focal_length_35mm(result.FocalLengthIn35mm);
ASSIGN_OR_RETURN(auto focal_length_pixels,
MP_ASSIGN_OR_RETURN(auto focal_length_pixels,
ComputeFocalLengthInPixels(properties.image_width(),
properties.image_height(),
properties.focal_length_35mm(),
@ -151,7 +151,7 @@ class ImageFilePropertiesCalculator : public CalculatorBase {
if (cc->InputSidePackets().NumEntries() == 1) {
const std::string& image_bytes =
cc->InputSidePackets().Index(0).Get<std::string>();
ASSIGN_OR_RETURN(properties_, GetImageFileProperites(image_bytes));
MP_ASSIGN_OR_RETURN(properties_, GetImageFileProperites(image_bytes));
read_properties_ = true;
}
@ -169,7 +169,7 @@ class ImageFilePropertiesCalculator : public CalculatorBase {
return absl::OkStatus();
}
const std::string& image_bytes = cc->Inputs().Index(0).Get<std::string>();
ASSIGN_OR_RETURN(properties_, GetImageFileProperites(image_bytes));
MP_ASSIGN_OR_RETURN(properties_, GetImageFileProperites(image_bytes));
read_properties_ = true;
}
if (read_properties_) {

24
mediapipe/calculators/image/warp_affine_calculator.cc
View File

@ -79,8 +79,8 @@ class WarpAffineRunnerHolder<ImageFrame> {
}
absl::StatusOr<RunnerType*> GetRunner() {
if (!runner_) {
ASSIGN_OR_RETURN(runner_,
CreateAffineTransformationOpenCvRunner(interpolation_));
MP_ASSIGN_OR_RETURN(
runner_, CreateAffineTransformationOpenCvRunner(interpolation_));
}
return runner_.get();
}
@ -108,8 +108,9 @@ class WarpAffineRunnerHolder<mediapipe::GpuBuffer> {
}
absl::StatusOr<RunnerType*> GetRunner() {
if (!runner_) {
ASSIGN_OR_RETURN(runner_, CreateAffineTransformationGlRunner(
gl_helper_, gpu_origin_, interpolation_));
MP_ASSIGN_OR_RETURN(
runner_, CreateAffineTransformationGlRunner(gl_helper_, gpu_origin_,
interpolation_));
}
return runner_.get();
}
@ -151,23 +152,24 @@ class WarpAffineRunnerHolder<mediapipe::Image> {
AffineTransformation::BorderMode border_mode) override {
if (input.UsesGpu()) {
#if !MEDIAPIPE_DISABLE_GPU
ASSIGN_OR_RETURN(auto* runner, gpu_holder_.GetRunner());
ASSIGN_OR_RETURN(auto result, runner->Run(input.GetGpuBuffer(), matrix,
size, border_mode));
MP_ASSIGN_OR_RETURN(auto* runner, gpu_holder_.GetRunner());
MP_ASSIGN_OR_RETURN(
auto result,
runner->Run(input.GetGpuBuffer(), matrix, size, border_mode));
return mediapipe::Image(*result);
#else
return absl::UnavailableError("GPU support is disabled");
#endif // !MEDIAPIPE_DISABLE_GPU
}
#if !MEDIAPIPE_DISABLE_OPENCV
ASSIGN_OR_RETURN(auto* runner, cpu_holder_.GetRunner());
MP_ASSIGN_OR_RETURN(auto* runner, cpu_holder_.GetRunner());
const auto& frame_ptr = input.GetImageFrameSharedPtr();
// Wrap image into image frame.
const ImageFrame image_frame(frame_ptr->Format(), frame_ptr->Width(),
frame_ptr->Height(), frame_ptr->WidthStep(),
const_cast<uint8_t*>(frame_ptr->PixelData()),
[](uint8_t* data){});
ASSIGN_OR_RETURN(auto result,
MP_ASSIGN_OR_RETURN(auto result,
runner->Run(image_frame, matrix, size, border_mode));
return mediapipe::Image(std::make_shared<ImageFrame>(std::move(result)));
#else
@ -213,8 +215,8 @@ class WarpAffineCalculatorImpl : public mediapipe::api2::NodeImpl<InterfaceT> {
AffineTransformation::Size output_size;
output_size.width = out_width;
output_size.height = out_height;
ASSIGN_OR_RETURN(auto* runner, holder_.GetRunner());
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(auto* runner, holder_.GetRunner());
MP_ASSIGN_OR_RETURN(
auto result,
runner->Run(
*InterfaceT::kInImage(cc), transform, output_size,

8
mediapipe/calculators/tensor/audio_to_tensor_calculator.cc
View File

@ -517,7 +517,7 @@ absl::Status AudioToTensorCalculator::OutputTensor(const Matrix& block,
// The last two elements are Nyquist component.
fft_output_matrix(fft_size_ - 2) = fft_output_[1]; // Nyquist real part
fft_output_matrix(fft_size_ - 1) = 0.0f; // Nyquist imagery part
ASSIGN_OR_RETURN(output_tensor, ConvertToTensor(fft_output_matrix,
MP_ASSIGN_OR_RETURN(output_tensor, ConvertToTensor(fft_output_matrix,
{2, fft_size_ / 2}));
break;
}
@ -529,7 +529,7 @@ absl::Status AudioToTensorCalculator::OutputTensor(const Matrix& block,
// The last two elements are Nyquist component.
fft_output_matrix(fft_size_) = fft_output_[1]; // Nyquist real part
fft_output_matrix(fft_size_ + 1) = 0.0f; // Nyquist imagery part
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
output_tensor,
ConvertToTensor(fft_output_matrix, {2, (fft_size_ + 2) / 2}));
break;
@ -537,7 +537,7 @@ absl::Status AudioToTensorCalculator::OutputTensor(const Matrix& block,
case Options::WITHOUT_DC_AND_NYQUIST: {
Matrix fft_output_matrix =
Eigen::Map<const Matrix>(fft_output_.data() + 2, 1, fft_size_ - 2);
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
output_tensor,
ConvertToTensor(fft_output_matrix, {2, (fft_size_ - 2) / 2}));
break;
@ -547,7 +547,7 @@ absl::Status AudioToTensorCalculator::OutputTensor(const Matrix& block,
}
} else {
ASSIGN_OR_RETURN(output_tensor,
MP_ASSIGN_OR_RETURN(output_tensor,
ConvertToTensor(block, {num_channels_, num_samples_}));
}
kTensorsOut(cc).Send(std::move(output_tensor), timestamp);

2
mediapipe/calculators/tensor/bert_preprocessor_calculator.cc
View File

@ -161,7 +161,7 @@ absl::Status BertPreprocessorCalculator::Open(CalculatorContext* cc) {
&kMetadataExtractorSideIn(cc).Get();
const tflite::ProcessUnit* tokenizer_metadata =
metadata_extractor->GetInputProcessUnit(kTokenizerProcessUnitIndex);
ASSIGN_OR_RETURN(tokenizer_,
MP_ASSIGN_OR_RETURN(tokenizer_,
tasks::text::tokenizers::CreateTokenizerFromProcessUnit(
tokenizer_metadata, metadata_extractor));

7
mediapipe/calculators/tensor/bert_preprocessor_calculator_test.cc
View File

@ -67,9 +67,10 @@ absl::StatusOr<std::vector<std::vector<int>>> RunBertPreprocessorCalculator(
tool::AddVectorSink("tensors", &graph_config, &output_packets);
std::string model_buffer = tasks::core::LoadBinaryContent(model_path.data());
ASSIGN_OR_RETURN(std::unique_ptr<ModelMetadataExtractor> metadata_extractor,
ModelMetadataExtractor::CreateFromModelBuffer(
model_buffer.data(), model_buffer.size()));
MP_ASSIGN_OR_RETURN(
std::unique_ptr<ModelMetadataExtractor> metadata_extractor,
ModelMetadataExtractor::CreateFromModelBuffer(model_buffer.data(),
model_buffer.size()));
// Run the graph.
CalculatorGraph graph;
MP_RETURN_IF_ERROR(graph.Initialize(

19
mediapipe/calculators/tensor/image_to_tensor_calculator.cc
View File

@ -192,17 +192,18 @@ class ImageToTensorCalculator : public Node {
}
#if MEDIAPIPE_DISABLE_GPU
ASSIGN_OR_RETURN(auto image, GetInputImage(kIn(cc)));
MP_ASSIGN_OR_RETURN(auto image, GetInputImage(kIn(cc)));
#else
const bool is_input_gpu = kInGpu(cc).IsConnected();
ASSIGN_OR_RETURN(auto image, is_input_gpu ? GetInputImage(kInGpu(cc))
MP_ASSIGN_OR_RETURN(auto image, is_input_gpu ? GetInputImage(kInGpu(cc))
: GetInputImage(kIn(cc)));
#endif // MEDIAPIPE_DISABLE_GPU
RotatedRect roi = GetRoi(image->width(), image->height(), norm_rect);
const int tensor_width = params_.output_width.value_or(image->width());
const int tensor_height = params_.output_height.value_or(image->height());
ASSIGN_OR_RETURN(auto padding, PadRoi(tensor_width, tensor_height,
MP_ASSIGN_OR_RETURN(auto padding,
PadRoi(tensor_width, tensor_height,
options_.keep_aspect_ratio(), &roi));
if (kOutLetterboxPadding(cc).IsConnected()) {
kOutLetterboxPadding(cc).Send(padding);
@ -247,17 +248,17 @@ class ImageToTensorCalculator : public Node {
if (!gpu_converter_) {
#if !MEDIAPIPE_DISABLE_GPU
#if MEDIAPIPE_METAL_ENABLED
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
gpu_converter_,
CreateMetalConverter(cc, GetBorderMode(options_.border_mode())));
#elif MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
ASSIGN_OR_RETURN(gpu_converter_,
MP_ASSIGN_OR_RETURN(gpu_converter_,
CreateImageToGlBufferTensorConverter(
cc, DoesGpuInputStartAtBottom(options_),
GetBorderMode(options_.border_mode())));
#else
if (!gpu_converter_) {
ASSIGN_OR_RETURN(gpu_converter_,
MP_ASSIGN_OR_RETURN(gpu_converter_,
CreateImageToGlTextureTensorConverter(
cc, DoesGpuInputStartAtBottom(options_),
GetBorderMode(options_.border_mode())));
@ -272,7 +273,8 @@ class ImageToTensorCalculator : public Node {
} else {
if (!cpu_converter_) {
#if !MEDIAPIPE_DISABLE_OPENCV
ASSIGN_OR_RETURN(cpu_converter_,
MP_ASSIGN_OR_RETURN(
cpu_converter_,
CreateOpenCvConverter(
cc, GetBorderMode(options_.border_mode()),
GetOutputTensorType(/*uses_gpu=*/false, params_)));
@ -280,7 +282,8 @@ class ImageToTensorCalculator : public Node {
// to get access to a FrameBuffer view. Investigate if GetGpuBuffer() can be
// made available even with MEDIAPIPE_DISABLE_GPU set.
#elif MEDIAPIPE_ENABLE_HALIDE
ASSIGN_OR_RETURN(cpu_converter_,
MP_ASSIGN_OR_RETURN(
cpu_converter_,
CreateFrameBufferConverter(
cc, GetBorderMode(options_.border_mode()),
GetOutputTensorType(/*uses_gpu=*/false, params_)));

11
mediapipe/calculators/tensor/image_to_tensor_converter_frame_buffer.cc
View File

@ -175,8 +175,8 @@ absl::Status FrameBufferProcessor::CropRotateResize90Degrees(
cropped_buffer_ = std::make_unique<uint8_t[]>(cropped_buffer_size);
cropped_buffer_size_ = cropped_buffer_size;
}
ASSIGN_OR_RETURN(cropped,
frame_buffer::CreateFromRawBuffer(
MP_ASSIGN_OR_RETURN(
cropped, frame_buffer::CreateFromRawBuffer(
cropped_buffer_.get(), cropped_dims, input->format()));
}
MP_RETURN_IF_ERROR(
@ -194,7 +194,7 @@ absl::Status FrameBufferProcessor::CropRotateResize90Degrees(
rotated_buffer_ = std::make_unique<uint8_t[]>(rotated_buffer_size);
rotated_buffer_size_ = rotated_buffer_size;
}
ASSIGN_OR_RETURN(auto rotated, frame_buffer::CreateFromRawBuffer(
MP_ASSIGN_OR_RETURN(auto rotated, frame_buffer::CreateFromRawBuffer(
rotated_buffer_.get(), rotated_dims,
cropped->format()));
}
@ -217,8 +217,9 @@ absl::Status FrameBufferProcessor::ConvertToFloatTensor(
RET_CHECK(output_tensor.element_type() == Tensor::ElementType::kFloat32);
constexpr float kInputImageRangeMin = 0.0f;
constexpr float kInputImageRangeMax = 255.0f;
ASSIGN_OR_RETURN(auto transform, GetValueRangeTransformation(
kInputImageRangeMin, kInputImageRangeMax,
MP_ASSIGN_OR_RETURN(
auto transform,
GetValueRangeTransformation(kInputImageRangeMin, kInputImageRangeMax,
range_min, range_max));
return frame_buffer::ToFloatTensor(*input_frame, transform.scale,
transform.offset, output_tensor);

8
mediapipe/calculators/tensor/image_to_tensor_converter_gl_buffer.cc
View File

@ -255,7 +255,7 @@ class GlProcessor : public ImageToTensorConverter {
<< "OpenGL ES 3.1 is required.";
command_queue_ = tflite::gpu::gl::NewCommandQueue(gpu_info);
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto extractor,
SubRectExtractorGl::Create(gl_helper_.GetGlContext(),
input_starts_at_bottom, border_mode));
@ -293,9 +293,9 @@ class GlProcessor : public ImageToTensorConverter {
constexpr float kInputImageRangeMin = 0.0f;
constexpr float kInputImageRangeMax = 1.0f;
ASSIGN_OR_RETURN(auto transform,
GetValueRangeTransformation(kInputImageRangeMin,
kInputImageRangeMax,
MP_ASSIGN_OR_RETURN(auto transform,
GetValueRangeTransformation(
kInputImageRangeMin, kInputImageRangeMax,
range_min, range_max));
const int output_size = output_tensor.bytes() / output_shape.dims[0];

6
mediapipe/calculators/tensor/image_to_tensor_converter_gl_texture.cc
View File

@ -193,9 +193,9 @@ class GlProcessor : public ImageToTensorConverter {
constexpr float kInputImageRangeMin = 0.0f;
constexpr float kInputImageRangeMax = 1.0f;
ASSIGN_OR_RETURN(auto transform,
GetValueRangeTransformation(kInputImageRangeMin,
kInputImageRangeMax,
MP_ASSIGN_OR_RETURN(auto transform,
GetValueRangeTransformation(
kInputImageRangeMin, kInputImageRangeMax,
range_min, range_max));
auto tensor_view = output_tensor.GetOpenGlTexture2dWriteView();
MP_RETURN_IF_ERROR(ExtractSubRect(input_texture, roi,

4
mediapipe/calculators/tensor/image_to_tensor_converter_metal.cc
View File

@ -345,7 +345,7 @@ class MetalProcessor : public ImageToTensorConverter {
absl::Status Init(CalculatorContext* cc, BorderMode border_mode) {
metal_helper_ = [[MPPMetalHelper alloc] initWithCalculatorContext:cc];
RET_CHECK(metal_helper_);
ASSIGN_OR_RETURN(extractor_, SubRectExtractorMetal::Make(
MP_ASSIGN_OR_RETURN(extractor_, SubRectExtractorMetal::Make(
metal_helper_.mtlDevice,
OutputFormat::kF32C4, border_mode));
return absl::OkStatus();
@ -373,7 +373,7 @@ class MetalProcessor : public ImageToTensorConverter {
constexpr float kInputImageRangeMin = 0.0f;
constexpr float kInputImageRangeMax = 1.0f;
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto transform,
GetValueRangeTransformation(kInputImageRangeMin, kInputImageRangeMax,
range_min, range_max));

2
mediapipe/calculators/tensor/image_to_tensor_converter_opencv.cc
View File

@ -159,7 +159,7 @@ class OpenCvProcessor : public ImageToTensorConverter {
constexpr float kInputImageRangeMin = 0.0f;
constexpr float kInputImageRangeMax = 255.0f;
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto transform,
GetValueRangeTransformation(kInputImageRangeMin, kInputImageRangeMax,
range_min, range_max));

