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facial-search: a graph from Powder.gg matching memes to faces

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This commit is contained in:
Pierre Fenoll 2020-01-14 18:06:01 +01:00
parent 63e679d99c
commit 978fee3cdb
35 changed files with 2999 additions and 0 deletions
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33
.github/workflows/workflow.yml vendored Normal file
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on: push
name: FacialSearch iOS framework
jobs:
ios:
name: run
runs-on: macos-latest
env:
BAZELISK_GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
steps:
- name: Checkout
uses: actions/checkout@v2
- name: Install dependencies
run: |
bazelisk version
brew install python opencv@3
brew uninstall --ignore-dependencies glog
sudo ln -s -f /usr/local/bin/python3.9 /usr/local/bin/python
pip3 install --user future six numpy
- name: Build
run: |
python mediapipe/examples/facial_search/images/download_images.py
bazelisk build --copt=-fembed-bitcode --apple_bitcode=embedded --config=ios_arm64 mediapipe/examples/facial_search/ios:FacialSearch
./mediapipe/examples/facial_search/ios/patch_ios_framework.sh bazel-bin/mediapipe/examples/facial_search/ios/FacialSearch.zip ObjcppLib.h
mv -v bazel-bin/mediapipe/examples/facial_search/ios/FacialSearch.framework .
- name: Upload artifact
uses: actions/upload-artifact@v1
with:
name: FacialSearch.framework
path: FacialSearch.framework

2
mediapipe/MediaPipe.tulsiproj/Configs/MediaPipe.tulsigen
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"additionalFilePaths" : [ "additionalFilePaths" : [
"/BUILD", "/BUILD",
"mediapipe/BUILD", "mediapipe/BUILD",
"mediapipe/examples/facial_search/ios/BUILD",
"mediapipe/examples/ios/common/BUILD", "mediapipe/examples/ios/common/BUILD",
"mediapipe/examples/ios/facedetectioncpu/BUILD", "mediapipe/examples/ios/facedetectioncpu/BUILD",
"mediapipe/examples/ios/facedetectiongpu/BUILD", "mediapipe/examples/ios/facedetectiongpu/BUILD",
@ -23,6 +24,7 @@
"mediapipe/objc/testing/app/BUILD" "mediapipe/objc/testing/app/BUILD"
], ],
"buildTargets" : [ "buildTargets" : [
"//mediapipe/examples/facial_search/ios:FacialSearchGpuApp",
"//mediapipe/examples/ios/facedetectioncpu:FaceDetectionCpuApp", "//mediapipe/examples/ios/facedetectioncpu:FaceDetectionCpuApp",
"//mediapipe/examples/ios/facedetectiongpu:FaceDetectionGpuApp", "//mediapipe/examples/ios/facedetectiongpu:FaceDetectionGpuApp",
"//mediapipe/examples/ios/faceeffect:FaceEffectApp", "//mediapipe/examples/ios/faceeffect:FaceEffectApp",

1
mediapipe/MediaPipe.tulsiproj/project.tulsiconf
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"packages" : [ "packages" : [
"", "",
"mediapipe", "mediapipe",
"mediapipe/examples/facial_search/ios",
"mediapipe/examples/ios", "mediapipe/examples/ios",
"mediapipe/examples/ios/facedetectioncpu", "mediapipe/examples/ios/facedetectioncpu",
"mediapipe/examples/ios/facedetectiongpu", "mediapipe/examples/ios/facedetectiongpu",

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mediapipe/examples/facial_search/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"]) # Apache 2.0
package(default_visibility = ["//visibility:public"])
cc_library(
name = "embeddings_database",
hdrs = [
"embeddings.h",
"labels.h",
],
)

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mediapipe/examples/facial_search/README.md Normal file
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## Make sure to download the memes
```
python mediapipe/examples/facial_search/images/download_images.py
```
## Run on CPU
```
bazel run --platform_suffix=_cpu \
--copt=-fdiagnostics-color=always --run_under="cd $PWD && " \
-c opt --define MEDIAPIPE_DISABLE_GPU=1 \
mediapipe/examples/facial_search/desktop:facial_search \
-- \
--calculator_graph_config_file=mediapipe/examples/facial_search/graphs/facial_search_cpu.pbtxt \
--images_folder_path=mediapipe/examples/facial_search/images/
```
## Run on GPU
```
bazel run --platform_suffix=_gpu \
--copt=-fdiagnostics-color=always --run_under="cd $PWD && " \
-c opt --copt -DMESA_EGL_NO_X11_HEADERS --copt -DEGL_NO_X11 \
mediapipe/examples/facial_search/desktop:facial_search \
-- \
--calculator_graph_config_file=mediapipe/examples/facial_search/graphs/facial_search_gpu.pbtxt \
--images_folder_path=mediapipe/examples/facial_search/images/
```

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mediapipe/examples/facial_search/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.
load("//mediapipe/framework/port:build_config.bzl", "mediapipe_cc_proto_library")
licenses(["notice"]) # Apache 2.0
package(default_visibility = ["//visibility:public"])
proto_library(
name = "closest_embeddings_calculator_proto",
srcs = ["closest_embeddings_calculator.proto"],
visibility = ["//visibility:public"],
deps = ["//mediapipe/framework:calculator_proto"],
)
mediapipe_cc_proto_library(
name = "closest_embeddings_calculator_cc_proto",
srcs = ["closest_embeddings_calculator.proto"],
cc_deps = ["//mediapipe/framework:calculator_cc_proto"],
visibility = ["//visibility:public"],
deps = [":closest_embeddings_calculator_proto"],
)
cc_library(
name = "closest_embeddings_calculator",
srcs = ["closest_embeddings_calculator.cc"],
visibility = ["//visibility:public"],
deps = [
":closest_embeddings_calculator_cc_proto",
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework:timestamp",
"//mediapipe/framework/formats:classification_cc_proto",
"//mediapipe/framework/port:status",
],
alwayslink = 1,
)

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mediapipe/examples/facial_search/calculators/closest_embeddings_calculator.cc 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.
#include <cmath>
#include "mediapipe/examples/facial_search/calculators/closest_embeddings_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/formats/classification.pb.h"
#include "mediapipe/framework/port/ret_check.h"
#include "mediapipe/framework/port/status.h"
#define COUNTOF(ARRAY) (sizeof(ARRAY) / sizeof(ARRAY[0]))
namespace mediapipe {
namespace {
constexpr char kClassifications[] = "CLASSIFICATIONS";
constexpr char kCollection[] = "COLLECTION";
constexpr char kLabels[] = "LABELS";
constexpr char kFloats[] = "FLOATS";
typedef std::vector<Classification> Classifications;
typedef std::vector<float> Floats;
typedef std::vector<Floats> Collection;
typedef std::vector<std::string> Labels;
} // namespace
// Given a flat vector of embeddings, finds the top k closests vectors
// from the embeddings collection and returns the value associated with these
// vectors.
//
// Inputs:
// FLOATS: the input embedding to compare, as an std::vector of floats.
// COLLECTION: an std::vector of embeddings that this calculcator compares
// FLOATS against. LABELS: an (optional) std::vector of strings whose indices
// match COLLECTION's. CLASSIFICATIONS: the k-closest embeddings as an
// std::vector of Classification.s where
// Classification.id is the embedding's index in COLLECTION,
// Classification.label is the embedding's index in LABELS
// and Classification.score is the distance between the two
// embeddings.
//
// Options:
// top_k: number of embeddings closest to input to search for.
//
// Notes:
// * The distance function used by default is the Euclidian distance.
// * Every vector in COLLECTION must have the same dimension as the input
// vector.
// * When given an empty input vector, an empty output vector is returned.
//
// Usage example:
// node {
// calculator: "ClosestEmbeddingsCalculator"
// input_side_packet: "COLLECTION:embeddings_collection"
// input_side_packet: "LABELS:collection_labels"
// input_stream: "FLOATS:embeddings_vector"
// output_stream: "CLASSIFICATIONS:memes"
// options: {
// [mediapipe.ClosestEmbeddingsCalculatorOptions.ext]: {
// top_k: 3
// }
// }
// }
class ClosestEmbeddingsCalculator : public CalculatorBase {
public:
ClosestEmbeddingsCalculator() {}
~ClosestEmbeddingsCalculator() override {}
static ::mediapipe::Status GetContract(CalculatorContract* cc) {
RET_CHECK(cc->InputSidePackets().HasTag(kCollection));
cc->InputSidePackets().Tag(kCollection).Set<Collection>();
if (cc->InputSidePackets().HasTag(kLabels))
cc->InputSidePackets().Tag(kLabels).Set<Labels>();
RET_CHECK(cc->Inputs().HasTag(kFloats));
cc->Inputs().Tag(kFloats).Set<Floats>();
RET_CHECK(cc->Outputs().HasTag(kClassifications));
cc->Outputs().Tag(kClassifications).Set<Classifications>();
return ::mediapipe::OkStatus();
}
::mediapipe::Status Open(CalculatorContext* cc) override {
cc->SetOffset(TimestampDiff(0));
collection_ = cc->InputSidePackets().Tag(kCollection).Get<Collection>();
RET_CHECK(!collection_.empty());
if (cc->InputSidePackets().HasTag(kLabels)) {
labels_ = cc->InputSidePackets().Tag(kLabels).Get<Labels>();
RET_CHECK_EQ(labels_.size(), collection_.size());
}
const auto& options = cc->Options<ClosestEmbeddingsCalculatorOptions>();
top_k_ = std::min(size_t(options.top_k()), collection_.size());
RET_CHECK_NE(top_k_, 0);
return ::mediapipe::OkStatus();
}
::mediapipe::Status Process(CalculatorContext* cc) override {
const auto input = cc->Inputs().Tag(kFloats).Get<Floats>();
auto output = absl::make_unique<Classifications>();
if (input.empty()) {
cc->Outputs()
.Tag(kClassifications)
.Add(output.release(), cc->InputTimestamp());
return ::mediapipe::OkStatus();
}
RET_CHECK_EQ(input.size(), collection_[0].size())
<< "Embeddings should have " << collection_[0].size()
<< " dimensions. Got " << input.size() << " floats.";
output->reserve(top_k_);
RET_CHECK_OK(AppendKClosest(input, output.get()));
cc->Outputs()
.Tag(kClassifications)
.Add(output.release(), cc->InputTimestamp());
return ::mediapipe::OkStatus();
}
private:
size_t top_k_;
Collection collection_;
Labels labels_;
::mediapipe::Status AppendKClosest(const Floats& input,
Classifications* best) {
auto matches = Classifications();
matches.reserve(top_k_);
for (int i = 0; i < collection_.size(); ++i) {
const auto& item = collection_[i];
RET_CHECK_EQ(item.size(), input.size());
Classification classification;
classification.set_index(i);
classification.set_score(EuclidianDistance(item, input));
if (!labels_.empty()) classification.set_label(labels_[i]);
matches.emplace_back(classification);
}
TopK(matches);
for (const auto match : matches) {
best->emplace_back(match);
}
return ::mediapipe::OkStatus();
}
float EuclidianDistance(const Floats& a, const Floats& b) {
float sum = 0;
for (int i = 0; i < a.size(); ++i) sum += (a[i] - b[i]) * (a[i] - b[i]);
return std::sqrt(sum);
}
void TopK(Classifications& classifications) {
if (classifications.size() > 1 && classifications.size() > top_k_) {
std::partial_sort(classifications.begin(),
classifications.begin() + top_k_, classifications.end(),
[](const Classification& a, const Classification& b) {
// Sorts such that results closest to zero are at the
// top
return a.score() < b.score();
});
classifications.erase(classifications.begin() + top_k_,
classifications.end());
}
}
};
REGISTER_CALCULATOR(ClosestEmbeddingsCalculator);
} // namespace mediapipe

