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Merge pull request #19425 from TolyaTalamanov:at/async-infer

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[G-API] Implement async infer

* Implement async infer

* Fix typo
This commit is contained in:
Anatoliy Talamanov
2021-02-12 15:28:37 +03:00
committed by GitHub
parent 767127c92e
commit ba8d20e9ae
3 changed files with 740 additions and 217 deletions
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modules/gapi/test/infer/gapi_infer_ie_test.cpp
+349
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@@ -15,6 +15,7 @@
#include <ade/util/iota_range.hpp>
#include <opencv2/gapi/infer/ie.hpp>
#include <opencv2/gapi/streaming/cap.hpp>
#include "backends/ie/util.hpp"
#include "backends/ie/giebackend/giewrapper.hpp"
@@ -22,6 +23,21 @@
namespace opencv_test
{
namespace {
void initTestDataPath()
{
#ifndef WINRT
static bool initialized = false;
if (!initialized)
{
// Since G-API has no own test data (yet), it is taken from the common space
const char* testDataPath = getenv("OPENCV_TEST_DATA_PATH");
if (testDataPath) {
cvtest::addDataSearchPath(testDataPath);
}
initialized = true;
}
#endif // WINRT
}
class TestMediaBGR final: public cv::MediaFrame::IAdapter {
cv::Mat m_mat;
@@ -937,6 +953,339 @@ TEST_F(ROIListNV12, Infer2MediaInputNV12)
validate();
}
TEST(Infer, TestStreamingInfer)
{
initTestDataPath();
initDLDTDataPath();
std::string filepath = findDataFile("cv/video/768x576.avi");
cv::gapi::ie::detail::ParamDesc params;
params.model_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.xml");
params.weights_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.bin");
params.device_id = "CPU";
// Load IE network, initialize input data using that.
cv::Mat in_mat;
cv::Mat gapi_age, gapi_gender;
using AGInfo = std::tuple<cv::GMat, cv::GMat>;
G_API_NET(AgeGender, <AGInfo(cv::GMat)>, "test-age-gender");
cv::GMat in;
cv::GMat age, gender;
std::tie(age, gender) = cv::gapi::infer<AgeGender>(in);
cv::GComputation comp(cv::GIn(in), cv::GOut(age, gender));
auto pp = cv::gapi::ie::Params<AgeGender> {
params.model_path, params.weights_path, params.device_id
}.cfgOutputLayers({ "age_conv3", "prob" });
std::size_t num_frames = 0u;
std::size_t max_frames = 10u;
cv::VideoCapture cap;
cap.open(filepath);
if (!cap.isOpened())
throw SkipTestException("Video file can not be opened");
cap >> in_mat;
auto pipeline = comp.compileStreaming(cv::compile_args(cv::gapi::networks(pp)));
pipeline.setSource<cv::gapi::wip::GCaptureSource>(filepath);
pipeline.start();
while (num_frames < max_frames && pipeline.pull(cv::gout(gapi_age, gapi_gender)))
{
IE::Blob::Ptr ie_age, ie_gender;
{
auto plugin = cv::gimpl::ie::wrap::getPlugin(params);
auto net = cv::gimpl::ie::wrap::readNetwork(params);
setNetParameters(net);
auto this_network = cv::gimpl::ie::wrap::loadNetwork(plugin, net, params);
auto infer_request = this_network.CreateInferRequest();
infer_request.SetBlob("data", cv::gapi::ie::util::to_ie(in_mat));
infer_request.Infer();
ie_age = infer_request.GetBlob("age_conv3");
ie_gender = infer_request.GetBlob("prob");
}
// Validate with IE itself (avoid DNN module dependency here)
normAssert(cv::gapi::ie::util::to_ocv(ie_age), gapi_age, "Test age output" );
normAssert(cv::gapi::ie::util::to_ocv(ie_gender), gapi_gender, "Test gender output");
++num_frames;
cap >> in_mat;
}
pipeline.stop();
}
TEST(InferROI, TestStreamingInfer)
{
initTestDataPath();
initDLDTDataPath();
std::string filepath = findDataFile("cv/video/768x576.avi");
cv::gapi::ie::detail::ParamDesc params;
params.model_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.xml");
params.weights_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.bin");
params.device_id = "CPU";
// Load IE network, initialize input data using that.
