Deformation model

mediapipe/examples/android/src/java/com/google/mediapipe/apps/deformation/BUILD

@@ -0,0 +1,81 @@
+# 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",
+    ],
+)
+

mediapipe/examples/desktop/deformation/BUILD

@@ -0,0 +1,29 @@
+# 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",
+    ],
+)
+
+
+

mediapipe/graphs/deformation/BUILD

@@ -0,0 +1,54 @@
+# 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"],
+)
+

mediapipe/graphs/deformation/calculators/BUILD

@@ -0,0 +1,51 @@
+# 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,
+)
+
+
+

mediapipe/graphs/deformation/calculators/Tensor.h

@@ -0,0 +1,224 @@
+#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()
+    {
+    }
+};

mediapipe/graphs/deformation/calculators/face_processor_calculator.cc

@@ -0,0 +1,593 @@
+// 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

mediapipe/graphs/deformation/config/BUILD

@@ -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(["**"]),
+)
+

mediapipe/graphs/deformation/config/additionalNoseIndexes1.txt

@@ -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

mediapipe/graphs/deformation/config/additionalNoseIndexes2.txt

@@ -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

mediapipe/graphs/deformation/config/additionalNoseIndexes3.txt

@@ -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

mediapipe/graphs/deformation/config/cheekbonesIndexes.txt

@@ -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

mediapipe/graphs/deformation/config/faceOvalIndexes.txt

@@ -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

mediapipe/graphs/deformation/config/index_names.txt

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

mediapipe/graphs/deformation/config/lowerLipCnt.txt

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

mediapipe/graphs/deformation/config/mediumFaceIndexes.txt

@@ -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

mediapipe/graphs/deformation/config/mediumNoseIndexes.txt

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

mediapipe/graphs/deformation/config/noseAllIndexes.txt

@@ -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

mediapipe/graphs/deformation/config/tmp.txt

@@ -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
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mediapipe/graphs/deformation/config/upperLipCnt.txt

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

mediapipe/graphs/deformation/config/widerLowerLipPts1.txt

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

mediapipe/graphs/deformation/config/widerUpperLipPts1.txt

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

mediapipe/graphs/deformation/deformation_cpu.pbtxt

@@ -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"
+}

mediapipe/graphs/deformation/deformation_mobile.pbtxt

@@ -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"
+}