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mediapipe/examples/facial_search/calculators/closest_embeddings_calculator.proto Normal file
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syntax = "proto2";
package mediapipe;
import "mediapipe/framework/calculator.proto";
message ClosestEmbeddingsCalculatorOptions {
extend CalculatorOptions {
optional ClosestEmbeddingsCalculatorOptions ext = 107632442;
}
optional uint32 top_k = 1 [default = 1];
}

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mediapipe/examples/facial_search/desktop/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.
load("@rules_cc//cc:defs.bzl", "cc_binary")
licenses(["notice"]) # Apache 2.0
package(default_visibility = ["//visibility:public"])
cc_binary(
name = "facial_search",
srcs = [
"cpu_gpu_compatibility.h",
"demo.cc",
],
deps = [
"//mediapipe/examples/facial_search:embeddings_database",
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework/formats:image_frame",
"//mediapipe/framework/formats:image_frame_opencv",
"//mediapipe/framework/port:file_helpers",
"//mediapipe/framework/port:opencv_highgui",
"//mediapipe/framework/port:opencv_imgproc",
"//mediapipe/framework/port:opencv_video",
"//mediapipe/framework/port:parse_text_proto",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/flags:flag",
"@com_google_absl//absl/flags:parse",
] + select({
"//mediapipe/gpu:disable_gpu": [
"//mediapipe/examples/facial_search/graphs:cpu_calculators",
],
"//conditions:default": [
"//mediapipe/examples/facial_search/graphs:gpu_calculators",
"//mediapipe/gpu:gl_calculator_helper",
"//mediapipe/gpu:gpu_buffer",
"//mediapipe/gpu:gpu_shared_data_internal",
],
}),
)

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mediapipe/examples/facial_search/desktop/cpu_gpu_compatibility.h 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.
#ifndef MEDIAPIPE_EXAMPLES_FACIAL_SEARCH_COMPAT_H_
#define MEDIAPIPE_EXAMPLES_FACIAL_SEARCH_COMPAT_H_
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/port/status.h"
#if !defined(MEDIAPIPE_DISABLE_GPU)
#include "mediapipe/gpu/gl_calculator_helper.h"
#include "mediapipe/gpu/gpu_buffer.h"
#include "mediapipe/gpu/gpu_shared_data_internal.h"
#endif
#if !defined(MEDIAPIPE_DISABLE_GPU)
#define MAYBE_INIT_GPU(graph) \
LOG(INFO) << "Initialize the GPU."; \
ASSIGN_OR_RETURN(auto gpu_resources, mediapipe::GpuResources::Create()); \
MP_RETURN_IF_ERROR(graph.SetGpuResources(std::move(gpu_resources))); \
mediapipe::GlCalculatorHelper gpu_helper; \
gpu_helper.InitializeForTest(graph.GetGpuResources().get())
#else // !MEDIAPIPE_DISABLE_GPU
#define MAYBE_INIT_GPU(graph) LOG(INFO) << "Not built for GPU."
#endif
#if !defined(MEDIAPIPE_DISABLE_GPU)
#define ADD_INPUT_FRAME(inputStream, captured, timestamp) \
auto the_input_frame = absl::make_unique<mediapipe::ImageFrame>( \
mediapipe::ImageFormat::SRGBA, captured.cols, captured.rows, \
mediapipe::ImageFrame::kGlDefaultAlignmentBoundary); \
cv::Mat input_frame_mat = \
mediapipe::formats::MatView(the_input_frame.get()); \
captured.copyTo(input_frame_mat); \
/* Send image packet into the graph. */ \
MP_RETURN_IF_ERROR( \
gpu_helper.RunInGlContext([&the_input_frame, &timestamp, &graph, \
&gpu_helper]() -> ::mediapipe::Status { \
/* Convert ImageFrame to GpuBuffer. */ \
auto texture = gpu_helper.CreateSourceTexture(*the_input_frame.get()); \
auto gpu_frame = texture.GetFrame<mediapipe::GpuBuffer>(); \
glFlush(); \
texture.Release(); \
/* Send GPU image packet into the graph. */ \
MP_RETURN_IF_ERROR(graph.AddPacketToInputStream( \
inputStream, \
mediapipe::Adopt(gpu_frame.release()).At(timestamp))); \
return ::mediapipe::OkStatus(); \
}))
#else // !MEDIAPIPE_DISABLE_GPU
#define ADD_INPUT_FRAME(inputStream, captured, timestamp) \
auto the_input_frame = absl::make_unique<mediapipe::ImageFrame>( \
mediapipe::ImageFormat::SRGBA, captured.cols, captured.rows, \
mediapipe::ImageFrame::kDefaultAlignmentBoundary); \
cv::Mat input_frame_mat = \
mediapipe::formats::MatView(the_input_frame.get()); \
captured.copyTo(input_frame_mat); \
/* Send image packet into the graph. */ \
MP_RETURN_IF_ERROR(graph.AddPacketToInputStream( \
inputStream, mediapipe::Adopt(the_input_frame.release()).At(timestamp)))
#endif
#if !defined(MEDIAPIPE_DISABLE_GPU)
#define GET_OUTPUT_FRAME_MAT(packet, ofmat) \
std::unique_ptr<mediapipe::ImageFrame> output_frame; \
MP_RETURN_IF_ERROR(gpu_helper.RunInGlContext( \
[&packet, &output_frame, &gpu_helper]() -> ::mediapipe::Status { \
auto& gpu_frame = packet.Get<mediapipe::GpuBuffer>(); \
auto texture = gpu_helper.CreateSourceTexture(gpu_frame); \
output_frame = absl::make_unique<mediapipe::ImageFrame>( \
mediapipe::ImageFormatForGpuBufferFormat(gpu_frame.format()), \
gpu_frame.width(), gpu_frame.height(), \
mediapipe::ImageFrame::kGlDefaultAlignmentBoundary); \
gpu_helper.BindFramebuffer(texture); \
const auto info = \
mediapipe::GlTextureInfoForGpuBufferFormat(gpu_frame.format(), 0); \
glReadPixels(0, 0, texture.width(), texture.height(), info.gl_format, \
info.gl_type, output_frame->MutablePixelData()); \
glFlush(); \
texture.Release(); \
return ::mediapipe::OkStatus(); \
})); \
cv::Mat ofmat = mediapipe::formats::MatView(output_frame.get()); \
cv::cvtColor(ofmat, ofmat, cv::COLOR_RGB2BGR)
#else // !MEDIAPIPE_DISABLE_GPU
#define GET_OUTPUT_FRAME_MAT(packet, ofmat) \
auto& output_frame = packet.Get<mediapipe::ImageFrame>(); \
cv::Mat ofmat = mediapipe::formats::MatView(&output_frame); \
cv::cvtColor(ofmat, ofmat, cv::COLOR_RGB2BGR)
#endif
#endif // MEDIAPIPE_EXAMPLES_FACIAL_SEARCH_COMPAT_H_

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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.
//
// An example of sending OpenCV webcam frames into a MediaPipe graph.
// This example requires a linux computer and a GPU with EGL support drivers.
#include <cstdlib>
#include "absl/flags/flag.h"
#include "absl/flags/parse.h"
#include "mediapipe/framework/formats/classification.pb.h"
#include "mediapipe/framework/formats/image_frame.h"
#include "mediapipe/framework/formats/image_frame_opencv.h"
#include "mediapipe/framework/port/file_helpers.h"
#include "mediapipe/framework/port/opencv_highgui_inc.h"
#include "mediapipe/framework/port/opencv_imgproc_inc.h"
#include "mediapipe/framework/port/opencv_video_inc.h"
#include "mediapipe/framework/port/parse_text_proto.h"
constexpr char kWindowName[] = "Find memes that match your facial expression";
#include "cpu_gpu_compatibility.h"
#include "mediapipe/examples/facial_search/embeddings.h"
#include "mediapipe/examples/facial_search/labels.h"
DEFINE_string(
calculator_graph_config_file, "",
"Name of file containing text format CalculatorGraphConfig proto.");
DEFINE_string(input_video_path, "",
"Full path of video to load. "
"If not provided, attempt to use a webcam.");
DEFINE_bool(log_embeddings, false, "Print embeddings vector in the log.");
DEFINE_bool(without_window, false, "Do not setup opencv window.");
DEFINE_string(images_folder_path, "", "Full path of images directory.");
::mediapipe::Status RunMPPGraph() {
std::string pbtxt;
MP_RETURN_IF_ERROR(
mediapipe::file::GetContents(FLAGS_calculator_graph_config_file, &pbtxt));
LOG(INFO) << "Get calculator graph config contents: " << pbtxt;
auto config =
mediapipe::ParseTextProtoOrDie<mediapipe::CalculatorGraphConfig>(pbtxt);
LOG(INFO) << "Initialize the calculator graph.";
const auto labels = ::mediapipe::MyCollectionLabels();
const auto collection = ::mediapipe::MyEmbeddingsCollection();
std::map<std::string, ::mediapipe::Packet> input_side_packets = {
{"collection_labels", ::mediapipe::MakePacket<decltype(labels)>(labels)},
{"embeddings_collection",
::mediapipe::MakePacket<decltype(collection)>(collection)},
};
mediapipe::CalculatorGraph graph;
MP_RETURN_IF_ERROR(graph.Initialize(config, input_side_packets));
MAYBE_INIT_GPU(graph);
LOG(INFO) << "Load the video.";
cv::VideoCapture capture;
const bool load_video = !FLAGS_input_video_path.empty();
if (load_video)
capture.open(FLAGS_input_video_path);
else
capture.open(0);
RET_CHECK(capture.isOpened());
const double invCaptureFPS = 1.0 / capture.get(cv::CAP_PROP_FPS);
if (!FLAGS_without_window) {
cv::namedWindow(kWindowName, cv::WINDOW_AUTOSIZE);
RET_CHECK(!FLAGS_images_folder_path.empty());
}
LOG(INFO) << "Start running the calculator graph.";
ASSIGN_OR_RETURN(mediapipe::OutputStreamPoller pollerForEmbeddings,
graph.AddOutputStreamPoller("embeddings"));
ASSIGN_OR_RETURN(mediapipe::OutputStreamPoller pollerForEmbeddingsPresence,
graph.AddOutputStreamPoller("embeddings_presence"));
ASSIGN_OR_RETURN(mediapipe::OutputStreamPoller pollerForMemes,
graph.AddOutputStreamPoller("memes"));
MP_RETURN_IF_ERROR(graph.StartRun({}));
LOG(INFO) << "Start grabbing and processing frames.";
for (size_t n = 0; true; ++n) {
// Capture opencv camera or video frame.
cv::Mat camera_frame;
capture >> camera_frame;
if (camera_frame.empty()) break; // End of video.
if (!load_video)
cv::flip(camera_frame, camera_frame, /*flipcode=HORIZONTAL*/ 1);
if (!FLAGS_without_window) {
cv::imshow("You", camera_frame);
const int pressed_key = cv::waitKey(5);
if (pressed_key >= 0 && pressed_key != 255) continue;
}
cv::cvtColor(camera_frame, camera_frame, cv::COLOR_BGR2RGBA, 4);
const auto ts = mediapipe::Timestamp::FromSeconds(n * invCaptureFPS);
LOG(INFO) << "ts = " << ts;
ADD_INPUT_FRAME("input_frame", camera_frame, ts);
mediapipe::Packet presence;
if (!pollerForEmbeddingsPresence.Next(&presence)) break;
if (!presence.Get<bool>()) continue;
if (FLAGS_log_embeddings) {
LOG(INFO) << "polling for embeddings";
mediapipe::Packet packet;
if (!pollerForEmbeddings.Next(&packet)) break;
const auto& embedding = packet.Get<std::vector<float>>();
std::ostringstream oss;
oss << "{";
for (float f : embedding) oss << f << ",";
oss << "},\n";
LOG(INFO) << oss.str();
}
LOG(INFO) << "polling for memes";
mediapipe::Packet packet;
if (!pollerForMemes.Next(&packet)) break;
const auto& memes = packet.Get<std::vector<mediapipe::Classification>>();
LOG(INFO) << "#memes: " << memes.size();
for (const auto& meme : memes) {
LOG(INFO) << meme.score() << " <-- " << meme.label();
}
if (!FLAGS_without_window && !memes.empty()) {
const auto img_path = FLAGS_images_folder_path + memes[0].label();
const auto image = cv::imread(img_path, cv::IMREAD_UNCHANGED);
RET_CHECK(image.data) << "Couldn't load " << img_path;
cv::imshow(kWindowName, image);
// Press any key to exit.
const int pressed_key = cv::waitKey(5);
if (pressed_key >= 0 && pressed_key != 255) break;
}
}
LOG(INFO) << "Shutting down.";
MP_RETURN_IF_ERROR(graph.CloseAllInputStreams());
return graph.WaitUntilDone();
}
int main(int argc, char** argv) {
google::InitGoogleLogging(argv[0]);
gflags::ParseCommandLineFlags(&argc, &argv, true);
::mediapipe::Status run_status = RunMPPGraph();
if (!run_status.ok()) {
LOG(ERROR) << "Failed to run the graph: " << run_status.message();
} else {
LOG(INFO) << "Success!";
}
return 0;
}