cv::Mat in_mat;
cv::Mat gapi_age, gapi_gender;
cv::Rect rect(cv::Point{64, 60}, cv::Size{96, 96});
using AGInfo = std::tuple<cv::GMat, cv::GMat>;
G_API_NET(AgeGender, <AGInfo(cv::GMat)>, "test-age-gender");
cv::GMat in;
cv::GOpaque<cv::Rect> roi;
cv::GMat age, gender;
std::tie(age, gender) = cv::gapi::infer<AgeGender>(roi, in);
cv::GComputation comp(cv::GIn(in, roi), cv::GOut(age, gender));
auto pp = cv::gapi::ie::Params<AgeGender> {
params.model_path, params.weights_path, params.device_id
}.cfgOutputLayers({ "age_conv3", "prob" });
std::size_t num_frames = 0u;
std::size_t max_frames = 10u;
cv::VideoCapture cap;
cap.open(filepath);
if (!cap.isOpened())
throw SkipTestException("Video file can not be opened");
cap >> in_mat;
auto pipeline = comp.compileStreaming(cv::compile_args(cv::gapi::networks(pp)));
pipeline.setSource(
cv::gin(cv::gapi::wip::make_src<cv::gapi::wip::GCaptureSource>(filepath), rect));
pipeline.start();
while (num_frames < max_frames && pipeline.pull(cv::gout(gapi_age, gapi_gender)))
{
// Load & run IE network
IE::Blob::Ptr ie_age, ie_gender;
{
auto plugin = cv::gimpl::ie::wrap::getPlugin(params);
auto net = cv::gimpl::ie::wrap::readNetwork(params);
setNetParameters(net);
auto this_network = cv::gimpl::ie::wrap::loadNetwork(plugin, net, params);
auto infer_request = this_network.CreateInferRequest();
const auto ie_rc = IE::ROI {
0u
, static_cast<std::size_t>(rect.x)
, static_cast<std::size_t>(rect.y)
, static_cast<std::size_t>(rect.width)
, static_cast<std::size_t>(rect.height)
};
IE::Blob::Ptr roi_blob = IE::make_shared_blob(cv::gapi::ie::util::to_ie(in_mat), ie_rc);
infer_request.SetBlob("data", roi_blob);
infer_request.Infer();
ie_age = infer_request.GetBlob("age_conv3");
ie_gender = infer_request.GetBlob("prob");
}
// Validate with IE itself (avoid DNN module dependency here)
normAssert(cv::gapi::ie::util::to_ocv(ie_age), gapi_age, "Test age output" );
normAssert(cv::gapi::ie::util::to_ocv(ie_gender), gapi_gender, "Test gender output");
++num_frames;
cap >> in_mat;
}
pipeline.stop();
}
TEST(InferList, TestStreamingInfer)
{
initTestDataPath();
initDLDTDataPath();
std::string filepath = findDataFile("cv/video/768x576.avi");
cv::gapi::ie::detail::ParamDesc params;
params.model_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.xml");
params.weights_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.bin");
params.device_id = "CPU";
// Load IE network, initialize input data using that.
cv::Mat in_mat;
std::vector<cv::Mat> ie_ages;
std::vector<cv::Mat> ie_genders;
std::vector<cv::Mat> gapi_ages;
std::vector<cv::Mat> gapi_genders;
std::vector<cv::Rect> roi_list = {
cv::Rect(cv::Point{64, 60}, cv::Size{ 96, 96}),
cv::Rect(cv::Point{50, 32}, cv::Size{128, 160}),
};
using AGInfo = std::tuple<cv::GMat, cv::GMat>;
G_API_NET(AgeGender, <AGInfo(cv::GMat)>, "test-age-gender");
cv::GMat in;
cv::GArray<cv::Rect> roi;
cv::GArray<GMat> age, gender;
std::tie(age, gender) = cv::gapi::infer<AgeGender>(roi, in);
cv::GComputation comp(cv::GIn(in, roi), cv::GOut(age, gender));
auto pp = cv::gapi::ie::Params<AgeGender> {
params.model_path, params.weights_path, params.device_id
}.cfgOutputLayers({ "age_conv3", "prob" });
std::size_t num_frames = 0u;
std::size_t max_frames = 10u;
cv::VideoCapture cap;
cap.open(filepath);
if (!cap.isOpened())
throw SkipTestException("Video file can not be opened");
cap >> in_mat;
auto pipeline = comp.compileStreaming(cv::compile_args(cv::gapi::networks(pp)));
pipeline.setSource(
cv::gin(cv::gapi::wip::make_src<cv::gapi::wip::GCaptureSource>(filepath), roi_list));
pipeline.start();
while (num_frames < max_frames && pipeline.pull(cv::gout(gapi_ages, gapi_genders)))
{
{
auto plugin = cv::gimpl::ie::wrap::getPlugin(params);
auto net = cv::gimpl::ie::wrap::readNetwork(params);
setNetParameters(net);
auto this_network = cv::gimpl::ie::wrap::loadNetwork(plugin, net, params);
auto infer_request = this_network.CreateInferRequest();
auto frame_blob = cv::gapi::ie::util::to_ie(in_mat);
for (auto &&rc : roi_list) {
const auto ie_rc = IE::ROI {
0u
, static_cast<std::size_t>(rc.x)
, static_cast<std::size_t>(rc.y)
, static_cast<std::size_t>(rc.width)
, static_cast<std::size_t>(rc.height)
};
infer_request.SetBlob("data", IE::make_shared_blob(frame_blob, ie_rc));
infer_request.Infer();
using namespace cv::gapi::ie::util;
ie_ages.push_back(to_ocv(infer_request.GetBlob("age_conv3")).clone());
ie_genders.push_back(to_ocv(infer_request.GetBlob("prob")).clone());
}
} // namespace IE = ..
