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Deformation model

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This commit is contained in:
mslight 2022-07-19 16:11:27 +04:00
parent d7bc754150
commit a6ca4007f4
24 changed files with 2831 additions and 0 deletions
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81
mediapipe/examples/android/src/java/com/google/mediapipe/apps/deformation/BUILD Normal file
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# Copyright 2019 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.
licenses(["notice"])
package(default_visibility = ["//visibility:private"])
cc_binary(
name = "libmediapipe_jni.so",
linkshared = 1,
linkstatic = 1,
deps = [
"//mediapipe/graphs/deformation:mobile_calculators",
"//mediapipe/java/com/google/mediapipe/framework/jni:mediapipe_framework_jni",
],
)
cc_library(
name = "mediapipe_jni_lib",
srcs = [":libmediapipe_jni.so"],
alwayslink = 1,
)
ASSETS_DIR = "//mediapipe/graphs/deformation/config"
android_binary(
name = "deformationgpu",
srcs = glob(["*.java"]),
assets = [
"//mediapipe/graphs/deformation:mobile_gpu.binarypb",
"//mediapipe/modules/face_landmark:face_landmark_with_attention.tflite",
"//mediapipe/modules/face_detection:face_detection_short_range.tflite",
ASSETS_DIR+":triangles.txt",
ASSETS_DIR+":index_names.txt",
ASSETS_DIR+":mediumFaceIndexes.txt",
ASSETS_DIR+":mediumNoseIndexes.txt",
ASSETS_DIR+":noseAllIndexes.txt",
ASSETS_DIR+":cheekbonesIndexes.txt",
ASSETS_DIR+":additionalNoseIndexes1.txt",
ASSETS_DIR+":additionalNoseIndexes2.txt",
ASSETS_DIR+":additionalNoseIndexes3.txt",
ASSETS_DIR+":faceOvalIndexes.txt",
ASSETS_DIR+":lowerLipCnt.txt",
ASSETS_DIR+":upperLipCnt.txt",
ASSETS_DIR+":widerLowerLipPts1.txt",
ASSETS_DIR+":widerUpperLipPts1.txt",
],
assets_dir = "",
manifest = "//mediapipe/examples/android/src/java/com/google/mediapipe/apps/basic:AndroidManifest.xml",
manifest_values = {
"applicationId": "com.google.mediapipe.apps.deformationgpu",
"appName": "Deformation",
"mainActivity": "com.google.mediapipe.apps.basic.MainActivity",
"cameraFacingFront": "True",
"binaryGraphName": "mobile_gpu.binarypb",
"inputVideoStreamName": "input_video",
"outputVideoStreamName": "output_video",
"flipFramesVertically": "True",
"converterNumBuffers": "2",
},
multidex = "native",
deps = [
":mediapipe_jni_lib",
"//mediapipe/examples/android/src/java/com/google/mediapipe/apps/basic:basic_lib",
"//mediapipe/framework/formats:landmark_java_proto_lite",
"//mediapipe/java/com/google/mediapipe/framework:android_framework",
"//mediapipe/modules/face_geometry/protos:face_geometry_java_proto_lite",
],
)

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# 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.
licenses(["notice"])
package(default_visibility = ["//mediapipe/examples:__subpackages__"])
# Linux only
cc_binary(
name = "deformation_cpu",
deps = [
"//mediapipe/examples/desktop:demo_run_graph_main",
"//mediapipe/graphs/deformation:desktop_calculators",
],
)

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mediapipe/graphs/deformation/BUILD Normal file
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# Copyright 2019 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.
load(
"//mediapipe/framework/tool:mediapipe_graph.bzl",
"mediapipe_binary_graph",
)
licenses(["notice"])
package(default_visibility = ["//visibility:public"])
cc_library(
name = "mobile_calculators",
deps = [
"//mediapipe/graphs/deformation/calculators:face_processor_calculator",
"//mediapipe/calculators/core:flow_limiter_calculator",
"//mediapipe/calculators/image:image_transformation_calculator",
"//mediapipe/modules/face_landmark:face_landmark_front_gpu",
"//mediapipe/calculators/core:constant_side_packet_calculator",
"//mediapipe/gpu:gpu_buffer_to_image_frame_calculator",
"//mediapipe/gpu:image_frame_to_gpu_buffer_calculator",
],
)
cc_library(
name = "desktop_calculators",
deps = [
"//mediapipe/graphs/deformation/calculators:face_processor_calculator",
"//mediapipe/calculators/core:flow_limiter_calculator",
"//mediapipe/calculators/image:image_transformation_calculator",
"//mediapipe/modules/face_landmark:face_landmark_front_cpu",
"//mediapipe/calculators/core:constant_side_packet_calculator",
],
)
mediapipe_binary_graph(
name = "mobile_gpu_binary_graph",
graph = "deformation_mobile.pbtxt",
output_name = "mobile_gpu.binarypb",
deps = [":mobile_calculators"],
)

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mediapipe/graphs/deformation/calculators/BUILD Normal file
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# Copyright 2020 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.
licenses(["notice"])
package(default_visibility = ["//visibility:public"])
cc_library(
name = "face_processor_calculator",
srcs = ["face_processor_calculator.cc"],
hdrs = ["Tensor.h"],
visibility = ["//visibility:public"],
deps = [
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework:calculator_options_cc_proto",
"//mediapipe/framework/formats:landmark_cc_proto",
"//mediapipe/framework/formats:video_stream_header",
"//mediapipe/framework/formats:location_data_cc_proto",
"@com_google_absl//absl/memory",
"@com_google_absl//absl/strings",
"//mediapipe/framework/formats:image_format_cc_proto",
"//mediapipe/framework/formats:image_frame",
"//mediapipe/framework/formats:image_frame_opencv",
"//mediapipe/framework/port:opencv_core",
"//mediapipe/framework/port:opencv_imgproc",
"//mediapipe/framework/port:opencv_highgui",
"//mediapipe/framework/port:vector",
"//mediapipe/framework/deps:file_path",
"//mediapipe/framework/formats/object_detection:anchor_cc_proto",
"//mediapipe/framework/port:file_helpers",
"//mediapipe/framework/port:integral_types",
"//mediapipe/framework/port:parse_text_proto",
"//mediapipe/util:resource_util",
"@com_google_absl//absl/flags:flag",
],
alwayslink = 1,
)