10
mediapipe/calculators/tensor/inference_calculator_cpu.cc
View File

@ -60,7 +60,7 @@ absl::Status InferenceCalculatorCpuImpl::UpdateContract(
}
absl::Status InferenceCalculatorCpuImpl::Open(CalculatorContext* cc) {
ASSIGN_OR_RETURN(inference_runner_, CreateInferenceRunner(cc));
MP_ASSIGN_OR_RETURN(inference_runner_, CreateInferenceRunner(cc));
return absl::OkStatus();
}
@ -71,7 +71,7 @@ absl::Status InferenceCalculatorCpuImpl::Process(CalculatorContext* cc) {
const auto& input_tensors = *kInTensors(cc);
RET_CHECK(!input_tensors.empty());
ASSIGN_OR_RETURN(std::vector<Tensor> output_tensors,
MP_ASSIGN_OR_RETURN(std::vector<Tensor> output_tensors,
inference_runner_->Run(cc, input_tensors));
kOutTensors(cc).Send(std::move(output_tensors));
return absl::OkStatus();
@ -84,11 +84,11 @@ absl::Status InferenceCalculatorCpuImpl::Close(CalculatorContext* cc) {
absl::StatusOr<std::unique_ptr<InferenceRunner>>
InferenceCalculatorCpuImpl::CreateInferenceRunner(CalculatorContext* cc) {
ASSIGN_OR_RETURN(auto model_packet, GetModelAsPacket(cc));
ASSIGN_OR_RETURN(auto op_resolver_packet, GetOpResolverAsPacket(cc));
MP_ASSIGN_OR_RETURN(auto model_packet, GetModelAsPacket(cc));
MP_ASSIGN_OR_RETURN(auto op_resolver_packet, GetOpResolverAsPacket(cc));
const int interpreter_num_threads =
cc->Options<mediapipe::InferenceCalculatorOptions>().cpu_num_thread();
ASSIGN_OR_RETURN(TfLiteDelegatePtr delegate, MaybeCreateDelegate(cc));
MP_ASSIGN_OR_RETURN(TfLiteDelegatePtr delegate, MaybeCreateDelegate(cc));
return CreateInferenceInterpreterDelegateRunner(
std::move(model_packet), std::move(op_resolver_packet),
std::move(delegate), interpreter_num_threads);

2
mediapipe/calculators/tensor/inference_calculator_gl.cc
View File

@ -100,7 +100,7 @@ absl::Status InferenceCalculatorGlImpl::GpuInferenceRunner::Init(
absl::Status InferenceCalculatorGlImpl::GpuInferenceRunner::LoadModel(
CalculatorContext* cc) {
ASSIGN_OR_RETURN(model_packet_, GetModelAsPacket(cc));
MP_ASSIGN_OR_RETURN(model_packet_, GetModelAsPacket(cc));
const auto& model = *model_packet_.Get();
if (kSideInOpResolver(cc).IsConnected()) {
const tflite::OpResolver& op_resolver = kSideInOpResolver(cc).Get();

8
mediapipe/calculators/tensor/inference_calculator_gl_advanced.cc
View File

@ -170,7 +170,7 @@ absl::Status
InferenceCalculatorGlAdvancedImpl::GpuInferenceRunner::InitTFLiteGPURunner(
CalculatorContext* cc,
const mediapipe::InferenceCalculatorOptions::Delegate& delegate) {
ASSIGN_OR_RETURN(model_packet_, GetModelAsPacket(cc));
MP_ASSIGN_OR_RETURN(model_packet_, GetModelAsPacket(cc));
const auto& model = *model_packet_.Get();
bool allow_precision_loss = delegate.gpu().allow_precision_loss();
@ -306,7 +306,7 @@ InferenceCalculatorGlAdvancedImpl::OnDiskCacheHelper::SaveGpuCaches(
tflite::gpu::TFLiteGPURunner* gpu_runner) const {
if (use_kernel_caching_) {
// Save kernel file.
ASSIGN_OR_RETURN(std::vector<uint8_t> kernel_cache,
MP_ASSIGN_OR_RETURN(std::vector<uint8_t> kernel_cache,
gpu_runner->GetSerializedBinaryCache());
std::string cache_str(kernel_cache.begin(), kernel_cache.end());
MP_RETURN_IF_ERROR(
@ -314,7 +314,7 @@ InferenceCalculatorGlAdvancedImpl::OnDiskCacheHelper::SaveGpuCaches(
}
if (use_serialized_model_) {
// Save serialized model file.
ASSIGN_OR_RETURN(std::vector<uint8_t> serialized_model_vec,
MP_ASSIGN_OR_RETURN(std::vector<uint8_t> serialized_model_vec,
gpu_runner->GetSerializedModel());
absl::string_view serialized_model(
reinterpret_cast<char*>(serialized_model_vec.data()),
@ -412,7 +412,7 @@ absl::Status InferenceCalculatorGlAdvancedImpl::Process(CalculatorContext* cc) {
RET_CHECK(!input_tensors.empty());
auto output_tensors = absl::make_unique<std::vector<Tensor>>();
ASSIGN_OR_RETURN(*output_tensors,
MP_ASSIGN_OR_RETURN(*output_tensors,
gpu_inference_runner_->Process(cc, input_tensors));
kOutTensors(cc).Send(std::move(output_tensors));

4
mediapipe/calculators/tensor/inference_calculator_metal.cc
View File

@ -208,9 +208,9 @@ absl::Status InferenceCalculatorMetalImpl::Close(CalculatorContext* cc) {
absl::Status InferenceCalculatorMetalImpl::InitInterpreter(
CalculatorContext* cc) {
ASSIGN_OR_RETURN(model_packet_, GetModelAsPacket(cc));
MP_ASSIGN_OR_RETURN(model_packet_, GetModelAsPacket(cc));
const auto& model = *model_packet_.Get();
ASSIGN_OR_RETURN(auto op_resolver_packet, GetOpResolverAsPacket(cc));
MP_ASSIGN_OR_RETURN(auto op_resolver_packet, GetOpResolverAsPacket(cc));
const auto& op_resolver = op_resolver_packet.Get();
tflite::InterpreterBuilder interpreter_builder(model, op_resolver);
AddDelegate(cc, &interpreter_builder);

10
mediapipe/calculators/tensor/inference_calculator_xnnpack.cc
View File

@ -58,7 +58,7 @@ absl::Status InferenceCalculatorXnnpackImpl::UpdateContract(
}
absl::Status InferenceCalculatorXnnpackImpl::Open(CalculatorContext* cc) {
ASSIGN_OR_RETURN(inference_runner_, CreateInferenceRunner(cc));
MP_ASSIGN_OR_RETURN(inference_runner_, CreateInferenceRunner(cc));
return absl::OkStatus();
}
@ -69,7 +69,7 @@ absl::Status InferenceCalculatorXnnpackImpl::Process(CalculatorContext* cc) {
const auto& input_tensors = *kInTensors(cc);
RET_CHECK(!input_tensors.empty());
ASSIGN_OR_RETURN(std::vector<Tensor> output_tensors,
MP_ASSIGN_OR_RETURN(std::vector<Tensor> output_tensors,
inference_runner_->Run(cc, input_tensors));
kOutTensors(cc).Send(std::move(output_tensors));
return absl::OkStatus();
@ -82,11 +82,11 @@ absl::Status InferenceCalculatorXnnpackImpl::Close(CalculatorContext* cc) {
absl::StatusOr<std::unique_ptr<InferenceRunner>>
InferenceCalculatorXnnpackImpl::CreateInferenceRunner(CalculatorContext* cc) {
ASSIGN_OR_RETURN(auto model_packet, GetModelAsPacket(cc));
ASSIGN_OR_RETURN(auto op_resolver_packet, GetOpResolverAsPacket(cc));
MP_ASSIGN_OR_RETURN(auto model_packet, GetModelAsPacket(cc));
MP_ASSIGN_OR_RETURN(auto op_resolver_packet, GetOpResolverAsPacket(cc));
const int interpreter_num_threads =
cc->Options<mediapipe::InferenceCalculatorOptions>().cpu_num_thread();
ASSIGN_OR_RETURN(TfLiteDelegatePtr delegate, CreateDelegate(cc));
MP_ASSIGN_OR_RETURN(TfLiteDelegatePtr delegate, CreateDelegate(cc));
return CreateInferenceInterpreterDelegateRunner(
std::move(model_packet), std::move(op_resolver_packet),
std::move(delegate), interpreter_num_threads);

4
mediapipe/calculators/tensor/regex_preprocessor_calculator.cc
View File

@ -106,7 +106,7 @@ absl::Status RegexPreprocessorCalculator::Open(CalculatorContext* cc) {
return absl::InvalidArgumentError("No tensor metadata found");
}
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
const auto* tokenizer_metadata,
metadata_extractor->FindFirstProcessUnit(
*tensor_metadata, tflite::ProcessUnitOptions_RegexTokenizerOptions));
@ -115,7 +115,7 @@ absl::Status RegexPreprocessorCalculator::Open(CalculatorContext* cc) {
}
const tflite::RegexTokenizerOptions* regex_tokenizer_options =
tokenizer_metadata->options_as<tflite::RegexTokenizerOptions>();
ASSIGN_OR_RETURN(tokenizer_,
MP_ASSIGN_OR_RETURN(tokenizer_,
tasks::text::tokenizers::CreateRegexTokenizerFromOptions(
regex_tokenizer_options, metadata_extractor));

7
mediapipe/calculators/tensor/regex_preprocessor_calculator_test.cc
View File

@ -67,9 +67,10 @@ absl::StatusOr<std::vector<int>> RunRegexPreprocessorCalculator(
tool::AddVectorSink("tensors", &graph_config, &output_packets);
std::string model_buffer = tasks::core::LoadBinaryContent(kTestModelPath);
ASSIGN_OR_RETURN(std::unique_ptr<ModelMetadataExtractor> metadata_extractor,
ModelMetadataExtractor::CreateFromModelBuffer(
model_buffer.data(), model_buffer.size()));
MP_ASSIGN_OR_RETURN(
std::unique_ptr<ModelMetadataExtractor> metadata_extractor,
ModelMetadataExtractor::CreateFromModelBuffer(model_buffer.data(),
model_buffer.size()));
// Run the graph.
CalculatorGraph graph;
MP_RETURN_IF_ERROR(graph.Initialize(

2
mediapipe/calculators/tensor/tensor_converter_calculator.cc
View File

@ -656,7 +656,7 @@ absl::Status TensorConverterCalculator::LoadOptions(CalculatorContext* cc,
}
// Get y-flip mode.
ASSIGN_OR_RETURN(flip_vertically_, ShouldFlipVertically(options, use_gpu));
MP_ASSIGN_OR_RETURN(flip_vertically_, ShouldFlipVertically(options, use_gpu));
// Get row_major_matrix mode.
row_major_matrix_ = options.row_major_matrix();

2
mediapipe/calculators/tensor/tensors_to_classification_calculator.cc
View File

@ -110,7 +110,7 @@ absl::Status TensorsToClassificationCalculator::Open(CalculatorContext* cc) {
sort_by_descending_score_ = options.sort_by_descending_score();
if (options.has_label_map_path()) {
std::string string_path;
ASSIGN_OR_RETURN(string_path,
MP_ASSIGN_OR_RETURN(string_path,
PathToResourceAsFile(options.label_map_path()));
std::string label_map_string;
MP_RETURN_IF_ERROR(

7
mediapipe/calculators/tensor/tensors_to_segmentation_calculator.cc
View File

@ -267,7 +267,8 @@ absl::Status TensorsToSegmentationCalculator::Process(CalculatorContext* cc) {
{
RET_CHECK(!input_tensors.empty());
RET_CHECK(input_tensors[0].element_type() == Tensor::ElementType::kFloat32);
ASSIGN_OR_RETURN(auto hwc, GetHwcFromDims(input_tensors[0].shape().dims));
MP_ASSIGN_OR_RETURN(auto hwc,
GetHwcFromDims(input_tensors[0].shape().dims));
int tensor_channels = std::get<2>(hwc);
typedef mediapipe::TensorsToSegmentationCalculatorOptions Options;
switch (options_.activation()) {
@ -330,7 +331,7 @@ absl::Status TensorsToSegmentationCalculator::ProcessCpu(
// Get input streams, and dimensions.
const auto& input_tensors =
cc->Inputs().Tag(kTensorsTag).Get<std::vector<Tensor>>();
ASSIGN_OR_RETURN(auto hwc, GetHwcFromDims(input_tensors[0].shape().dims));
MP_ASSIGN_OR_RETURN(auto hwc, GetHwcFromDims(input_tensors[0].shape().dims));
auto [tensor_height, tensor_width, tensor_channels] = hwc;
int output_width = tensor_width, output_height = tensor_height;
if (cc->Inputs().HasTag(kOutputSizeTag)) {
@ -441,7 +442,7 @@ absl::Status TensorsToSegmentationCalculator::ProcessGpu(
// Get input streams, and dimensions.
const auto& input_tensors =
cc->Inputs().Tag(kTensorsTag).Get<std::vector<Tensor>>();
ASSIGN_OR_RETURN(auto hwc, GetHwcFromDims(input_tensors[0].shape().dims));
MP_ASSIGN_OR_RETURN(auto hwc, GetHwcFromDims(input_tensors[0].shape().dims));
auto [tensor_height, tensor_width, tensor_channels] = hwc;
int output_width = tensor_width, output_height = tensor_height;
if (cc->Inputs().HasTag(kOutputSizeTag)) {

7
mediapipe/calculators/tensor/universal_sentence_encoder_preprocessor_calculator_test.cc
View File

@ -61,9 +61,10 @@ RunUniversalSentenceEncoderPreprocessorCalculator(absl::string_view text) {
std::string model_buffer =
tasks::core::LoadBinaryContent(kTestModelPath.data());
ASSIGN_OR_RETURN(std::unique_ptr<ModelMetadataExtractor> metadata_extractor,
ModelMetadataExtractor::CreateFromModelBuffer(
model_buffer.data(), model_buffer.size()));
MP_ASSIGN_OR_RETURN(
std::unique_ptr<ModelMetadataExtractor> metadata_extractor,
ModelMetadataExtractor::CreateFromModelBuffer(model_buffer.data(),
model_buffer.size()));
// Run the graph.
CalculatorGraph graph;
MP_RETURN_IF_ERROR(graph.Initialize(

8
mediapipe/calculators/tensorflow/object_detection_tensors_to_detections_calculator.cc
View File

@ -151,7 +151,7 @@ class ObjectDetectionTensorsToDetectionsCalculator : public CalculatorBase {
tf::Tensor input_num_detections_tensor =
tf::Tensor(tf::DT_FLOAT, tf::TensorShape({0}));
if (cc->Inputs().HasTag(kClasses)) {
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
input_num_detections_tensor,
MaybeSqueezeDims(kNumDetections,
cc->Inputs().Tag(kNumDetections).Get<tf::Tensor>()));
@ -160,12 +160,12 @@ class ObjectDetectionTensorsToDetectionsCalculator : public CalculatorBase {
RET_CHECK_EQ(input_num_detections_tensor.dtype(), tf::DT_FLOAT);
}
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto input_boxes_tensor,
MaybeSqueezeDims(kBoxes, cc->Inputs().Tag(kBoxes).Get<tf::Tensor>()));
RET_CHECK_EQ(input_boxes_tensor.dtype(), tf::DT_FLOAT);
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto input_scores_tensor,
MaybeSqueezeDims(kScores, cc->Inputs().Tag(kScores).Get<tf::Tensor>()));
RET_CHECK_EQ(input_scores_tensor.dtype(), tf::DT_FLOAT);
@ -173,7 +173,7 @@ class ObjectDetectionTensorsToDetectionsCalculator : public CalculatorBase {
tf::Tensor input_classes_tensor =
tf::Tensor(tf::DT_FLOAT, tf::TensorShape({0}));
if (cc->Inputs().HasTag(kClasses)) {
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
input_classes_tensor,
MaybeSqueezeDims(kClasses,
cc->Inputs().Tag(kClasses).Get<tf::Tensor>()));

