Add a GpuOrigin parameter to TensorConverterCalculator

The parameter superseeds flip_vertically. GpuOrigin works more generally than flip_vertically because CONVENTIONAL works on both iOS (no flip) and Android (yes flip). If not set, the calculator falls back to flip_vertically for backwards compatibility.

Note that web demos actually use TOP_LEFT image orientation, so they shouldn't be flipped, but they still are by CONVENTIONAL. That's being discussed right now.

PiperOrigin-RevId: 553400525
This commit is contained in:
MediaPipe Team 2023-08-03 01:37:51 -07:00 committed by Copybara-Service
parent 9325af0af3
commit a0b91e4062
4 changed files with 166 additions and 20 deletions

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@ -620,6 +620,7 @@ mediapipe_proto_library(
deps = [ deps = [
"//mediapipe/framework:calculator_options_proto", "//mediapipe/framework:calculator_options_proto",
"//mediapipe/framework:calculator_proto", "//mediapipe/framework:calculator_proto",
"//mediapipe/gpu:gpu_origin_proto",
], ],
) )
@ -649,7 +650,11 @@ cc_library(
"//mediapipe/framework/formats:matrix", "//mediapipe/framework/formats:matrix",
"//mediapipe/framework/formats:tensor", "//mediapipe/framework/formats:tensor",
"//mediapipe/framework/port:ret_check", "//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"//mediapipe/framework/port:statusor",
"//mediapipe/gpu:gpu_origin_cc_proto",
"//mediapipe/util:resource_util", "//mediapipe/util:resource_util",
"@com_google_absl//absl/strings:str_format",
] + select({ ] + select({
"//mediapipe/gpu:disable_gpu": [], "//mediapipe/gpu:disable_gpu": [],
"//conditions:default": ["tensor_converter_calculator_gpu_deps"], "//conditions:default": ["tensor_converter_calculator_gpu_deps"],

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@ -15,6 +15,9 @@
#include <string> #include <string>
#include <vector> #include <vector>
#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "absl/strings/str_format.h"
#include "mediapipe/calculators/tensor/tensor_converter_calculator.pb.h" #include "mediapipe/calculators/tensor/tensor_converter_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h" #include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/formats/image_frame.h" #include "mediapipe/framework/formats/image_frame.h"
@ -22,7 +25,7 @@
#include "mediapipe/framework/formats/tensor.h" #include "mediapipe/framework/formats/tensor.h"
#include "mediapipe/framework/port.h" #include "mediapipe/framework/port.h"
#include "mediapipe/framework/port/ret_check.h" #include "mediapipe/framework/port/ret_check.h"
#include "mediapipe/util/resource_util.h" #include "mediapipe/gpu/gpu_origin.pb.h"
#if !MEDIAPIPE_DISABLE_GPU #if !MEDIAPIPE_DISABLE_GPU
#include "mediapipe/gpu/gpu_buffer.h" #include "mediapipe/gpu/gpu_buffer.h"
@ -43,12 +46,36 @@
#endif // !MEDIAPIPE_DISABLE_GPU #endif // !MEDIAPIPE_DISABLE_GPU
namespace { namespace {
constexpr int kWorkgroupSize = 8; // Block size for GPU shader. constexpr int kWorkgroupSize = 8; // Block size for GPU shader.
// Commonly used to compute the number of blocks to launch in a kernel. // Commonly used to compute the number of blocks to launch in a kernel.
int NumGroups(const int size, const int group_size) { // NOLINT int NumGroups(const int size, const int group_size) { // NOLINT
return (size + group_size - 1) / group_size; return (size + group_size - 1) / group_size;
} }
absl::StatusOr<bool> ShouldFlipVertically(
const mediapipe::TensorConverterCalculatorOptions& options) {
if (!options.has_gpu_origin()) {
return options.flip_vertically();
}
switch (options.gpu_origin()) {
case mediapipe::GpuOrigin::TOP_LEFT:
return false;
case mediapipe::GpuOrigin::DEFAULT:
case mediapipe::GpuOrigin::CONVENTIONAL:
// TOP_LEFT on Metal, BOTTOM_LEFT on OpenGL.
#ifdef __APPLE__
return false;
#else
return true;
#endif
}
return absl::InvalidArgumentError(
absl::StrFormat("Unhandled GPU origin %i", options.gpu_origin()));
}
typedef Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> typedef Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>
RowMajorMatrixXf; RowMajorMatrixXf;
typedef Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::ColMajor> typedef Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::ColMajor>
@ -58,6 +85,7 @@ constexpr char kImageFrameTag[] = "IMAGE";
constexpr char kGpuBufferTag[] = "IMAGE_GPU"; constexpr char kGpuBufferTag[] = "IMAGE_GPU";
constexpr char kTensorsTag[] = "TENSORS"; constexpr char kTensorsTag[] = "TENSORS";
constexpr char kMatrixTag[] = "MATRIX"; constexpr char kMatrixTag[] = "MATRIX";
} // namespace } // namespace
namespace mediapipe { namespace mediapipe {
@ -593,7 +621,7 @@ absl::Status TensorConverterCalculator::LoadOptions(CalculatorContext* cc) {
} }
// Get y-flip mode. // Get y-flip mode.
flip_vertically_ = options.flip_vertically(); ASSIGN_OR_RETURN(flip_vertically_, ShouldFlipVertically(options));
// Get row_major_matrix mode. // Get row_major_matrix mode.
row_major_matrix_ = options.row_major_matrix(); row_major_matrix_ = options.row_major_matrix();