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mediapipe/graphs/deformation/calculators/Tensor.h Normal file
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#include <iostream>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <cmath>
#include <numeric>
using namespace std;
using namespace cv;
template <typename T>
class Tensor
{
private:
vector<int> dims;
Mat M;
int dtype;
void _set_dtype() {
if (typeid(T).name() == typeid(double).name())
dtype = CV_64F;
else if (typeid(T).name() == typeid(int).name())
dtype = CV_32S;
else
dtype = CV_64F;
}
public:
Tensor() {
_set_dtype();
dims = vector<int>{ 3, 3 };
M = Mat(dims, dtype);
}
Tensor(vector<int> _dims) {
_set_dtype();
dims = _dims;
M = Mat(dims, dtype);
}
Tensor(Mat _M) {
dims = vector<int>(_M.size.p, _M.size.p + _M.size.dims());
M = _M;
dtype = _M.type();
}
Tensor(const Tensor<T>& _m) {
dims = _m.dims;
M = _m.M;
dtype = _m.dtype;
}
Tensor(T** arr, int _n, int _m) {
_set_dtype();
dims = { _n, _m };
M = Mat(dims, dtype);
for (int i = 0; i < _n; i++)
for (int j = 0; j < _m; j++)
M.at<T>(Vec<int, 2>(i, j)) = arr[i][j];
}
vector<T> get_1d_data() {
return vector<T>(M.ptr<T>(0), M.ptr<T>(0) + dims[1]);
}
T at(vector<int> _indexes) {
return M.at<T>(_indexes.data());
}
Tensor index(int i1) {
return Tensor(M.row(i1));
}
Tensor index(vector<int> _indexes) {
vector<int> _dims;
_dims = dims;
_dims[0] = 0;
Mat _M = Mat(_dims, dtype);
for (int i = 0; i < _indexes.size(); ++i)
_M.push_back(M.row(_indexes[i]));
return Tensor(_M);
}
Tensor index(vector<vector<int>> _indexes) {
vector<int> _dims;
_dims = dims;
_dims[0] = 0;
Mat _M = Mat(_dims, dtype);
Mat tmp_M, _tmp_M;
for (int i = 0; i < _indexes.size(); ++i) {
_M.push_back(this->index(_indexes[i]).M);
}
return Tensor(_M.reshape(1, _indexes.size()));
}
Tensor index(Range r1, int index2) {
if (r1.end < 0) {
r1.end = M.rows + r1.end + 1;
}
return Tensor(M(r1, Range::all()).col(index2));
}
Tensor index(Range r1, Range r2) {
if (r1.end < 0) {
r1.end = M.rows + r1.end + 1;
}
if (r2.end < 0) {
r2.end = M.cols + r2.end + 1;
}
if (r1.start < 0 && r1.start > -2000000000) {
r1.start = M.rows + r1.start;
}
if (r2.start < 0 && r2.start > -2000000000) {
r2.start = M.cols + r2.start;
}
return Tensor(M(r1, r2));
}
Tensor concat(Tensor t, int dim) {
Mat dst;
if (dim == 0) {
vconcat(M, t.M, dst);
}
if (dim == 1) {
hconcat(M, t.M, dst);
}
return Tensor(dst);
}
Tensor matmul(Tensor t) {
return Tensor(M * t.M);
}
Tensor inverse() {
return Tensor(M.inv());
}
Tensor transpose() {
return Tensor(M.t());
}
T norm() {
int ndims = dims.size();
int size = 1;
for (int i = 0; i < ndims; i++) {
size = size * dims[i];
}
vector<int> _index(ndims, 0);
T _norm = pow(M.at<T>(_index.data()), 2);
for (int i = 0; i < size - 1; i++) {
_index[ndims - 1] += 1;
for (int j = ndims-1; j >= 0; j--) {
if (_index[j] >= dims[j]) {
_index[j] = 0;
_index[j - 1] += 1;
}
}
_norm += pow(M.at<T>(_index.data()), 2);
}
return sqrt(_norm);
}
friend ostream& operator<<(ostream& os, const Tensor<T>& _M){
os << _M.M;
return os;
}
friend const Tensor operator-(const Tensor& t) {
return Tensor(-t.M);
}
friend const Tensor operator/(const Tensor& t1, const Tensor& t2) {
return Tensor(t1.M.mul(1 / t2.M));
}
friend const Tensor operator*(const Tensor& t1, const Tensor& t2) {
return Tensor(t1.M.mul(t2.M));
}
friend const Tensor operator+(const Tensor& t1, const Tensor& t2) {
return Tensor(t1.M + t2.M);
}
friend const Tensor operator-(const Tensor& t1, const Tensor& t2) {
return Tensor(t1.M - t2.M);
}
friend const Tensor operator/(const Tensor& t1, const T& val) {
return Tensor(t1.M / val);
}
friend const Tensor operator*(const Tensor& t1, const T& val) {
return Tensor(t1.M * val);
}
friend const Tensor operator-(const Tensor& t1, const T& val) {
return Tensor(t1.M - val);
}
friend const Tensor operator*(const T& val, const Tensor& t1) {
return Tensor(t1.M * val);
}
static vector<int> sort_indexes(const vector<T>& v) {
vector<int> idx(v.size());
iota(idx.begin(), idx.end(), 0);
stable_sort(idx.begin(), idx.end(), [&v](int i1, int i2) {return v[i1] < v[i2]; });
return idx;
}
~Tensor()
{
}
};

