Project import generated by Copybara.

GitOrigin-RevId: 08c2016a4df5aef571b464a4d4491f38c6b2af10
This commit is contained in:
MediaPipe Team
2021-06-03 17:04:35 -04:00
committed by chuoling
parent ae05ad04b3
commit 8b57bf879b
118 changed files with 3999 additions and 391 deletions
+73
View File
@@ -753,3 +753,76 @@ cc_test(
"//mediapipe/framework/port:gtest_main",
],
)
# Copied from /mediapipe/calculators/tflite/BUILD
selects.config_setting_group(
name = "gpu_inference_disabled",
match_any = [
"//mediapipe/gpu:disable_gpu",
],
)
mediapipe_proto_library(
name = "tensors_to_segmentation_calculator_proto",
srcs = ["tensors_to_segmentation_calculator.proto"],
visibility = ["//visibility:public"],
deps = [
"//mediapipe/framework:calculator_options_proto",
"//mediapipe/framework:calculator_proto",
"//mediapipe/gpu:gpu_origin_proto",
],
)
cc_library(
name = "tensors_to_segmentation_calculator",
srcs = ["tensors_to_segmentation_calculator.cc"],
copts = select({
"//mediapipe:apple": [
"-x objective-c++",
"-fobjc-arc", # enable reference-counting
],
"//conditions:default": [],
}),
visibility = ["//visibility:public"],
deps = [
":tensors_to_segmentation_calculator_cc_proto",
"@com_google_absl//absl/strings:str_format",
"@com_google_absl//absl/strings",
"@com_google_absl//absl/types:span",
"//mediapipe/framework/formats:image",
"//mediapipe/framework/formats:image_frame",
"//mediapipe/framework/formats:image_opencv",
"//mediapipe/framework/formats:tensor",
"//mediapipe/framework/port:opencv_imgproc",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework:calculator_context",
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework:port",
"//mediapipe/util:resource_util",
"@org_tensorflow//tensorflow/lite:framework",
"//mediapipe/gpu:gpu_origin_cc_proto",
"//mediapipe/framework/port:statusor",
] + selects.with_or({
"//mediapipe/gpu:disable_gpu": [],
"//conditions:default": [
"//mediapipe/gpu:gl_calculator_helper",
"//mediapipe/gpu:gl_simple_shaders",
"//mediapipe/gpu:gpu_buffer",
"//mediapipe/gpu:shader_util",
],
}) + selects.with_or({
":gpu_inference_disabled": [],
"//mediapipe:ios": [
"//mediapipe/gpu:MPPMetalUtil",
"//mediapipe/gpu:MPPMetalHelper",
],
"//conditions:default": [
"@org_tensorflow//tensorflow/lite/delegates/gpu:gl_delegate",
"@org_tensorflow//tensorflow/lite/delegates/gpu/gl:gl_program",
"@org_tensorflow//tensorflow/lite/delegates/gpu/gl:gl_shader",
"@org_tensorflow//tensorflow/lite/delegates/gpu/gl:gl_texture",
"@org_tensorflow//tensorflow/lite/delegates/gpu/gl/converters:util",
],
}),
alwayslink = 1,
)
@@ -105,6 +105,15 @@ void ConvertAnchorsToRawValues(const std::vector<Anchor>& anchors,
// for anchors (e.g. for SSD models) depend on the outputs of the
// detection model. The size of anchor tensor must be (num_boxes *
// 4).
//
// Input side packet:
// ANCHORS (optional) - The anchors used for decoding the bounding boxes, as a
// vector of `Anchor` protos. Not required if post-processing is built-in
// the model.
// IGNORE_CLASSES (optional) - The list of class ids that should be ignored, as
// a vector of integers. It overrides the corresponding field in the
// calculator options.
//
// Output:
// DETECTIONS - Result MediaPipe detections.
//
@@ -132,8 +141,11 @@ class TensorsToDetectionsCalculator : public Node {
static constexpr Input<std::vector<Tensor>> kInTensors{"TENSORS"};
static constexpr SideInput<std::vector<Anchor>>::Optional kInAnchors{
"ANCHORS"};
static constexpr SideInput<std::vector<int>>::Optional kSideInIgnoreClasses{
"IGNORE_CLASSES"};
static constexpr Output<std::vector<Detection>> kOutDetections{"DETECTIONS"};
MEDIAPIPE_NODE_CONTRACT(kInTensors, kInAnchors, kOutDetections);
MEDIAPIPE_NODE_CONTRACT(kInTensors, kInAnchors, kSideInIgnoreClasses,
kOutDetections);
static absl::Status UpdateContract(CalculatorContract* cc);
absl::Status Open(CalculatorContext* cc) override;
@@ -566,8 +578,15 @@ absl::Status TensorsToDetectionsCalculator::LoadOptions(CalculatorContext* cc) {
kNumCoordsPerBox,
num_coords_);
for (int i = 0; i < options_.ignore_classes_size(); ++i) {
ignore_classes_.insert(options_.ignore_classes(i));
if (kSideInIgnoreClasses(cc).IsConnected()) {
RET_CHECK(!kSideInIgnoreClasses(cc).IsEmpty());
for (int ignore_class : *kSideInIgnoreClasses(cc)) {
ignore_classes_.insert(ignore_class);
}
} else {
for (int i = 0; i < options_.ignore_classes_size(); ++i) {
ignore_classes_.insert(options_.ignore_classes(i));
}
}
return absl::OkStatus();
@@ -56,7 +56,7 @@ message TensorsToDetectionsCalculatorOptions {
// [x_center, y_center, w, h].
optional bool reverse_output_order = 14 [default = false];
// The ids of classes that should be ignored during decoding the score for
// each predicted box.