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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.
#ifndef MEDIAPIPE_EXAMPLES_FACIAL_SEARCH_EMBEDDINGS_H_
#define MEDIAPIPE_EXAMPLES_FACIAL_SEARCH_EMBEDDINGS_H_
#include <vector>
namespace mediapipe {
const std::vector<std::vector<float>>& MyEmbeddingsCollection() {
static const std::vector<std::vector<float>> data = {
{0.360273,0.344299,-0.0601011,-0.0874571,-0.115668,-0.0172118,-0.0885485,0.264329,0.258976,0.000407169,-0.144043,-0.0182962,-0.0467717,-0.00249628,0.143685,-0.243664,0.0482081,-0.165425,-0.205157,-0.131136,0.352415,0.297783,0.090929,-0.139581,0.0360719,-0.0971549,-0.0127887,-0.0632506,-0.131023,-0.124878,-0.230134,-0.0489221,0.0767414,0.0447687,-0.103306,0.083289,0.203843,0.016971,-0.0801557,0.100098,0.22525,0.113119,-0.14363,-0.0690399,-0.283145,0.347141,-0.210801,-0.192435,0.302335,0.0188467,-0.142579,-0.407477,0.226639,-0.0164238,-0.00861372,-0.0454978,0.0355433,0.212059,-0.142849,-0.11361,-0.0787473,-0.0379442,0.0452453,-0.00798978,},
{0.318508,0.249886,-0.115154,-0.0730376,-0.187152,0.0396216,0.0505298,0.169197,0.352139,0.100405,-0.125271,-0.191171,-0.0134611,0.0796566,0.235819,-0.329756,0.0387886,-0.14595,-0.200429,-0.0798391,0.379982,0.119879,0.189558,-0.0639621,0.0913184,0.0255879,-0.0537018,-0.144633,-0.0646085,0.0365192,-0.0853716,-0.0725883,0.0781156,0.100849,-0.143935,0.0422517,0.197704,-0.0292149,0.122674,-0.0126583,0.294607,0.105169,-0.105966,-0.231691,-0.315402,0.402549,-0.0538364,-0.161181,0.391495,-0.0100625,-0.011637,-0.253579,0.250504,0.113486,0.209101,-0.0219375,0.0701367,0.256599,-0.0684085,-0.071408,-0.0120566,-0.132653,0.0125479,0.0576287,},
{0.325262,0.32928,-0.0227119,-0.137462,-0.143023,-0.0279421,-0.119785,0.267961,0.294252,0.0222093,-0.134782,-0.0382973,-0.00631426,-0.0292132,0.15267,-0.21202,0.0434223,-0.178312,-0.217174,-0.150065,0.334962,0.324984,0.106173,-0.160539,0.0684176,-0.110556,0.00895015,-0.0904209,-0.155617,-0.158414,-0.251649,-0.0903043,0.0317738,0.0169524,-0.117981,0.125301,0.194611,0.0458508,-0.0843728,0.0581117,0.258964,0.151901,-0.130525,-0.0817891,-0.293952,0.339044,-0.209209,-0.221465,0.340999,0.0069143,-0.138424,-0.405797,0.249794,-0.0481222,0.0236612,-0.0663456,0.0419176,0.207716,-0.172457,-0.12006,-0.0778105,0.0064223,0.0281377,-0.0209497,},
{0.306382,0.315247,-0.012325,-0.183931,-0.164453,-0.0522663,-0.109623,0.27201,0.317369,0.0282128,-0.123773,-0.0924757,-0.00313972,-0.0768318,0.172827,-0.196492,0.0440636,-0.138324,-0.216843,-0.152871,0.363662,0.319582,0.132875,-0.145934,0.0690874,-0.0771255,0.0182008,-0.128543,-0.158056,-0.149366,-0.237543,-0.0957797,0.0173511,0.0158658,-0.137325,0.150811,0.189168,0.0605078,-0.0543792,0.0443284,0.278685,0.162854,-0.163519,-0.0666793,-0.323751,0.345357,-0.220509,-0.249592,0.339764,0.00298731,-0.126348,-0.403189,0.292829,-0.0716793,0.0423921,-0.110006,0.042801,0.226869,-0.203283,-0.117354,-0.0634841,0.0230317,0.052782,-0.0682892,},
{0.338427,0.265398,-0.0275832,-0.100719,-0.185678,-0.0537828,-0.0926256,0.23777,0.296712,0.0524824,-0.100414,-0.0648169,-0.0656427,-0.035464,0.155403,-0.24084,0.0645928,-0.152585,-0.269832,-0.154228,0.335621,0.294165,0.106705,-0.154819,0.0987954,-0.160922,-0.00959375,-0.127159,-0.174685,-0.171453,-0.16602,-0.0718391,0.0303322,0.0192406,-0.0767172,0.0655644,0.192971,0.0575009,-0.128603,0.0594169,0.26037,0.141041,-0.117453,-0.0965049,-0.315703,0.35071,-0.163124,-0.228596,0.38985,-0.0451808,-0.135407,-0.389219,0.249238,0.0201468,0.0684455,-0.0485432,0.0302722,0.179657,-0.146936,-0.0552407,-0.0423196,-0.104139,0.0188916,-0.0208175,},
{0.355396,0.301085,-0.0740759,-0.0338421,-0.131099,0.0433599,-0.0208602,0.251003,0.281141,0.0306869,-0.113517,-0.0531262,-0.061923,0.104566,0.202619,-0.281404,0.0759911,-0.128102,-0.216162,-0.133683,0.35445,0.182672,0.119471,-0.128705,0.0359774,-0.0745939,-0.0638574,-0.1204,-0.0794186,-0.0337682,-0.143883,-0.0274828,0.0806934,0.0652223,-0.0605229,-0.00395597,0.235793,0.00479844,-0.0187269,0.063849,0.225617,0.077894,-0.154125,-0.143152,-0.296537,0.397859,-0.133685,-0.16179,0.337889,0.0208034,-0.0564092,-0.353877,0.223101,0.0944612,0.062843,-0.0227218,0.0708016,0.190903,-0.0792401,-0.0454141,-0.0189112,-0.100011,0.0774671,0.050441,},
{0.320085,0.268325,-0.128621,-0.071697,-0.151939,-0.0059406,-0.0188711,0.135222,0.3891,0.083281,-0.106805,-0.232411,-0.0596809,0.127448,0.22285,-0.288132,0.0149883,-0.130134,-0.20586,-0.114541,0.401313,0.124658,0.183961,-0.102603,0.0828049,0.0728461,-0.113325,-0.168498,-0.0904611,0.01476,-0.101791,-0.0439827,0.163579,0.0757737,-0.156089,0.00420617,0.186158,0.0222519,0.0888372,-0.0787775,0.278347,0.118629,-0.135177,-0.268086,-0.289374,0.396181,-0.111509,-0.18652,0.367359,-0.000632096,-0.0245633,-0.257022,0.233957,0.126828,0.249755,-0.0677688,0.123006,0.276647,-0.0835453,-0.120341,0.0171696,-0.112617,0.0464262,0.0771694,},
{0.318949,0.359606,-0.0814702,-0.106398,-0.1197,0.0591663,-0.0436736,0.287091,0.281112,0.0266814,-0.135669,-0.0440341,-0.016775,0.0455387,0.193396,-0.267153,0.0488719,-0.120146,-0.203079,-0.153818,0.332703,0.225785,0.0961039,-0.12654,0.0324361,-0.0483454,-0.0187725,-0.0964152,-0.0906417,-0.0357446,-0.195106,-0.0450568,0.0590893,0.103371,-0.121107,0.0453483,0.221735,0.0193647,0.00650701,0.0850196,0.234853,0.0750904,-0.171047,-0.113835,-0.303464,0.363741,-0.167023,-0.15981,0.330458,0.0101715,-0.0630308,-0.374736,0.258651,0.00567824,0.0410449,-0.0538444,0.0979758,0.222692,-0.142807,-0.0785648,-0.0458839,-0.0172269,0.0799239,0.00814222,},
{0.307079,0.22881,0.0297349,-0.124125,-0.171157,-0.0657267,-0.108027,0.200318,0.314083,0.0204639,-0.0599499,-0.1246,-0.0221423,-0.0349033,0.0977495,-0.189956,0.0678073,-0.157155,-0.241323,-0.207178,0.390847,0.286646,0.142758,-0.18341,0.0821922,-0.221356,-0.0665478,-0.116451,-0.179508,-0.171386,-0.186046,-0.0815089,0.0256136,-0.0682682,-0.0647167,0.0787328,0.164794,0.0953565,-0.175174,-5.29743e-05,0.271637,0.151928,-0.118048,-0.0761628,-0.312571,0.375768,-0.184119,-0.23487,0.336836,-0.0114414,-0.143397,-0.390486,0.264609,0.037542,0.0620895,-0.100508,0.0177446,0.162371,-0.142406,-0.0366981,0.00564983,-0.137154,-0.000310304,-0.0268266,},
{0.310229,0.329943,-0.0195658,-0.186195,-0.100672,-0.0750193,-0.12137,0.270256,0.296221,0.00714324,-0.134814,-0.0903694,-0.00827323,-0.0228784,0.161414,-0.191257,0.0374067,-0.139336,-0.201782,-0.198916,0.342827,0.334832,0.126807,-0.154851,0.0540382,-0.0399038,-0.0144955,-0.103355,-0.158811,-0.138871,-0.272362,-0.0892844,0.0410632,0.0152716,-0.135802,0.158546,0.174518,0.0531193,-0.0502995,0.061322,0.247107,0.156809,-0.188794,-0.0586758,-0.294702,0.33846,-0.244503,-0.240059,0.310854,0.0328215,-0.13986,-0.399933,0.25295,-0.0881528,0.0235612,-0.123792,0.0780249,0.234244,-0.199764,-0.138045,-0.0949635,0.0359434,0.0444352,-0.0453881,},