8
mediapipe/calculators/tflite/tflite_inference_calculator.cc
View File

@ -489,7 +489,7 @@ absl::Status TfLiteInferenceCalculator::WriteKernelsToFile() {
#if MEDIAPIPE_TFLITE_GL_INFERENCE && defined(MEDIAPIPE_ANDROID)
if (use_kernel_caching_) {
// Save kernel file.
ASSIGN_OR_RETURN(std::vector<uint8_t> kernel_cache,
MP_ASSIGN_OR_RETURN(std::vector<uint8_t> kernel_cache,
tflite_gpu_runner_->GetSerializedBinaryCache());
std::string cache_str(kernel_cache.begin(), kernel_cache.end());
MP_RETURN_IF_ERROR(
@ -733,7 +733,7 @@ absl::Status TfLiteInferenceCalculator::ReadKernelsFromFile() {
absl::Status TfLiteInferenceCalculator::InitTFLiteGPURunner(
CalculatorContext* cc) {
#if MEDIAPIPE_TFLITE_GL_INFERENCE
ASSIGN_OR_RETURN(model_packet_, GetModelAsPacket(*cc));
MP_ASSIGN_OR_RETURN(model_packet_, GetModelAsPacket(*cc));
const auto& model = *model_packet_.Get<TfLiteModelPtr>();
tflite::ops::builtin::BuiltinOpResolverWithoutDefaultDelegates
@ -817,7 +817,7 @@ absl::Status TfLiteInferenceCalculator::InitTFLiteGPURunner(
gpu_data_out_.resize(tflite_gpu_runner_->outputs_size());
for (int i = 0; i < tflite_gpu_runner_->outputs_size(); ++i) {
gpu_data_out_[i] = absl::make_unique<GPUData>();
ASSIGN_OR_RETURN(gpu_data_out_[i]->elements,
MP_ASSIGN_OR_RETURN(gpu_data_out_[i]->elements,
tflite_gpu_runner_->GetOutputElements(i));
// Create and bind input buffer.
MP_RETURN_IF_ERROR(
@ -839,7 +839,7 @@ absl::Status TfLiteInferenceCalculator::LoadModel(CalculatorContext* cc) {
return absl::OkStatus();
}
ASSIGN_OR_RETURN(model_packet_, GetModelAsPacket(*cc));
MP_ASSIGN_OR_RETURN(model_packet_, GetModelAsPacket(*cc));
const auto& model = *model_packet_.Get<TfLiteModelPtr>();
tflite::ops::builtin::BuiltinOpResolverWithoutDefaultDelegates

2
mediapipe/calculators/tflite/tflite_tensors_to_classification_calculator.cc
View File

@ -101,7 +101,7 @@ absl::Status TfLiteTensorsToClassificationCalculator::Open(
top_k_ = options_.top_k();
if (options_.has_label_map_path()) {
std::string string_path;
ASSIGN_OR_RETURN(string_path,
MP_ASSIGN_OR_RETURN(string_path,
PathToResourceAsFile(options_.label_map_path()));
std::string label_map_string;
MP_RETURN_IF_ERROR(file::GetContents(string_path, &label_map_string));

4
mediapipe/calculators/util/association_calculator.h
View File

@ -171,13 +171,13 @@ class AssociationCalculator : public CalculatorBase {
// Compare this element with elements of the input collection. If this
// element has high overlap with elements of the collection, remove
// those elements from the collection and add this element.
ASSIGN_OR_RETURN(auto cur_rect, GetRectangle(element));
MP_ASSIGN_OR_RETURN(auto cur_rect, GetRectangle(element));
bool change_id = false;
int new_elem_id = -1;
for (auto uit = current->begin(); uit != current->end();) {
ASSIGN_OR_RETURN(auto prev_rect, GetRectangle(*uit));
MP_ASSIGN_OR_RETURN(auto prev_rect, GetRectangle(*uit));
if (CalculateIou(cur_rect, prev_rect) >
options_.min_similarity_threshold()) {
std::pair<bool, int> prev_id = GetId(*uit);

2
mediapipe/calculators/util/detection_label_id_to_text_calculator.cc
View File

@ -83,7 +83,7 @@ absl::Status DetectionLabelIdToTextCalculator::Open(CalculatorContext* cc) {
<< "Only can set one of the following fields in the CalculatorOptions: "
"label_map_path, label, and label_items.";
std::string string_path;
ASSIGN_OR_RETURN(string_path,
MP_ASSIGN_OR_RETURN(string_path,
PathToResourceAsFile(options.label_map_path()));
std::string label_map_string;
MP_RETURN_IF_ERROR(

8
mediapipe/calculators/util/detection_transformation_calculator.cc
View File

@ -96,9 +96,9 @@ absl::StatusOr<LocationData::Format> GetLocationDataFormat(
std::vector<Detection>& detections) {
RET_CHECK(!detections.empty());
LocationData::Format output_format;
ASSIGN_OR_RETURN(output_format, GetLocationDataFormat(detections[0]));
MP_ASSIGN_OR_RETURN(output_format, GetLocationDataFormat(detections[0]));
for (int i = 1; i < detections.size(); ++i) {
ASSIGN_OR_RETURN(LocationData::Format format,
MP_ASSIGN_OR_RETURN(LocationData::Format format,
GetLocationDataFormat(detections[i]));
if (output_format != format) {
return absl::InvalidArgumentError(
@ -243,7 +243,7 @@ class DetectionTransformationCalculator : public Node {
OutputEmptyDetections(cc);
return absl::OkStatus();
}
ASSIGN_OR_RETURN(input_location_data_format,
MP_ASSIGN_OR_RETURN(input_location_data_format,
GetLocationDataFormat(transformed_detections));
for (Detection& detection : transformed_detections) {
MP_RETURN_IF_ERROR(ConvertBoundingBox(image_size, &detection));
@ -254,7 +254,7 @@ class DetectionTransformationCalculator : public Node {
OutputEmptyDetections(cc);
return absl::OkStatus();
}
ASSIGN_OR_RETURN(input_location_data_format,
MP_ASSIGN_OR_RETURN(input_location_data_format,
GetLocationDataFormat(kInDetection(cc).Get()));
MP_RETURN_IF_ERROR(
ConvertBoundingBox(image_size, &transformed_detection));

2
mediapipe/calculators/util/landmarks_refinement_calculator.cc
View File

@ -137,7 +137,7 @@ class LandmarksRefinementCalculatorImpl
}
// Validate indexes mapping and get total number of refined landmarks.
ASSIGN_OR_RETURN(n_refined_landmarks_,
MP_ASSIGN_OR_RETURN(n_refined_landmarks_,
GetNumberOfRefinedLandmarks(options_.refinement()));
// Validate that number of refinements and landmark streams is the same.

3
mediapipe/calculators/util/landmarks_smoothing_calculator.cc
View File

@ -43,7 +43,8 @@ class LandmarksSmoothingCalculatorImpl
: public NodeImpl<LandmarksSmoothingCalculator> {
public:
absl::Status Open(CalculatorContext* cc) override {
ASSIGN_OR_RETURN(landmarks_filter_,
MP_ASSIGN_OR_RETURN(
landmarks_filter_,
InitializeLandmarksFilter(
cc->Options<LandmarksSmoothingCalculatorOptions>()));
return absl::OkStatus();

3
mediapipe/calculators/util/landmarks_smoothing_calculator_utils.cc
View File

@ -348,7 +348,8 @@ absl::StatusOr<LandmarksFilter*> MultiLandmarkFilters::GetOrCreate(
return it->second.get();
}
ASSIGN_OR_RETURN(auto landmarks_filter, InitializeLandmarksFilter(options));
MP_ASSIGN_OR_RETURN(auto landmarks_filter,
InitializeLandmarksFilter(options));
filters_[tracking_id] = std::move(landmarks_filter);
return filters_[tracking_id].get();
}

4
mediapipe/calculators/util/landmarks_transformation_calculator.cc
View File

@ -119,9 +119,9 @@ class LandmarksTransformationCalculatorImpl
for (auto& transformation : options.transformation()) {
if (transformation.has_normalize_translation()) {
ASSIGN_OR_RETURN(landmarks, NormalizeTranslation(landmarks));
MP_ASSIGN_OR_RETURN(landmarks, NormalizeTranslation(landmarks));
} else if (transformation.has_flip_axis()) {
ASSIGN_OR_RETURN(landmarks,
MP_ASSIGN_OR_RETURN(landmarks,
FlipAxis(landmarks, transformation.flip_axis()));
} else {
RET_CHECK_FAIL() << "Unknown landmarks transformation";

2
mediapipe/calculators/util/local_file_contents_calculator.cc
View File

@ -86,7 +86,7 @@ class LocalFileContentsCalculator : public CalculatorBase {
++input_id, ++output_id) {
std::string file_path =
cc->InputSidePackets().Get(input_id).Get<std::string>();
ASSIGN_OR_RETURN(file_path, PathToResourceAsFile(file_path));
MP_ASSIGN_OR_RETURN(file_path, PathToResourceAsFile(file_path));
std::string contents;
MP_RETURN_IF_ERROR(GetResourceContents(

3
mediapipe/calculators/util/multi_landmarks_smoothing_calculator.cc
View File

@ -83,7 +83,8 @@ class MultiLandmarksSmoothingCalculatorImpl
image_width, image_height);
}
ASSIGN_OR_RETURN(auto* landmarks_filter,
MP_ASSIGN_OR_RETURN(
auto* landmarks_filter,
multi_filters_.GetOrCreate(
tracking_ids[i],
cc->Options<LandmarksSmoothingCalculatorOptions>()));

3
mediapipe/calculators/util/multi_world_landmarks_smoothing_calculator.cc
View File

@ -74,7 +74,8 @@ class MultiWorldLandmarksSmoothingCalculatorImpl
object_scale = GetObjectScale(object_scale_roi_vec.value()[i]);
}
ASSIGN_OR_RETURN(auto* landmarks_filter,
MP_ASSIGN_OR_RETURN(
auto* landmarks_filter,
multi_filters_.GetOrCreate(
tracking_ids[i],
cc->Options<LandmarksSmoothingCalculatorOptions>()));

4
mediapipe/calculators/util/refine_landmarks_from_heatmap_calculator.cc
View File

@ -77,7 +77,7 @@ class RefineLandmarksFromHeatmapCalculatorImpl
const auto& options =
cc->Options<mediapipe::RefineLandmarksFromHeatmapCalculatorOptions>();
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto out_lms,
RefineLandmarksFromHeatMap(
in_lms, hm_raw, hm_tensor.shape().dims, options.kernel_size(),
@ -108,7 +108,7 @@ absl::StatusOr<mediapipe::NormalizedLandmarkList> RefineLandmarksFromHeatMap(
const float* heatmap_raw_data, const std::vector<int>& heatmap_dims,
int kernel_size, float min_confidence_to_refine, bool refine_presence,
bool refine_visibility) {
ASSIGN_OR_RETURN(auto hm_dims, GetHwcFromDims(heatmap_dims));
MP_ASSIGN_OR_RETURN(auto hm_dims, GetHwcFromDims(heatmap_dims));
auto [hm_height, hm_width, hm_channels] = hm_dims;
RET_CHECK_EQ(in_lms.landmark_size(), hm_channels)

3
mediapipe/calculators/util/timed_box_list_id_to_label_calculator.cc
View File

@ -73,7 +73,8 @@ absl::Status TimedBoxListIdToLabelCalculator::Open(CalculatorContext* cc) {
cc->Options<::mediapipe::TimedBoxListIdToLabelCalculatorOptions>();
std::string string_path;
ASSIGN_OR_RETURN(string_path, PathToResourceAsFile(options.label_map_path()));
MP_ASSIGN_OR_RETURN(string_path,
PathToResourceAsFile(options.label_map_path()));
std::string label_map_string;
MP_RETURN_IF_ERROR(file::GetContents(string_path, &label_map_string));

2
mediapipe/calculators/util/to_image_calculator.cc
View File

@ -86,7 +86,7 @@ absl::Status ToImageCalculator::UpdateContract(CalculatorContract* cc) {
}
absl::Status ToImageCalculator::Process(CalculatorContext* cc) {
ASSIGN_OR_RETURN(auto output, GetInputImage(cc));
MP_ASSIGN_OR_RETURN(auto output, GetInputImage(cc));
kOut(cc).Send(output.At(cc->InputTimestamp()));
return absl::OkStatus();
}

2
mediapipe/calculators/util/top_k_scores_calculator.cc
View File

@ -227,7 +227,7 @@ absl::Status TopKScoresCalculator::Process(CalculatorContext* cc) {
absl::Status TopKScoresCalculator::LoadLabelmap(std::string label_map_path) {
std::string string_path;
ASSIGN_OR_RETURN(string_path, PathToResourceAsFile(label_map_path));
MP_ASSIGN_OR_RETURN(string_path, PathToResourceAsFile(label_map_path));
std::string label_map_string;
MP_RETURN_IF_ERROR(file::GetContents(string_path, &label_map_string));

2
mediapipe/calculators/video/box_detector_calculator.cc
View File

@ -207,7 +207,7 @@ absl::Status BoxDetectorCalculator::Open(CalculatorContext* cc) {
for (const auto& filename : options_.index_proto_filename()) {
std::string string_path;
ASSIGN_OR_RETURN(string_path, PathToResourceAsFile(filename));
MP_ASSIGN_OR_RETURN(string_path, PathToResourceAsFile(filename));
std::string index_string;
MP_RETURN_IF_ERROR(file::GetContents(string_path, &index_string));
BoxDetectorIndex predefined_index;

2
mediapipe/calculators/video/motion_analysis_calculator.cc
View File

@ -478,7 +478,7 @@ absl::Status MotionAnalysisCalculator::Process(CalculatorContext* cc) {
// Fill in timestamps we process.
if (!selection_stream->Value().IsEmpty()) {
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
frame_selection_result,
selection_stream->Value().ConsumeOrCopy<FrameSelectionResult>());
use_frame = true;

2
mediapipe/examples/coral/demo_run_graph_main.cc
View File

@ -87,7 +87,7 @@ absl::Status RunMPPGraph() {
}
ABSL_LOG(INFO) << "Start running the calculator graph.";
ASSIGN_OR_RETURN(mediapipe::OutputStreamPoller poller,
MP_ASSIGN_OR_RETURN(mediapipe::OutputStreamPoller poller,
graph.AddOutputStreamPoller(kOutputStream));
MP_RETURN_IF_ERROR(graph.StartRun({}));

2
mediapipe/examples/desktop/demo_run_graph_main.cc
View File

@ -79,7 +79,7 @@ absl::Status RunMPPGraph() {
}
ABSL_LOG(INFO) << "Start running the calculator graph.";
ASSIGN_OR_RETURN(mediapipe::OutputStreamPoller poller,
MP_ASSIGN_OR_RETURN(mediapipe::OutputStreamPoller poller,
graph.AddOutputStreamPoller(kOutputStream));
MP_RETURN_IF_ERROR(graph.StartRun({}));

4
mediapipe/examples/desktop/demo_run_graph_main_gpu.cc
View File

@ -62,7 +62,7 @@ absl::Status RunMPPGraph() {
MP_RETURN_IF_ERROR(graph.Initialize(config));
ABSL_LOG(INFO) << "Initialize the GPU.";
ASSIGN_OR_RETURN(auto gpu_resources, mediapipe::GpuResources::Create());
MP_ASSIGN_OR_RETURN(auto gpu_resources, mediapipe::GpuResources::Create());
MP_RETURN_IF_ERROR(graph.SetGpuResources(std::move(gpu_resources)));
mediapipe::GlCalculatorHelper gpu_helper;
gpu_helper.InitializeForTest(graph.GetGpuResources().get());
@ -89,7 +89,7 @@ absl::Status RunMPPGraph() {
}
ABSL_LOG(INFO) << "Start running the calculator graph.";
ASSIGN_OR_RETURN(mediapipe::OutputStreamPoller poller,
MP_ASSIGN_OR_RETURN(mediapipe::OutputStreamPoller poller,
graph.AddOutputStreamPoller(kOutputStream));
MP_RETURN_IF_ERROR(graph.StartRun({}));

2
mediapipe/examples/desktop/hello_world/hello_world.cc
View File

@ -42,7 +42,7 @@ absl::Status PrintHelloWorld() {
CalculatorGraph graph;
MP_RETURN_IF_ERROR(graph.Initialize(config));
ASSIGN_OR_RETURN(OutputStreamPoller poller,
MP_ASSIGN_OR_RETURN(OutputStreamPoller poller,
graph.AddOutputStreamPoller("out"));
MP_RETURN_IF_ERROR(graph.StartRun({}));
// Give 10 input packets that contains the same string "Hello World!".