// each predicted box. Can be overridden with IGNORE_CLASSES side packet.
repeated int32 ignore_classes = 8;
optional bool sigmoid_score = 15 [default = false];
@@ -0,0 +1,885 @@
// Copyright 2021 The MediaPipe Authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include <vector>
#include "absl/strings/str_format.h"
#include "absl/types/span.h"
#include "mediapipe/calculators/tensor/tensors_to_segmentation_calculator.pb.h"
#include "mediapipe/framework/calculator_context.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/formats/image.h"
#include "mediapipe/framework/formats/image_opencv.h"
#include "mediapipe/framework/formats/tensor.h"
#include "mediapipe/framework/port.h"
#include "mediapipe/framework/port/opencv_imgproc_inc.h"
#include "mediapipe/framework/port/ret_check.h"
#include "mediapipe/framework/port/statusor.h"
#include "mediapipe/gpu/gpu_origin.pb.h"
#include "mediapipe/util/resource_util.h"
#include "tensorflow/lite/interpreter.h"
#if !MEDIAPIPE_DISABLE_GPU
#include "mediapipe/gpu/gl_calculator_helper.h"
#include "mediapipe/gpu/gl_simple_shaders.h"
#include "mediapipe/gpu/gpu_buffer.h"
#include "mediapipe/gpu/shader_util.h"
#endif // !MEDIAPIPE_DISABLE_GPU
#if MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
#include "tensorflow/lite/delegates/gpu/gl/converters/util.h"
#include "tensorflow/lite/delegates/gpu/gl/gl_program.h"
#include "tensorflow/lite/delegates/gpu/gl/gl_shader.h"
#include "tensorflow/lite/delegates/gpu/gl/gl_texture.h"
#include "tensorflow/lite/delegates/gpu/gl_delegate.h"
#endif // MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
#if MEDIAPIPE_METAL_ENABLED
#import <CoreVideo/CoreVideo.h>
#import <Metal/Metal.h>
#import <MetalKit/MetalKit.h>
#import "mediapipe/gpu/MPPMetalHelper.h"
#include "mediapipe/gpu/MPPMetalUtil.h"
#endif // MEDIAPIPE_METAL_ENABLED
namespace {
constexpr int kWorkgroupSize = 8; // Block size for GPU shader.
enum { ATTRIB_VERTEX, ATTRIB_TEXTURE_POSITION, NUM_ATTRIBUTES };
// Commonly used to compute the number of blocks to launch in a kernel.
int NumGroups(const int size, const int group_size) { // NOLINT
return (size + group_size - 1) / group_size;
}
bool CanUseGpu() {
#if !MEDIAPIPE_DISABLE_GPU || MEDIAPIPE_METAL_ENABLED
// TODO: Configure GPU usage policy in individual calculators.
constexpr bool kAllowGpuProcessing = true;
return kAllowGpuProcessing;
#else
return false;
#endif // !MEDIAPIPE_DISABLE_GPU || MEDIAPIPE_METAL_ENABLED
}
constexpr char kTensorsTag[] = "TENSORS";
constexpr char kOutputSizeTag[] = "OUTPUT_SIZE";
constexpr char kMaskTag[] = "MASK";
absl::StatusOr<std::tuple<int, int, int>> GetHwcFromDims(
const std::vector<int>& dims) {
if (dims.size() == 3) {
return std::make_tuple(dims[0], dims[1], dims[2]);
} else if (dims.size() == 4) {
// BHWC format check B == 1
RET_CHECK_EQ(1, dims[0]) << "Expected batch to be 1 for BHWC heatmap";
return std::make_tuple(dims[1], dims[2], dims[3]);
} else {
RET_CHECK(false) << "Invalid shape for segmentation tensor " << dims.size();
}
}
} // namespace
namespace mediapipe {
#if MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
using ::tflite::gpu::gl::GlProgram;
using ::tflite::gpu::gl::GlShader;
#endif // MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
// Converts Tensors from a tflite segmentation model to an image mask.
//
// Performs optional upscale to OUTPUT_SIZE dimensions if provided,
// otherwise the mask is the same size as input tensor.
//
// If at least one input tensor is already on GPU, processing happens on GPU and
// the output mask is also stored on GPU. Otherwise, processing and the output
// mask are both on CPU.
//
// On GPU, the mask is an RGBA image, in both the R & A channels, scaled 0-1.
// On CPU, the mask is a ImageFormat::VEC32F1 image, with values scaled 0-1.
//
//
// Inputs:
// One of the following TENSORS tags:
// TENSORS: Vector of Tensor,
// The tensor dimensions are specified in this calculator's options.
