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Merge pull request #21232 from sivanov-work:vpl_gpu_remote_infer

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G-API: oneVPL DX11 inference

* Draft GPU infer

* Fix incorrect subresource_id for array of textures

* Fix for TheOneSurface in different Frames

* Turn on VPP param configuration

* Add cropIn params

* Remove infer sync sample

* Remove comments

* Remove DX11AllocResource extra init

* Add condition for NV12 processing in giebackend

* Add VPP frames pool param configurable

* -M Remove extra WARN & INFOs, Fix custom MAC

* Remove global vars from example, Fix some comments, Disable blobParam due to OV issue

* Conflict resolving

* Revert back pointer cast for cv::any
This commit is contained in:
Sergey Ivanov
2022-01-24 17:05:26 +03:00
committed by GitHub
parent 574320ec3f
commit 266835cd2e
30 changed files with 1443 additions and 172 deletions
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modules/gapi/samples/onevpl_infer_single_roi.cpp
+69 -24
View File
@@ -45,10 +45,15 @@ const std::string keys =
"{ faced | AUTO | Target device for face detection model (e.g. AUTO, GPU, VPU, ...) }"
"{ cfg_params | <prop name>:<value>;<prop name>:<value> | Semicolon separated list of oneVPL mfxVariants which is used for configuring source (see `MFXSetConfigFilterProperty` by https://spec.oneapi.io/versions/latest/elements/oneVPL/source/index.html) }"
"{ streaming_queue_capacity | 1 | Streaming executor queue capacity. Calculated automaticaly if 0 }"
"{ frames_pool_size | 0 | OneVPL source applies this parameter as preallocated frames pool size}";
"{ frames_pool_size | 0 | OneVPL source applies this parameter as preallocated frames pool size}"
"{ vpp_frames_pool_size | 0 | OneVPL source applies this parameter as preallocated frames pool size for VPP preprocessing results}"
"{ source_preproc_enable | 0 | Turn on OneVPL source frame preprocessing using network input description instead of IE plugin preprocessing}";
namespace {
bool is_gpu(const std::string &device_name) {
return device_name.find("GPU") != std::string::npos;
}
std::string get_weights_path(const std::string &model_path) {
const auto EXT_LEN = 4u;
const auto sz = model_path.size();
@@ -123,8 +128,9 @@ using GRect = cv::GOpaque<cv::Rect>;
using GSize = cv::GOpaque<cv::Size>;
using GPrims = cv::GArray<cv::gapi::wip::draw::Prim>;
G_API_OP(LocateROI, <GRect(GSize)>, "sample.custom.locate-roi") {
static cv::GOpaqueDesc outMeta(const cv::GOpaqueDesc &) {
G_API_OP(LocateROI, <GRect(GSize, std::reference_wrapper<const std::string>)>, "sample.custom.locate-roi") {
static cv::GOpaqueDesc outMeta(const cv::GOpaqueDesc &,
std::reference_wrapper<const std::string>) {
return cv::empty_gopaque_desc();
}
};
@@ -145,18 +151,30 @@ GAPI_OCV_KERNEL(OCVLocateROI, LocateROI) {
// but only crops the input image to square (this is
// the most convenient aspect ratio for detectors to use)
static void run(const cv::Size& in_size, cv::Rect &out_rect) {
static void run(const cv::Size& in_size,
std::reference_wrapper<const std::string> device_id_ref,
cv::Rect &out_rect) {
// Identify the central point & square size (- some padding)
const auto center = cv::Point{in_size.width/2, in_size.height/2};
auto sqside = std::min(in_size.width, in_size.height);
// NB: GPU plugin in InferenceEngine doesn't support ROI at now
if (!is_gpu(device_id_ref.get())) {
const auto center = cv::Point{in_size.width/2, in_size.height/2};
auto sqside = std::min(in_size.width, in_size.height);
// Now build the central square ROI
out_rect = cv::Rect{ center.x - sqside/2
, center.y - sqside/2
, sqside
, sqside
};
// Now build the central square ROI
out_rect = cv::Rect{ center.x - sqside/2
, center.y - sqside/2
, sqside
, sqside
};
} else {
// use whole frame for GPU device
out_rect = cv::Rect{ 0
, 0
, in_size.width
, in_size.height
};
}
}
};
@@ -193,11 +211,14 @@ int main(int argc, char *argv[]) {
}
// get file name
std::string file_path = cmd.get<std::string>("input");
const std::string output = cmd.get<std::string>("output");
const auto file_path = cmd.get<std::string>("input");
const auto output = cmd.get<std::string>("output");
const auto face_model_path = cmd.get<std::string>("facem");
const auto streaming_queue_capacity = cmd.get<uint32_t>("streaming_queue_capacity");