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mediapipe/graphs/deformation/calculators/face_processor_calculator.cc Normal file
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// Copyright 2019 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 <math.h>
#include <algorithm>
#include <cmath>
#include <string>
#include <iostream>
#include <fstream>
//#include <android/log.h>
#include <memory>
#include "Tensor.h"
#include "absl/strings/str_cat.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/calculator_options.pb.h"
#include "mediapipe/framework/formats/image_format.pb.h"
#include "mediapipe/framework/formats/image_frame.h"
#include "mediapipe/framework/formats/image_frame_opencv.h"
#include "mediapipe/framework/formats/video_stream_header.h"
#include "mediapipe/framework/formats/landmark.pb.h"
#include "mediapipe/framework/port/logging.h"
#include "mediapipe/framework/port/opencv_core_inc.h"
#include "mediapipe/framework/port/opencv_imgproc_inc.h"
#include "mediapipe/framework/port/opencv_highgui_inc.h"
#include "mediapipe/framework/port/status.h"
#include "mediapipe/framework/port/logging.h"
#include "mediapipe/framework/port/vector.h"
#include "mediapipe/framework/port/file_helpers.h"
#include "mediapipe/framework/deps/file_path.h"
#include "mediapipe/util/resource_util.h"
namespace mediapipe
{
namespace
{
constexpr char kImageFrameTag[] = "IMAGE";
constexpr char kVectorTag[] = "VECTOR";
constexpr char kLandmarksTag[] = "LANDMARKS";
constexpr char kNormLandmarksTag[] = "NORM_LANDMARKS";
tuple<int, int> _normalized_to_pixel_coordinates(float normalized_x,
float normalized_y, int image_width, int image_height)
{
// Converts normalized value pair to pixel coordinates
int x_px = min<int>(floor(normalized_x * image_width), image_width - 1);
int y_px = min<int>(floor(normalized_y * image_height), image_height - 1);
return {x_px, y_px};
};
inline bool HasImageTag(mediapipe::CalculatorContext *cc) { return false; }
bool NormalizedtoPixelCoordinates(double normalized_x, double normalized_y, double normalized_z,
int image_width, int image_height, double *x_px,
double *y_px, double *z_px)
{
CHECK(x_px != nullptr);
CHECK(y_px != nullptr);
CHECK_GT(image_width, 0);
CHECK_GT(image_height, 0);
if (normalized_x < 0 || normalized_x > 1.0 || normalized_y < 0 ||
normalized_y > 1.0 || normalized_z < 0 ||
normalized_z > 1.0)
{
VLOG(1) << "Normalized coordinates must be between 0.0 and 1.0";
}
*x_px = static_cast<double>(normalized_x) * image_width;
*y_px = static_cast<double>(normalized_y) * image_height;
*z_px = static_cast<double>(normalized_z) * image_width;
// 2280
return true;
}
template <class LandmarkType>
bool IsLandmarkVisibleAndPresent(const LandmarkType &landmark,
bool utilize_visibility,
float visibility_threshold,
bool utilize_presence,
float presence_threshold)
{
if (utilize_visibility && landmark.has_visibility() &&
landmark.visibility() < visibility_threshold)
{
return false;
}
if (utilize_presence && landmark.has_presence() &&
landmark.presence() < presence_threshold)
{
return false;
}
return true;
}
} // namespace
class FaceProcessorCalculator : public CalculatorBase
{
public:
FaceProcessorCalculator() = default;
~FaceProcessorCalculator() override = default;
static absl::Status GetContract(CalculatorContract *cc);
// From Calculator.
absl::Status Open(CalculatorContext *cc) override;
absl::Status Process(CalculatorContext *cc) override;
absl::Status Close(CalculatorContext *cc) override;
private:
absl::Status CreateRenderTargetCpu(CalculatorContext *cc,
unique_ptr<Mat> &image_mat,
ImageFormat::Format *target_format);
absl::Status RenderToCpu(
CalculatorContext *cc, const ImageFormat::Format &target_format,
uchar *data_image, unique_ptr<Mat> &image_mat);
absl::Status SetData(CalculatorContext *cc);
absl::Status ProcessImage(CalculatorContext *cc,
ImageFormat::Format &target_format);
static absl::StatusOr<string> ReadContentBlobFromFile(
const string &unresolved_path)
{
ASSIGN_OR_RETURN(string resolved_path,
mediapipe::PathToResourceAsFile(unresolved_path),
_ << "Failed to resolve path! Path = " << unresolved_path);
string content_blob;
MP_RETURN_IF_ERROR(
mediapipe::GetResourceContents(resolved_path, &content_blob))
<< "Failed to read content blob! Resolved path = " << resolved_path;
return content_blob;
}
// Indicates if image frame is available as input.
bool image_frame_available_ = false;
unique_ptr<Mat> image_mat;
vector<string> index_names;
map<string, vector<int>> indexes;
map<string, Tensor<double>> masks;
vector<vector<int>> _trianglesIndexes;
Tensor<double> __facePts;
int image_width_;
int image_height_;
Mat mat_image_;
};
absl::Status FaceProcessorCalculator::GetContract(CalculatorContract *cc)
{
CHECK_GE(cc->Inputs().NumEntries(), 1);
if (cc->Inputs().HasTag(kImageFrameTag))
{
cc->Inputs().Tag(kImageFrameTag).Set<ImageFrame>();
CHECK(cc->Outputs().HasTag(kImageFrameTag));
}
RET_CHECK(cc->Inputs().HasTag(kLandmarksTag) ||
cc->Inputs().HasTag(kNormLandmarksTag))
<< "None of the input streams are provided.";
RET_CHECK(!(cc->Inputs().HasTag(kLandmarksTag) &&
cc->Inputs().HasTag(kNormLandmarksTag)))
<< "Can only one type of landmark can be taken. Either absolute or "
"normalized landmarks.";
