mirror/opencv
1
0
Fork 0
mirror of https://github.com/opencv/opencv.git synced 2025-06-12 04:12:52 +08:00
Code Issues Actions Packages Projects Releases Wiki Activity

Merge pull request #20856 from TolyaTalamanov:at/cfg-batch-size

Browse Source 
G-API: Extend ie::Params to specify batch size

* Add cfgBatchSize to ie::Params

* Fix comments to review
This commit is contained in:
Anatoliy Talamanov 2021-10-18 19:31:48 +03:00 committed by GitHub
parent 0cf79155d4
commit b5a9a6793b
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
6 changed files with 94 additions and 9 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

3
modules/gapi/include/opencv2/gapi/infer/bindings_ie.hpp
View File

@ -44,6 +44,9 @@ public:
GAPI_WRAP
PyParams& cfgNumRequests(size_t nireq);
GAPI_WRAP
PyParams& cfgBatchSize(const size_t size);
GBackend backend() const;
std::string tag() const;
cv::util::any params() const;

31
modules/gapi/include/opencv2/gapi/infer/ie.hpp
View File

@ -79,6 +79,8 @@ struct ParamDesc {
// NB: An optional config to setup RemoteContext for IE
cv::util::any context_config;
size_t batch_size;
};
} // namespace detail
@ -120,7 +122,8 @@ public:
, {}
, {}
, 1u
, {}} {
, {}
, 1u} {
};
/** @overload
@ -141,7 +144,8 @@ public:
, {}
, {}
, 1u
, {}} {
, {}
, 1u} {
};
/** @brief Specifies sequence of network input layers names for inference.
@ -316,6 +320,19 @@ public:
return *this;
}
/** @brief Specifies the inference batch size.
The function is used to specify inference batch size.
Follow https://docs.openvinotoolkit.org/latest/classInferenceEngine_1_1CNNNetwork.html#a8e9d19270a48aab50cb5b1c43eecb8e9 for additional information
@param size batch size which will be used.
@return reference to this parameter structure.
*/
Params<Net>& cfgBatchSize(const size_t size) {
desc.batch_size = size;
return *this;
}
// BEGIN(G-API's network parametrization API)
GBackend backend() const { return cv::gapi::ie::backend(); }
std::string tag() const { return Net::tag(); }
@ -350,7 +367,7 @@ public:
const std::string &device)
: desc{ model, weights, device, {}, {}, {}, 0u, 0u,
detail::ParamDesc::Kind::Load, true, {}, {}, {}, 1u,
{}},
{}, 1u},
m_tag(tag) {
};
@ -368,7 +385,7 @@ public:
const std::string &device)
: desc{ model, {}, device, {}, {}, {}, 0u, 0u,
detail::ParamDesc::Kind::Import, true, {}, {}, {}, 1u,
{}},
{}, 1u},
m_tag(tag) {
};
@ -435,6 +452,12 @@ public:
return *this;
}
/** @see ie::Params::cfgBatchSize */
Params& cfgBatchSize(const size_t size) {
desc.batch_size = size;
return *this;
}
// BEGIN(G-API's network parametrization API)
GBackend backend() const { return cv::gapi::ie::backend(); }
std::string tag() const { return m_tag; }

6
modules/gapi/src/backends/ie/bindings_ie.cpp
View File

@ -49,3 +49,9 @@ cv::gapi::ie::PyParams& cv::gapi::ie::PyParams::cfgNumRequests(size_t nireq) {
m_priv->cfgNumRequests(nireq);
return *this;
}
cv::gapi::ie::PyParams&
cv::gapi::ie::PyParams::cfgBatchSize(const size_t size) {
m_priv->cfgBatchSize(size);
return *this;
}

5
modules/gapi/src/backends/ie/giebackend.cpp
View File

@ -237,6 +237,7 @@ struct IEUnit {
if (params.kind == cv::gapi::ie::detail::ParamDesc::Kind::Load) {
net = cv::gimpl::ie::wrap::readNetwork(params);
net.setBatchSize(params.batch_size);
inputs = net.getInputsInfo();
outputs = net.getOutputsInfo();
} else if (params.kind == cv::gapi::ie::detail::ParamDesc::Kind::Import) {
@ -1412,11 +1413,11 @@ std::vector<int> cv::gapi::ie::util::to_ocv(const IE::SizeVector &dims) {
return toCV(dims);
}
IE::Blob::Ptr cv::gapi::ie::util::to_ie(cv::Mat &blob) {
IE::Blob::Ptr cv::gapi::ie::util::to_ie(const cv::Mat &blob) {
return wrapIE(blob, cv::gapi::ie::TraitAs::IMAGE);
}
IE::Blob::Ptr cv::gapi::ie::util::to_ie(cv::Mat &y_plane, cv::Mat &uv_plane) {
IE::Blob::Ptr cv::gapi::ie::util::to_ie(const cv::Mat &y_plane, const cv::Mat &uv_plane) {
auto y_blob = wrapIE(y_plane, cv::gapi::ie::TraitAs::IMAGE);
auto uv_blob = wrapIE(uv_plane, cv::gapi::ie::TraitAs::IMAGE);
#if INF_ENGINE_RELEASE >= 2021010000

4
modules/gapi/src/backends/ie/util.hpp
View File

@ -27,8 +27,8 @@ namespace util {
// test suite only.
GAPI_EXPORTS std::vector<int> to_ocv(const InferenceEngine::SizeVector &dims);
GAPI_EXPORTS cv::Mat to_ocv(InferenceEngine::Blob::Ptr blob);
GAPI_EXPORTS InferenceEngine::Blob::Ptr to_ie(cv::Mat &blob);
GAPI_EXPORTS InferenceEngine::Blob::Ptr to_ie(cv::Mat &y_plane, cv::Mat &uv_plane);
GAPI_EXPORTS InferenceEngine::Blob::Ptr to_ie(const cv::Mat &blob);
GAPI_EXPORTS InferenceEngine::Blob::Ptr to_ie(const cv::Mat &y_plane, const cv::Mat &uv_plane);
}}}}

54
modules/gapi/test/infer/gapi_infer_ie_test.cpp
View File

@ -2,7 +2,7 @@
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
//
// Copyright (C) 2019-2020 Intel Corporation
// Copyright (C) 2019-2021 Intel Corporation
#include "../test_precomp.hpp"
@ -2187,6 +2187,58 @@ TEST_F(LimitedSourceInfer, ReleaseFrameAsync)
run(max_frames, resources_limit, nireq);
}
TEST(TestAgeGenderIE, InferWithBatch)
{
initDLDTDataPath();
constexpr int batch_size = 4;
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";
cv::Mat in_mat({batch_size, 3, 320, 240}, CV_8U);
cv::randu(in_mat, 0, 255);
cv::Mat 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);
net.setBatchSize(batch_size);
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");
}
// Configure & run G-API
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" })
.cfgBatchSize(batch_size);
comp.apply(cv::gin(in_mat), cv::gout(gapi_age, gapi_gender),
cv::compile_args(cv::gapi::networks(pp)));
// 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");
}
} // namespace opencv_test
#endif // HAVE_INF_ENGINE