// OUTPUT_SIZE(optional): std::pair<int, int>,
// If provided, the size to upscale mask to.
//
// Output:
// MASK: An Image output mask, RGBA(GPU) / VEC32F1(CPU).
//
// Options:
// See tensors_to_segmentation_calculator.proto
//
// Usage example:
// node {
// calculator: "TensorsToSegmentationCalculator"
// input_stream: "TENSORS:tensors"
// input_stream: "OUTPUT_SIZE:size"
// output_stream: "MASK:hair_mask"
// node_options: {
// [mediapipe.TensorsToSegmentationCalculatorOptions] {
// output_layer_index: 1
// # gpu_origin: CONVENTIONAL # or TOP_LEFT
// }
// }
// }
//
// Currently only OpenGLES 3.1 and CPU backends supported.
// TODO Refactor and add support for other backends/platforms.
//
class TensorsToSegmentationCalculator : public CalculatorBase {
public:
static absl::Status GetContract(CalculatorContract* cc);
absl::Status Open(CalculatorContext* cc) override;
absl::Status Process(CalculatorContext* cc) override;
absl::Status Close(CalculatorContext* cc) override;
private:
absl::Status LoadOptions(CalculatorContext* cc);
absl::Status InitGpu(CalculatorContext* cc);
absl::Status ProcessGpu(CalculatorContext* cc);
absl::Status ProcessCpu(CalculatorContext* cc);
void GlRender();
bool DoesGpuTextureStartAtBottom() {
return options_.gpu_origin() != mediapipe::GpuOrigin_Mode_TOP_LEFT;
}
template <class T>
absl::Status ApplyActivation(cv::Mat& tensor_mat, cv::Mat* small_mask_mat);
::mediapipe::TensorsToSegmentationCalculatorOptions options_;
#if !MEDIAPIPE_DISABLE_GPU
mediapipe::GlCalculatorHelper gpu_helper_;
GLuint upsample_program_;
#if MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
std::unique_ptr<GlProgram> mask_program_31_;
#else
GLuint mask_program_20_;
#endif // MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
#if MEDIAPIPE_METAL_ENABLED
MPPMetalHelper* metal_helper_ = nullptr;
id<MTLComputePipelineState> mask_program_;
#endif // MEDIAPIPE_METAL_ENABLED
#endif // !MEDIAPIPE_DISABLE_GPU
};
REGISTER_CALCULATOR(TensorsToSegmentationCalculator);
// static
absl::Status TensorsToSegmentationCalculator::GetContract(
CalculatorContract* cc) {
RET_CHECK(!cc->Inputs().GetTags().empty());
RET_CHECK(!cc->Outputs().GetTags().empty());
// Inputs.
cc->Inputs().Tag(kTensorsTag).Set<std::vector<Tensor>>();
if (cc->Inputs().HasTag(kOutputSizeTag)) {
cc->Inputs().Tag(kOutputSizeTag).Set<std::pair<int, int>>();
}
// Outputs.
cc->Outputs().Tag(kMaskTag).Set<Image>();
if (CanUseGpu()) {
#if !MEDIAPIPE_DISABLE_GPU
MP_RETURN_IF_ERROR(mediapipe::GlCalculatorHelper::UpdateContract(cc));
#if MEDIAPIPE_METAL_ENABLED
MP_RETURN_IF_ERROR([MPPMetalHelper updateContract:cc]);
#endif // MEDIAPIPE_METAL_ENABLED
#endif // !MEDIAPIPE_DISABLE_GPU
}
return absl::OkStatus();
}
absl::Status TensorsToSegmentationCalculator::Open(CalculatorContext* cc) {
cc->SetOffset(TimestampDiff(0));
bool use_gpu = false;
if (CanUseGpu()) {
#if !MEDIAPIPE_DISABLE_GPU
use_gpu = true;
MP_RETURN_IF_ERROR(gpu_helper_.Open(cc));
#if MEDIAPIPE_METAL_ENABLED
metal_helper_ = [[MPPMetalHelper alloc] initWithCalculatorContext:cc];
RET_CHECK(metal_helper_);
#endif // MEDIAPIPE_METAL_ENABLED
#endif // !MEDIAPIPE_DISABLE_GPU
}
MP_RETURN_IF_ERROR(LoadOptions(cc));
if (use_gpu) {
#if !MEDIAPIPE_DISABLE_GPU
MP_RETURN_IF_ERROR(InitGpu(cc));
#else
RET_CHECK_FAIL() << "GPU processing disabled.";
#endif // !MEDIAPIPE_DISABLE_GPU
}
return absl::OkStatus();
}
absl::Status TensorsToSegmentationCalculator::Process(CalculatorContext* cc) {
if (cc->Inputs().Tag(kTensorsTag).IsEmpty()) {
return absl::OkStatus();
}
const auto& input_tensors =
cc->Inputs().Tag(kTensorsTag).Get<std::vector<Tensor>>();
bool use_gpu = false;
if (CanUseGpu()) {
// Use GPU processing only if at least one input tensor is already on GPU.
for (const auto& tensor : input_tensors) {
if (tensor.ready_on_gpu()) {
use_gpu = true;
break;
}
}
}
// Validate tensor channels and activation type.