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@ -3,6 +3,7 @@ syntax = "proto2";
package mediapipe; package mediapipe;
import "mediapipe/framework/calculator.proto"; import "mediapipe/framework/calculator.proto";
import "mediapipe/gpu/gpu_origin.proto";
// Full Example: // Full Example:
// //
@ -43,8 +44,14 @@ message TensorConverterCalculatorOptions {
// with a coordinate system where the origin is at the bottom-left corner // with a coordinate system where the origin is at the bottom-left corner
// (e.g., in OpenGL) whereas the ML model expects an image with a top-left // (e.g., in OpenGL) whereas the ML model expects an image with a top-left
// origin. // origin.
// Prefer gpu_origin over this field.
optional bool flip_vertically = 2 [default = false]; optional bool flip_vertically = 2 [default = false];
// Determines when the input image should be flipped vertically.
// See GpuOrigin.Mode for more information.
// If unset, falls back to flip_vertically for backwards compatibility.
optional GpuOrigin.Mode gpu_origin = 10;
// Controls how many channels of the input image get passed through to the // Controls how many channels of the input image get passed through to the
// tensor. Valid values are 1,3,4 only. Ignored for iOS GPU. // tensor. Valid values are 1,3,4 only. Ignored for iOS GPU.
optional int32 max_num_channels = 3 [default = 3]; optional int32 max_num_channels = 3 [default = 3];