8
mediapipe/examples/desktop/iris_tracking/iris_depth_from_image_desktop.cc
View File

@ -57,15 +57,15 @@ absl::StatusOr<std::string> ReadFileToString(const std::string& file_path) {
absl::Status ProcessImage(std::unique_ptr<mediapipe::CalculatorGraph> graph) {
ABSL_LOG(INFO) << "Load the image.";
ASSIGN_OR_RETURN(const std::string raw_image,
MP_ASSIGN_OR_RETURN(const std::string raw_image,
ReadFileToString(absl::GetFlag(FLAGS_input_image_path)));
ABSL_LOG(INFO) << "Start running the calculator graph.";
ASSIGN_OR_RETURN(mediapipe::OutputStreamPoller output_image_poller,
MP_ASSIGN_OR_RETURN(mediapipe::OutputStreamPoller output_image_poller,
graph->AddOutputStreamPoller(kOutputImageStream));
ASSIGN_OR_RETURN(mediapipe::OutputStreamPoller left_iris_depth_poller,
MP_ASSIGN_OR_RETURN(mediapipe::OutputStreamPoller left_iris_depth_poller,
graph->AddOutputStreamPoller(kLeftIrisDepthMmStream));
ASSIGN_OR_RETURN(mediapipe::OutputStreamPoller right_iris_depth_poller,
MP_ASSIGN_OR_RETURN(mediapipe::OutputStreamPoller right_iris_depth_poller,
graph->AddOutputStreamPoller(kRightIrisDepthMmStream));
MP_RETURN_IF_ERROR(graph->StartRun({}));

4
mediapipe/examples/desktop/simple_run_graph_main.cc
View File

@ -83,7 +83,7 @@ absl::Status OutputSidePacketsToLocalFile(mediapipe::CalculatorGraph& graph) {
std::vector<std::string> side_packet_names =
absl::StrSplit(absl::GetFlag(FLAGS_output_side_packets), ',');
for (const std::string& side_packet_name : side_packet_names) {
ASSIGN_OR_RETURN(auto status_or_packet,
MP_ASSIGN_OR_RETURN(auto status_or_packet,
graph.GetOutputSidePacket(side_packet_name));
file << absl::StrCat(side_packet_name, ":",
status_or_packet.Get<std::string>(), "\n");
@ -125,7 +125,7 @@ absl::Status RunMPPGraph() {
MP_RETURN_IF_ERROR(graph.Initialize(config, input_side_packets));
if (!absl::GetFlag(FLAGS_output_stream).empty() &&
!absl::GetFlag(FLAGS_output_stream_file).empty()) {
ASSIGN_OR_RETURN(auto poller, graph.AddOutputStreamPoller(
MP_ASSIGN_OR_RETURN(auto poller, graph.AddOutputStreamPoller(
absl::GetFlag(FLAGS_output_stream)));
ABSL_LOG(INFO) << "Start running the calculator graph.";
MP_RETURN_IF_ERROR(graph.StartRun({}));

6
mediapipe/framework/api2/node_test.cc
View File

@ -530,9 +530,9 @@ struct ConsumerNode : public Node {
MEDIAPIPE_NODE_CONTRACT(kInt, kGeneric, kOneOf);
absl::Status Process(CalculatorContext* cc) override {
ASSIGN_OR_RETURN(auto maybe_int, kInt(cc).Consume());
ASSIGN_OR_RETURN(auto maybe_float, kGeneric(cc).Consume<float>());
ASSIGN_OR_RETURN(auto maybe_int2, kOneOf(cc).Consume<int>());
MP_ASSIGN_OR_RETURN(auto maybe_int, kInt(cc).Consume());
MP_ASSIGN_OR_RETURN(auto maybe_float, kGeneric(cc).Consume<float>());
MP_ASSIGN_OR_RETURN(auto maybe_int2, kOneOf(cc).Consume<int>());
return {};
}
};

6
mediapipe/framework/calculator_graph.cc
View File

@ -207,7 +207,7 @@ absl::Status CalculatorGraph::InitializeStreams() {
// Initialize GraphInputStreams.
int graph_input_stream_count = 0;
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto input_tag_map,
tool::TagMap::Create(validated_graph_->Config().input_stream()));
for (const auto& stream_name : input_tag_map->Names()) {
@ -371,7 +371,7 @@ absl::Status CalculatorGraph::InitializeExecutors() {
"CalculatorGraph::SetExecutor() call.";
}
// clang-format off
ASSIGN_OR_RETURN(Executor* executor,
MP_ASSIGN_OR_RETURN(Executor* executor,
ExecutorRegistry::CreateByNameInNamespace(
validated_graph_->Package(),
executor_config.type(), executor_config.options()));
@ -1335,7 +1335,7 @@ absl::Status CalculatorGraph::CreateDefaultThreadPool(
}
options->set_num_threads(num_threads);
// clang-format off
ASSIGN_OR_RETURN(Executor* executor,
MP_ASSIGN_OR_RETURN(Executor* executor,
ThreadPoolExecutor::Create(extendable_options));
// clang-format on
return SetExecutorInternal("", std::shared_ptr<Executor>(executor));

16
mediapipe/framework/calculator_node.cc
View File

@ -303,11 +303,12 @@ absl::Status CalculatorNode::InitializeInputStreamHandler(
const ProtoString& input_stream_handler_name =
handler_config.input_stream_handler();
RET_CHECK(!input_stream_handler_name.empty());
ASSIGN_OR_RETURN(input_stream_handler_,
MP_ASSIGN_OR_RETURN(
input_stream_handler_,
InputStreamHandlerRegistry::CreateByNameInNamespace(
validated_graph_->Package(), input_stream_handler_name,
input_stream_types.TagMap(),
&calculator_context_manager_, handler_config.options(),
input_stream_types.TagMap(), &calculator_context_manager_,
handler_config.options(),
/*calculator_run_in_parallel=*/max_in_flight_ > 1),
_ << "\"" << input_stream_handler_name
<< "\" is not a registered input stream handler.");
@ -321,11 +322,12 @@ absl::Status CalculatorNode::InitializeOutputStreamHandler(
const ProtoString& output_stream_handler_name =
handler_config.output_stream_handler();
RET_CHECK(!output_stream_handler_name.empty());
ASSIGN_OR_RETURN(output_stream_handler_,
MP_ASSIGN_OR_RETURN(
output_stream_handler_,
OutputStreamHandlerRegistry::CreateByNameInNamespace(
validated_graph_->Package(), output_stream_handler_name,
output_stream_types.TagMap(),
&calculator_context_manager_, handler_config.options(),
output_stream_types.TagMap(), &calculator_context_manager_,
handler_config.options(),
/*calculator_run_in_parallel=*/max_in_flight_ > 1),
_ << "\"" << output_stream_handler_name
<< "\" is not a registered output stream handler.");
@ -420,7 +422,7 @@ absl::Status CalculatorNode::PrepareForRun(
MP_RETURN_IF_ERROR(calculator_context_manager_.PrepareForRun(std::bind(
&CalculatorNode::ConnectShardsToStreams, this, std::placeholders::_1)));
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto calculator_factory,
CalculatorBaseRegistry::CreateByNameInNamespace(
validated_graph_->Package(), calculator_state_->CalculatorType()));

10
mediapipe/framework/calculator_runner.cc
View File

@ -111,19 +111,19 @@ absl::Status CalculatorRunner::InitializeFromNodeConfig(
node_config_.mutable_input_side_packet());
}
ASSIGN_OR_RETURN(auto input_map,
MP_ASSIGN_OR_RETURN(auto input_map,
tool::TagMap::Create(node_config_.input_stream()));
inputs_ = absl::make_unique<StreamContentsSet>(input_map);
ASSIGN_OR_RETURN(auto output_map,
MP_ASSIGN_OR_RETURN(auto output_map,
tool::TagMap::Create(node_config_.output_stream()));
outputs_ = absl::make_unique<StreamContentsSet>(output_map);
ASSIGN_OR_RETURN(auto input_side_map,
MP_ASSIGN_OR_RETURN(auto input_side_map,
tool::TagMap::Create(node_config_.input_side_packet()));
input_side_packets_ = absl::make_unique<PacketSet>(input_side_map);
ASSIGN_OR_RETURN(auto output_side_map,
MP_ASSIGN_OR_RETURN(auto output_side_map,
tool::TagMap::Create(node_config_.output_side_packet()));
output_side_packets_ = absl::make_unique<PacketSet>(output_side_map);
@ -353,7 +353,7 @@ absl::Status CalculatorRunner::Run() {
node_config_.output_side_packet(i), &tag, &index, &name));
Packet& contents = output_side_packets_->Get(
tag, (index == -1) ? ++positional_index : index);
ASSIGN_OR_RETURN(contents, graph_->GetOutputSidePacket(name));
MP_ASSIGN_OR_RETURN(contents, graph_->GetOutputSidePacket(name));
}
return absl::OkStatus();
}

32
mediapipe/framework/deps/status_macros.h
View File

@ -97,27 +97,27 @@
//
// Interface:
//
// ASSIGN_OR_RETURN(lhs, rexpr)
// ASSIGN_OR_RETURN(lhs, rexpr, error_expression);
// MP_ASSIGN_OR_RETURN(lhs, rexpr)
// MP_ASSIGN_OR_RETURN(lhs, rexpr, error_expression);
//
// WARNING: expands into multiple statements; it cannot be used in a single
// statement (e.g. as the body of an if statement without {})!
//
// Example: Declaring and initializing a new variable (ValueType can be anything
// that can be initialized with assignment, including references):
// ASSIGN_OR_RETURN(ValueType value, MaybeGetValue(arg));
// MP_ASSIGN_OR_RETURN(ValueType value, MaybeGetValue(arg));
//
// Example: Assigning to an existing variable:
// ValueType value;
// ASSIGN_OR_RETURN(value, MaybeGetValue(arg));
// MP_ASSIGN_OR_RETURN(value, MaybeGetValue(arg));
//
// Example: Assigning to an expression with side effects:
// MyProto data;
// ASSIGN_OR_RETURN(*data.mutable_str(), MaybeGetValue(arg));
// MP_ASSIGN_OR_RETURN(*data.mutable_str(), MaybeGetValue(arg));
// // No field "str" is added on error.
//
// Example: Assigning to a std::unique_ptr.
// ASSIGN_OR_RETURN(std::unique_ptr<T> ptr, MaybeGetPtr(arg));
// MP_ASSIGN_OR_RETURN(std::unique_ptr<T> ptr, MaybeGetPtr(arg));
//
// If passed, the `error_expression` is evaluated to produce the return
// value. The expression may reference any variable visible in scope, as
@ -128,16 +128,16 @@
// returnable by the function, including (void). For example:
//
// Example: Adjusting the error message.
// ASSIGN_OR_RETURN(ValueType value, MaybeGetValue(query),
// MP_ASSIGN_OR_RETURN(ValueType value, MaybeGetValue(query),
// _ << "while processing query " << query.DebugString());
//
// Example: Logging the error on failure.
// ASSIGN_OR_RETURN(ValueType value, MaybeGetValue(query), _.LogError());
// MP_ASSIGN_OR_RETURN(ValueType value, MaybeGetValue(query), _.LogError());
//
#define ASSIGN_OR_RETURN(...) \
#define MP_ASSIGN_OR_RETURN(...) \
MP_STATUS_MACROS_IMPL_GET_VARIADIC_( \
(__VA_ARGS__, MP_STATUS_MACROS_IMPL_ASSIGN_OR_RETURN_3_, \
MP_STATUS_MACROS_IMPL_ASSIGN_OR_RETURN_2_)) \
(__VA_ARGS__, MP_STATUS_MACROS_IMPL_MP_ASSIGN_OR_RETURN_3_, \
MP_STATUS_MACROS_IMPL_MP_ASSIGN_OR_RETURN_2_)) \
(__VA_ARGS__)
// =================================================================
@ -150,16 +150,16 @@
#define MP_STATUS_MACROS_IMPL_GET_VARIADIC_(args) \
MP_STATUS_MACROS_IMPL_GET_VARIADIC_HELPER_ args
#define MP_STATUS_MACROS_IMPL_ASSIGN_OR_RETURN_2_(lhs, rexpr) \
MP_STATUS_MACROS_IMPL_ASSIGN_OR_RETURN_( \
#define MP_STATUS_MACROS_IMPL_MP_ASSIGN_OR_RETURN_2_(lhs, rexpr) \
MP_STATUS_MACROS_IMPL_MP_ASSIGN_OR_RETURN_( \
MP_STATUS_MACROS_IMPL_CONCAT_(_status_or_value, __LINE__), lhs, rexpr, \
return mediapipe::StatusBuilder( \
std::move(MP_STATUS_MACROS_IMPL_CONCAT_(_status_or_value, __LINE__)) \
.status(), \
MEDIAPIPE_LOC))
#define MP_STATUS_MACROS_IMPL_ASSIGN_OR_RETURN_3_(lhs, rexpr, \
#define MP_STATUS_MACROS_IMPL_MP_ASSIGN_OR_RETURN_3_(lhs, rexpr, \
error_expression) \
MP_STATUS_MACROS_IMPL_ASSIGN_OR_RETURN_( \
MP_STATUS_MACROS_IMPL_MP_ASSIGN_OR_RETURN_( \
MP_STATUS_MACROS_IMPL_CONCAT_(_status_or_value, __LINE__), lhs, rexpr, \
mediapipe::StatusBuilder _( \
std::move(MP_STATUS_MACROS_IMPL_CONCAT_(_status_or_value, __LINE__)) \
@ -167,7 +167,7 @@
MEDIAPIPE_LOC); \
(void)_; /* error_expression is allowed to not use this variable */ \
return (error_expression))
#define MP_STATUS_MACROS_IMPL_ASSIGN_OR_RETURN_(statusor, lhs, rexpr, \
#define MP_STATUS_MACROS_IMPL_MP_ASSIGN_OR_RETURN_(statusor, lhs, rexpr, \
error_expression) \
auto statusor = (rexpr); \
if (ABSL_PREDICT_FALSE(!statusor.ok())) { \

2
mediapipe/framework/input_side_packet_handler.cc
View File

@ -29,7 +29,7 @@ absl::Status InputSidePacketHandler::PrepareForRun(
std::function<void(absl::Status)> error_callback) {
int missing_input_side_packet_count;
prev_input_side_packets_ = std::move(input_side_packets_);
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
input_side_packets_,
tool::FillPacketSet(*input_side_packet_types, all_side_packets,
&missing_input_side_packet_count));

4
mediapipe/framework/output_stream_poller.h
View File

@ -28,8 +28,8 @@ class OutputStreamPoller {
OutputStreamPoller(const OutputStreamPoller&) = delete;
OutputStreamPoller& operator=(const OutputStreamPoller&) = delete;
OutputStreamPoller(OutputStreamPoller&&) = default;
// Move assignment needs to be explicitly defaulted to allow ASSIGN_OR_RETURN
// on `StatusOr<OutputStreamPoller>`.
// Move assignment needs to be explicitly defaulted to allow
// MP_ASSIGN_OR_RETURN on `StatusOr<OutputStreamPoller>`.
OutputStreamPoller& operator=(OutputStreamPoller&&) = default;
// Resets OutputStramPollerImpl and cleans the internal packet queue.