{0.344287,0.331681,-0.110711,-0.0849471,-0.138897,0.0501213,0.0198136,0.214632,0.297392,0.101464,-0.161769,-0.0955185,-0.0337375,0.0733783,0.229012,-0.311638,0.0764837,-0.17813,-0.172201,-0.0758149,0.354941,0.12761,0.134915,-0.0515817,0.0393597,0.0346223,-0.0339405,-0.0891455,-0.05254,0.0416615,-0.157187,-0.0655268,0.100648,0.137445,-0.150314,0.0158545,0.252786,-0.0291017,0.11226,-0.0222318,0.236223,0.0396605,-0.0939128,-0.180733,-0.301278,0.390418,-0.0843458,-0.113913,0.33251,0.032603,-0.0791966,-0.322725,0.24759,0.0516376,0.10153,-0.00514907,0.0814217,0.276704,-0.0783346,-0.104283,-0.044639,-0.0286115,0.092483,0.0716573,},
{0.296133,0.241589,-0.0987693,-0.0804043,-0.173511,0.0695879,0.0534834,0.186568,0.30639,0.0960323,-0.126115,-0.150848,-0.00145964,0.0446058,0.2437,-0.315794,0.0545066,-0.183374,-0.194116,-0.0529656,0.374882,0.152058,0.170572,-0.0351776,0.0655939,0.0370918,-0.0225046,-0.113088,-0.078141,0.0474878,-0.0801063,-0.113728,0.086861,0.144432,-0.172273,0.0403162,0.225323,-0.0440852,0.115197,-0.0100354,0.293727,0.0798405,-0.0670418,-0.182355,-0.34785,0.378084,-0.0627472,-0.129962,0.379515,0.0118176,-0.0425753,-0.29043,0.261015,0.0883289,0.19787,-0.0064624,0.0211013,0.281812,-0.0499057,-0.0632223,-0.0298522,-0.116669,0.0314379,0.0498679,},
{0.352871,0.337732,-0.0653371,-0.045443,-0.110721,0.0334488,-0.0603855,0.266984,0.264961,0.0116271,-0.116645,-0.0167193,-0.0734081,0.0303945,0.17234,-0.288698,0.07288,-0.142997,-0.209317,-0.117541,0.337666,0.253176,0.0948208,-0.156639,0.0474403,-0.0726385,-0.0506858,-0.0913342,-0.115654,-0.0577065,-0.160289,-0.0409435,0.0875943,0.104892,-0.063282,0.0222173,0.257647,-0.0101233,-0.0406285,0.103768,0.202388,0.0666511,-0.139954,-0.0723892,-0.297661,0.360716,-0.185972,-0.169777,0.338664,0.0122426,-0.0717004,-0.411217,0.245988,0.0459334,0.047695,-0.0189444,0.0563516,0.212151,-0.0855067,-0.0864692,-0.0668478,-0.0730168,0.0666377,0.0337336,},
{0.388538,0.341431,-0.0775281,-0.0431642,-0.107186,0.00915812,-0.0493844,0.261677,0.268958,-0.00350644,-0.120065,-0.0125907,-0.078002,0.0279799,0.154131,-0.283882,0.0563876,-0.137857,-0.201694,-0.121531,0.338493,0.267341,0.0959656,-0.16076,0.0397023,-0.067252,-0.0510807,-0.0861091,-0.111477,-0.0606824,-0.181214,-0.021082,0.0930901,0.0912825,-0.0608193,0.0444028,0.245796,-0.00925682,-0.0344847,0.109914,0.212804,0.0734442,-0.162665,-0.0719536,-0.28428,0.35065,-0.187998,-0.186493,0.310841,0.0209802,-0.0642645,-0.409563,0.234371,0.0321582,0.0234947,-0.0332354,0.068731,0.217496,-0.101609,-0.078901,-0.0735263,-0.0646544,0.0656712,0.0152659,},
{0.331338,0.259909,-0.120834,-0.0573443,-0.192277,0.0589223,0.0520888,0.165004,0.330613,0.102001,-0.137785,-0.169838,-0.0169369,0.0706278,0.243846,-0.335466,0.0418686,-0.156341,-0.185043,-0.0680414,0.384427,0.129504,0.189897,-0.0604905,0.0997903,0.05474,-0.0445177,-0.143749,-0.066726,0.0380801,-0.0922936,-0.0671152,0.085368,0.129282,-0.136782,0.0419251,0.203753,-0.050655,0.136562,-0.00543834,0.305791,0.0987109,-0.0931438,-0.229169,-0.31852,0.388921,-0.0584404,-0.149579,0.386107,-0.0163189,-0.00713679,-0.253317,0.250291,0.112969,0.209256,-0.00324434,0.0701798,0.273459,-0.0759804,-0.0850519,-0.0336064,-0.107856,0.0242881,0.0576473,},
{0.37138,0.332599,-0.106323,-0.0698364,-0.1508,0.0335721,0.022922,0.203903,0.299403,0.0975356,-0.134815,-0.0906056,-0.0457977,0.100077,0.234902,-0.296368,0.0934631,-0.160725,-0.161955,-0.0998385,0.352922,0.10904,0.115548,-0.0809659,0.0665576,0.0012876,-0.0480976,-0.114317,-0.0707604,0.0566706,-0.121904,-0.0427213,0.0787458,0.11943,-0.117418,0.0134981,0.252917,-0.0154556,0.0654239,0.00335963,0.247336,0.0159169,-0.123306,-0.144953,-0.292063,0.39801,-0.078169,-0.116139,0.325554,0.0403471,-0.0711036,-0.31929,0.230637,0.103841,0.117349,0.00515646,0.0637846,0.236677,-0.0531953,-0.0594427,-0.0337795,-0.0771331,0.0858982,0.0622918,},
{0.348222,0.34062,-0.0722753,-0.0757628,-0.128174,-0.0274891,-0.097611,0.27129,0.283191,0.013577,-0.122648,-0.0231612,-0.0559726,-0.00523109,0.155688,-0.258201,0.0533742,-0.1552,-0.215475,-0.136796,0.323154,0.292888,0.0848273,-0.161771,0.0695059,-0.0927762,-0.0167867,-0.0854196,-0.142102,-0.110863,-0.188188,-0.0539707,0.0757844,0.0614021,-0.0926535,0.0625578,0.230125,0.0260207,-0.0681151,0.0736313,0.219971,0.114521,-0.128311,-0.0755052,-0.293602,0.338328,-0.183055,-0.192197,0.346131,-0.00417221,-0.108639,-0.401007,0.244372,-0.0027942,0.0428526,-0.0433004,0.0474002,0.209935,-0.130152,-0.0859238,-0.0589042,-0.0515936,0.0345244,0.00778554,},
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{0.38573,0.303465,-0.0754598,-0.0255031,-0.156568,-0.00171386,-0.0475291,0.24712,0.259051,0.0137797,-0.104914,-0.00982348,-0.103518,0.000981707,0.16665,-0.291489,0.0720745,-0.137881,-0.232301,-0.0991366,0.349961,0.240611,0.111483,-0.146154,0.0696501,-0.0857632,-0.0332411,-0.117529,-0.129217,-0.0777895,-0.124353,-0.00427798,0.101995,0.0814745,-0.0625252,0.0221946,0.248991,-0.000535702,-0.0645014,0.110968,0.250233,0.0683392,-0.141237,-0.0586718,-0.315773,0.354119,-0.172362,-0.164601,0.323575,-0.00707823,-0.0723127,-0.40626,0.273393,0.0748597,0.0769935,-0.0202469,0.0157731,0.215997,-0.0835498,-0.0565348,-0.0572276,-0.118293,0.0680315,0.0048003,},
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{0.330991,0.279398,-0.120469,-0.0833162,-0.167197,0.0565343,0.0485062,0.197139,0.311949,0.0730728,-0.124144,-0.139497,-0.0357092,0.0766358,0.246247,-0.325406,0.0594532,-0.150058,-0.20014,-0.0560743,0.359931,0.152295,0.174846,-0.0374332,0.0542755,0.0545942,-0.0274563,-0.0897123,-0.0731688,0.0546418,-0.0977137,-0.0764365,0.101154,0.143496,-0.166845,0.0443745,0.20117,-0.069582,0.138324,-0.00901727,0.281793,0.0729901,-0.0920696,-0.194218,-0.327893,0.386344,-0.0630254,-0.13497,0.35218,0.00899709,-0.0355214,-0.280734,0.246162,0.0773838,0.163112,-0.000704707,0.0299085,0.279164,-0.0506025,-0.0647249,-0.0333138,-0.112542,0.0517399,0.0443644,},
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{0.323782,0.280495,-0.0776463,-0.0770336,-0.162604,0.101495,0.0393389,0.243438,0.295902,0.0786101,-0.111131,-0.0737151,-0.0286817,0.0486636,0.224631,-0.293034,0.0707783,-0.108098,-0.222452,-0.108061,0.353533,0.159791,0.117831,-0.0784991,0.0333824,-0.05016,-0.0328623,-0.159113,-0.0632954,0.00332638,-0.0954522,-0.0377172,0.0538288,0.148361,-0.0903919,-0.000231512,0.260504,-0.0136243,0.0430311,0.071758,0.25728,0.0245965,-0.136658,-0.129636,-0.345829,0.373848,-0.102946,-0.16379,0.369789,0.0253724,-0.0240529,-0.356846,0.27427,0.0825051,0.119279,-0.0280021,0.0627598,0.236163,-0.0825359,-0.0236759,-0.0226616,-0.0773077,0.0891304,0.034674,},
{0.283063,0.333678,-0.0544758,-0.0795028,-0.0579202,0.0977261,-0.0594736,0.234974,0.225774,-0.0407756,-0.0780969,-0.10317,-0.0584269,0.0707849,0.183553,-0.263574,0.0627723,-0.11179,-0.166371,-0.172229,0.394149,0.254527,0.138252,-0.0628142,0.0271166,0.0121564,-0.0661133,-0.087068,-0.0620072,-0.0044925,-0.186256,-0.0423568,0.126357,0.060832,-0.157059,0.0358163,0.176872,0.00798568,-0.0445168,0.0434527,0.24124,0.110748,-0.184763,-0.113197,-0.349284,0.394837,-0.217976,-0.148329,0.280999,0.0877668,-0.0898789,-0.368177,0.227633,0.0473953,0.0626762,-0.0860037,0.0713354,0.254507,-0.110176,-0.0672436,-0.00699837,-0.0752132,0.131568,0.0193134,},
};
return data;
}
} // namespace mediapipe
#endif // MEDIAPIPE_EXAMPLES_FACIAL_SEARCH_EMBEDDINGS_H_