{
RET_CHECK(!input_tensors.empty());
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()) {
case Options::NONE:
RET_CHECK_EQ(tensor_channels, 1);
break;
case Options::SIGMOID:
RET_CHECK_EQ(tensor_channels, 1);
break;
case Options::SOFTMAX:
RET_CHECK_EQ(tensor_channels, 2);
break;
}
}
if (use_gpu) {
#if !MEDIAPIPE_DISABLE_GPU
MP_RETURN_IF_ERROR(gpu_helper_.RunInGlContext([this, cc]() -> absl::Status {
MP_RETURN_IF_ERROR(ProcessGpu(cc));
return absl::OkStatus();
}));
#else
RET_CHECK_FAIL() << "GPU processing disabled.";
#endif // !MEDIAPIPE_DISABLE_GPU
} else {
MP_RETURN_IF_ERROR(ProcessCpu(cc));
}
return absl::OkStatus();
}
absl::Status TensorsToSegmentationCalculator::Close(CalculatorContext* cc) {
#if !MEDIAPIPE_DISABLE_GPU
gpu_helper_.RunInGlContext([this] {
if (upsample_program_) glDeleteProgram(upsample_program_);
upsample_program_ = 0;
#if MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
mask_program_31_.reset();
#else
if (mask_program_20_) glDeleteProgram(mask_program_20_);
mask_program_20_ = 0;
#endif // MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
#if MEDIAPIPE_METAL_ENABLED
mask_program_ = nil;
#endif // MEDIAPIPE_METAL_ENABLED
});
#endif // !MEDIAPIPE_DISABLE_GPU
return absl::OkStatus();
}
absl::Status TensorsToSegmentationCalculator::ProcessCpu(
CalculatorContext* cc) {
// 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));
auto [tensor_height, tensor_width, tensor_channels] = hwc;
int output_width = tensor_width, output_height = tensor_height;
if (cc->Inputs().HasTag(kOutputSizeTag)) {
const auto& size =
cc->Inputs().Tag(kOutputSizeTag).Get<std::pair<int, int>>();
output_width = size.first;
output_height = size.second;
}
// Create initial working mask.
cv::Mat small_mask_mat(cv::Size(tensor_width, tensor_height), CV_32FC1);
// Wrap input tensor.
auto raw_input_tensor = &input_tensors[0];
auto raw_input_view = raw_input_tensor->GetCpuReadView();
const float* raw_input_data = raw_input_view.buffer<float>();
cv::Mat tensor_mat(cv::Size(tensor_width, tensor_height),
CV_MAKETYPE(CV_32F, tensor_channels),
const_cast<float*>(raw_input_data));
// Process mask tensor and apply activation function.
if (tensor_channels == 2) {
MP_RETURN_IF_ERROR(ApplyActivation<cv::Vec2f>(tensor_mat, &small_mask_mat));
} else if (tensor_channels == 1) {
RET_CHECK(mediapipe::TensorsToSegmentationCalculatorOptions::SOFTMAX !=
options_.activation()); // Requires 2 channels.
if (mediapipe::TensorsToSegmentationCalculatorOptions::NONE ==
options_.activation()) // Pass-through optimization.
tensor_mat.copyTo(small_mask_mat);
else
MP_RETURN_IF_ERROR(ApplyActivation<float>(tensor_mat, &small_mask_mat));
} else {
RET_CHECK_FAIL() << "Unsupported number of tensor channels "
<< tensor_channels;
}
// Send out image as CPU packet.
std::shared_ptr<ImageFrame> mask_frame = std::make_shared<ImageFrame>(
ImageFormat::VEC32F1, output_width, output_height);
std::unique_ptr<Image> output_mask = absl::make_unique<Image>(mask_frame);
cv::Mat output_mat = formats::MatView(output_mask.get());
// Upsample small mask into output.
cv::resize(small_mask_mat, output_mat, cv::Size(output_width, output_height));
cc->Outputs().Tag(kMaskTag).Add(output_mask.release(), cc->InputTimestamp());
return absl::OkStatus();
}
template <class T>
absl::Status TensorsToSegmentationCalculator::ApplyActivation(
cv::Mat& tensor_mat, cv::Mat* small_mask_mat) {
// Configure activation function.
const int output_layer_index = options_.output_layer_index();
typedef mediapipe::TensorsToSegmentationCalculatorOptions Options;
const auto activation_fn = [&](const cv::Vec2f& mask_value) {
float new_mask_value = 0;
// TODO consider moving switch out of the loop,
// and also avoid float/Vec2f casting.
switch (options_.activation()) {
case Options::NONE: {
new_mask_value = mask_value[0];
break;
}
case Options::SIGMOID: {
const float pixel0 = mask_value[0];
new_mask_value = 1.0 / (std::exp(-pixel0) + 1.0);
break;
}
case Options::SOFTMAX: {
const float pixel0 = mask_value[0];
const float pixel1 = mask_value[1];
const float max_pixel = std::max(pixel0, pixel1);
const float min_pixel = std::min(pixel0, pixel1);
const float softmax_denom =
/*exp(max_pixel - max_pixel)=*/1.0f +
std::exp(min_pixel - max_pixel);
new_mask_value = std::exp(mask_value[output_layer_index] - max_pixel) /
softmax_denom;
break;
}
}
return new_mask_value;
};
// Process mask tensor.