if (cc->Inputs().HasTag(kLandmarksTag))
{
cc->Inputs().Tag(kLandmarksTag).Set<vector<LandmarkList>>();
}
if (cc->Inputs().HasTag(kNormLandmarksTag))
{
cc->Inputs().Tag(kNormLandmarksTag).Set<vector<NormalizedLandmarkList>>();
}
if (cc->Outputs().HasTag(kImageFrameTag))
{
cc->Outputs().Tag(kImageFrameTag).Set<ImageFrame>();
}
return absl::OkStatus();
}
absl::Status FaceProcessorCalculator::Open(CalculatorContext *cc)
{
cc->SetOffset(TimestampDiff(0));
if (cc->Inputs().HasTag(kImageFrameTag) || HasImageTag(cc))
{
image_frame_available_ = true;
}
// Set the output header based on the input header (if present).
const char *tag = kImageFrameTag;
if (image_frame_available_ && !cc->Inputs().Tag(tag).Header().IsEmpty())
{
const auto &input_header =
cc->Inputs().Tag(tag).Header().Get<VideoHeader>();
auto *output_video_header = new VideoHeader(input_header);
cc->Outputs().Tag(tag).SetHeader(Adopt(output_video_header));
}
return absl::OkStatus();
}
absl::Status FaceProcessorCalculator::Process(CalculatorContext *cc)
{
if (cc->Inputs().HasTag(kImageFrameTag) &&
cc->Inputs().Tag(kImageFrameTag).IsEmpty())
{
return absl::OkStatus();
}
// Initialize render target, drawn with OpenCV.
ImageFormat::Format target_format;
MP_RETURN_IF_ERROR(CreateRenderTargetCpu(cc, image_mat, &target_format));
mat_image_ = *image_mat.get();
image_width_ = image_mat->cols;
image_height_ = image_mat->rows;
MP_RETURN_IF_ERROR(SetData(cc));
if (cc->Inputs().HasTag(kNormLandmarksTag) &&
!cc->Inputs().Tag(kNormLandmarksTag).IsEmpty())
{
MP_RETURN_IF_ERROR(ProcessImage(cc, target_format));
}
uchar *image_mat_ptr = image_mat->data;
MP_RETURN_IF_ERROR(RenderToCpu(cc, target_format, image_mat_ptr, image_mat));
return absl::OkStatus();
}
absl::Status FaceProcessorCalculator::Close(CalculatorContext *cc)
{
return absl::OkStatus();
}
absl::Status FaceProcessorCalculator::RenderToCpu(
CalculatorContext *cc, const ImageFormat::Format &target_format,
uchar *data_image, unique_ptr<Mat> &image_mat)
{
auto output_frame = absl::make_unique<ImageFrame>(
target_format, mat_image_.cols, mat_image_.rows);
output_frame->CopyPixelData(target_format, mat_image_.cols, mat_image_.rows, data_image,
ImageFrame::kDefaultAlignmentBoundary);
if (cc->Outputs().HasTag(kImageFrameTag))
{
cc->Outputs()
.Tag(kImageFrameTag)
.Add(output_frame.release(), cc->InputTimestamp());
}
return absl::OkStatus();
}
absl::Status FaceProcessorCalculator::CreateRenderTargetCpu(
CalculatorContext *cc, unique_ptr<Mat> &image_mat,
ImageFormat::Format *target_format)
{
if (image_frame_available_)
{
const auto &input_frame =
cc->Inputs().Tag(kImageFrameTag).Get<ImageFrame>();
int target_mat_type;
switch (input_frame.Format())
{
case ImageFormat::SRGBA:
*target_format = ImageFormat::SRGBA;
target_mat_type = CV_8UC4;
break;
case ImageFormat::SRGB:
*target_format = ImageFormat::SRGB;
target_mat_type = CV_8UC3;
break;
case ImageFormat::GRAY8:
*target_format = ImageFormat::SRGB;
target_mat_type = CV_8UC3;
break;
default:
return absl::UnknownError("Unexpected image frame format.");
break;
}
image_mat = absl::make_unique<Mat>(
input_frame.Height(), input_frame.Width(), target_mat_type);
auto input_mat = formats::MatView(&input_frame);
if (input_frame.Format() == ImageFormat::GRAY8)
{
Mat rgb_mat;
cvtColor(input_mat, rgb_mat, CV_GRAY2RGBA);
rgb_mat.copyTo(*image_mat);
}
else
{
input_mat.copyTo(*image_mat);
}
}
else
{
image_mat = absl::make_unique<Mat>(
1920, 1280, CV_8UC4,
Scalar::all(255.0));
*target_format = ImageFormat::SRGBA;
}
return absl::OkStatus();
}
absl::Status FaceProcessorCalculator::SetData(CalculatorContext *cc)
{
masks.clear();
_trianglesIndexes.clear();
string filename = "mediapipe/graphs/deformation/config/triangles.txt";
string content_blob;
ASSIGN_OR_RETURN(content_blob,
ReadContentBlobFromFile(filename),
_ << "Failed to read texture blob from file!");
istringstream stream(content_blob);
double points[854][3];
vector<int> tmp;
for (int i = 0; i < 854; ++i)
{
string line;
tmp = {};
for (int j = 0; j < 3; ++j)
{
stream >> points[i][j];
tmp.push_back((int)points[i][j]);
}
_trianglesIndexes.push_back(tmp);
}
filename = "./mediapipe/graphs/deformation/config/index_names.txt";
ASSIGN_OR_RETURN(content_blob,
ReadContentBlobFromFile(filename),
_ << "Failed to read texture blob from file!");
istringstream stream2(content_blob);
string line;
vector<int> idxs;
while (getline(stream2, line))
{
index_names.push_back(line);
}
stream2.clear();
for (int i = 0; i < index_names.size(); i++)
{
filename = "./mediapipe/graphs/deformation/config/" + index_names[i] + ".txt";
ASSIGN_OR_RETURN(content_blob,
ReadContentBlobFromFile(filename),
_ << "Failed to read texture blob from file!");
stream2.str(content_blob);
while (getline(stream2, line))
{
idxs.push_back(stoi(line));
}
indexes[index_names[i]] = idxs;
idxs = {};
stream2.clear();
}
double **zero_arr;
for (int i = 0; i < index_names.size(); i++)
{
zero_arr = (double **)new double *[478];
for (int j = 0; j < 478; j++)
{
zero_arr[j] = (double *)new double[1];
zero_arr[j][0] = 0.0;
}
for (int j = 0; j < indexes[index_names[i]].size(); j++)
{
zero_arr[indexes[index_names[i]][j]][0] = 1;
}
masks[index_names[i]] = Tensor<double>(zero_arr, 478, 1);
}
return absl::OkStatus();
}