2
mediapipe/framework/packet.cc
View File

@ -55,7 +55,7 @@ const HolderBase* GetHolder(const Packet& packet) {
absl::StatusOr<Packet> PacketFromDynamicProto(const std::string& type_name,
const std::string& serialized) {
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto message_holder,
packet_internal::MessageHolderRegistry::CreateByName(type_name));
auto* message =

10
mediapipe/framework/packet.h
View File

@ -150,16 +150,16 @@ class Packet {
// general recommendation is to avoid calling this function.
//
// Example usage:
// ASSIGN_OR_RETURN(std::unique_ptr<Detection> detection,
// MP_ASSIGN_OR_RETURN(std::unique_ptr<Detection> detection,
// p.ConsumeOrCopy<Detection>());
// // The unique_ptr type can be omitted with auto.
// ASSIGN_OR_RETURN(auto detection, p.ConsumeOrCopy<Detection>());
// If you would like to crash on failure (prefer ASSIGN_OR_RETURN):
// MP_ASSIGN_OR_RETURN(auto detection, p.ConsumeOrCopy<Detection>());
// If you would like to crash on failure (prefer MP_ASSIGN_OR_RETURN):
// auto detection = p.ConsumeOrCopy<Detection>().value();
// // In functions which do not return absl::Status use an adaptor
// // function as the third argument to ASSIGN_OR_RETURN. In tests,
// // function as the third argument to MP_ASSIGN_OR_RETURN. In tests,
// // use an adaptor which returns void.
// ASSIGN_OR_RETURN(auto detection, p.ConsumeOrCopy<Detection>(),
// MP_ASSIGN_OR_RETURN(auto detection, p.ConsumeOrCopy<Detection>(),
// _.With([](const absl::Status& status) {
// MP_EXPECT_OK(status);
// // Use CHECK_OK to crash and report a usable line

2
mediapipe/framework/packet_generator_graph.cc
View File

@ -97,7 +97,7 @@ absl::Status Generate(const ValidatedGraphConfig& validated_graph,
validated_graph.Config().packet_generator(generator_index);
const auto& generator_name = generator_config.packet_generator();
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto static_access,
internal::StaticAccessToGeneratorRegistry::CreateByNameInNamespace(
validated_graph.Package(), generator_name),

7
mediapipe/framework/profiler/graph_profiler.cc
View File

@ -246,7 +246,7 @@ absl::Status GraphProfiler::Start(mediapipe::Executor* executor) {
if (is_tracing_ && IsTraceIntervalEnabled(profiler_config_, tracer()) &&
executor != nullptr) {
// Inform the user via logging the path to the trace logs.
ASSIGN_OR_RETURN(std::string trace_log_path, GetTraceLogPath());
MP_ASSIGN_OR_RETURN(std::string trace_log_path, GetTraceLogPath());
// Check that we can actually write to it.
auto status =
file::SetContents(absl::StrCat(trace_log_path, "trace_writing_check"),
@ -655,7 +655,8 @@ absl::StatusOr<std::string> GraphProfiler::GetTraceLogPath() {
"Trace log writing is disabled, unable to get trace_log_path.");
}
if (profiler_config_.trace_log_path().empty()) {
ASSIGN_OR_RETURN(std::string directory_path, GetDefaultTraceLogDirectory());
MP_ASSIGN_OR_RETURN(std::string directory_path,
GetDefaultTraceLogDirectory());
std::string trace_log_path =
absl::StrCat(directory_path, "/", kDefaultLogFilePrefix);
return trace_log_path;
@ -705,7 +706,7 @@ absl::Status GraphProfiler::WriteProfile() {
// Logging is disabled, so we can exit writing without error.
return absl::OkStatus();
}
ASSIGN_OR_RETURN(std::string trace_log_path, GetTraceLogPath());
MP_ASSIGN_OR_RETURN(std::string trace_log_path, GetTraceLogPath());
int log_interval_count = GetLogIntervalCount(profiler_config_);
int log_file_count = GetLogFileCount(profiler_config_);
GraphProfile profile;

2
mediapipe/framework/profiler/profiler_resource_util_common.cc
View File

@ -33,7 +33,7 @@ absl::StatusOr<std::string> GetLogDirectory() {
}
absl::StatusOr<std::string> PathToLogFile(const std::string& path) {
ASSIGN_OR_RETURN(std::string log_dir, GetLogDirectory());
MP_ASSIGN_OR_RETURN(std::string log_dir, GetLogDirectory());
std::string result = file::JoinPath(log_dir, path);
MP_RETURN_IF_ERROR(
mediapipe::file::RecursivelyCreateDir(file::Dirname(result)));

15
mediapipe/framework/tool/options_field_util.cc
View File

@ -175,7 +175,8 @@ StatusOr<int> FindExtensionIndex(const FieldData& message_data,
}
std::string& extension_type = entry->extension_type;
std::vector<FieldData> field_values;
ASSIGN_OR_RETURN(field_values, GetFieldValues(message_data, *entry->field));
MP_ASSIGN_OR_RETURN(field_values,
GetFieldValues(message_data, *entry->field));
for (int i = 0; i < field_values.size(); ++i) {
FieldData extension = ParseProtobufAny(field_values[i]);
if (extension_type == "*" ||
@ -275,7 +276,7 @@ absl::Status FindExtension(const FieldData& message_data,
}
// For repeated protobuf::Any, find the index for the extension_type.
ASSIGN_OR_RETURN(int index, FindExtensionIndex(message_data, entry));
MP_ASSIGN_OR_RETURN(int index, FindExtensionIndex(message_data, entry));
if (index != -1) {
entry->index = index;
return absl::OkStatus();
@ -367,7 +368,7 @@ absl::StatusOr<std::vector<FieldData>> GetFieldValues(
MP_RETURN_IF_ERROR(FindExtension(message_data, &head));
}
RET_CHECK_NE(head.field, nullptr);
ASSIGN_OR_RETURN(results, GetFieldValues(message_data, *head.field));
MP_ASSIGN_OR_RETURN(results, GetFieldValues(message_data, *head.field));
if (IsProtobufAny(head.field)) {
for (int i = 0; i < results.size(); ++i) {
results[i] = ParseProtobufAny(results[i]);
@ -381,7 +382,7 @@ absl::StatusOr<std::vector<FieldData>> GetFieldValues(
}
if (!tail.empty()) {
FieldData child = results.at(index);
ASSIGN_OR_RETURN(results, GetFieldValues(child, tail));
MP_ASSIGN_OR_RETURN(results, GetFieldValues(child, tail));
} else if (index > -1) {
FieldData child = results.at(index);
results.clear();
@ -394,7 +395,7 @@ absl::StatusOr<std::vector<FieldData>> GetFieldValues(
absl::StatusOr<FieldData> GetField(const FieldData& message_data,
const FieldPath& field_path) {
std::vector<FieldData> results;
ASSIGN_OR_RETURN(results, GetFieldValues(message_data, field_path));
MP_ASSIGN_OR_RETURN(results, GetFieldValues(message_data, field_path));
if (results.empty()) {
FieldPathEntry tail = field_path.back();
return absl::OutOfRangeError(absl::StrCat(
@ -452,12 +453,12 @@ absl::Status MergeFieldValues(FieldData& message_data,
: field_path.back().field->type();
std::vector<FieldData> results = values;
std::vector<FieldData> prevs;
ASSIGN_OR_RETURN(prevs, GetFieldValues(message_data, field_path));
MP_ASSIGN_OR_RETURN(prevs, GetFieldValues(message_data, field_path));
if (field_type == FieldType::TYPE_MESSAGE) {
for (int i = 0; i < std::min(values.size(), prevs.size()); ++i) {
FieldData& v = results[i];
FieldData& b = prevs[i];
ASSIGN_OR_RETURN(v, MergeMessages(b, v));
MP_ASSIGN_OR_RETURN(v, MergeMessages(b, v));
}
}
status.Update(SetFieldValues(message_data, field_path, results));

7
mediapipe/framework/tool/options_util.cc
View File

@ -88,10 +88,10 @@ absl::Status CopyLiteralOptions(CalculatorGraphConfig::Node parent_node,
FieldData parent_options;
ASSIGN_IF_OK(parent_options,
GetNodeOptions(parent_data, graph_extension_type));
ASSIGN_OR_RETURN(graph_options,
MP_ASSIGN_OR_RETURN(graph_options,
MergeMessages(graph_options, parent_options));
FieldData node_options;
ASSIGN_OR_RETURN(node_options,
MP_ASSIGN_OR_RETURN(node_options,
GetNodeOptions(node_data, node_extension_type));
if (!node_options.has_message_value() ||
!graph_options.has_message_value()) {
@ -100,7 +100,8 @@ absl::Status CopyLiteralOptions(CalculatorGraphConfig::Node parent_node,
FieldPath graph_path = GetPath(graph_tag, MessageType(graph_options));
FieldPath node_path = GetPath(node_tag, MessageType(node_options));
std::vector<FieldData> packet_data;
ASSIGN_OR_RETURN(packet_data, GetFieldValues(graph_options, graph_path));
MP_ASSIGN_OR_RETURN(packet_data,
GetFieldValues(graph_options, graph_path));
MP_RETURN_IF_ERROR(
MergeFieldValues(node_options, node_path, packet_data));
options_field_util::SetOptionsMessage(node_options, &node);

4
mediapipe/framework/tool/options_util_test.cc
View File

@ -338,8 +338,8 @@ absl::Status Equals(std::vector<FieldData> b1, std::vector<FieldData> b2) {
using tool::options_field_util::AsPacket;
RET_CHECK_EQ(b1.size(), b2.size());
for (int i = 0; i < b1.size(); ++i) {
ASSIGN_OR_RETURN(Packet p1, AsPacket(b1.at(i)));
ASSIGN_OR_RETURN(Packet p2, AsPacket(b2.at(i)));
MP_ASSIGN_OR_RETURN(Packet p1, AsPacket(b1.at(i)));
MP_ASSIGN_OR_RETURN(Packet p2, AsPacket(b2.at(i)));
MP_RETURN_IF_ERROR(Equals(p1.Get<FieldType>(), p2.Get<FieldType>()));
}
return absl::OkStatus();

4
mediapipe/framework/tool/packet_generator_wrapper_calculator.cc
View File

@ -15,7 +15,7 @@ absl::Status PacketGeneratorWrapperCalculator::GetContract(
CalculatorContract* cc) {
const auto& options =
cc->Options<::mediapipe::PacketGeneratorWrapperCalculatorOptions>();
ASSIGN_OR_RETURN(auto static_access,
MP_ASSIGN_OR_RETURN(auto static_access,
mediapipe::internal::StaticAccessToGeneratorRegistry::
CreateByNameInNamespace(options.package(),
options.packet_generator()));
@ -30,7 +30,7 @@ absl::Status PacketGeneratorWrapperCalculator::GetContract(
absl::Status PacketGeneratorWrapperCalculator::Open(CalculatorContext* cc) {
const auto& options =
cc->Options<::mediapipe::PacketGeneratorWrapperCalculatorOptions>();
ASSIGN_OR_RETURN(auto static_access,
MP_ASSIGN_OR_RETURN(auto static_access,
mediapipe::internal::StaticAccessToGeneratorRegistry::
CreateByNameInNamespace(options.package(),
options.packet_generator()));

6
mediapipe/framework/tool/proto_util_lite.cc
View File

@ -196,7 +196,7 @@ absl::Status ProtoUtilLite::ReplaceFieldRange(
proto_path.erase(proto_path.begin());
FieldType type =
!proto_path.empty() ? WireFormatLite::TYPE_MESSAGE : field_type;
ASSIGN_OR_RETURN(auto r, AccessField(entry, type, *message));
MP_ASSIGN_OR_RETURN(auto r, AccessField(entry, type, *message));
FieldAccess& access = r.first;
int index = r.second;
std::vector<FieldValue>& v = *access.mutable_field_values();
@ -223,7 +223,7 @@ absl::Status ProtoUtilLite::GetFieldRange(
proto_path.erase(proto_path.begin());
FieldType type =
!proto_path.empty() ? WireFormatLite::TYPE_MESSAGE : field_type;
ASSIGN_OR_RETURN(auto r, AccessField(entry, type, message));
MP_ASSIGN_OR_RETURN(auto r, AccessField(entry, type, message));
FieldAccess& access = r.first;
int index = r.second;
std::vector<FieldValue>& v = *access.mutable_field_values();
@ -252,7 +252,7 @@ absl::Status ProtoUtilLite::GetFieldCount(const FieldValue& message,
proto_path.erase(proto_path.begin());
FieldType type =
!proto_path.empty() ? WireFormatLite::TYPE_MESSAGE : field_type;
ASSIGN_OR_RETURN(auto r, AccessField(entry, type, message));
MP_ASSIGN_OR_RETURN(auto r, AccessField(entry, type, message));
FieldAccess& access = r.first;
int index = r.second;
std::vector<FieldValue>& v = *access.mutable_field_values();

13
mediapipe/framework/tool/subgraph_expansion.cc
View File

@ -62,8 +62,8 @@ absl::Status FindIgnoredStreams(
const proto_ns::RepeatedPtrField<ProtoString>& src_streams,
const proto_ns::RepeatedPtrField<ProtoString>& dst_streams,
std::set<std::string>* result) {
ASSIGN_OR_RETURN(auto src_map, tool::TagMap::Create(src_streams));
ASSIGN_OR_RETURN(auto dst_map, tool::TagMap::Create(dst_streams));
MP_ASSIGN_OR_RETURN(auto src_map, tool::TagMap::Create(src_streams));
MP_ASSIGN_OR_RETURN(auto dst_map, tool::TagMap::Create(dst_streams));
for (auto id = src_map->BeginId(); id < src_map->EndId(); ++id) {
std::pair<std::string, int> tag_index = src_map->TagAndIndexFromId(id);
if (!dst_map->GetId(tag_index.first, tag_index.second).IsValid()) {
@ -149,8 +149,8 @@ absl::Status FindCorrespondingStreams(
std::map<std::string, std::string>* stream_map,
const proto_ns::RepeatedPtrField<ProtoString>& src_streams,
const proto_ns::RepeatedPtrField<ProtoString>& dst_streams) {
ASSIGN_OR_RETURN(auto src_map, tool::TagMap::Create(src_streams));
ASSIGN_OR_RETURN(auto dst_map, tool::TagMap::Create(dst_streams));
MP_ASSIGN_OR_RETURN(auto src_map, tool::TagMap::Create(src_streams));
MP_ASSIGN_OR_RETURN(auto dst_map, tool::TagMap::Create(dst_streams));
for (const auto& it : dst_map->Mapping()) {
const std::string& tag = it.first;
const TagMap::TagData* src_tag_data =
@ -299,8 +299,9 @@ absl::Status ExpandSubgraphs(CalculatorGraphConfig* config,
std::string node_name = CanonicalNodeName(*config, node_id);
MP_RETURN_IF_ERROR(ValidateSubgraphFields(node));
SubgraphContext subgraph_context(&node, service_manager);
ASSIGN_OR_RETURN(auto subgraph, graph_registry->CreateByName(
config->package(), node.calculator(),
MP_ASSIGN_OR_RETURN(
auto subgraph,
graph_registry->CreateByName(config->package(), node.calculator(),
&subgraph_context));
MP_RETURN_IF_ERROR(mediapipe::tool::DefineGraphOptions(node, &subgraph));
MP_RETURN_IF_ERROR(PrefixNames(node_name, &subgraph));

4
mediapipe/framework/tool/switch/graph_processor.cc
View File

@ -8,9 +8,9 @@ namespace mediapipe {
absl::Status GraphProcessor::Initialize(CalculatorGraphConfig graph_config) {
graph_config_ = graph_config;
ASSIGN_OR_RETURN(graph_input_map_,
MP_ASSIGN_OR_RETURN(graph_input_map_,
tool::TagMap::Create(graph_config_.input_stream()));
ASSIGN_OR_RETURN(graph_output_map_,
MP_ASSIGN_OR_RETURN(graph_output_map_,
tool::TagMap::Create(graph_config_.output_stream()));
return absl::OkStatus();
}

2
mediapipe/framework/tool/tag_map.h
View File

@ -53,7 +53,7 @@ class TagMap {
// Create a TagMap from a repeated string proto field of TAG:<index>:name.
// This is the most common usage:
// ASSIGN_OR_RETURN(std::shared_ptr<TagMap> tag_map,
// MP_ASSIGN_OR_RETURN(std::shared_ptr<TagMap> tag_map,
// tool::TagMap::Create(node.input_streams()));
static absl::StatusOr<std::shared_ptr<TagMap>> Create(
const proto_ns::RepeatedPtrField<ProtoString>& tag_index_names) {