for (int i = 0; i < tensor_mat.rows; ++i) {
for (int j = 0; j < tensor_mat.cols; ++j) {
const T& input_pix = tensor_mat.at<T>(i, j);
const float mask_value = activation_fn(input_pix);
small_mask_mat->at<float>(i, j) = mask_value;
}
}
return absl::OkStatus();
}
// Steps:
// 1. receive tensor
// 2. process segmentation tensor into small mask
// 3. upsample small mask into output mask to be same size as input image
absl::Status TensorsToSegmentationCalculator::ProcessGpu(
CalculatorContext* cc) {
#if !MEDIAPIPE_DISABLE_GPU
// 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));
auto [tensor_height, tensor_width, tensor_channels] = hwc;
int output_width = tensor_width, output_height = tensor_height;
if (cc->Inputs().HasTag(kOutputSizeTag)) {
const auto& size =
cc->Inputs().Tag(kOutputSizeTag).Get<std::pair<int, int>>();
output_width = size.first;
output_height = size.second;
}
// Create initial working mask texture.
#if MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
tflite::gpu::gl::GlTexture small_mask_texture;
#else
mediapipe::GlTexture small_mask_texture;
#endif // MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
// Run shader, process mask tensor.
#if MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
{
MP_RETURN_IF_ERROR(CreateReadWriteRgbaImageTexture(
tflite::gpu::DataType::UINT8, // GL_RGBA8
{tensor_width, tensor_height}, &small_mask_texture));
const int output_index = 0;
glBindImageTexture(output_index, small_mask_texture.id(), 0, GL_FALSE, 0,
GL_WRITE_ONLY, GL_RGBA8);
auto read_view = input_tensors[0].GetOpenGlBufferReadView();
glBindBufferBase(GL_SHADER_STORAGE_BUFFER, 2, read_view.name());
const tflite::gpu::uint3 workgroups = {
NumGroups(tensor_width, kWorkgroupSize),
NumGroups(tensor_height, kWorkgroupSize), 1};
glUseProgram(mask_program_31_->id());
glUniform2i(glGetUniformLocation(mask_program_31_->id(), "out_size"),
tensor_width, tensor_height);
MP_RETURN_IF_ERROR(mask_program_31_->Dispatch(workgroups));
}
#elif MEDIAPIPE_METAL_ENABLED
{
id<MTLCommandBuffer> command_buffer = [metal_helper_ commandBuffer];
command_buffer.label = @"SegmentationKernel";
id<MTLComputeCommandEncoder> command_encoder =
[command_buffer computeCommandEncoder];
[command_encoder setComputePipelineState:mask_program_];
auto read_view = input_tensors[0].GetMtlBufferReadView(command_buffer);
[command_encoder setBuffer:read_view.buffer() offset:0 atIndex:0];
mediapipe::GpuBuffer small_mask_buffer = [metal_helper_
mediapipeGpuBufferWithWidth:tensor_width
height:tensor_height
format:mediapipe::GpuBufferFormat::kBGRA32];
id<MTLTexture> small_mask_texture_metal =
[metal_helper_ metalTextureWithGpuBuffer:small_mask_buffer];
[command_encoder setTexture:small_mask_texture_metal atIndex:1];
unsigned int out_size[] = {static_cast<unsigned int>(tensor_width),
static_cast<unsigned int>(tensor_height)};
[command_encoder setBytes:&out_size length:sizeof(out_size) atIndex:2];
MTLSize threads_per_group = MTLSizeMake(kWorkgroupSize, kWorkgroupSize, 1);
MTLSize threadgroups =
MTLSizeMake(NumGroups(tensor_width, kWorkgroupSize),
NumGroups(tensor_height, kWorkgroupSize), 1);
[command_encoder dispatchThreadgroups:threadgroups
threadsPerThreadgroup:threads_per_group];
[command_encoder endEncoding];
[command_buffer commit];
small_mask_texture = gpu_helper_.CreateSourceTexture(small_mask_buffer);
}
#else
{
small_mask_texture = gpu_helper_.CreateDestinationTexture(
tensor_width, tensor_height,
mediapipe::GpuBufferFormat::kBGRA32); // actually GL_RGBA8
// Go through CPU if not already texture 2D (no direct conversion yet).
// Tensor::GetOpenGlTexture2dReadView() doesn't automatically convert types.
if (!input_tensors[0].ready_as_opengl_texture_2d()) {
(void)input_tensors[0].GetCpuReadView();
}
auto read_view = input_tensors[0].GetOpenGlTexture2dReadView();
gpu_helper_.BindFramebuffer(small_mask_texture);
glActiveTexture(GL_TEXTURE1);
glBindTexture(GL_TEXTURE_2D, read_view.name());
glUseProgram(mask_program_20_);
GlRender();
glBindTexture(GL_TEXTURE_2D, 0);
glFlush();
}
#endif // MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
// Upsample small mask into output.
mediapipe::GlTexture output_texture = gpu_helper_.CreateDestinationTexture(
output_width, output_height,
mediapipe::GpuBufferFormat::kBGRA32); // actually GL_RGBA8
// Run shader, upsample result.