106
mediapipe/examples/facial_search/generate_header.sh Executable file
View File

@ -0,0 +1,106 @@
#!/bin/bash
set -eu
set -o pipefail
[[ $# -ne 1 ]] && echo "Usage: $0 <path/to/images directory>" && exit 1
[[ ! -d "$1" ]] && echo "Not a directory: $1" && exit 2
images=$(python -c "import os; print(os.path.realpath('$1'))")
embeddings=$(python -c "import os; print(os.path.realpath('$(dirname "$0")'))")/embeddings.h
labels=$(python -c "import os; print(os.path.realpath('$(dirname "$0")'))")/labels.h
bazel build \
--platform_suffix=_cpu \
-c opt --define MEDIAPIPE_DISABLE_GPU=1 \
mediapipe/examples/facial_search/desktop:facial_search
cat << EOF >"$embeddings"
// 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.
#ifndef MEDIAPIPE_EXAMPLES_FACIAL_SEARCH_EMBEDDINGS_H_
#define MEDIAPIPE_EXAMPLES_FACIAL_SEARCH_EMBEDDINGS_H_
#include <vector>
namespace mediapipe {
const std::vector<std::vector<float>>& MyEmbeddingsCollection() {
static const std::vector<std::vector<float>> data = {
EOF
cat << EOF >"$labels"
// Copyright 2020 The MediaPipe Authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#ifndef MEDIAPIPE_EXAMPLES_FACIAL_SEARCH_LABELS_H_
#define MEDIAPIPE_EXAMPLES_FACIAL_SEARCH_LABELS_H_
#include <vector>
namespace mediapipe {
const std::vector<std::string>& MyCollectionLabels() {
static const std::vector<std::string> data = {
EOF
pushd "$(dirname "$(dirname "$(dirname "$(dirname "$0")")")")" >/dev/null
while read -r image; do
case "$image" in
*BUILD|*.gitignore|*download_images.py) continue
esac
echo "Running inference for $(basename "$image")"
if GLOG_logtostderr=1 ./bazel-bin/mediapipe/examples/facial_search/desktop/facial_search \
--calculator_graph_config_file=mediapipe/examples/facial_search/graphs/facial_search_cpu.pbtxt \
--input_video_path="$image" \
--log_embeddings \
--without_window \
2>&1 \
| grep -Eo '\{.+' >>"$embeddings"; then
echo ' "'"$(basename "$image")"'",' >>"$labels"
else
echo "Failed to process embeddings of $(basename "$image")"
fi
done < <(find "$images" -type f | sort)
popd
cat << EOF >>"$embeddings"
};
return data;
}
} // namespace mediapipe
#endif // MEDIAPIPE_EXAMPLES_FACIAL_SEARCH_EMBEDDINGS_H_
EOF
cat << EOF >>"$labels"
};
return data;
}
} // namespace mediapipe
#endif // MEDIAPIPE_EXAMPLES_FACIAL_SEARCH_LABELS_H_
EOF

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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.
load("@rules_cc//cc:defs.bzl", "cc_library")
load("//mediapipe/framework/tool:mediapipe_graph.bzl", "mediapipe_binary_graph", "mediapipe_simple_subgraph")
licenses(["notice"]) # Apache 2.0
package(default_visibility = ["//visibility:public"])
cc_library(
name = "cpu_calculators",
deps = [
":subgraph_face_embeddings_cpu",
"//mediapipe/calculators/core:flow_limiter_calculator",
"//mediapipe/calculators/core:packet_presence_calculator",
"//mediapipe/examples/facial_search/calculators:closest_embeddings_calculator",
"//mediapipe/modules/face_detection:face_detection_short_range_cpu",
],
)
cc_library(
name = "gpu_calculators",
deps = [
":subgraph_face_embeddings_gpu",
"//mediapipe/calculators/core:flow_limiter_calculator",
"//mediapipe/calculators/core:packet_presence_calculator",
"//mediapipe/examples/facial_search/calculators:closest_embeddings_calculator",
"//mediapipe/gpu:gpu_buffer_to_image_frame_calculator",
"//mediapipe/modules/face_detection:face_detection_short_range_gpu",
],
)
mediapipe_binary_graph(
name = "facial_search_cpu_binary_graph",
graph = "facial_search_cpu.pbtxt",
output_name = "facial_search_cpu.binarypb",
deps = [":cpu_calculators"],
)
mediapipe_binary_graph(
name = "facial_search_gpu_binary_graph",
graph = "facial_search_gpu.pbtxt",
output_name = "facial_search_gpu.binarypb",
deps = [":gpu_calculators"],
)
cc_library(
name = "face_embeddings_calculators",
deps = [
"//mediapipe/calculators/image:image_cropping_calculator",
"//mediapipe/calculators/image:image_transformation_calculator",
"//mediapipe/calculators/tflite:tflite_converter_calculator",
"//mediapipe/calculators/tflite:tflite_inference_calculator",
"//mediapipe/calculators/tflite:tflite_tensors_to_floats_calculator",
"//mediapipe/calculators/util:detections_to_rects_calculator",
],
)
mediapipe_simple_subgraph(
name = "subgraph_face_embeddings_cpu",
graph = "subgraph_face_embeddings_cpu.pbtxt",
register_as = "FaceEmbeddingsSubgraph",
deps = [":face_embeddings_calculators"],
)
mediapipe_simple_subgraph(
name = "subgraph_face_embeddings_gpu",
graph = "subgraph_face_embeddings_gpu.pbtxt",
register_as = "FaceEmbeddingsSubgraph",
deps = [
":face_embeddings_calculators",
"//mediapipe/gpu:gpu_buffer_to_image_frame_calculator",
],
)

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input_stream: "input_frame"
output_stream: "embeddings"
output_stream: "embeddings_presence"
output_stream: "memes"
node {
calculator: "FlowLimiterCalculator"
input_stream: "input_frame"
input_stream: "FINISHED:embeddings"
input_stream_info: {
tag_index: "FINISHED"
back_edge: true
}
output_stream: "input_frame_throttled"
}
node {
calculator: "FaceDetectionShortRangeCpu"
input_stream: "IMAGE:input_frame_throttled"
output_stream: "DETECTIONS:head_detections"
}
node {
calculator: "FaceEmbeddingsSubgraph"
input_stream: "IMAGE:input_frame_throttled"
input_stream: "DETECTIONS:head_detections"
output_stream: "FLOATS:embeddings"
}
node {
calculator: "PacketPresenceCalculator"
input_stream: "PACKET:embeddings"
output_stream: "PRESENCE:embeddings_presence"
}
node {
calculator: "ClosestEmbeddingsCalculator"
input_side_packet: "COLLECTION:embeddings_collection"
input_side_packet: "LABELS:collection_labels"
input_stream: "FLOATS:embeddings"
output_stream: "CLASSIFICATIONS:memes"
node_options: {
[type.googleapis.com/mediapipe.ClosestEmbeddingsCalculatorOptions] {
top_k: 3
}
}
}

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input_stream: "input_frame"
output_stream: "embeddings"
output_stream: "embeddings_presence"
output_stream: "memes"
node {
calculator: "FlowLimiterCalculator"
input_stream: "input_frame"
input_stream: "FINISHED:embeddings"
input_stream_info: {
tag_index: "FINISHED"
back_edge: true
}
output_stream: "input_frame_throttled"
}
node {
calculator: "FaceDetectionShortRangeGpu"
input_stream: "IMAGE:input_frame_throttled"
output_stream: "DETECTIONS:head_detections"
}
node {
calculator: "FaceEmbeddingsSubgraph"
input_stream: "IMAGE:input_frame_throttled"
input_stream: "DETECTIONS:head_detections"
output_stream: "FLOATS:embeddings"
}
node {
calculator: "PacketPresenceCalculator"
input_stream: "PACKET:embeddings"
output_stream: "PRESENCE:embeddings_presence"
}
node {
calculator: "ClosestEmbeddingsCalculator"
input_side_packet: "COLLECTION:embeddings_collection"
input_side_packet: "LABELS:collection_labels"
input_stream: "FLOATS:embeddings"
output_stream: "CLASSIFICATIONS:memes"
node_options: {
[type.googleapis.com/mediapipe.ClosestEmbeddingsCalculatorOptions] {
top_k: 3
}
}
}

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# MediaPipe graph that performs face detection with TensorFlow Lite on CPU.
# Used in the examples in
# mediapipe/examples/facial_search.
type: "FaceEmbeddingsSubgraph"
input_stream: "IMAGE:input_frame"
input_stream: "DETECTIONS:head_detections"
output_stream: "FLOATS:embeddings"
# DetectionsToRectsCalculator takes DETECTIONS in and outputs NORM_RECT of
# the first detection.
node {
calculator: "DetectionsToRectsCalculator"
input_stream: "DETECTIONS:head_detections"
output_stream: "NORM_RECT:head_rect"
node_options: {
[type.googleapis.com/mediapipe.DetectionsToRectsCalculatorOptions] {
output_zero_rect_for_empty_detections: true
}
}
}
node {
calculator: "ImageCroppingCalculator"
input_stream: "IMAGE:input_frame"
input_stream: "NORM_RECT:head_rect"
output_stream: "IMAGE:cropped_head"
}
node {
calculator: "ImageTransformationCalculator"
input_stream: "IMAGE:cropped_head"
output_stream: "IMAGE:scaled_head"
node_options: {
[type.googleapis.com/mediapipe.ImageTransformationCalculatorOptions] {
output_width: 140
output_height: 140
scale_mode: FIT
}
}
}
node {
calculator: "TfLiteConverterCalculator"
input_stream: "IMAGE:scaled_head"
output_stream: "TENSORS:scaled_head_tensor"
}
node {
calculator: "TfLiteInferenceCalculator"
input_stream: "TENSORS:scaled_head_tensor"
output_stream: "TENSORS:embeddings_tensors"
node_options: {
[type.googleapis.com/mediapipe.TfLiteInferenceCalculatorOptions] {
use_gpu: false
model_path: "mediapipe/models/face_embeddings.tflite"
}
}
}
node {
calculator: "TfLiteTensorsToFloatsCalculator"
input_stream: "TENSORS:embeddings_tensors"
output_stream: "FLOATS:embeddings"
}

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# MediaPipe graph that performs face detection with TensorFlow Lite on GPU.
# Used in the examples in
# mediapipe/examples/facial_search.
type: "FaceEmbeddingsSubgraph"
input_stream: "IMAGE:input_frame"
input_stream: "DETECTIONS:head_detections"
output_stream: "FLOATS:embeddings"
# DetectionsToRectsCalculator takes DETECTIONS in and outputs NORM_RECT of
# the first detection.
node {
calculator: "DetectionsToRectsCalculator"
input_stream: "DETECTIONS:head_detections"
output_stream: "NORM_RECT:head_rect"
node_options: {
[type.googleapis.com/mediapipe.DetectionsToRectsCalculatorOptions] {
output_zero_rect_for_empty_detections: true
}
}
}
node {
calculator: "ImageCroppingCalculator"
input_stream: "IMAGE_GPU:input_frame"
input_stream: "NORM_RECT:head_rect"
output_stream: "IMAGE_GPU:cropped_head"
}
node {
calculator: "ImageTransformationCalculator"
input_stream: "IMAGE_GPU:cropped_head"
output_stream: "IMAGE_GPU:scaled_head"
node_options: {
[type.googleapis.com/mediapipe.ImageTransformationCalculatorOptions] {
output_width: 140
output_height: 140
scale_mode: FIT
}
}
}
node {
calculator: "GpuBufferToImageFrameCalculator"
input_stream: "scaled_head"
output_stream: "scaled_head_cpu"
}
node {
calculator: "TfLiteConverterCalculator"
input_stream: "IMAGE:scaled_head_cpu"
output_stream: "TENSORS:scaled_head_tensor"
}
# Runs inference on CPU as this tflite uses operations that are not supported on GPU.
# Warnings shown when attempting to run on GPU:
# ERROR: Next operations are not supported by GPU delegate:
# MAXIMUM: Operation is not supported.
# MEAN: Operation is not supported.
# First 0 operations will run on the GPU, and the remaining 81 on the CPU.
node {
calculator: "TfLiteInferenceCalculator"
input_stream: "TENSORS:scaled_head_tensor"
output_stream: "TENSORS:embeddings_tensors"
node_options: {
[type.googleapis.com/mediapipe.TfLiteInferenceCalculatorOptions] {
use_gpu: false
model_path: "mediapipe/models/face_embeddings.tflite"
}
}
}
node {
calculator: "TfLiteTensorsToFloatsCalculator"
input_stream: "TENSORS:embeddings_tensors"
output_stream: "FLOATS:embeddings"
}

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/*.jpg

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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"]) # Apache 2.0
package(default_visibility = ["//visibility:public"])
filegroup(
name = "jpgs",
srcs = glob(["*.jpg"]),
)