8
mediapipe/framework/tool/test_util.cc
View File

@ -215,14 +215,15 @@ bool CompareImageFrames(const ImageFrame& image1, const ImageFrame& image2,
absl::Status CompareAndSaveImageOutput(
absl::string_view golden_image_path, const ImageFrame& actual,
const ImageFrameComparisonOptions& options) {
ASSIGN_OR_RETURN(auto output_img_path, SavePngTestOutput(actual, "output"));
MP_ASSIGN_OR_RETURN(auto output_img_path,
SavePngTestOutput(actual, "output"));
auto expected =
LoadTestImage(GetTestFilePath(golden_image_path), ImageFormat::UNKNOWN);
if (!expected.ok()) {
return expected.status();
}
ASSIGN_OR_RETURN(auto expected_img_path,
MP_ASSIGN_OR_RETURN(auto expected_img_path,
SavePngTestOutput(**expected, "expected"));
std::unique_ptr<ImageFrame> diff_img;
@ -230,7 +231,8 @@ absl::Status CompareAndSaveImageOutput(
options.max_alpha_diff, options.max_avg_diff,
diff_img);
if (diff_img) {
ASSIGN_OR_RETURN(auto diff_img_path, SavePngTestOutput(*diff_img, "diff"));
MP_ASSIGN_OR_RETURN(auto diff_img_path,
SavePngTestOutput(*diff_img, "diff"));
}
return status;

4
mediapipe/framework/tool/validate_type.cc
View File

@ -46,7 +46,7 @@ absl::Status RunGeneratorFillExpectations(
// side packet.
PacketGeneratorConfig config = input_config;
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto static_access,
internal::StaticAccessToGeneratorRegistry::CreateByNameInNamespace(
package, config.packet_generator()),
@ -81,7 +81,7 @@ absl::Status RunGenerateAndValidateTypes(
const std::string& package) {
ABSL_CHECK(output_side_packets);
// Get static access to functions.
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto static_access,
internal::StaticAccessToGeneratorRegistry::CreateByNameInNamespace(
package, packet_generator_name),

13
mediapipe/framework/validated_graph_config.cc
View File

@ -216,9 +216,10 @@ absl::Status NodeTypeInfo::Initialize(
LegacyCalculatorSupport::Scoped<CalculatorContract> s(&contract_);
// A number of calculators use the non-CC methods on GlCalculatorHelper
// even though they are CalculatorBase-based.
ASSIGN_OR_RETURN(auto calculator_factory,
CalculatorBaseRegistry::CreateByNameInNamespace(
validated_graph.Package(), node_class),
MP_ASSIGN_OR_RETURN(
auto calculator_factory,
CalculatorBaseRegistry::CreateByNameInNamespace(validated_graph.Package(),
node_class),
_ << "Unable to find Calculator \"" << node_class << "\"");
MP_RETURN_IF_ERROR(calculator_factory->GetContract(&contract_)).SetPrepend()
<< node_class << ": ";
@ -261,7 +262,7 @@ absl::Status NodeTypeInfo::Initialize(
// Run FillExpectations.
const std::string& node_class = node.packet_generator();
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto static_access,
internal::StaticAccessToGeneratorRegistry::CreateByNameInNamespace(
validated_graph.Package(), node_class),
@ -302,7 +303,7 @@ absl::Status NodeTypeInfo::Initialize(
// Run FillExpectations.
const std::string& node_class = node.status_handler();
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto static_access,
internal::StaticAccessToStatusHandlerRegistry::CreateByNameInNamespace(
validated_graph.Package(), node_class),
@ -602,7 +603,7 @@ absl::Status ValidatedGraphConfig::AddOutputSidePacketsForNode(
absl::Status ValidatedGraphConfig::InitializeStreamInfo(
bool* need_sorting_ptr) {
// Define output streams for graph input streams.
ASSIGN_OR_RETURN(std::shared_ptr<tool::TagMap> graph_input_streams,
MP_ASSIGN_OR_RETURN(std::shared_ptr<tool::TagMap> graph_input_streams,
tool::TagMap::Create(config_.input_stream()));
for (int index = 0; index < graph_input_streams->Names().size(); ++index) {
std::string name = graph_input_streams->Names()[index];

2
mediapipe/gpu/gl_context_egl.cc
View File

@ -177,7 +177,7 @@ absl::Status GlContext::CreateContextInternal(EGLContext share_context,
}
absl::Status GlContext::CreateContext(EGLContext share_context) {
ASSIGN_OR_RETURN(display_, GetInitializedEglDisplay());
MP_ASSIGN_OR_RETURN(display_, GetInitializedEglDisplay());
auto status = CreateContextInternal(share_context, 3);
if (!status.ok()) {

6
mediapipe/gpu/gpu_shared_data_internal.cc
View File

@ -74,7 +74,7 @@ GpuResources::StatusOrGpuResources GpuResources::Create() {
GpuResources::StatusOrGpuResources GpuResources::Create(
PlatformGlContext external_context) {
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
std::shared_ptr<GlContext> context,
GlContext::Create(external_context, kGlContextUseDedicatedThread));
std::shared_ptr<GpuResources> gpu_resources(
@ -150,7 +150,7 @@ absl::Status GpuResources::PrepareGpuNode(CalculatorNode* node) {
#endif // !__EMSCRIPTEN__
node_key_[node_id] = context_key;
ASSIGN_OR_RETURN(std::shared_ptr<GlContext> context,
MP_ASSIGN_OR_RETURN(std::shared_ptr<GlContext> context,
GetOrCreateGlContext(context_key));
if (kGlContextUseDedicatedThread) {
@ -186,7 +186,7 @@ GlContext::StatusOrGlContext GpuResources::GetOrCreateGlContext(
const std::string& key) {
auto it = gl_key_context_.find(key);
if (it == gl_key_context_.end()) {
ASSIGN_OR_RETURN(std::shared_ptr<GlContext> new_context,
MP_ASSIGN_OR_RETURN(std::shared_ptr<GlContext> new_context,
GlContext::Create(*gl_key_context_[SharedContextKey()],
kGlContextUseDedicatedThread));
it = gl_key_context_.emplace(key, new_context).first;

2
mediapipe/java/com/google/mediapipe/framework/jni/graph.cc
View File

@ -589,7 +589,7 @@ absl::Status Graph::SetParentGlContext(int64_t java_gl_context) {
"trying to set the parent GL context, but the gpu shared "
"data has already been set up.");
}
ASSIGN_OR_RETURN(gpu_resources_,
MP_ASSIGN_OR_RETURN(gpu_resources_,
mediapipe::GpuResources::Create(
reinterpret_cast<EGLContext>(java_gl_context)));
#endif // MEDIAPIPE_DISABLE_GPU

15
mediapipe/modules/face_geometry/effect_renderer_calculator.cc
View File

@ -119,19 +119,19 @@ class EffectRendererCalculator : public CalculatorBase {
absl::optional<face_geometry::Mesh3d> effect_mesh_3d;
if (options.has_effect_mesh_3d_path()) {
ASSIGN_OR_RETURN(effect_mesh_3d,
ReadMesh3dFromFile(options.effect_mesh_3d_path()),
MP_ASSIGN_OR_RETURN(
effect_mesh_3d, ReadMesh3dFromFile(options.effect_mesh_3d_path()),
_ << "Failed to read the effect 3D mesh from file!");
MP_RETURN_IF_ERROR(face_geometry::ValidateMesh3d(*effect_mesh_3d))
<< "Invalid effect 3D mesh!";
}
ASSIGN_OR_RETURN(ImageFrame effect_texture,
MP_ASSIGN_OR_RETURN(ImageFrame effect_texture,
ReadTextureFromFile(options.effect_texture_path()),
_ << "Failed to read the effect texture from file!");
ASSIGN_OR_RETURN(effect_renderer_,
MP_ASSIGN_OR_RETURN(effect_renderer_,
CreateEffectRenderer(environment, effect_mesh_3d,
std::move(effect_texture)),
_ << "Failed to create the effect renderer!");
@ -202,7 +202,7 @@ class EffectRendererCalculator : public CalculatorBase {
private:
static absl::StatusOr<ImageFrame> ReadTextureFromFile(
const std::string& texture_path) {
ASSIGN_OR_RETURN(std::string texture_blob,
MP_ASSIGN_OR_RETURN(std::string texture_blob,
ReadContentBlobFromFile(texture_path),
_ << "Failed to read texture blob from file!");
@ -246,7 +246,7 @@ class EffectRendererCalculator : public CalculatorBase {
static absl::StatusOr<face_geometry::Mesh3d> ReadMesh3dFromFile(
const std::string& mesh_3d_path) {
ASSIGN_OR_RETURN(std::string mesh_3d_blob,
MP_ASSIGN_OR_RETURN(std::string mesh_3d_blob,
ReadContentBlobFromFile(mesh_3d_path),
_ << "Failed to read mesh 3D blob from file!");
@ -259,7 +259,8 @@ class EffectRendererCalculator : public CalculatorBase {
static absl::StatusOr<std::string> ReadContentBlobFromFile(
const std::string& unresolved_path) {
ASSIGN_OR_RETURN(std::string resolved_path,
MP_ASSIGN_OR_RETURN(
std::string resolved_path,
mediapipe::PathToResourceAsFile(unresolved_path),
_ << "Failed to resolve path! Path = " << unresolved_path);

11
mediapipe/modules/face_geometry/geometry_pipeline_calculator.cc
View File

@ -92,7 +92,7 @@ class GeometryPipelineCalculator : public CalculatorBase {
const auto& options = cc->Options<FaceGeometryPipelineCalculatorOptions>();
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
face_geometry::GeometryPipelineMetadata metadata,
ReadMetadataFromFile(options.metadata_path()),
_ << "Failed to read the geometry pipeline metadata from file!");
@ -109,7 +109,7 @@ class GeometryPipelineCalculator : public CalculatorBase {
MP_RETURN_IF_ERROR(face_geometry::ValidateEnvironment(environment))
<< "Invalid environment!";
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
geometry_pipeline_,
face_geometry::CreateGeometryPipeline(environment, metadata),
_ << "Failed to create a geometry pipeline!");
@ -136,7 +136,7 @@ class GeometryPipelineCalculator : public CalculatorBase {
auto multi_face_geometry =
absl::make_unique<std::vector<face_geometry::FaceGeometry>>();
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
*multi_face_geometry,
geometry_pipeline_->EstimateFaceGeometry(
multi_face_landmarks, //
@ -160,7 +160,7 @@ class GeometryPipelineCalculator : public CalculatorBase {
private:
static absl::StatusOr<face_geometry::GeometryPipelineMetadata>
ReadMetadataFromFile(const std::string& metadata_path) {
ASSIGN_OR_RETURN(std::string metadata_blob,
MP_ASSIGN_OR_RETURN(std::string metadata_blob,
ReadContentBlobFromFile(metadata_path),
_ << "Failed to read a metadata blob from file!");
@ -173,7 +173,8 @@ class GeometryPipelineCalculator : public CalculatorBase {
static absl::StatusOr<std::string> ReadContentBlobFromFile(
const std::string& unresolved_path) {
ASSIGN_OR_RETURN(std::string resolved_path,
MP_ASSIGN_OR_RETURN(
std::string resolved_path,
mediapipe::PathToResourceAsFile(unresolved_path),
_ << "Failed to resolve path! Path = " << unresolved_path);

30
mediapipe/modules/face_geometry/libs/effect_renderer.cc
View File

@ -48,19 +48,19 @@ struct RenderableMesh3d {
RenderableMesh3d renderable_mesh_3d;
renderable_mesh_3d.vertex_size = GetVertexSize(vertex_type);
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
renderable_mesh_3d.vertex_position_size,
GetVertexComponentSize(vertex_type, VertexComponent::POSITION),
_ << "Failed to get the position vertex size!");
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
renderable_mesh_3d.tex_coord_position_size,
GetVertexComponentSize(vertex_type, VertexComponent::TEX_COORD),
_ << "Failed to get the tex coord vertex size!");
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
renderable_mesh_3d.vertex_position_offset,
GetVertexComponentOffset(vertex_type, VertexComponent::POSITION),
_ << "Failed to get the position vertex offset!");
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
renderable_mesh_3d.tex_coord_position_offset,
GetVertexComponentOffset(vertex_type, VertexComponent::TEX_COORD),
_ << "Failed to get the tex coord vertex offset!");
@ -473,12 +473,12 @@ class EffectRendererImpl : public EffectRenderer {
}
// Wrap both source and destination textures.
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
std::unique_ptr<Texture> src_texture,
Texture::WrapExternalTexture(src_texture_name, src_texture_target,
frame_width, frame_height),
_ << "Failed to wrap the external source texture");
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
std::unique_ptr<Texture> dst_texture,
Texture::WrapExternalTexture(dst_texture_name, dst_texture_target,
frame_width, frame_height),
@ -506,14 +506,14 @@ class EffectRendererImpl : public EffectRenderer {
const FaceGeometry& face_geometry = multi_face_geometry[i];
// Extract the face pose transformation matrix.
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
face_pose_transform_matrices[i],
Convert4x4MatrixDataToArrayFormat(
face_geometry.pose_transform_matrix()),
_ << "Failed to extract the face pose transformation matrix!");
// Extract the face mesh as a renderable.
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
renderable_face_meshes[i],
RenderableMesh3d::CreateFromProtoMesh3d(face_geometry.mesh()),
_ << "Failed to extract a renderable face mesh!");
@ -699,24 +699,26 @@ absl::StatusOr<std::unique_ptr<EffectRenderer>> CreateEffectRenderer(
<< "Invalid effect 3D mesh!";
}
ASSIGN_OR_RETURN(std::unique_ptr<RenderTarget> render_target,
MP_ASSIGN_OR_RETURN(std::unique_ptr<RenderTarget> render_target,
RenderTarget::Create(),
_ << "Failed to create a render target!");
ASSIGN_OR_RETURN(std::unique_ptr<Renderer> renderer, Renderer::Create(),
MP_ASSIGN_OR_RETURN(std::unique_ptr<Renderer> renderer, Renderer::Create(),
_ << "Failed to create a renderer!");
ASSIGN_OR_RETURN(RenderableMesh3d renderable_quad_mesh_3d,
MP_ASSIGN_OR_RETURN(
RenderableMesh3d renderable_quad_mesh_3d,
RenderableMesh3d::CreateFromProtoMesh3d(CreateQuadMesh3d()),
_ << "Failed to create a renderable quad mesh!");
absl::optional<RenderableMesh3d> renderable_effect_mesh_3d;
if (effect_mesh_3d) {
ASSIGN_OR_RETURN(renderable_effect_mesh_3d,
MP_ASSIGN_OR_RETURN(
renderable_effect_mesh_3d,
RenderableMesh3d::CreateFromProtoMesh3d(*effect_mesh_3d),
_ << "Failed to create a renderable effect mesh!");
}
ASSIGN_OR_RETURN(std::unique_ptr<Texture> empty_color_gl_texture,
MP_ASSIGN_OR_RETURN(std::unique_ptr<Texture> empty_color_gl_texture,
Texture::CreateFromImageFrame(CreateEmptyColorTexture()),
_ << "Failed to create an empty color texture!");
ASSIGN_OR_RETURN(std::unique_ptr<Texture> effect_gl_texture,
MP_ASSIGN_OR_RETURN(std::unique_ptr<Texture> effect_gl_texture,
Texture::CreateFromImageFrame(effect_texture),
_ << "Failed to create an effect texture!");

4
mediapipe/modules/face_geometry/libs/geometry_pipeline.cc
View File

@ -142,7 +142,7 @@ class ScreenToMetricSpaceConverter {
Eigen::Matrix3Xf intermediate_landmarks(screen_landmarks);
ChangeHandedness(intermediate_landmarks);
ASSIGN_OR_RETURN(const float first_iteration_scale,
MP_ASSIGN_OR_RETURN(const float first_iteration_scale,
EstimateScale(intermediate_landmarks),
_ << "Failed to estimate first iteration scale!");
@ -167,7 +167,7 @@ class ScreenToMetricSpaceConverter {
canonical_metric_landmarks_.colwise().homogeneous())
.row(2);
}
ASSIGN_OR_RETURN(const float second_iteration_scale,
MP_ASSIGN_OR_RETURN(const float second_iteration_scale,
EstimateScale(intermediate_landmarks),
_ << "Failed to estimate second iteration scale!");