absl::Status FaceProcessorCalculator::ProcessImage(CalculatorContext *cc,
ImageFormat::Format &target_format)
{
double alfaNose = 0.7;
double alfaLips = 0.2;
double alfaCheekbones = 0.2;
if (cc->Inputs().HasTag(kNormLandmarksTag))
{
const vector<NormalizedLandmarkList> &landmarks =
cc->Inputs().Tag(kNormLandmarksTag).Get<vector<NormalizedLandmarkList>>();
int n = 478;
int m = 3;
double **_points = (double **)new double *[n];
for (int i = 0; i < n; i++)
_points[i] = (double *)new double[m];
for (int i = 0; i < landmarks[0].landmark_size(); ++i)
{
const NormalizedLandmark &landmark = landmarks[0].landmark(i);
if (!IsLandmarkVisibleAndPresent<NormalizedLandmark>(
landmark, false,
0.0, false,
0.0))
{
continue;
}
const auto &point = landmark;
double x = -1;
double y = -1;
double z = -1;
CHECK(NormalizedtoPixelCoordinates(point.x(), point.y(), point.z(), image_width_,
image_height_, &x, &y, &z));
_points[i][0] = x;
_points[i][1] = y;
_points[i][2] = z;
}
__facePts = Tensor<double>(_points, n, m);
}
cvtColor(mat_image_, mat_image_, COLOR_BGRA2RGB);
Mat clone_image = mat_image_.clone();
Tensor<double> ___facePts = __facePts - 0;
Tensor<double> _X = __facePts.index(indexes["mediumNoseIndexes"]).index(Range::all(), Range(0, 1));
Tensor<double> __YZ = __facePts.index(indexes["mediumNoseIndexes"]).index(Range::all(), Range(1, -1));
Tensor<double> ___YZ = __YZ.concat(Tensor<double>(Mat::ones(9, 1, CV_64F)), 1);
Tensor<double> _b = ___YZ.transpose().matmul(___YZ).inverse().matmul(___YZ.transpose()).matmul(_X);
Tensor<double> _ort = Tensor<double>(Mat::ones(1, 1, CV_64F)).concat(-_b.index(Range(0, 2), Range::all()), 0);
double _D = _b.at({2, 0}) / _ort.norm();
_ort = _ort / _ort.norm();
Tensor<double> _mask;
Tensor<double> _dsts;
vector<string> _indexes;
_indexes = {"cheekbonesIndexes", "noseAllIndexes", "additionalNoseIndexes1", "additionalNoseIndexes2", "additionalNoseIndexes3"};
vector<double> coeffs;
coeffs = {alfaCheekbones * 0.2, alfaNose * 0.2, alfaNose * 0.1, alfaNose * 0.05, alfaNose * 0.025};
_mask = masks["faceOvalIndexes"];
_dsts = _mask * (___facePts.matmul(_ort) - _D);
___facePts = ___facePts + _dsts.matmul(_ort.transpose()) * 0.05;
__facePts = __facePts + _dsts.matmul(_ort.transpose()) * 0.05;
for (int i = 0; i < 5; i++)
{
_mask = masks[_indexes[i]];
_dsts = _mask * (___facePts.matmul(_ort) - _D);
___facePts = ___facePts - coeffs[i] * _dsts.matmul(_ort.transpose());
}
_D = -1;
Tensor<double> _lipsSupprotPoint = (___facePts.index(11) + ___facePts.index(16)) / 2;
Tensor<double> _ABC = _lipsSupprotPoint.concat(___facePts.index(291), 0).concat(___facePts.index(61), 0).inverse().matmul(Tensor<double>(Mat::ones(3, 1, CV_64F))) * _D;
_D = _D / _ABC.norm();
_ort = _ABC / _ABC.norm();
_indexes = {"upperLipCnt", "lowerLipCnt", "widerUpperLipPts1", "widerLowerLipPts1"};
coeffs = {alfaLips, alfaLips * 0.5, alfaLips * 0.5, alfaLips * 0.25};
for (int i = 0; i < 4; i++)
{
_mask = masks[_indexes[i]];
_dsts = _mask * (___facePts.matmul(_ort) - _D);
___facePts = ___facePts + coeffs[i] * _dsts.matmul(_ort.transpose());
}
Tensor<double> tmp_order = ___facePts.index(_trianglesIndexes);
tmp_order = -tmp_order.index(Range::all(), 2) - tmp_order.index(Range::all(), 5) - tmp_order.index(Range::all(), 8);
tmp_order = tmp_order.transpose();
vector<double> __order = tmp_order.get_1d_data();
vector<int> _order = tmp_order.sort_indexes(__order);
Tensor<double> _src = __facePts.index(_trianglesIndexes).index(_order);
Tensor<double> _dst = ___facePts.index(_trianglesIndexes).index(_order);
Mat outImage = mat_image_.clone();
for (int i = 0; i < 854; ++i)
{
if (i == 246)
{
int pointer = 0;
}
Tensor<double> __t1 = _src.index(vector<int>{i});
Tensor<double> __t2 = _dst.index(vector<int>{i});
vector<Point> t1;
vector<Point> t2;
for (int i = 0; i < 3; ++i)
{
t1.push_back(Point(
(int)(__t1.at(vector<int>{0, 3 * i})),
(int)(__t1.at(vector<int>{0, 3 * i + 1}))));
t2.push_back(Point(
(int)(__t2.at(vector<int>{0, 3 * i})),
(int)(__t2.at(vector<int>{0, 3 * i + 1}))));
}
Rect r1 = boundingRect(t1);
Rect r2 = boundingRect(t2);
Point2f srcTri[3];
Point2f dstTri[3];
vector<Point> t1Rect;
vector<Point> t2Rect;
for (int i = 0; i < 3; ++i)
{
srcTri[i] = Point2f(t1[i].x - r1.x, t1[i].y - r1.y);
dstTri[i] = Point2f(t2[i].x - r2.x, t2[i].y - r2.y);
t1Rect.push_back(Point(t1[i].x - r1.x, t1[i].y - r1.y));
t2Rect.push_back(Point(t2[i].x - r2.x, t2[i].y - r2.y));
}
Mat _dst;
Mat mask = Mat::zeros(r2.height, r2.width, CV_8U);
fillConvexPoly(mask, t2Rect, Scalar(1.0, 1.0, 1.0), 16, 0);
if (r1.x + r1.width < clone_image.cols && r1.x >= 0 && r1.x + r1.width >= 0 && r1.y >= 0 && r1.y
< clone_image.rows && r1.y + r1.height < clone_image.rows)
{
Mat imgRect = mat_image_(Range(r1.y, r1.y + r1.height), Range(r1.x, r1.x + r1.width));
Mat warpMat = getAffineTransform(srcTri, dstTri);
warpAffine(imgRect, _dst, warpMat, mask.size());
for (int i = r2.y; i < r2.y + r2.height; ++i)
{
for (int j = r2.x; j < r2.x + r2.width; ++j)
{
if ((int)mask.at<uchar>(i - r2.y, j - r2.x) > 0)
{
outImage.at<Vec3b>(i, j) = _dst.at<Vec3b>(i - r2.y, j - r2.x);
}
}
}
}
}
cvtColor(outImage, *image_mat, COLOR_RGB2BGRA);
return absl::OkStatus();
}
REGISTER_CALCULATOR(FaceProcessorCalculator);
} // namespace mediapipe