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@ -259,25 +259,22 @@ TEST_F(TensorConverterCalculatorTest, SetOutputRange) {
for (std::pair<float, float> range : range_values) { for (std::pair<float, float> range : range_values) {
CalculatorGraph graph; CalculatorGraph graph;
CalculatorGraphConfig graph_config = CalculatorGraphConfig graph_config =
mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>( mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(absl::Substitute(
absl::Substitute(R"( R"pb(
input_stream: "input_image" input_stream: "input_image"
node { node {
calculator: "TensorConverterCalculator" calculator: "TensorConverterCalculator"
input_stream: "IMAGE:input_image" input_stream: "IMAGE:input_image"
output_stream: "TENSORS:tensor" output_stream: "TENSORS:tensor"
options { options {
[mediapipe.TensorConverterCalculatorOptions.ext] { [mediapipe.TensorConverterCalculatorOptions.ext] {
output_tensor_float_range { output_tensor_float_range { min: $0 max: $1 }
min: $0 }
max: $1 }
} }
} )pb",
} /*$0=*/range.first,
} /*$1=*/range.second));
)",
/*$0=*/range.first,
/*$1=*/range.second));
std::vector<Packet> output_packets; std::vector<Packet> output_packets;
tool::AddVectorSink("tensor", &graph_config, &output_packets); tool::AddVectorSink("tensor", &graph_config, &output_packets);
@ -320,4 +317,113 @@ TEST_F(TensorConverterCalculatorTest, SetOutputRange) {
} }
} }
TEST_F(TensorConverterCalculatorTest, FlipVertically) {
CalculatorGraph graph;
CalculatorGraphConfig graph_config =
mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(R"pb(
input_stream: "input_image"
node {
calculator: "TensorConverterCalculator"
input_stream: "IMAGE:input_image"
output_stream: "TENSORS:tensor"
options {
[mediapipe.TensorConverterCalculatorOptions.ext] {
flip_vertically: true
output_tensor_float_range { min: 0 max: 255 }
}
}
}
)pb");
std::vector<Packet> output_packets;
tool::AddVectorSink("tensor", &graph_config, &output_packets);
// Run the graph.
MP_ASSERT_OK(graph.Initialize(graph_config));
MP_ASSERT_OK(graph.StartRun({}));
auto input_image = absl::make_unique<ImageFrame>(ImageFormat::GRAY8, 1, 2);
cv::Mat mat = mediapipe::formats::MatView(input_image.get());
constexpr uint8_t kY0Value = 100;
constexpr uint8_t kY1Value = 200;
mat.at<uint8_t>(0, 0) = kY0Value;
mat.at<uint8_t>(1, 0) = kY1Value; // Note: y, x!
MP_ASSERT_OK(graph.AddPacketToInputStream(
"input_image", Adopt(input_image.release()).At(Timestamp(0))));
// Wait until the calculator finishes processing.
MP_ASSERT_OK(graph.WaitUntilIdle());
ASSERT_THAT(output_packets.size(), Eq(1));
// Get and process results.
const std::vector<Tensor>& tensor_vec =
output_packets[0].Get<std::vector<Tensor>>();
EXPECT_THAT(tensor_vec.size(), Eq(1));
const Tensor* tensor = &tensor_vec[0];
EXPECT_THAT(tensor->element_type(), Eq(Tensor::ElementType::kFloat32));
const float* dataf = tensor->GetCpuReadView().buffer<float>();
EXPECT_EQ(kY1Value, static_cast<int>(roundf(dataf[0]))); // Y0, Y1 flipped!
EXPECT_EQ(kY0Value, static_cast<int>(roundf(dataf[1])));
// Fully close graph at end, otherwise calculator+tensors are destroyed
// after calling WaitUntilDone().
MP_ASSERT_OK(graph.CloseInputStream("input_image"));
MP_ASSERT_OK(graph.WaitUntilDone());
}
TEST_F(TensorConverterCalculatorTest, GpuOriginOverridesFlipVertically) {
CalculatorGraph graph;
CalculatorGraphConfig graph_config =
mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(R"pb(
input_stream: "input_image"
node {
calculator: "TensorConverterCalculator"
input_stream: "IMAGE:input_image"
output_stream: "TENSORS:tensor"
options {
[mediapipe.TensorConverterCalculatorOptions.ext] {
flip_vertically: true
gpu_origin: TOP_LEFT
output_tensor_float_range { min: 0 max: 255 }
}
}
}
)pb");
std::vector<Packet> output_packets;
tool::AddVectorSink("tensor", &graph_config, &output_packets);
// Run the graph.
MP_ASSERT_OK(graph.Initialize(graph_config));
MP_ASSERT_OK(graph.StartRun({}));
auto input_image = absl::make_unique<ImageFrame>(ImageFormat::GRAY8, 1, 2);
cv::Mat mat = mediapipe::formats::MatView(input_image.get());
constexpr uint8_t kY0Value = 100;
constexpr uint8_t kY1Value = 200;
mat.at<uint8_t>(0, 0) = kY0Value;
mat.at<uint8_t>(1, 0) = kY1Value; // Note: y, x!
MP_ASSERT_OK(graph.AddPacketToInputStream(
"input_image", Adopt(input_image.release()).At(Timestamp(0))));
// Wait until the calculator finishes processing.
MP_ASSERT_OK(graph.WaitUntilIdle());
EXPECT_THAT(output_packets.size(), Eq(1));
// Get and process results.
const std::vector<Tensor>& tensor_vec =
output_packets[0].Get<std::vector<Tensor>>();
EXPECT_THAT(tensor_vec.size(), Eq(1));
const Tensor* tensor = &tensor_vec[0];
EXPECT_THAT(tensor->element_type(), Eq(Tensor::ElementType::kFloat32));
const float* dataf = tensor->GetCpuReadView().buffer<float>();
EXPECT_EQ(kY0Value, static_cast<int>(roundf(dataf[0]))); // Not flipped!
EXPECT_EQ(kY1Value, static_cast<int>(roundf(dataf[1])));
// Fully close graph at end, otherwise calculator+tensors are destroyed
// after calling WaitUntilDone().
MP_ASSERT_OK(graph.CloseInputStream("input_image"));
MP_ASSERT_OK(graph.WaitUntilDone());
}
} // namespace mediapipe } // namespace mediapipe