2
mediapipe/modules/face_geometry/libs/procrustes_solver.cc
View File

@ -172,7 +172,7 @@ class FloatPrecisionProcrustesSolver : public ProcrustesSolver {
MP_RETURN_IF_ERROR(ComputeOptimalRotation(
weighted_targets * centered_weighted_sources.transpose(), rotation))
<< "Failed to compute the optimal rotation!";
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
float scale,
ComputeOptimalScale(centered_weighted_sources, weighted_sources,
weighted_targets, rotation),

10
mediapipe/objc/util.cc
View File

@ -315,7 +315,7 @@ absl::Status CreateCVPixelBufferForImageFramePacket(
auto image_frame = std::const_pointer_cast<mediapipe::ImageFrame>(
mediapipe::SharedPtrWithPacket<mediapipe::ImageFrame>(
image_frame_packet));
ASSIGN_OR_RETURN(*out_buffer, CreateCVPixelBufferForImageFrame(
MP_ASSIGN_OR_RETURN(*out_buffer, CreateCVPixelBufferForImageFrame(
image_frame, can_overwrite));
return absl::OkStatus();
}
@ -339,7 +339,7 @@ absl::StatusOr<CFHolder<CVPixelBufferRef>> CreateCVPixelBufferForImageFrame(
if (can_overwrite) {
v_dest = v_image;
} else {
ASSIGN_OR_RETURN(pixel_buffer,
MP_ASSIGN_OR_RETURN(pixel_buffer,
CreateCVPixelBufferWithoutPool(
frame.Width(), frame.Height(), pixel_format));
status = CVPixelBufferLockBaseAddress(*pixel_buffer,
@ -456,9 +456,9 @@ absl::StatusOr<CFHolder<CVPixelBufferRef>> CreateCVPixelBufferCopyingImageFrame(
}
CVReturn cv_err;
ASSIGN_OR_RETURN(pixel_buffer, CreateCVPixelBufferWithoutPool(
image_frame.Width(), image_frame.Height(),
pixel_format));
MP_ASSIGN_OR_RETURN(pixel_buffer, CreateCVPixelBufferWithoutPool(
image_frame.Width(),
image_frame.Height(), pixel_format));
cv_err =
CVPixelBufferLockBaseAddress(*pixel_buffer, kCVPixelBufferLock_ReadOnly);
RET_CHECK(cv_err == kCVReturnSuccess)

8
mediapipe/tasks/cc/audio/audio_classifier/audio_classifier_graph.cc
View File

@ -91,7 +91,7 @@ absl::StatusOr<AudioTensorSpecs> BuildPreprocessingSpecs(
}
const auto* input_tensor =
(*primary_subgraph->tensors())[(*primary_subgraph->inputs())[0]];
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
const auto* audio_tensor_metadata,
GetAudioTensorMetadataIfAny(*model_resources.GetMetadataExtractor(), 0));
return BuildInputAudioTensorSpecs(*input_tensor, audio_tensor_metadata);
@ -154,11 +154,11 @@ class AudioClassifierGraph : public core::ModelTaskGraph {
public:
absl::StatusOr<CalculatorGraphConfig> GetConfig(
SubgraphContext* sc) override {
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
const auto* model_resources,
CreateModelResources<proto::AudioClassifierGraphOptions>(sc));
Graph graph;
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto output_streams,
BuildAudioClassificationTask(
sc->Options<proto::AudioClassifierGraphOptions>(), *model_resources,
@ -202,7 +202,7 @@ class AudioClassifierGraph : public core::ModelTaskGraph {
}
// Adds AudioToTensorCalculator and connects it to the graph input streams.
ASSIGN_OR_RETURN(auto audio_tensor_specs,
MP_ASSIGN_OR_RETURN(auto audio_tensor_specs,
BuildPreprocessingSpecs(model_resources));
auto& audio_to_tensor = graph.AddNode("AudioToTensorCalculator");
ConfigureAudioToTensorCalculator(

8
mediapipe/tasks/cc/audio/audio_embedder/audio_embedder_graph.cc
View File

@ -83,7 +83,7 @@ absl::StatusOr<AudioTensorSpecs> BuildPreprocessingSpecs(
}
const auto* input_tensor =
(*primary_subgraph->tensors())[(*primary_subgraph->inputs())[0]];
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
const auto* audio_tensor_metadata,
GetAudioTensorMetadataIfAny(*model_resources.GetMetadataExtractor(), 0));
return BuildInputAudioTensorSpecs(*input_tensor, audio_tensor_metadata);
@ -144,11 +144,11 @@ class AudioEmbedderGraph : public core::ModelTaskGraph {
public:
absl::StatusOr<CalculatorGraphConfig> GetConfig(
SubgraphContext* sc) override {
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
const auto* model_resources,
CreateModelResources<proto::AudioEmbedderGraphOptions>(sc));
Graph graph;
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto output_streams,
BuildAudioEmbeddingTask(
sc->Options<proto::AudioEmbedderGraphOptions>(), *model_resources,
@ -178,7 +178,7 @@ class AudioEmbedderGraph : public core::ModelTaskGraph {
MediaPipeTasksStatus::kMetadataNotFoundError);
}
// Adds AudioToTensorCalculator and connects it to the graph input streams.
ASSIGN_OR_RETURN(auto audio_tensor_specs,
MP_ASSIGN_OR_RETURN(auto audio_tensor_specs,
BuildPreprocessingSpecs(model_resources));
auto& audio_to_tensor = graph.AddNode("AudioToTensorCalculator");
ConfigureAudioToTensorCalculator(

2
mediapipe/tasks/cc/audio/core/audio_task_api_factory.h
View File

@ -81,7 +81,7 @@ class AudioTaskApiFactory {
"callback shouldn't be provided.",
MediaPipeTasksStatus::kInvalidTaskGraphConfigError);
}
ASSIGN_OR_RETURN(auto runner,
MP_ASSIGN_OR_RETURN(auto runner,
tasks::core::TaskRunner::Create(
std::move(graph_config), std::move(resolver),
std::move(packets_callback)));

2
mediapipe/tasks/cc/audio/utils/audio_tensor_specs.cc
View File

@ -107,7 +107,7 @@ absl::StatusOr<AudioTensorSpecs> BuildInputAudioTensorSpecs(
MediaPipeTasksStatus::kMetadataNotFoundError);
}
ASSIGN_OR_RETURN(const AudioProperties* props,
MP_ASSIGN_OR_RETURN(const AudioProperties* props,
GetAudioPropertiesIfAny(*audio_tensor_metadata));
// Input-related specifications.
int tensor_shape_size = audio_tensor.shape()->size();

4
mediapipe/tasks/cc/components/calculators/classification_aggregation_calculator_test.cc
View File

@ -98,12 +98,12 @@ class ClassificationAggregationCalculatorTest : public tflite::testing::Test {
MP_RETURN_IF_ERROR(calculator_graph_.Initialize(graph.GetConfig()));
if (connect_timestamps) {
ASSIGN_OR_RETURN(auto poller, calculator_graph_.AddOutputStreamPoller(
MP_ASSIGN_OR_RETURN(auto poller, calculator_graph_.AddOutputStreamPoller(
kTimestampedClassificationsName));
MP_RETURN_IF_ERROR(calculator_graph_.StartRun(/*extra_side_packets=*/{}));
return poller;
}
ASSIGN_OR_RETURN(auto poller, calculator_graph_.AddOutputStreamPoller(
MP_ASSIGN_OR_RETURN(auto poller, calculator_graph_.AddOutputStreamPoller(
kClassificationsName));
MP_RETURN_IF_ERROR(calculator_graph_.StartRun(/*extra_side_packets=*/{}));
return poller;

4
mediapipe/tasks/cc/components/calculators/embedding_aggregation_calculator_test.cc
View File

@ -74,12 +74,12 @@ class EmbeddingAggregationCalculatorTest : public tflite::testing::Test {
MP_RETURN_IF_ERROR(calculator_graph_.Initialize(graph.GetConfig()));
if (connect_timestamps) {
ASSIGN_OR_RETURN(auto poller, calculator_graph_.AddOutputStreamPoller(
MP_ASSIGN_OR_RETURN(auto poller, calculator_graph_.AddOutputStreamPoller(
kTimestampedEmbeddingsName));
MP_RETURN_IF_ERROR(calculator_graph_.StartRun(/*extra_side_packets=*/{}));
return poller;
}
ASSIGN_OR_RETURN(auto poller, calculator_graph_.AddOutputStreamPoller(
MP_ASSIGN_OR_RETURN(auto poller, calculator_graph_.AddOutputStreamPoller(
kEmbeddingsOutName));
MP_RETURN_IF_ERROR(calculator_graph_.StartRun(/*extra_side_packets=*/{}));
return poller;

2
mediapipe/tasks/cc/components/calculators/score_calibration_calculator.cc
View File

@ -178,7 +178,7 @@ absl::Status ScoreCalibrationCalculator::Process(CalculatorContext* cc) {
for (int i = 0; i < num_scores; ++i) {
// Use the "safe" flavor as we need to check that the externally provided
// indices are not out-of-bounds.
ASSIGN_OR_RETURN(raw_calibrated_scores[i],
MP_ASSIGN_OR_RETURN(raw_calibrated_scores[i],
SafeComputeCalibratedScore(
static_cast<int>(raw_indices[i]), raw_scores[i]));
}

25
mediapipe/tasks/cc/components/processors/classification_postprocessing_graph.cc
View File

@ -180,7 +180,7 @@ absl::StatusOr<LabelItems> GetLabelItemsIfAny(
LabelItems empty_label_items;
return empty_label_items;
}
ASSIGN_OR_RETURN(absl::string_view labels_file,
MP_ASSIGN_OR_RETURN(absl::string_view labels_file,
metadata_extractor.GetAssociatedFile(labels_filename));
const std::string display_names_filename =
ModelMetadataExtractor::FindFirstAssociatedFileName(
@ -188,8 +188,9 @@ absl::StatusOr<LabelItems> GetLabelItemsIfAny(
locale);
absl::string_view display_names_file;
if (!display_names_filename.empty()) {
ASSIGN_OR_RETURN(display_names_file, metadata_extractor.GetAssociatedFile(
display_names_filename));
MP_ASSIGN_OR_RETURN(
display_names_file,
metadata_extractor.GetAssociatedFile(display_names_filename));
}
return mediapipe::BuildLabelMapFromFiles(labels_file, display_names_file);
}
@ -199,7 +200,7 @@ absl::StatusOr<LabelItems> GetLabelItemsIfAny(
absl::StatusOr<float> GetScoreThreshold(
const ModelMetadataExtractor& metadata_extractor,
const TensorMetadata& tensor_metadata) {
ASSIGN_OR_RETURN(const ProcessUnit* score_thresholding_process_unit,
MP_ASSIGN_OR_RETURN(const ProcessUnit* score_thresholding_process_unit,
metadata_extractor.FindFirstProcessUnit(
tensor_metadata,
tflite::ProcessUnitOptions_ScoreThresholdingOptions));
@ -255,7 +256,7 @@ absl::Status ConfigureScoreCalibrationIfAny(
return absl::OkStatus();
}
// Get ScoreCalibrationOptions, if any.
ASSIGN_OR_RETURN(const ProcessUnit* score_calibration_process_unit,
MP_ASSIGN_OR_RETURN(const ProcessUnit* score_calibration_process_unit,
metadata_extractor.FindFirstProcessUnit(
*tensor_metadata,
tflite::ProcessUnitOptions_ScoreCalibrationOptions));
@ -276,7 +277,7 @@ absl::Status ConfigureScoreCalibrationIfAny(
"parameters file with type TENSOR_AXIS_SCORE_CALIBRATION.",
MediaPipeTasksStatus::kMetadataAssociatedFileNotFoundError);
}
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
absl::string_view score_calibration_file,
metadata_extractor.GetAssociatedFile(score_calibration_filename));
ScoreCalibrationCalculatorOptions calculator_options;
@ -317,14 +318,14 @@ absl::Status ConfigureTensorsToClassificationCalculator(
LabelItems label_items;
float score_threshold = kDefaultScoreThreshold;
if (tensor_metadata != nullptr) {
ASSIGN_OR_RETURN(label_items,
MP_ASSIGN_OR_RETURN(label_items,
GetLabelItemsIfAny(metadata_extractor, *tensor_metadata,
options.display_names_locale()));
ASSIGN_OR_RETURN(score_threshold,
GetScoreThreshold(metadata_extractor, *tensor_metadata));
MP_ASSIGN_OR_RETURN(score_threshold, GetScoreThreshold(metadata_extractor,
*tensor_metadata));
}
// Allowlist / denylist.
ASSIGN_OR_RETURN(auto allow_or_deny_categories,
MP_ASSIGN_OR_RETURN(auto allow_or_deny_categories,
GetAllowOrDenyCategoryIndicesIfAny(options, label_items));
if (!allow_or_deny_categories.empty()) {
if (options.category_allowlist_size()) {
@ -359,7 +360,7 @@ absl::Status ConfigureClassificationPostprocessingGraph(
const proto::ClassifierOptions& classifier_options,
proto::ClassificationPostprocessingGraphOptions* options) {
MP_RETURN_IF_ERROR(SanityCheckClassifierOptions(classifier_options));
ASSIGN_OR_RETURN(const auto heads_properties,
MP_ASSIGN_OR_RETURN(const auto heads_properties,
GetClassificationHeadsProperties(model_resources));
for (int i = 0; i < heads_properties.num_heads; ++i) {
MP_RETURN_IF_ERROR(ConfigureScoreCalibrationIfAny(
@ -406,7 +407,7 @@ class ClassificationPostprocessingGraph : public mediapipe::Subgraph {
absl::StatusOr<mediapipe::CalculatorGraphConfig> GetConfig(
mediapipe::SubgraphContext* sc) override {
Graph graph;
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto output_streams,
BuildClassificationPostprocessing(
sc->Options<proto::ClassificationPostprocessingGraphOptions>(),

6
mediapipe/tasks/cc/components/processors/classification_postprocessing_graph_test.cc
View File

@ -422,7 +422,7 @@ class PostprocessingTest : public tflite::testing::Test {
absl::StatusOr<OutputStreamPoller> BuildGraph(
absl::string_view model_name, const proto::ClassifierOptions& options,
bool connect_timestamps = false) {
ASSIGN_OR_RETURN(auto model_resources,
MP_ASSIGN_OR_RETURN(auto model_resources,
CreateModelResourcesForModel(model_name));
Graph graph;
@ -450,12 +450,12 @@ class PostprocessingTest : public tflite::testing::Test {
MP_RETURN_IF_ERROR(calculator_graph_.Initialize(graph.GetConfig()));
if (connect_timestamps) {
ASSIGN_OR_RETURN(auto poller, calculator_graph_.AddOutputStreamPoller(
MP_ASSIGN_OR_RETURN(auto poller, calculator_graph_.AddOutputStreamPoller(
kTimestampedClassificationsName));
MP_RETURN_IF_ERROR(calculator_graph_.StartRun(/*extra_side_packets=*/{}));
return poller;
}
ASSIGN_OR_RETURN(auto poller, calculator_graph_.AddOutputStreamPoller(
MP_ASSIGN_OR_RETURN(auto poller, calculator_graph_.AddOutputStreamPoller(
kClassificationsName));
MP_RETURN_IF_ERROR(calculator_graph_.StartRun(/*extra_side_packets=*/{}));
return poller;

37
mediapipe/tasks/cc/components/processors/detection_postprocessing_graph.cc
View File