34
mediapipe/graphs/deformation/config/BUILD Normal file
View File

@ -0,0 +1,34 @@
# Copyright 2020 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.
licenses(["notice"])
package(default_visibility = ["//visibility:public"])
load("//mediapipe/framework:encode_binary_proto.bzl", "encode_binary_proto")
encode_binary_proto(
name = "triangles",
input = "triangles.pbtxt",
message_type = "mediapipe.face_geometry.Mesh3d",
output = "triangles.binarypb",
deps = [
"//mediapipe/modules/face_geometry/protos:mesh_3d_proto",
],
)
exports_files(
srcs = glob(["**"]),
)

24
mediapipe/graphs/deformation/config/additionalNoseIndexes1.txt Normal file
View File

@ -0,0 +1,24 @@
128
2
8
266
417
36
423
193
453
326
327
328
329
203
464
350
97
98
99
100
357
233
244
121

24
mediapipe/graphs/deformation/config/additionalNoseIndexes2.txt Normal file
View File

@ -0,0 +1,24 @@
391
9
393
285
413
164
165
167
425
426
55
189
452
330
205
206
463
341
349
101
232
112
243
120

40
mediapipe/graphs/deformation/config/additionalNoseIndexes3.txt Normal file
View File

@ -0,0 +1,40 @@
0
256
133
267
269
151
280
26
411
155
414
37
39
295
427
50
436
441
187
190
65
322
450
451
207
336
337
216
347
92
221
348
230
231
362
107
108
118
119
382

26
mediapipe/graphs/deformation/config/cheekbonesIndexes.txt Normal file
View File

@ -0,0 +1,26 @@
135
137
138
395
394
401
147
411
416
169
170
433
177
435
434
187
192
213
214
215
352
364
366
367
376
123

36
mediapipe/graphs/deformation/config/faceOvalIndexes.txt Normal file
View File

@ -0,0 +1,36 @@
10
21
54
58
67
93
103
109
127
132
136
148
149
150
152
162
172
176
234
251
284
288
297
323
332
338
356
361
365
377
378
379
389
397
400
454

12
mediapipe/graphs/deformation/config/index_names.txt Normal file
View File

@ -0,0 +1,12 @@
mediumNoseIndexes
mediumFaceIndexes
noseAllIndexes
cheekbonesIndexes
additionalNoseIndexes1
additionalNoseIndexes2
additionalNoseIndexes3
faceOvalIndexes
upperLipCnt
lowerLipCnt
widerUpperLipPts1
widerLowerLipPts1

7
mediapipe/graphs/deformation/config/lowerLipCnt.txt Normal file
View File

@ -0,0 +1,7 @@
91
181
84
17
314
405
321

28
mediapipe/graphs/deformation/config/mediumFaceIndexes.txt Normal file
View File

@ -0,0 +1,28 @@
0
1
2
4
5
6
8
9
10
11
12
13
14
15
16
17
18
19
151
152
164
168
175
195
197
199
200
94

9
mediapipe/graphs/deformation/config/mediumNoseIndexes.txt Normal file
View File

@ -0,0 +1,9 @@
1
195
4
5
6
197
168
19
94

95
mediapipe/graphs/deformation/config/noseAllIndexes.txt Normal file
View File

@ -0,0 +1,95 @@
1
3
4
5
6
19
20
44
45
47
48
49
51
59
60
64
75
79
94
102
114
115
122
125
126
129
131
134
141
142
166
168
174
188
195
196
197
198
209
217
218
219
220
235
236
237
238
239
240
241
242
245
248
250
274
275
277
278
279
281
289
290
294
305
309
331
343
344
351
354
355
358
360
363
370
371
392
399
412
419
420
429
437
438
439
440
455
456
457
458
459
460
461
462
465