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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.
from __future__ import print_function
import os
import subprocess
import sys
URLS = {
"3c563d87e3ba699b9ba75403f1b347c915abdf5dea35ead204dd09356697b769": "https://imgflip.com/s/meme/10-Guy.jpg",
"bcf0c567978794099b3151418e3907778252e1471cfe930fb30da7ca56ddae99": "https://imgflip.com/s/meme/1990s-First-World-Problems.jpg",
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"08dfb3a818e507a515c94d461ee0241fc7893078ddbab31e9cbf9e421bd0ac95": "https://imgflip.com/s/meme/Bill-OReilly.jpg",
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"784b4a5cff62db79421d86a6e258d9808def39c804c99d589fdaf17ec6d73f5c": "https://imgflip.com/s/meme/Bitch-Please.jpg",
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"009ea4ff8ec125f771a8b768f4adbb3e04e6e6f4fce615c2485ed9b21fcaf654": "https://imgflip.com/s/meme/Booty-Warrior.jpg",
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"dd4f767714f3bc7986ca0d978b56171a5b5c4f07354148d161d6cd4a542131e3": "https://imgflip.com/s/meme/Brian-Burke-On-The-Phone.jpg",
"08f05a26b8e42358192e5b3093defc437fce11a52e9a70268e7777d8930ace6d": "https://imgflip.com/s/meme/Brian-Williams-Was-There-2.jpg",
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}
IMAGES_PATH = 'mediapipe/examples/facial_search/images'
if __name__ == '__main__':
for sha, url in URLS.items():
image_path = sha + '.jpg'
local_path = os.path.join(IMAGES_PATH, image_path)
if not os.path.exists(local_path):
print('Downloading {!r}'.format(url))
return_code = subprocess.call(
["curl", "--fail", "--output", local_path, url],
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
if return_code:
print('Could not retrieve contents from {!r}'.format(url))

48
mediapipe/examples/facial_search/ios/AppDelegate.swift 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.
import UIKit
@UIApplicationMain
class AppDelegate: UIResponder, UIApplicationDelegate {
lazy var window: UIWindow? = .init(frame: UIScreen.main.bounds)
func application(
_ application: UIApplication,
didFinishLaunchingWithOptions launchOptions: [UIApplication.LaunchOptionsKey: Any]?
) -> Bool {
window?.rootViewController = FacialSearchViewController()
window?.makeKeyAndVisible()
return true
}
func applicationWillResignActive(_ application: UIApplication) {
// Sent when the application is about to move from active to inactive state. This can occur for certain types of temporary interruptions (such as an incoming phone call or SMS message) or when the user quits the application and it begins the transition to the background state.
// Use this method to pause ongoing tasks, disable timers, and invalidate graphics rendering callbacks. Games should use this method to pause the game.
}
func applicationDidEnterBackground(_ application: UIApplication) {
// Use this method to release shared resources, save user data, invalidate timers, and store enough application state information to restore your application to its current state in case it is terminated later.
}
func applicationWillEnterForeground(_ application: UIApplication) {
// Called as part of the transition from the background to the active state; here you can undo many of the changes made on entering the background.
}
func applicationDidBecomeActive(_ application: UIApplication) {
// Restart any tasks that were paused (or not yet started) while the application was inactive. If the application was previously in the background, optionally refresh the user interface.
}
}

135
mediapipe/examples/facial_search/ios/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("@build_bazel_rules_apple//apple:ios.bzl", "ios_application", "ios_framework")
load("@build_bazel_rules_swift//swift:swift.bzl", "swift_library")
load(
"//mediapipe/examples/ios:bundle_id.bzl",
"BUNDLE_ID_PREFIX",
"example_provisioning",
)
licenses(["notice"]) # Apache 2.0
MIN_IOS_VERSION = "11.1"
IOS_FAMILIES = [
"iphone",
"ipad",
]
# Build this .ipa with:
# bazel build --config=ios_arm64 mediapipe/examples/facial_search/ios:FacialSearchGpuApp
ios_application(
name = "FacialSearchGpuApp",
app_icons = ["//mediapipe/examples/ios/common:AppIcon"],
bundle_id = BUNDLE_ID_PREFIX + ".FacialSearchGpu",
families = IOS_FAMILIES,
infoplists = [
"//mediapipe/examples/ios/common:Info.plist",
"Info.plist",
],
minimum_os_version = MIN_IOS_VERSION,
provisioning_profile = example_provisioning(),
deps = [":FacialSearchGpuAppLibrary"],
)
swift_library(
name = "FacialSearchGpuAppLibrary",
srcs = [
"AppDelegate.swift",
"Cameras.swift",
"DotDot.swift",
"FacialSearchViewController.swift",
],
data = ["Base.lproj/Main.storyboard"],
deps = [
":ObjcppLib",
"@ios_opencv//:OpencvFramework",
],
)
FRAMEWORK_HEADERS = [
"ObjcppLib.h",
]
# Using Mediapipe in an iOS Swift app (without Tulsi)
# Create new Swift app: XCode: File > New > Project...
# Select iOS > "Single View App" > Next
# Select Language: Swift > Next > Create
# Delete these files from the new project: (Move to Trash)
# * AppDelegate.swift
# * ViewController.swift
# Copy these files to your app: (if asked, do not create a bridging header)
# * AppDelegate.swift
# * Cameras.swift
# * DotDot.swift
# * FacialSearchViewController.swift
# Edit your app's Info.plist:
# * Create key "NSCameraUsageDescription" with value: "This app uses the camera to demonstrate live video processing."
# Edit your Main.storyboard's custom class, setting it to FacialSearchViewController (in the Identity inspector)
# Run: bazel build --copt=-fembed-bitcode --apple_bitcode=embedded --config=ios_arm64 mediapipe/examples/facial_search/ios:FacialSearch
# (some linker warnings about global C++ symbols may appear)
# Run: ./mediapipe/examples/facial_search/ios/patch_ios_framework.sh bazel-bin/mediapipe/examples/facial_search/ios/FacialSearch.zip ObjcppLib.h
# Note: append the contents of FRAMEWORK_HEADERS separated by spaces (here: ObjcppLib.h).
# Run: open bazel-bin/mediapipe/examples/facial_search/ios and drag and drop
# the FacialSearch.framework folder into your app files (check: Copy items if needed > Finish)
# Make sure the framework gets embedded into the app:
# In General > Frameworks, Libraries, and Embedded Content set FacialSearch.framework to "Embed & Sign".
# Connect your device and run.
ios_framework(
name = "FacialSearch",
hdrs = FRAMEWORK_HEADERS,
bundle_id = BUNDLE_ID_PREFIX + ".FacialSearchFramework",
bundle_name = "FacialSearch",
families = IOS_FAMILIES,
infoplists = [
"//mediapipe/examples/ios/common:Info.plist",
"Info.plist",
],
minimum_os_version = MIN_IOS_VERSION,
visibility = ["//visibility:public"],
deps = [
":ObjcppLib",
"@ios_opencv//:OpencvFramework",
],
)
objc_library(
name = "ObjcppLib",
srcs = [
"Classification.mm",
"ObjcppLib.mm",
],
hdrs = FRAMEWORK_HEADERS,
copts = ["-std=c++17"], # https://github.com/google/mediapipe/issues/2275#issuecomment-877145926
data = [
"//mediapipe/examples/facial_search/graphs:facial_search_gpu.binarypb",
"//mediapipe/examples/facial_search/images:jpgs",
"//mediapipe/models:face_embeddings.tflite",
"//mediapipe/modules/face_detection:face_detection_short_range.tflite",
],
deps = [
"//mediapipe/objc:mediapipe_framework_ios",
"//mediapipe/objc:mediapipe_input_sources_ios",
"//mediapipe/objc:mediapipe_layer_renderer",
] + select({
"//mediapipe:ios_i386": [],
"//mediapipe:ios_x86_64": [],
"//conditions:default": [
"//mediapipe/examples/facial_search/graphs:gpu_calculators",
"//mediapipe/examples/facial_search:embeddings_database",
],
}),
)

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mediapipe/examples/facial_search/ios/Base.lproj/Main.storyboard Normal file
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<?xml version="1.0" encoding="UTF-8"?>
<document type="com.apple.InterfaceBuilder3.CocoaTouch.Storyboard.XIB" version="3.0" toolsVersion="14490.70" targetRuntime="iOS.CocoaTouch" propertyAccessControl="none" useAutolayout="YES" useTraitCollections="YES" useSafeAreas="YES" colorMatched="YES" initialViewController="BYZ-38-t0r">
<device id="retina4_7" orientation="portrait">
<adaptation id="fullscreen"/>
</device>
<dependencies>
<plugIn identifier="com.apple.InterfaceBuilder.IBCocoaTouchPlugin" version="14490.49"/>
<capability name="Safe area layout guides" minToolsVersion="9.0"/>
<capability name="documents saved in the Xcode 8 format" minToolsVersion="8.0"/>
</dependencies>
<scenes>
<!--View Controller-->
<scene sceneID="tne-QT-ifu">
<objects>
<viewController id="BYZ-38-t0r" customClass="ViewController" sceneMemberID="viewController">
<view key="view" contentMode="scaleToFill" id="8bC-Xf-vdC">
<rect key="frame" x="0.0" y="0.0" width="375" height="667"/>
<autoresizingMask key="autoresizingMask" widthSizable="YES" heightSizable="YES"/>
<subviews>
<view contentMode="scaleToFill" fixedFrame="YES" translatesAutoresizingMaskIntoConstraints="NO" id="EfB-xq-knP">
<rect key="frame" x="0.0" y="20" width="375" height="647"/>
<autoresizingMask key="autoresizingMask" widthSizable="YES" heightSizable="YES"/>
<subviews>
<label opaque="NO" userInteractionEnabled="NO" contentMode="left" horizontalHuggingPriority="251" verticalHuggingPriority="251" fixedFrame="YES" text="Camera access needed for this demo. Please enable camera access in the Settings app." textAlignment="center" lineBreakMode="tailTruncation" numberOfLines="0" baselineAdjustment="alignBaselines" adjustsFontSizeToFit="NO" translatesAutoresizingMaskIntoConstraints="NO" id="emf-N5-sEd">
<rect key="frame" x="57" y="248" width="260" height="151"/>
<autoresizingMask key="autoresizingMask" flexibleMinX="YES" flexibleMaxX="YES" flexibleMinY="YES" flexibleMaxY="YES"/>
<fontDescription key="fontDescription" type="system" pointSize="17"/>
<color key="textColor" white="1" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/>
<nil key="highlightedColor"/>
</label>
</subviews>
<color key="backgroundColor" white="0.0" alpha="1" colorSpace="custom" customColorSpace="genericGamma22GrayColorSpace"/>
<accessibility key="accessibilityConfiguration" label="PreviewDisplayView">
<bool key="isElement" value="YES"/>
</accessibility>
</view>
</subviews>
<color key="backgroundColor" red="1" green="1" blue="1" alpha="1" colorSpace="custom" customColorSpace="sRGB"/>
<viewLayoutGuide key="safeArea" id="6Tk-OE-BBY"/>
</view>
<connections>
<outlet property="_liveView" destination="EfB-xq-knP" id="JQp-2n-q9q"/>
<outlet property="_noCameraLabel" destination="emf-N5-sEd" id="91G-3Z-cU3"/>
</connections>
</viewController>
<placeholder placeholderIdentifier="IBFirstResponder" id="dkx-z0-nzr" sceneMemberID="firstResponder"/>
</objects>
<point key="canvasLocation" x="48.799999999999997" y="20.239880059970016"/>
</scene>
</scenes>
</document>