const auto source_queue_capacity = cmd.get<uint32_t>("frames_pool_size");
const auto source_decode_queue_capacity = cmd.get<uint32_t>("frames_pool_size");
const auto source_vpp_queue_capacity = cmd.get<uint32_t>("vpp_frames_pool_size");
const auto vpl_source_preproc_enable = cmd.get<uint32_t>("source_preproc_enable");
const auto device_id = cmd.get<std::string>("faced");
// check ouput file extension
if (!output.empty()) {
@@ -214,6 +235,12 @@ int main(int argc, char *argv[]) {
try {
std::string line;
while (std::getline(params_list, line, ';')) {
if (vpl_source_preproc_enable == 0) {
if (line.find("vpp.") != std::string::npos) {
// skip VPP preprocessing primitives if not requested
continue;
}
}
source_cfgs.push_back(cfg::create_from_string(line));
}
} catch (const std::exception& ex) {
@@ -221,11 +248,13 @@ int main(int argc, char *argv[]) {
return -1;
}
if (source_queue_capacity != 0) {
source_cfgs.push_back(cv::gapi::wip::onevpl::CfgParam::create_frames_pool_size(source_queue_capacity));
if (source_decode_queue_capacity != 0) {
source_cfgs.push_back(cv::gapi::wip::onevpl::CfgParam::create_frames_pool_size(source_decode_queue_capacity));
}
if (source_vpp_queue_capacity != 0) {
source_cfgs.push_back(cv::gapi::wip::onevpl::CfgParam::create_vpp_frames_pool_size(source_vpp_queue_capacity));
}
const std::string& device_id = cmd.get<std::string>("faced");
auto face_net = cv::gapi::ie::Params<custom::FaceDetector> {
face_model_path, // path to topology IR
get_weights_path(face_model_path), // path to weights
@@ -247,7 +276,7 @@ int main(int argc, char *argv[]) {
auto dx11_dev = createCOMPtrGuard<ID3D11Device>();
auto dx11_ctx = createCOMPtrGuard<ID3D11DeviceContext>();
if (device_id.find("GPU") != std::string::npos) {
if (is_gpu(device_id)) {
auto adapter_factory = createCOMPtrGuard<IDXGIFactory>();
{
IDXGIFactory* out_factory = nullptr;
@@ -294,11 +323,25 @@ int main(int argc, char *argv[]) {
#endif // HAVE_D3D11
#endif // HAVE_DIRECTX
// set ctx_config for GPU device only - no need in case of CPU device type
if (device_id.find("GPU") != std::string::npos) {
if (is_gpu(device_id)) {
InferenceEngine::ParamMap ctx_config({{"CONTEXT_TYPE", "VA_SHARED"},
{"VA_DEVICE", accel_device_ptr} });
face_net.cfgContextParams(ctx_config);
face_net.pluginConfig({{"GPU_NV12_TWO_INPUTS", "YES" }});
std::cout <<"/*******************************************************/\n"
"ATTENTION: GPU Inference Engine preprocessing is not vital as expected!"
" Please consider param \"source_preproc_enable=1\" and specify "
" appropriated media frame transformation using oneVPL::VPP primitives"
" which force onevpl::GSource to produce tranformed media frames."
" For exploring list of supported transformations please find out "
" vpp_* related stuff in"
" gapi/include/opencv2/gapi/streaming/onevpl/cfg_params.hpp"
" Pay attention that to obtain expected result In this case VPP "
" transformation must match network input params."
" Please vote/create issue about exporting network params using GAPI\n"
"/******************************************************/" << std::endl;
}
#endif // HAVE_INF_ENGINE
@@ -314,7 +357,7 @@ int main(int argc, char *argv[]) {
// Create source
cv::Ptr<cv::gapi::wip::IStreamSource> cap;
try {
if (device_id.find("GPU") != std::string::npos) {
if (is_gpu(device_id)) {
cap = cv::gapi::wip::make_onevpl_src(file_path, source_cfgs,
device_id,
accel_device_ptr,
@@ -334,7 +377,7 @@ int main(int argc, char *argv[]) {
// Now build the graph
cv::GFrame in;
auto size = cv::gapi::streaming::size(in);
auto roi = custom::LocateROI::on(size);
auto roi = custom::LocateROI::on(size, std::cref(device_id));
auto blob = cv::gapi::infer<custom::FaceDetector>(roi, in);
cv::GArray<cv::Rect> rcs = cv::gapi::parseSSD(blob, size, 0.5f, true, true);
auto out_frame = cv::gapi::wip::draw::renderFrame(in, custom::BBoxes::on(rcs, roi));
@@ -397,6 +440,8 @@ typename cv::gapi::wip::onevpl::CfgParam create_from_string(const std::string &l
std::string name = line.substr(0, name_endline_pos);
std::string value = line.substr(name_endline_pos + 1);
return cv::gapi::wip::onevpl::CfgParam::create(name, value);
return cv::gapi::wip::onevpl::CfgParam::create(name, value,
/* vpp params strongly optional */
name.find("vpp.") == std::string::npos);
}
}