478
mediapipe/graphs/deformation/config/tmp.txt Normal file
View File

@ -0,0 +1,478 @@
362.31481075286865 600.8182525634766 -49.94013011455536
359.64590549468994 543.0130004882812 -87.40982294082642
360.086088180542 561.5730667114258 -46.17353081703186
347.2103476524353 485.1922607421875 -64.30929780006409
359.8048210144043 525.0722122192383 -92.92720198631287
360.4503107070923 501.8289566040039 -86.14297807216644
362.4685335159302 444.8126220703125 -41.42429620027542
245.9792947769165 443.63861083984375 28.838303983211517
363.6971139907837 394.8170471191406 -30.798228979110718
364.1529178619385 369.5340347290039 -34.45447951555252
366.7464208602905 289.53128814697266 -16.76752656698227
362.1213483810425 610.7015991210938 -47.918522357940674
361.9111490249634 622.2106170654297 -42.000214755535126
361.7901277542114 630.2610015869141 -33.034483194351196
361.80956840515137 630.5062103271484 -31.02048486471176
361.65876388549805 641.8568420410156 -31.974922120571136
361.32380962371826 655.2098846435547 -34.1738560795784
361.0052490234375 668.2077789306641 -29.830504059791565
358.64492654800415 676.3850402832031 -11.20004117488861
359.86140489578247 552.3215484619141 -79.14359271526337
346.4217138290405 552.1380233764648 -56.163471937179565
192.9905390739441 371.3102340698242 112.20251083374023
292.0316004753113 460.60115814208984 8.2303536683321
275.04276752471924 462.58548736572266 10.719646140933037
259.49241399765015 460.65929412841797 16.608951687812805
240.12107133865356 449.6390914916992 32.28025406599045
306.7124676704407 454.4320297241211 9.515418112277985
269.18585300445557 400.675048828125 3.427928164601326
288.8427543640137 403.7632751464844 2.093831095844507
250.83645343780518 403.60511779785156 10.545069873332977
239.18262004852295 411.6160583496094 18.1980961561203
228.3171844482422 460.1266860961914 41.43935680389404
302.79680728912354 691.3064575195312 9.149758592247963
241.1520266532898 437.7595520019531 35.078975558280945
189.48997735977173 447.4779510498047 118.62715244293213
212.72387266159058 445.54298400878906 59.737064838409424
282.91693925857544 530.6702423095703 -5.825772061944008
342.03819036483765 596.2926864624023 -46.076542139053345
344.00843381881714 621.6756820678711 -38.56708645820618
321.01934909820557 603.6526107788086 -35.2379634976387
307.75672674179077 612.1319580078125 -23.22000414133072
328.45593452453613 622.2881317138672 -31.554990112781525
316.4400243759155 624.019889831543 -20.421039909124374
292.482705116272 644.8335266113281 4.006892032921314
346.5736126899719 542.3727035522461 -85.37296950817108
344.0822696685791 525.3844833374023 -90.18237948417664
217.00727462768555 391.1960983276367 27.05360770225525
314.4440746307373 486.0729217529297 -9.935649186372757
311.9938015937805 539.7780990600586 -43.17997097969055
310.8665657043457 530.599479675293 -38.25033366680145
237.0926856994629 528.7818908691406 18.765471875667572
345.63275814056396 503.6951446533203 -80.07521510124207
253.07697772979736 370.8142852783203 -4.48684886097908
230.86107730865479 376.7497253417969 10.754622146487236
205.6266188621521 339.0149688720703 78.1203943490982
326.48303031921387 390.49964904785156 -23.940061926841736
305.56124210357666 412.823486328125 5.849309116601944
282.61058807373047 628.2186889648438 8.089985623955727
217.4528431892395 606.013298034668 162.1191930770874
324.4342088699341 549.4257736206055 -37.90909230709076
336.75106287002563 554.6352386474609 -39.987490475177765
293.8541293144226 627.0395278930664 4.047446697950363
297.9695391654968 627.4363708496094 -1.4645572006702423
223.25343132019043 364.15504455566406 18.954835832118988
312.2819137573242 548.3728408813477 -34.18475389480591
284.00705337524414 374.25506591796875 -16.747109591960907
281.1100745201111 358.78501892089844 -20.09346440434456
269.8329734802246 297.1759033203125 9.054293408989906
213.61764907836914 353.2844543457031 44.04454082250595
276.30271911621094 327.88902282714844 -6.657576039433479
209.54910278320312 383.55751037597656 41.906957030296326
200.42315483093262 379.8735046386719 74.44762945175171
342.41307735443115 609.2689514160156 -44.42476004362106
324.58361864089966 613.3655548095703 -34.433123767375946
311.8226981163025 618.1516265869141 -23.389243483543396
328.36570501327515 552.9110717773438 -34.33730721473694
295.9403944015503 627.3085021972656 1.058464301750064
302.7903914451599 633.2058334350586 -8.738560527563095
300.23465394973755 627.6346206665039 -1.9429570063948631
330.6955361366272 542.2183990478516 -60.3791481256485
319.926381111145 627.951774597168 -17.149565666913986
331.668963432312 628.3108901977539 -24.26801562309265
345.7926392555237 629.2702865600586 -30.250057876110077
337.8448462486267 674.9959564208984 -10.129471644759178
339.70123529434204 665.8506774902344 -28.294233977794647
341.120080947876 652.9856109619141 -31.669657230377197
343.2656764984131 639.5659255981445 -29.17739689350128
345.6427574157715 629.5268249511719 -28.149794340133667
319.5728015899658 628.4269332885742 -15.51249548792839
315.7986545562744 633.2476806640625 -17.23422959446907
311.2205743789673 639.5831680297852 -19.361704140901566
307.6517343521118 646.3972473144531 -16.121692210435867
298.32361221313477 595.7241058349609 -16.49742141366005
197.07026481628418 522.5712585449219 187.61728048324585
360.03939628601074 556.6411209106445 -57.723058462142944
310.6411099433899 628.126335144043 -7.598769888281822
306.76589727401733 630.5442428588867 -8.854755163192749
340.9685468673706 561.4918518066406 -40.77357888221741
318.58154296875 559.0150451660156 -22.706395983695984
339.0328288078308 558.0970001220703 -40.72387754917145
297.1806049346924 496.8467330932617 -3.014509230852127
271.3532495498657 508.8191604614258 4.138495959341526
308.9188528060913 539.0650939941406 -28.855242133140564
229.7728943824768 313.4063148498535 41.365743577480316
237.28271484375 334.8050308227539 17.421178221702576
247.82358169555664 355.85723876953125 -1.6578103601932526
303.48783016204834 655.7356262207031 -2.8776374459266663
320.89759826660156 365.4893493652344 -30.40818214416504
317.74295568466187 328.6730194091797 -21.479719877243042
314.16688442230225 290.34828186035156 -10.778319463133812
246.95883750915527 456.8497085571289 24.94966149330139
213.02721977233887 472.27821350097656 51.60349130630493
316.6361689567566 448.2948684692383 11.210014969110489
224.51123714447021 419.96166229248047 34.82187241315842
325.7254457473755 473.91719818115234 -16.364332884550095
320.2879858016968 531.8416595458984 -59.67542231082916
200.17237901687622 482.4532699584961 71.37396275997162
221.48051261901855 485.61683654785156 35.744640827178955
240.50400495529175 492.3386001586914 18.90147864818573
271.28535747528076 489.66487884521484 10.056736171245575
294.8106050491333 482.0330047607422 4.697423055768013
312.8950881958008 472.49622344970703 -0.738221537321806
346.81421756744385 449.1241455078125 -34.28698629140854
204.62121963500977 519.8909378051758 66.61324560642242
213.83495092391968 416.9788360595703 43.828730285167694
352.1424150466919 551.607666015625 -77.710622549057
316.08299016952515 503.18206787109375 -17.371298521757126
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404.33438301086426 546.3447189331055 -49.92307662963867
388.8867473602295 528.129768371582 -78.11590433120728
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494.4223165512085 393.13838958740234 -3.7459462881088257
508.447265625 402.79422760009766 6.417246758937836
512.7858781814575 440.90904235839844 31.261489391326904
547.2984409332275 490.5126190185547 103.35272312164307
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383.8312339782715 543.7438583374023 -71.36332511901855
398.81486892700195 557.1538543701172 -35.70137947797775
372.3822784423828 550.9265899658203 -76.46305739879608
370.69892406463623 555.1999664306641 -57.17661201953888
410.05074977874756 440.17982482910156 7.049205377697945
399.94487285614014 443.82862091064453 -2.0457570254802704
393.2704210281372 446.66893005371094 -12.368821799755096
491.9056749343872 434.00867462158203 13.69398057460785
505.40289402008057 422.0017623901367 14.507773518562317
278.070273399353 437.74181365966797 16.967550963163376
296.5090012550354 437.4724578857422 16.967550963163376
278.02658557891846 420.81432342529297 16.967550963163376
259.5726013183594 437.9621124267578 16.967550963163376
278.0579137802124 454.41627502441406 16.967550963163376
459.17272567749023 438.5255432128906 6.8281786143779755
478.56732845306396 439.512939453125 6.8281786143779755
459.9502229690552 422.17994689941406 6.8281786143779755
439.78996753692627 437.5259017944336 6.8281786143779755
458.3905506134033 454.89044189453125 6.8281786143779755