@ -221,15 +221,16 @@ absl::StatusOr<LabelItems> GetLabelItemsIfAny(
LabelItems empty_label_items;
return empty_label_items;
}
ASSIGN_OR_RETURN(absl::string_view labels_file,
MP_ASSIGN_OR_RETURN(absl::string_view labels_file,
metadata_extractor.GetAssociatedFile(labels_filename));
const std::string display_names_filename =
ModelMetadataExtractor::FindFirstAssociatedFileName(
tensor_metadata, associated_file_type, locale);
absl::string_view display_names_file;
if (!display_names_filename.empty()) {
ASSIGN_OR_RETURN(display_names_file, metadata_extractor.GetAssociatedFile(
display_names_filename));
MP_ASSIGN_OR_RETURN(
display_names_file,
metadata_extractor.GetAssociatedFile(display_names_filename));
}
return mediapipe::BuildLabelMapFromFiles(labels_file, display_names_file);
}
@ -237,7 +238,7 @@ absl::StatusOr<LabelItems> GetLabelItemsIfAny(
absl::StatusOr<float> GetScoreThreshold(
const ModelMetadataExtractor& metadata_extractor,
const TensorMetadata& tensor_metadata) {
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
const ProcessUnit* score_thresholding_process_unit,
metadata_extractor.FindFirstProcessUnit(
tensor_metadata, ProcessUnitOptions_ScoreThresholdingOptions));
@ -288,7 +289,7 @@ GetScoreCalibrationOptionsIfAny(
const ModelMetadataExtractor& metadata_extractor,
const TensorMetadata& tensor_metadata) {
// Get ScoreCalibrationOptions, if any.
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
const ProcessUnit* score_calibration_process_unit,
metadata_extractor.FindFirstProcessUnit(
tensor_metadata, tflite::ProcessUnitOptions_ScoreCalibrationOptions));
@ -309,7 +310,7 @@ GetScoreCalibrationOptionsIfAny(
"parameters file with type TENSOR_AXIS_SCORE_CALIBRATION.",
MediaPipeTasksStatus::kMetadataAssociatedFileNotFoundError);
}
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
absl::string_view score_calibration_file,
metadata_extractor.GetAssociatedFile(score_calibration_filename));
ScoreCalibrationCalculatorOptions score_calibration_calculator_options;
@ -393,11 +394,11 @@ absl::StatusOr<PostProcessingSpecs> BuildPostProcessingSpecs(
metadata_extractor->GetOutputTensorMetadata();
PostProcessingSpecs specs;
specs.max_results = options.max_results();
ASSIGN_OR_RETURN(specs.output_tensor_indices,
MP_ASSIGN_OR_RETURN(specs.output_tensor_indices,
GetOutputTensorIndices(output_tensors_metadata));
// Extracts mandatory BoundingBoxProperties and performs sanity checks on the
// fly.
ASSIGN_OR_RETURN(const BoundingBoxProperties* bounding_box_properties,
MP_ASSIGN_OR_RETURN(const BoundingBoxProperties* bounding_box_properties,
GetBoundingBoxProperties(*output_tensors_metadata->Get(
specs.output_tensor_indices[0])));
if (bounding_box_properties->index() == nullptr) {
@ -415,7 +416,7 @@ absl::StatusOr<PostProcessingSpecs> BuildPostProcessingSpecs(
// For models with in-model-nms, the label map is stored in the Category
// tensor which use TENSOR_VALUE_LABELS. For models with out-of-model-nms, the
// label map is stored in the Score tensor which use TENSOR_AXIS_LABELS.
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
specs.label_items,
GetLabelItemsIfAny(
*metadata_extractor,
@ -425,7 +426,7 @@ absl::StatusOr<PostProcessingSpecs> BuildPostProcessingSpecs(
options.display_names_locale()));
// Obtains allow/deny categories.
specs.is_allowlist = !options.category_allowlist().empty();
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
specs.allow_or_deny_categories,
GetAllowOrDenyCategoryIndicesIfAny(options, specs.label_items));
@ -433,7 +434,7 @@ absl::StatusOr<PostProcessingSpecs> BuildPostProcessingSpecs(
if (options.has_score_threshold()) {
specs.score_threshold = options.score_threshold();
} else {
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
specs.score_threshold,
GetScoreThreshold(
*metadata_extractor,
@ -444,7 +445,7 @@ absl::StatusOr<PostProcessingSpecs> BuildPostProcessingSpecs(
}
if (in_model_nms) {
// Builds score calibration options (if available) from metadata.
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
specs.score_calibration_options,
GetScoreCalibrationOptionsIfAny(
*metadata_extractor,
@ -741,7 +742,7 @@ absl::Status ConfigureDetectionPostprocessingGraph(
const ModelMetadataExtractor* metadata_extractor =
model_resources.GetMetadataExtractor();
if (in_model_nms) {
ASSIGN_OR_RETURN(auto post_processing_specs,
MP_ASSIGN_OR_RETURN(auto post_processing_specs,
BuildInModelNmsPostProcessingSpecs(detector_options,
metadata_extractor));
ConfigureInModelNmsTensorsToDetectionsCalculator(
@ -754,9 +755,9 @@ absl::Status ConfigureDetectionPostprocessingGraph(
std::move(*post_processing_specs.score_calibration_options);
}
} else {
ASSIGN_OR_RETURN(auto post_processing_specs,
BuildOutModelNmsPostProcessingSpecs(detector_options,
metadata_extractor));
MP_ASSIGN_OR_RETURN(auto post_processing_specs,
BuildOutModelNmsPostProcessingSpecs(
detector_options, metadata_extractor));
MP_RETURN_IF_ERROR(ConfigureOutModelNmsTensorsToDetectionsCalculator(
metadata_extractor, post_processing_specs,
options.mutable_tensors_to_detections_options()));
@ -795,7 +796,7 @@ class DetectionPostprocessingGraph : public mediapipe::Subgraph {
absl::StatusOr<mediapipe::CalculatorGraphConfig> GetConfig(
mediapipe::SubgraphContext* sc) override {
Graph graph;
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto output_streams,
BuildDetectionPostprocessing(
*sc->MutableOptions<proto::DetectionPostprocessingGraphOptions>(),
@ -823,7 +824,7 @@ class DetectionPostprocessingGraph : public mediapipe::Subgraph {
if (!graph_options.has_non_max_suppression_options()) {
// Calculators to perform score calibration, if specified in the options.
if (graph_options.has_score_calibration_options()) {
ASSIGN_OR_RETURN(tensors_in,
MP_ASSIGN_OR_RETURN(tensors_in,
CalibrateScores(tensors_in, graph_options, graph));
}
// Calculator to convert output tensors to a detection proto vector.

4
mediapipe/tasks/cc/components/processors/detection_postprocessing_graph_test.cc
View File

@ -318,7 +318,7 @@ class PostprocessingTest : public tflite::testing::Test {
protected:
absl::StatusOr<OutputStreamPoller> BuildGraph(
absl::string_view model_name, const proto::DetectorOptions& options) {
ASSIGN_OR_RETURN(auto model_resources,
MP_ASSIGN_OR_RETURN(auto model_resources,
CreateModelResourcesForModel(model_name));
Graph graph;
@ -335,7 +335,7 @@ class PostprocessingTest : public tflite::testing::Test {
postprocessing.Out(kDetectionsTag).SetName(std::string(kDetectionsName)) >>
graph[Output<std::vector<Detection>>(kDetectionsTag)];
MP_RETURN_IF_ERROR(calculator_graph_.Initialize(graph.GetConfig()));
ASSIGN_OR_RETURN(auto poller, calculator_graph_.AddOutputStreamPoller(
MP_ASSIGN_OR_RETURN(auto poller, calculator_graph_.AddOutputStreamPoller(
std::string(kDetectionsName)));
MP_RETURN_IF_ERROR(calculator_graph_.StartRun(/*extra_side_packets=*/{}));
return poller;

6
mediapipe/tasks/cc/components/processors/embedding_postprocessing_graph.cc
View File

@ -151,13 +151,13 @@ absl::Status ConfigureEmbeddingPostprocessingGraph(
const ModelResources& model_resources,
const proto::EmbedderOptions& embedder_options,
proto::EmbeddingPostprocessingGraphOptions* options) {
ASSIGN_OR_RETURN(bool has_quantized_outputs,
MP_ASSIGN_OR_RETURN(bool has_quantized_outputs,
HasQuantizedOutputs(model_resources));
options->set_has_quantized_outputs(has_quantized_outputs);
auto* tensors_to_embeddings_options =
options->mutable_tensors_to_embeddings_options();
*tensors_to_embeddings_options->mutable_embedder_options() = embedder_options;
ASSIGN_OR_RETURN(auto head_names, GetHeadNames(model_resources));
MP_ASSIGN_OR_RETURN(auto head_names, GetHeadNames(model_resources));
if (!head_names.empty()) {
*tensors_to_embeddings_options->mutable_head_names() = {head_names.begin(),
head_names.end()};
@ -197,7 +197,7 @@ class EmbeddingPostprocessingGraph : public mediapipe::Subgraph {
absl::StatusOr<mediapipe::CalculatorGraphConfig> GetConfig(
mediapipe::SubgraphContext* sc) override {
Graph graph;
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
auto output_streams,
BuildEmbeddingPostprocessing(
sc->Options<proto::EmbeddingPostprocessingGraphOptions>(),

8
mediapipe/tasks/cc/components/processors/embedding_postprocessing_graph_test.cc
View File

@ -159,7 +159,7 @@ class PostprocessingTest : public tflite::testing::Test {
absl::string_view model_name, const proto::EmbedderOptions& options,
bool connect_timestamps = false,
const std::vector<absl::string_view>& ignored_head_names = {}) {
ASSIGN_OR_RETURN(auto model_resources,
MP_ASSIGN_OR_RETURN(auto model_resources,
CreateModelResourcesForModel(model_name));
Graph graph;
@ -192,13 +192,13 @@ class PostprocessingTest : public tflite::testing::Test {
MP_RETURN_IF_ERROR(calculator_graph_.Initialize(graph.GetConfig()));
if (connect_timestamps) {
ASSIGN_OR_RETURN(auto poller, calculator_graph_.AddOutputStreamPoller(
MP_ASSIGN_OR_RETURN(auto poller, calculator_graph_.AddOutputStreamPoller(
kTimestampedEmbeddingsName));
MP_RETURN_IF_ERROR(calculator_graph_.StartRun(/*extra_side_packets=*/{}));
return poller;
}
ASSIGN_OR_RETURN(auto poller,
calculator_graph_.AddOutputStreamPoller(kEmbeddingsName));
MP_ASSIGN_OR_RETURN(
auto poller, calculator_graph_.AddOutputStreamPoller(kEmbeddingsName));
MP_RETURN_IF_ERROR(calculator_graph_.StartRun(/*extra_side_packets=*/{}));
return poller;
}

2
mediapipe/tasks/cc/components/processors/image_preprocessing_graph.cc
View File

@ -125,7 +125,7 @@ bool DetermineImagePreprocessingGpuBackend(
absl::Status ConfigureImagePreprocessingGraph(
const ModelResources& model_resources, bool use_gpu,
proto::ImagePreprocessingGraphOptions* options) {
ASSIGN_OR_RETURN(auto image_tensor_specs,
MP_ASSIGN_OR_RETURN(auto image_tensor_specs,
vision::BuildInputImageTensorSpecs(model_resources));
MP_RETURN_IF_ERROR(ConfigureImageToTensorCalculator(
image_tensor_specs, options->mutable_image_to_tensor_options()));

10
mediapipe/tasks/cc/components/processors/text_preprocessing_graph.cc
View File

@ -180,7 +180,7 @@ absl::Status ConfigureTextPreprocessingGraph(
MediaPipeTasksStatus::kInvalidArgumentError);
}
ASSIGN_OR_RETURN(TextModelType::ModelType model_type,
MP_ASSIGN_OR_RETURN(TextModelType::ModelType model_type,
GetModelType(model_resources));
const tflite::SubGraph& model_graph =
*(*model_resources.GetTfLiteModel()->subgraphs())[0];
@ -193,12 +193,12 @@ absl::Status ConfigureTextPreprocessingGraph(
}
case TextModelType::BERT_MODEL:
case TextModelType::REGEX_MODEL: {
ASSIGN_OR_RETURN(int max_seq_len, GetMaxSeqLen(model_graph));
MP_ASSIGN_OR_RETURN(int max_seq_len, GetMaxSeqLen(model_graph));
options.set_max_seq_len(max_seq_len);
}
}
if (model_type == TextModelType::BERT_MODEL) {
ASSIGN_OR_RETURN(bool has_dynamic_input_tensors,
MP_ASSIGN_OR_RETURN(bool has_dynamic_input_tensors,
HasDynamicInputTensors(model_graph));
options.set_has_dynamic_input_tensors(has_dynamic_input_tensors);
}
@ -227,7 +227,7 @@ class TextPreprocessingGraph : public mediapipe::Subgraph {
absl::StatusOr<mediapipe::CalculatorGraphConfig> GetConfig(
mediapipe::SubgraphContext* sc) override {
Graph graph;
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
Source<std::vector<Tensor>> tensors_in,
BuildTextPreprocessing(
sc->Options<TextPreprocessingGraphOptions>(),
@ -242,7 +242,7 @@ class TextPreprocessingGraph : public mediapipe::Subgraph {
absl::StatusOr<Source<std::vector<Tensor>>> BuildTextPreprocessing(
const TextPreprocessingGraphOptions& options, Source<std::string> text_in,
SideSource<ModelMetadataExtractor> metadata_extractor_in, Graph& graph) {
ASSIGN_OR_RETURN(std::string preprocessor_name,
MP_ASSIGN_OR_RETURN(std::string preprocessor_name,
GetCalculatorNameFromModelType(options.model_type()));
auto& text_preprocessor = graph.AddNode(preprocessor_name);
switch (options.model_type()) {

2
mediapipe/tasks/cc/core/external_file_handler.cc
View File

@ -122,7 +122,7 @@ absl::Status ExternalFileHandler::MapExternalFile() {
// Obtain file descriptor, offset and size.
int fd = -1;
if (!external_file_.file_name().empty()) {
ASSIGN_OR_RETURN(std::string file_name,
MP_ASSIGN_OR_RETURN(std::string file_name,
PathToResourceAsFile(external_file_.file_name()));
owned_fd_ = open(file_name.c_str(), O_RDONLY | O_BINARY);
if (owned_fd_ < 0) {

4
mediapipe/tasks/cc/core/model_asset_bundle_resources.cc
View File

@ -59,12 +59,12 @@ absl::Status ModelAssetBundleResources::ExtractFilesFromExternalFileProto() {
if (model_asset_bundle_file_->has_file_name()) {
// If the model asset bundle file name is a relative path, searches the file
// in a platform-specific location and returns the absolute path on success.
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
std::string path_to_resource,
mediapipe::PathToResourceAsFile(model_asset_bundle_file_->file_name()));
model_asset_bundle_file_->set_file_name(path_to_resource);
}
ASSIGN_OR_RETURN(model_asset_bundle_file_handler_,
MP_ASSIGN_OR_RETURN(model_asset_bundle_file_handler_,
ExternalFileHandler::CreateFromExternalFile(
model_asset_bundle_file_.get()));
const char* buffer_data =

6
mediapipe/tasks/cc/core/model_resources.cc
View File

@ -110,12 +110,12 @@ absl::Status ModelResources::BuildModelFromExternalFileProto() {
} else {
// If the model file name is a relative path, searches the file in a
// platform-specific location and returns the absolute path on success.
ASSIGN_OR_RETURN(std::string path_to_resource,
MP_ASSIGN_OR_RETURN(std::string path_to_resource,
PathToResourceAsFile(model_file_->file_name()));
model_file_->set_file_name(path_to_resource);
}
}
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
model_file_handler_,
ExternalFileHandler::CreateFromExternalFile(model_file_.get()));
const char* buffer_data = model_file_handler_->GetFileContent().data();
@ -152,7 +152,7 @@ absl::Status ModelResources::BuildModelFromExternalFileProto() {
model_packet_ = MakePacket<ModelPtr>(
model.release(), [](tflite::FlatBufferModel* model) { delete model; });
ASSIGN_OR_RETURN(auto model_metadata_extractor,
MP_ASSIGN_OR_RETURN(auto model_metadata_extractor,
metadata::ModelMetadataExtractor::CreateFromModelBuffer(
buffer_data, buffer_size));
metadata_extractor_packet_ = PacketAdopting<metadata::ModelMetadataExtractor>(

2
mediapipe/tasks/cc/core/model_resources_calculator.cc
View File

@ -109,7 +109,7 @@ class ModelResourcesCalculator : public api2::Node {
"ModelResourcesCacheService, and the CalculatorOptions has no "
"'model_file' field to create a local ModelResources.");
}
ASSIGN_OR_RETURN(
MP_ASSIGN_OR_RETURN(
model_resources_,
ModelResources::Create(
"", std::make_unique<proto::ExternalFile>(options.model_file())));

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