{
gpu_helper_.BindFramebuffer(output_texture);
glActiveTexture(GL_TEXTURE1);
#if MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
glBindTexture(GL_TEXTURE_2D, small_mask_texture.id());
#else
glBindTexture(GL_TEXTURE_2D, small_mask_texture.name());
#endif // MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
glUseProgram(upsample_program_);
GlRender();
glBindTexture(GL_TEXTURE_2D, 0);
glFlush();
}
// Send out image as GPU packet.
auto output_image = output_texture.GetFrame<Image>();
cc->Outputs().Tag(kMaskTag).Add(output_image.release(), cc->InputTimestamp());
// Cleanup
output_texture.Release();
#endif // !MEDIAPIPE_DISABLE_GPU
return absl::OkStatus();
}
void TensorsToSegmentationCalculator::GlRender() {
#if !MEDIAPIPE_DISABLE_GPU
static const GLfloat square_vertices[] = {
-1.0f, -1.0f, // bottom left
1.0f, -1.0f, // bottom right
-1.0f, 1.0f, // top left
1.0f, 1.0f, // top right
};
static const GLfloat texture_vertices[] = {
0.0f, 0.0f, // bottom left
1.0f, 0.0f, // bottom right
0.0f, 1.0f, // top left
1.0f, 1.0f, // top right
};
// vertex storage
GLuint vbo[2];
glGenBuffers(2, vbo);
GLuint vao;
glGenVertexArrays(1, &vao);
glBindVertexArray(vao);
// vbo 0
glBindBuffer(GL_ARRAY_BUFFER, vbo[0]);
glBufferData(GL_ARRAY_BUFFER, 4 * 2 * sizeof(GLfloat), square_vertices,
GL_STATIC_DRAW);
glEnableVertexAttribArray(ATTRIB_VERTEX);
glVertexAttribPointer(ATTRIB_VERTEX, 2, GL_FLOAT, 0, 0, nullptr);
// vbo 1
glBindBuffer(GL_ARRAY_BUFFER, vbo[1]);
glBufferData(GL_ARRAY_BUFFER, 4 * 2 * sizeof(GLfloat), texture_vertices,
GL_STATIC_DRAW);
glEnableVertexAttribArray(ATTRIB_TEXTURE_POSITION);
glVertexAttribPointer(ATTRIB_TEXTURE_POSITION, 2, GL_FLOAT, 0, 0, nullptr);
// draw
glDrawArrays(GL_TRIANGLE_STRIP, 0, 4);
// cleanup
glDisableVertexAttribArray(ATTRIB_VERTEX);
glDisableVertexAttribArray(ATTRIB_TEXTURE_POSITION);
glBindBuffer(GL_ARRAY_BUFFER, 0);
glBindVertexArray(0);
glDeleteVertexArrays(1, &vao);
glDeleteBuffers(2, vbo);
#endif // !MEDIAPIPE_DISABLE_GPU
}
absl::Status TensorsToSegmentationCalculator::LoadOptions(
CalculatorContext* cc) {
// Get calculator options specified in the graph.
options_ = cc->Options<::mediapipe::TensorsToSegmentationCalculatorOptions>();
return absl::OkStatus();
}
absl::Status TensorsToSegmentationCalculator::InitGpu(CalculatorContext* cc) {
#if !MEDIAPIPE_DISABLE_GPU
MP_RETURN_IF_ERROR(gpu_helper_.RunInGlContext([this]() -> absl::Status {
// A shader to process a segmentation tensor into an output mask.
// Currently uses 4 channels for output, and sets R+A channels as mask value.
#if MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
// GLES 3.1
const tflite::gpu::uint3 workgroup_size = {kWorkgroupSize, kWorkgroupSize,
1};
const std::string shader_header =
absl::StrCat(tflite::gpu::gl::GetShaderHeader(workgroup_size), R"(
precision highp float;
layout(rgba8, binding = 0) writeonly uniform highp image2D output_texture;
uniform ivec2 out_size;
)");
/* Shader defines will be inserted here. */
const std::string shader_src_main = R"(
layout(std430, binding = 2) readonly buffer B0 {
#ifdef TWO_CHANNEL_INPUT
vec2 elements[];
#else
float elements[];
#endif // TWO_CHANNEL_INPUT
} input_data; // data tensor
void main() {
int out_width = out_size.x;
int out_height = out_size.y;
ivec2 gid = ivec2(gl_GlobalInvocationID.xy);
if (gid.x >= out_width || gid.y >= out_height) { return; }
int linear_index = gid.y * out_width + gid.x;
#ifdef TWO_CHANNEL_INPUT
vec2 input_value = input_data.elements[linear_index];
#else
vec2 input_value = vec2(input_data.elements[linear_index], 0.0);
#endif // TWO_CHANNEL_INPUT
// Run activation function.