854
mediapipe/graphs/deformation/config/triangles.txt Normal file
View File

@ -0,0 +1,854 @@
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7
mediapipe/graphs/deformation/config/upperLipCnt.txt Normal file
View File

@ -0,0 +1,7 @@
40
39
37
0
267
269
270

9
mediapipe/graphs/deformation/config/widerLowerLipPts1.txt Normal file
View File

@ -0,0 +1,9 @@
106
43
335
273
18
83
182
406
313

9
mediapipe/graphs/deformation/config/widerUpperLipPts1.txt Normal file
View File

@ -0,0 +1,9 @@
322
164
165
391
167
393
186
410
92

48
mediapipe/graphs/deformation/deformation_cpu.pbtxt Normal file
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@ -0,0 +1,48 @@
# MediaPipe graph that performs face mesh with TensorFlow Lite on CPU.
# Input image. (ImageFrame)
input_stream: "input_video"
# Output image with rendered results. (ImageFrame)
output_stream: "output_video"
node {
calculator: "FlowLimiterCalculator"
input_stream: "input_video"
input_stream: "FINISHED:output_video"
input_stream_info: {
tag_index: "FINISHED"
back_edge: true
}
output_stream: "throttled_input_video"
}
# Defines side packets for further use in the graph.
node {
calculator: "ConstantSidePacketCalculator"
output_side_packet: "PACKET:0:num_faces"
output_side_packet: "PACKET:1:with_attention"
node_options: {
[type.googleapis.com/mediapipe.ConstantSidePacketCalculatorOptions]: {
packet { int_value: 1 }
packet { bool_value: true }
}
}
}
# Subgraph that detects faces and corresponding landmarks.
node {
calculator: "FaceLandmarkFrontCpu"
input_stream: "IMAGE:throttled_input_video"
input_side_packet: "NUM_FACES:num_faces"
input_side_packet: "WITH_ATTENTION:with_attention"
output_stream: "LANDMARKS:multi_face_landmarks"
}
node {
calculator: "FaceProcessorCalculator"
input_stream: "NORM_LANDMARKS:multi_face_landmarks"
input_stream: "IMAGE:throttled_input_video"
output_stream: "IMAGE:output_video"
}

59
mediapipe/graphs/deformation/deformation_mobile.pbtxt Normal file
View File

@ -0,0 +1,59 @@
# MediaPipe graph that performs hair segmentation with TensorFlow Lite on GPU.
# Used in the example in
# mediapipie/examples/android/src/java/com/mediapipe/apps/hairsegmentationgpu.
# Images on GPU coming into and out of the graph.
input_stream: "input_video"
output_stream: "output_video"
node {
calculator: "FlowLimiterCalculator"
input_stream: "input_video"
input_stream: "FINISHED:output_video"
input_stream_info: {
tag_index: "FINISHED"
back_edge: true
}
output_stream: "throttled_input_video"
}
# Defines side packets for further use in the graph.
node {
calculator: "ConstantSidePacketCalculator"
output_side_packet: "PACKET:with_attention"
node_options: {
[type.googleapis.com/mediapipe.ConstantSidePacketCalculatorOptions]: {
packet { bool_value: true }
}
}
}
# Defines side packets for further use in the graph.
node {
calculator: "GpuBufferToImageFrameCalculator"
input_stream: "throttled_input_video"
output_stream: "throttled_input_video_cpu"
}
# Subgraph that detects faces and corresponding landmarks.
node {
calculator: "FaceLandmarkFrontGpu"
input_stream: "IMAGE:throttled_input_video"
input_side_packet: "WITH_ATTENTION:with_attention"
output_stream: "LANDMARKS:multi_face_landmarks"
}
node {
calculator: "FaceProcessorCalculator"
input_stream: "NORM_LANDMARKS:multi_face_landmarks"
input_stream: "IMAGE:throttled_input_video_cpu"
output_stream: "IMAGE:out_image_frame"
}
# Defines side packets for further use in the graph.
node {
calculator: "ImageFrameToGpuBufferCalculator"
input_stream: "out_image_frame"
output_stream: "output_video"
}