// Validate with IE itself (avoid DNN module dependency here)
normAssert(ie_ages [0], gapi_ages [0], "0: Test age output");
normAssert(ie_genders[0], gapi_genders[0], "0: Test gender output");
normAssert(ie_ages [1], gapi_ages [1], "1: Test age output");
normAssert(ie_genders[1], gapi_genders[1], "1: Test gender output");
ie_ages.clear();
ie_genders.clear();
++num_frames;
cap >> in_mat;
}
pipeline.stop();
}
TEST(Infer2, TestStreamingInfer)
{
initTestDataPath();
initDLDTDataPath();
std::string filepath = findDataFile("cv/video/768x576.avi");
cv::gapi::ie::detail::ParamDesc params;
params.model_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.xml");
params.weights_path = findDataFile(SUBDIR + "age-gender-recognition-retail-0013.bin");
params.device_id = "CPU";
// Load IE network, initialize input data using that.
cv::Mat in_mat;
std::vector<cv::Mat> ie_ages;
std::vector<cv::Mat> ie_genders;
std::vector<cv::Mat> gapi_ages;
std::vector<cv::Mat> gapi_genders;
std::vector<cv::Rect> roi_list = {
cv::Rect(cv::Point{64, 60}, cv::Size{ 96, 96}),
cv::Rect(cv::Point{50, 32}, cv::Size{128, 160}),
};
using AGInfo = std::tuple<cv::GMat, cv::GMat>;
G_API_NET(AgeGender, <AGInfo(cv::GMat)>, "test-age-gender");
cv::GArray<cv::Rect> rr;
cv::GMat in;
cv::GArray<cv::GMat> age, gender;
std::tie(age, gender) = cv::gapi::infer2<AgeGender>(in, rr);
cv::GComputation comp(cv::GIn(in, rr), cv::GOut(age, gender));
auto pp = cv::gapi::ie::Params<AgeGender> {
params.model_path, params.weights_path, params.device_id
}.cfgOutputLayers({ "age_conv3", "prob" });
std::size_t num_frames = 0u;
std::size_t max_frames = 10u;
cv::VideoCapture cap;
cap.open(filepath);
if (!cap.isOpened())
throw SkipTestException("Video file can not be opened");
cap >> in_mat;
auto pipeline = comp.compileStreaming(cv::compile_args(cv::gapi::networks(pp)));
pipeline.setSource(
cv::gin(cv::gapi::wip::make_src<cv::gapi::wip::GCaptureSource>(filepath), roi_list));
pipeline.start();
while (num_frames < max_frames && pipeline.pull(cv::gout(gapi_ages, gapi_genders)))
{
{
auto plugin = cv::gimpl::ie::wrap::getPlugin(params);
auto net = cv::gimpl::ie::wrap::readNetwork(params);
setNetParameters(net);
auto this_network = cv::gimpl::ie::wrap::loadNetwork(plugin, net, params);
auto infer_request = this_network.CreateInferRequest();
auto frame_blob = cv::gapi::ie::util::to_ie(in_mat);
for (auto &&rc : roi_list) {
const auto ie_rc = IE::ROI {
0u
, static_cast<std::size_t>(rc.x)
, static_cast<std::size_t>(rc.y)
, static_cast<std::size_t>(rc.width)
, static_cast<std::size_t>(rc.height)
};
infer_request.SetBlob("data", IE::make_shared_blob(frame_blob, ie_rc));
infer_request.Infer();
using namespace cv::gapi::ie::util;
ie_ages.push_back(to_ocv(infer_request.GetBlob("age_conv3")).clone());
ie_genders.push_back(to_ocv(infer_request.GetBlob("prob")).clone());
}
} // namespace IE = ..
// Validate with IE itself (avoid DNN module dependency here)
normAssert(ie_ages [0], gapi_ages [0], "0: Test age output");
normAssert(ie_genders[0], gapi_genders[0], "0: Test gender output");
normAssert(ie_ages [1], gapi_ages [1], "1: Test age output");
normAssert(ie_genders[1], gapi_genders[1], "1: Test gender output");
ie_ages.clear();
ie_genders.clear();
++num_frames;
cap >> in_mat;
}
pipeline.stop();
}
} // namespace opencv_test
#endif // HAVE_INF_ENGINE