// One and only one of FN_SOFTMAX,FN_SIGMOID,FN_NONE will be defined.
#ifdef FN_SOFTMAX
// Only two channel input tensor is supported.
vec2 input_px = input_value.rg;
float shift = max(input_px.r, input_px.g);
float softmax_denom = exp(input_px.r - shift) + exp(input_px.g - shift);
float new_mask_value =
exp(input_px[OUTPUT_LAYER_INDEX] - shift) / softmax_denom;
#endif // FN_SOFTMAX
#ifdef FN_SIGMOID
float new_mask_value = 1.0 / (exp(-input_value.r) + 1.0);
#endif // FN_SIGMOID
#ifdef FN_NONE
float new_mask_value = input_value.r;
#endif // FN_NONE
#ifdef FLIP_Y_COORD
int y_coord = out_height - gid.y - 1;
#else
int y_coord = gid.y;
#endif // defined(FLIP_Y_COORD)
ivec2 output_coordinate = ivec2(gid.x, y_coord);
vec4 out_value = vec4(new_mask_value, 0.0, 0.0, new_mask_value);
imageStore(output_texture, output_coordinate, out_value);
})";
#elif MEDIAPIPE_METAL_ENABLED
// METAL
const std::string shader_header = R"(
#include <metal_stdlib>
using namespace metal;
)";
/* Shader defines will be inserted here. */
const std::string shader_src_main = R"(
kernel void segmentationKernel(
#ifdef TWO_CHANNEL_INPUT
device float2* elements [[ buffer(0) ]],
#else
device float* elements [[ buffer(0) ]],
#endif // TWO_CHANNEL_INPUT
texture2d<float, access::write> output_texture [[ texture(1) ]],
constant uint* out_size [[ buffer(2) ]],
uint2 gid [[ thread_position_in_grid ]])
{
uint out_width = out_size[0];
uint out_height = out_size[1];
if (gid.x >= out_width || gid.y >= out_height) { return; }
uint linear_index = gid.y * out_width + gid.x;
#ifdef TWO_CHANNEL_INPUT
float2 input_value = elements[linear_index];
#else
float2 input_value = float2(elements[linear_index], 0.0);
#endif // TWO_CHANNEL_INPUT
// Run activation function.
// One and only one of FN_SOFTMAX,FN_SIGMOID,FN_NONE will be defined.
#ifdef FN_SOFTMAX
// Only two channel input tensor is supported.
float2 input_px = input_value.xy;
float shift = max(input_px.x, input_px.y);
float softmax_denom = exp(input_px.r - shift) + exp(input_px.g - shift);
float new_mask_value =
exp(input_px[OUTPUT_LAYER_INDEX] - shift) / softmax_denom;
#endif // FN_SOFTMAX
#ifdef FN_SIGMOID
float new_mask_value = 1.0 / (exp(-input_value.x) + 1.0);
#endif // FN_SIGMOID
#ifdef FN_NONE
float new_mask_value = input_value.x;
#endif // FN_NONE
#ifdef FLIP_Y_COORD
int y_coord = out_height - gid.y - 1;
#else
int y_coord = gid.y;
#endif // defined(FLIP_Y_COORD)
uint2 output_coordinate = uint2(gid.x, y_coord);
float4 out_value = float4(new_mask_value, 0.0, 0.0, new_mask_value);
output_texture.write(out_value, output_coordinate);
}
)";
#else
// GLES 2.0
const std::string shader_header = absl::StrCat(
std::string(mediapipe::kMediaPipeFragmentShaderPreamble), R"(
DEFAULT_PRECISION(mediump, float)
)");
/* Shader defines will be inserted here. */
const std::string shader_src_main = R"(
in vec2 sample_coordinate;
uniform sampler2D input_texture;
#ifdef GL_ES
#define fragColor gl_FragColor
#else
out vec4 fragColor;
#endif // defined(GL_ES);
void main() {
vec4 input_value = texture2D(input_texture, sample_coordinate);
vec2 gid = sample_coordinate;
// Run activation function.
// One and only one of FN_SOFTMAX,FN_SIGMOID,FN_NONE will be defined.
#ifdef FN_SOFTMAX
// Only two channel input tensor is supported.
vec2 input_px = input_value.rg;
float shift = max(input_px.r, input_px.g);
float softmax_denom = exp(input_px.r - shift) + exp(input_px.g - shift);
float new_mask_value =
exp(mix(input_px.r, input_px.g, float(OUTPUT_LAYER_INDEX)) - shift) / softmax_denom;
#endif // FN_SOFTMAX
#ifdef FN_SIGMOID
float new_mask_value = 1.0 / (exp(-input_value.r) + 1.0);
#endif // FN_SIGMOID
#ifdef FN_NONE
float new_mask_value = input_value.r;
#endif // FN_NONE
#ifdef FLIP_Y_COORD
float y_coord = 1.0 - gid.y;
#else
float y_coord = gid.y;
#endif // defined(FLIP_Y_COORD)
vec2 output_coordinate = vec2(gid.x, y_coord);
vec4 out_value = vec4(new_mask_value, 0.0, 0.0, new_mask_value);
fragColor = out_value;
})";
#endif // MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
// Shader defines.