45
mediapipe/examples/facial_search/ios/Cameras.swift 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.
import ARKit
import AVFoundation
class FrontCamera: NSObject {
lazy var session: AVCaptureSession = .init()
lazy var device: AVCaptureDevice = AVCaptureDevice.default(
.builtInWideAngleCamera, for: .video, position: .front)!
lazy var input: AVCaptureDeviceInput = try! AVCaptureDeviceInput(device: device)
lazy var output: AVCaptureVideoDataOutput = .init()
override init() {
super.init()
output.videoSettings = [kCVPixelBufferPixelFormatTypeKey as String: kCVPixelFormatType_32BGRA]
session.addInput(input)
session.addOutput(output)
}
func setSampleBufferDelegate(_ delegate: AVCaptureVideoDataOutputSampleBufferDelegate) {
output.setSampleBufferDelegate(delegate, queue: .main)
}
func start() {
session.startRunning()
}
func stop() {
session.stopRunning()
}
}

27
mediapipe/examples/facial_search/ios/Classification.mm 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.
#import "ObjcppLib.h"
#include "mediapipe/framework/formats/classification.pb.h"
@implementation Classification
- (instancetype)init {
if (self = [super init]) {
}
return self;
}
@end

34
mediapipe/examples/facial_search/ios/DotDot.swift 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.
/**
Custom operator that calls the specified block `self` value as its argument and returns `self`.
Usage:
self.backgroundView = UILabel()..{
$0.backgroundColor = .red
$0.textColor = .white
$0.numberOfLines = 0
}
*/
infix operator ..: MultiplicationPrecedence
@discardableResult
public func .. <T>(object: T, block: (inout T) -> Void) -> T {
var object = object
block(&object)
return object
}

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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.
import AVFoundation
import SceneKit
import UIKit
#if canImport(FacialSearch)
// Either import standalone iOS framework...
import FacialSearch
func facialSearchBundle() -> Bundle {
return Bundle(for: FacialSearch.self)
}
#elseif canImport(mediapipe_examples_facial_search_ios_ObjcppLib)
// ...or import the ObjcppLib target linked using Bazel.
import mediapipe_examples_facial_search_ios_ObjcppLib
func facialSearchBundle() -> Bundle {
return Bundle.main
}
#endif
class FacialSearchViewController: UIViewController,
AVCaptureVideoDataOutputSampleBufferDelegate, FacialSearchDelegate
{
let camera = FrontCamera()
let displayLayer: AVSampleBufferDisplayLayer = .init()
let ffind: FacialSearch = FacialSearch()!
private lazy var cameraView: UIView = UIView() .. {
$0.translatesAutoresizingMaskIntoConstraints = false
}
private lazy var containView: UIView = UIView() .. {
$0.translatesAutoresizingMaskIntoConstraints = false
$0.clipsToBounds = true
}
private lazy var imgView: UIImageView = UIImageView() .. {
$0.translatesAutoresizingMaskIntoConstraints = false
$0.contentMode = .scaleAspectFill
}
override func viewDidLoad() {
super.viewDidLoad()
view.addSubview(cameraView)
view.addSubview(containView)
containView.addSubview(imgView)
NSLayoutConstraint.activate([
cameraView.topAnchor.constraint(equalTo: view.topAnchor),
cameraView.leadingAnchor.constraint(equalTo: view.leadingAnchor),
cameraView.trailingAnchor.constraint(equalTo: view.trailingAnchor),
cameraView.heightAnchor.constraint(equalTo: view.widthAnchor),
containView.topAnchor.constraint(equalTo: cameraView.bottomAnchor),
containView.leadingAnchor.constraint(equalTo: view.leadingAnchor),
containView.trailingAnchor.constraint(equalTo: view.trailingAnchor),
containView.bottomAnchor.constraint(equalTo: view.bottomAnchor),
imgView.topAnchor.constraint(equalTo: containView.topAnchor),
imgView.leadingAnchor.constraint(equalTo: containView.leadingAnchor),
imgView.trailingAnchor.constraint(equalTo: containView.trailingAnchor),
imgView.bottomAnchor.constraint(equalTo: containView.bottomAnchor),
])
cameraView.layer.addSublayer(displayLayer)
camera.setSampleBufferDelegate(self)
camera.start()
ffind.startGraph()
ffind.delegate = self
}
override func viewDidLayoutSubviews() {
super.viewDidLayoutSubviews()
displayLayer.frame = cameraView.bounds
}
func captureOutput(
_ output: AVCaptureOutput, didOutput sampleBuffer: CMSampleBuffer,
from connection: AVCaptureConnection
) {
connection.videoOrientation = AVCaptureVideoOrientation.portrait
displayLayer.enqueue(sampleBuffer)
let pixelBuffer = CMSampleBufferGetImageBuffer(sampleBuffer)
ffind.processVideoFrame(pixelBuffer)
}
func didReceive(_ memes: [Classification]!) {
NSLog("Got %d memes!", memes.count)
if memes.count != 0 {
DispatchQueue.main.async {
if let img = self.getImage(name: memes.last!.label) {
self.imgView.contentMode = .scaleAspectFill
self.imgView.image = img
}
}
}
}
func getImage(name: String) -> UIImage? {
NSLog("Loading image %@", name)
let nameWE = NSString(string: name).deletingPathExtension as String
let bundle = facialSearchBundle()
guard let url = bundle.url(forResource: nameWE, withExtension: "jpg") else {
fatalError("Can't load image")
}
NSLog("Image path: %@", url.path)
guard let image = UIImage(contentsOfFile: url.path) else {
fatalError("Image is not a .jpg")
}
NSLog("Image size: %@", image.size.debugDescription)
return image
}
func resizeImage(img: UIImage, size: CGSize) -> UIImage? {
let renderer = UIGraphicsImageRenderer(size: size)
return renderer.image { (context) in
img.draw(in: CGRect(origin: .zero, size: size))
}
}
}

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mediapipe/examples/facial_search/ios/Info.plist Normal file
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<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>NSCameraUsageDescription</key>
<string>This app uses the camera to demonstrate live video processing.</string>
<key>CFBundleDevelopmentRegion</key>
<string>en</string>
<key>CFBundleExecutable</key>
<string>$(EXECUTABLE_NAME)</string>
<key>CFBundleIdentifier</key>
<string>$(PRODUCT_BUNDLE_IDENTIFIER)</string>
<key>CFBundleInfoDictionaryVersion</key>
<string>6.0</string>
<key>CFBundleName</key>
<string>$(PRODUCT_NAME)</string>
<key>CFBundlePackageType</key>
<string>APPL</string>
<key>CFBundleShortVersionString</key>
<string>1.0</string>
<key>CFBundleVersion</key>
<string>1</string>
<key>LSRequiresIPhoneOS</key>
<true/>
<key>UILaunchStoryboardName</key>
<string>LaunchScreen</string>
<key>UIMainStoryboardFile</key>
<string>Main</string>
<key>UIRequiredDeviceCapabilities</key>
<array>
<string>armv7</string>
</array>
<key>UISupportedInterfaceOrientations</key>
<array>
<string>UIInterfaceOrientationPortrait</string>
</array>
<key>UISupportedInterfaceOrientations~ipad</key>
<array>
<string>UIInterfaceOrientationPortrait</string>
</array>
</dict>
</plist>

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mediapipe/examples/facial_search/ios/ObjcppLib.h 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.
#import <CoreVideo/CoreVideo.h>
#import <Foundation/Foundation.h>
@interface Classification : NSObject
- (instancetype)init;
@property uint32_t index;
@property float score;
@property NSString *label;
@end
@protocol FacialSearchDelegate <NSObject>
@optional
- (void)didReceive:(NSArray<Classification *> *)memes;
@end
@interface FacialSearch : NSObject
- (instancetype)init;
- (void)startGraph;
- (void)processVideoFrame:(CVPixelBufferRef)imageBuffer;
@property(weak, nonatomic) id<FacialSearchDelegate> delegate;
@property(nonatomic) size_t timestamp;
@end

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mediapipe/examples/facial_search/ios/ObjcppLib.mm 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.
#import "ObjcppLib.h"
#import "mediapipe/objc/MPPCameraInputSource.h"
#import "mediapipe/objc/MPPGraph.h"
#import "mediapipe/objc/MPPLayerRenderer.h"
#include "mediapipe/examples/facial_search/embeddings.h"
#include "mediapipe/examples/facial_search/labels.h"
#include "mediapipe/framework/formats/classification.pb.h"
static NSString* const kGraphName = @"facial_search_gpu";
static const char* kInputStream = "input_frame";
static const char* kMemesOutputStream = "memes";
@interface FacialSearch () <MPPGraphDelegate>
@property(nonatomic) MPPGraph* mediapipeGraph;
@end
@implementation FacialSearch {
}
#pragma mark - Cleanup methods
- (void)dealloc {
self.mediapipeGraph.delegate = nil;
[self.mediapipeGraph cancel];
// Ignore errors since we're cleaning up.
[self.mediapipeGraph closeAllInputStreamsWithError:nil];
[self.mediapipeGraph waitUntilDoneWithError:nil];
}
#pragma mark - MediaPipe graph methods
+ (MPPGraph*)loadGraphFromResource:(NSString*)resource {
// Load the graph config resource.
NSError* configLoadError = nil;
NSBundle* bundle = [NSBundle bundleForClass:[self class]];
if (!resource || resource.length == 0) {
return nil;
}
NSURL* graphURL = [bundle URLForResource:resource withExtension:@"binarypb"];
NSData* data = [NSData dataWithContentsOfURL:graphURL options:0 error:&configLoadError];
if (!data) {
NSLog(@"Failed to load MediaPipe graph config: %@", configLoadError);
return nil;
}
// Parse the graph config resource into mediapipe::CalculatorGraphConfig proto object.
mediapipe::CalculatorGraphConfig config;
config.ParseFromArray(data.bytes, data.length);
// Create MediaPipe graph with mediapipe::CalculatorGraphConfig proto object.
MPPGraph* newGraph = [[MPPGraph alloc] initWithGraphConfig:config];
// Add meme collection as side packets.
const auto labels = ::mediapipe::MyCollectionLabels();
const auto collection = ::mediapipe::MyEmbeddingsCollection();
[newGraph
addSidePackets:{
{"collection_labels", ::mediapipe::MakePacket<decltype(labels)>(labels)},
{"embeddings_collection",
::mediapipe::MakePacket<decltype(collection)>(collection)},
}];
[newGraph addFrameOutputStream:kMemesOutputStream outputPacketType:MPPPacketTypeRaw];
return newGraph;
}
- (instancetype)init {
self = [super init];
if (self) {
self.mediapipeGraph = [[self class] loadGraphFromResource:kGraphName];
self.mediapipeGraph.delegate = self;
// // Set maxFramesInFlight to a small value to avoid memory contention
// // for real-time processing.
// self.mediapipeGraph.maxFramesInFlight = 2;
NSLog(@"inited graph %@", kGraphName);
}
return self;
}
- (void)startGraph {
NSError* error;
if (![self.mediapipeGraph startWithError:&error]) {
NSLog(@"Failed to start graph: %@", error);
}
NSLog(@"Started graph %@", kGraphName);
}
#pragma mark - MPPGraphDelegate methods
// Receives CVPixelBufferRef from the MediaPipe graph. Invoked on a MediaPipe worker thread.
- (void)mediapipeGraph:(MPPGraph*)graph
didOutputPixelBuffer:(CVPixelBufferRef)pixelBuffer
fromStream:(const std::string&)streamName {
NSLog(@"recv pixelBuffer from %@", @(streamName.c_str()));
}
// Receives a raw packet from the MediaPipe graph. Invoked on a MediaPipe worker thread.
- (void)mediapipeGraph:(MPPGraph*)graph
didOutputPacket:(const ::mediapipe::Packet&)packet
fromStream:(const std::string&)streamName {
NSLog(@"recv packet @%@ from %@", @(packet.Timestamp().DebugString().c_str()),
@(streamName.c_str()));
if (streamName == kMemesOutputStream) {
if (packet.IsEmpty()) {
return;
}
const auto& memes = packet.Get<std::vector<::mediapipe::Classification>>();
if (memes.empty()) {
return;
}
NSMutableArray<Classification*>* result = [NSMutableArray array];
for (const auto& meme : memes) {
auto* c = [[Classification alloc] init];
if (c) {
c.index = meme.index();
c.score = meme.score();
c.label = @(meme.label().c_str());
NSLog(@"\tmeme %f: %@", c.score, c.label);
[result addObject:c];
}
}
NSLog(@"calling didReceive with %lu memes", memes.size());
[_delegate didReceive:result];
}
}
#pragma mark - MPPInputSourceDelegate methods
- (void)processVideoFrame:(CVPixelBufferRef)imageBuffer {
const auto ts =
mediapipe::Timestamp(self.timestamp++ * mediapipe::Timestamp::kTimestampUnitsPerSecond);
NSError* err = nil;
NSLog(@"sending imageBuffer @%@ to %s", @(ts.DebugString().c_str()), kInputStream);
auto sent = [self.mediapipeGraph sendPixelBuffer:imageBuffer
intoStream:kInputStream
packetType:MPPPacketTypePixelBuffer
timestamp:ts
allowOverwrite:NO
error:&err];
NSLog(@"imageBuffer %s", sent ? "sent!" : "not sent.");
if (err) {
NSLog(@"sendPixelBuffer error: %@", err);
}
}
@end

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mediapipe/examples/facial_search/ios/README.md Normal file
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python mediapipe/examples/facial_search/images/download_images.py
bazel build --copt=-fdiagnostics-color=always -c opt --config=ios_arm64 mediapipe/examples/facial_search/ios/FacialSearchGpuApp

66
mediapipe/examples/facial_search/ios/patch_ios_framework.sh Executable file
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#!/bin/bash
set -eu
set -o pipefail
# Adds modulemap & header files to an iOS Framework
# generated with bazel and encapsulating Mediapipe.
#
# This makes it so that the patched .framework can be imported into Xcode.
# For a long term solution track the following issue:
# https://github.com/bazelbuild/rules_apple/issues/355
[[ $# -lt 2 ]] && echo "Usage: $0 <path/to/zipped .framework> <hdrs>..." && exit 1
zipped=$(python -c "import os; print(os.path.realpath('$1'))"); shift
name=$(basename "$zipped" .zip)
parent=$(dirname "$zipped")
named="$parent"/"$name".framework
unzip "$zipped" -d "$parent"
mkdir "$named"/Modules
cat << EOF >"$named"/Modules/module.modulemap
framework module $name {
umbrella header "$name.h"
export *
module * { export * }
link framework "AVFoundation"
link framework "Accelerate"
link framework "AssetsLibrary"
link framework "CoreFoundation"
link framework "CoreGraphics"
link framework "CoreImage"
link framework "CoreMedia"
link framework "CoreVideo"
link framework "GLKit"
link framework "Metal"
link framework "MetalKit"
link framework "OpenGLES"
link framework "QuartzCore"
link framework "UIKit"
}
EOF
# NOTE: All these linked frameworks are required by mediapipe/objc.
cat << EOF >"$named"/Headers/$name.h
//
// $name.h
// $name
//
#import <Foundation/Foundation.h>
//! Project version number for $name.
FOUNDATION_EXPORT double ${name}VersionNumber;
//! Project version string for $name.
FOUNDATION_EXPORT const unsigned char ${name}VersionString[];
// In this header, you should import all the public headers of your framework using statements like #import <$name/PublicHeader.h>
EOF
until [[ $# -eq 0 ]]; do
printf '#import "'"$1"'"\n' "$1" >>"$named"/Headers/$name.h
shift
done

367
mediapipe/examples/facial_search/labels.h 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.
#ifndef MEDIAPIPE_EXAMPLES_FACIAL_SEARCH_LABELS_H_
#define MEDIAPIPE_EXAMPLES_FACIAL_SEARCH_LABELS_H_
#include <vector>
namespace mediapipe {
const std::vector<std::string>& MyCollectionLabels() {
static const std::vector<std::string> data = {
"00561d79ee42fbb0591b44f4ec0c23ff3fa12b2565494e560c1e75d6f6b91729.jpg",
"009ea4ff8ec125f771a8b768f4adbb3e04e6e6f4fce615c2485ed9b21fcaf654.jpg",
"026b4a607ed1fe3d670dc94cb1ffa641377940401dd44ab1fdbdf0321c878069.jpg",
"02b4cca3be4bc6c8b7c5e54192d8c3168f172fe36d71741df97505ec8808f0c3.jpg",
"0322a79e564d8967184c6977f97155a5dcbadb464475540fc458ab71564e2169.jpg",
"03c6f05c94b9368b12c2ae415993ed40b4c44067b6abedbe755010609e2097e1.jpg",
"05061c32b8e7fa7aa6c6629442d4a3c027e582a72a8dbf746f86e4cd23776283.jpg",
"05471555ce4b72102e129809747c340f3753e794d0cb9dfebb0688c77a351e7d.jpg",
"06a3a51573439ba504962bf65773920ed4e1005a173fe3a2b4a1376fc532bcf7.jpg",
"06f8a4b918d415bb8282c9fc04d4fe0601c961bfe8156e5932cbecfdd4e133a0.jpg",
"07d4d7db3de626ba98a8324f438d3d0a87ed786e9496ef6e94559ee1c26f96a8.jpg",
"07f91a87444d96669b285d6df9d7f18917b2d4555bc86c8649bd72ce2305f218.jpg",
"08dfb3a818e507a515c94d461ee0241fc7893078ddbab31e9cbf9e421bd0ac95.jpg",
"08f05a26b8e42358192e5b3093defc437fce11a52e9a70268e7777d8930ace6d.jpg",
"09c796ffc64a6357bdfd369e9be30904d177633e75c993433e94d268ac259f85.jpg",
"09d3a7e9c1bb9cf723800d00ec644e389479967553d89a45a93dfed22b06e91f.jpg",
"0aa87f73c449637a74b0514fa6759501a5d1e6d3382e7e070c3af6687857e99c.jpg",
"0baf7bc8ddb9608965fdc3d14f0397aa224c91366f5d77260c93e051bf41131d.jpg",
"0c32c4da3d6d0bc08f0d5527e587cd47bfd073cef623241a0b1c236f83b3a514.jpg",
"0d2269ab93e06f45f0433c60983561573dfdb4d8c87b1eb46d348d237dc5ce7b.jpg",
"0da23f7bdfe9be389410278c47695f730cf1dfde565799fea896887ac7ab5b9d.jpg",
"1162b1277809e382ed19d3d4586ed6adf5b80acb9cb65dd39b7ef3ce86148e22.jpg",
"1479529389293ea5df0a6efdce1debaa3c1d2a1f9ffcdbb211cc5f19459540b2.jpg",
"14b010b2f577e913d508d7916adc4ec3ed05dc2413462287f18ad66ee71f8e04.jpg",
"150512f54f5d32f50c8b500dbeaa7084b1048e207dd4f8a841db0a97c8603ceb.jpg",
"19066afc4533db4b8aa8b9d78bb032874e8dcb9fa08252853288aa62db2ee8d4.jpg",
"1a644408442b4e0e1b93aa84551fe59e2cc42d13c7f142772313b07e8e2700cf.jpg",
"1a77d8b9126d785ea0d6074d5826b6075039d8fb5ee31edb3ada140f48466521.jpg",
"1ba8f23f11fbb00311ca5de2c2f0a9093b0db3ac983d4bc527f34962101006cd.jpg",
"1bddffcc34516da32c757e2c69a9ae028d5061c7b83b65f91eb41e40ae061123.jpg",
"1c87452c2c6512e48bd8f5ffd279aefc9419c94a7e1f57c46097e29b05d60252.jpg",
"1e12afdae5eb968d6abbf2f0cdd3b266901fb16e0b4502b1a2dfd12b8e16246f.jpg",
"1fe4608f18937063128dbfec02f98e567a707cbc91642bb05b2cc207d4981d77.jpg",
"1feb71f85fa6273df5f731267970d2ce9e54717394eb40ff46ce9f06e9cec3c0.jpg",
"1fff9fd54d4fe4abdfb06b9e4de7beace20f11ebb908bdc5abdab37fea5992fd.jpg",
"20b6f62b55fa126b6845fc39c98019e85be8bad9efe933578053fb9528358e43.jpg",
"20cd3dc2870076159010279a8f29bd4365b3e3248ea30089abbb7eb5fb397b9b.jpg",
"226b4b62fa0922bce829a4f75cf6cec03a77f7132e8bcff06eadaf581b79eb6d.jpg",
"22cb27f0bbdd5f9c766fb66d9204bb7985b93fba48f57531ae4e55dfe6b82b55.jpg",
"2374636ea0833d7cea34b3f9ce69a3d2a05e874cd8f3e6a86159466db82dd43a.jpg",
"24a9012841870d44a857b26279a463f86b66f88b4d54b61552fe42ea4c3477ee.jpg",
"24f1dc74ef074a1272d46d522808d51f272692e52a8d235dd86c579a09e3916c.jpg",
"24f3b4cafaccb132a25784e6956a2faef28bf44bb15136bc0c7752c4021c51df.jpg",
"257dc45e450496cded7795bd652ad52ab1de7321161726948033893f12dcbf2b.jpg",
"25890b5a561e82fb7ebb2fda072754b0f290a2f23d58d55629a175091f4b7cc3.jpg",
"26fee6b9ca72421d66eb254c2a4ebd5aa4856dbb00179b151b2aee04784bf559.jpg",
"278474bdf15f453f7b092f2c218785b7ccb59100a4462ad61de950ee2c3503a2.jpg",
"27a021cfd40220fa7aa1356e529cbde485bb08d39c9d1882ec7fab28a0bfb63d.jpg",
"28806d3a94692a99b7a42f854b1ea1133038119da2d2286b0fda2c5a499e9445.jpg",
"28d168591cce45f9ded2b2eaf8c64caf183093236b4d31e6f9bb8202541a2597.jpg",
"2be5f741b6b5dc957019187bd748c5c8c5bdce35e31a984905c09eb6287f6596.jpg",
"2c7818483c23590849f88e6e0c7aa0586d8d0aea5d40792dbfa12594fbf70f99.jpg",
"2cbc5adcb79a84106d9f1ad873f7dfe4a9e696715694117409e776c821ec32aa.jpg",
"2ce04d4fea7b197c6e4c16e69a337949c365db1368655356a322ce4938343ec0.jpg",
"2d5328d281b08db6808e41a0e32c6c20d652f29f788a9615d2870c1b6267d8db.jpg",
"2ecdbec3d4156163a346f7adfc4f8fbb8ccbf2244ab1dc6a491e977bcdde03e0.jpg",
"2ef5f42377bef7958b4ae7795ed361fd536b202cb309ad8ebf6d6d4ee68ea84c.jpg",
"2f3a42256eed07d1bfceb03f49a8efece43187322ee48ba79bcbae33c071af5c.jpg",
"30794b874cb036cc92559a0668a40ba63e7cacd1afd5e402688640ba706e8223.jpg",
"3088348846fc9a01c05abc0eabc465130857cff41427a87d58d4bffc840e17a1.jpg",
"319ec3c098582e8f3099322ab36cff6384796f46d83f2aca1c99401ce04d6d76.jpg",
"320747d1b2461980657d0e5cbe50b2b27fae82aaf0bf1eee1a65f24c56603f83.jpg",
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};
return data;
}
} // namespace mediapipe
#endif // MEDIAPIPE_EXAMPLES_FACIAL_SEARCH_LABELS_H_

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