typedef mediapipe::TensorsToSegmentationCalculatorOptions Options;
const std::string output_layer_index =
"\n#define OUTPUT_LAYER_INDEX int(" +
std::to_string(options_.output_layer_index()) + ")";
const std::string flip_y_coord =
DoesGpuTextureStartAtBottom() ? "\n#define FLIP_Y_COORD" : "";
const std::string fn_none =
options_.activation() == Options::NONE ? "\n#define FN_NONE" : "";
const std::string fn_sigmoid =
options_.activation() == Options::SIGMOID ? "\n#define FN_SIGMOID" : "";
const std::string fn_softmax =
options_.activation() == Options::SOFTMAX ? "\n#define FN_SOFTMAX" : "";
const std::string two_channel = options_.activation() == Options::SOFTMAX
? "\n#define TWO_CHANNEL_INPUT"
: "";
const std::string shader_defines =
absl::StrCat(output_layer_index, flip_y_coord, fn_softmax, fn_sigmoid,
fn_none, two_channel);
// Build full shader.
const std::string shader_src_no_previous =
absl::StrCat(shader_header, shader_defines, shader_src_main);
// Vertex shader attributes.
const GLint attr_location[NUM_ATTRIBUTES] = {
ATTRIB_VERTEX,
ATTRIB_TEXTURE_POSITION,
};
const GLchar* attr_name[NUM_ATTRIBUTES] = {
"position",
"texture_coordinate",
};
// Main shader program & parameters
#if MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
GlShader shader_without_previous;
MP_RETURN_IF_ERROR(GlShader::CompileShader(
GL_COMPUTE_SHADER, shader_src_no_previous, &shader_without_previous));
mask_program_31_ = absl::make_unique<GlProgram>();
MP_RETURN_IF_ERROR(GlProgram::CreateWithShader(shader_without_previous,
mask_program_31_.get()));
#elif MEDIAPIPE_METAL_ENABLED
id<MTLDevice> device = metal_helper_.mtlDevice;
NSString* library_source =
[NSString stringWithUTF8String:shader_src_no_previous.c_str()];
NSError* error = nil;
id<MTLLibrary> library = [device newLibraryWithSource:library_source
options:nullptr
error:&error];
RET_CHECK(library != nil) << "Couldn't create shader library "
<< [[error localizedDescription] UTF8String];
id<MTLFunction> kernel_func = nil;
kernel_func = [library newFunctionWithName:@"segmentationKernel"];
RET_CHECK(kernel_func != nil) << "Couldn't create kernel function.";
mask_program_ =
[device newComputePipelineStateWithFunction:kernel_func error:&error];
RET_CHECK(mask_program_ != nil) << "Couldn't create pipeline state " <<
[[error localizedDescription] UTF8String];
#else
mediapipe::GlhCreateProgram(
mediapipe::kBasicVertexShader, shader_src_no_previous.c_str(),
NUM_ATTRIBUTES, &attr_name[0], attr_location, &mask_program_20_);
RET_CHECK(mask_program_20_) << "Problem initializing the program.";
glUseProgram(mask_program_20_);
glUniform1i(glGetUniformLocation(mask_program_20_, "input_texture"), 1);
#endif // MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
// Simple pass-through program, used for hardware upsampling.
mediapipe::GlhCreateProgram(
mediapipe::kBasicVertexShader, mediapipe::kBasicTexturedFragmentShader,
NUM_ATTRIBUTES, &attr_name[0], attr_location, &upsample_program_);
RET_CHECK(upsample_program_) << "Problem initializing the program.";
glUseProgram(upsample_program_);
glUniform1i(glGetUniformLocation(upsample_program_, "video_frame"), 1);
return absl::OkStatus();
}));
#endif // !MEDIAPIPE_DISABLE_GPU
return absl::OkStatus();
}
} // namespace mediapipe
@@ -0,0 +1,46 @@
// Copyright 2021 The MediaPipe Authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
syntax = "proto2";
package mediapipe;
import "mediapipe/framework/calculator.proto";
import "mediapipe/gpu/gpu_origin.proto";
message TensorsToSegmentationCalculatorOptions {
extend mediapipe.CalculatorOptions {
optional TensorsToSegmentationCalculatorOptions ext = 374311106;
}
// For CONVENTIONAL mode in OpenGL, textures start at bottom and needs
// to be flipped vertically as tensors are expected to start at top.
// (DEFAULT or unset is interpreted as CONVENTIONAL.)
optional GpuOrigin.Mode gpu_origin = 1;
// Supported activation functions for filtering.
enum Activation {
NONE = 0; // Assumes 1-channel input tensor.
SIGMOID = 1; // Assumes 1-channel input tensor.
SOFTMAX = 2; // Assumes 2-channel input tensor.
}
// Activation function to apply to input tensor.
// Softmax requires a 2-channel tensor, see output_layer_index below.
optional Activation activation = 2 [default = NONE];
// Channel to use for processing tensor.
// Only applies when using activation=SOFTMAX.
// Works on two channel input tensor only.
optional int32 output_layer_index = 3 [default = 1];
}