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Merge pull request #20925 from TolyaTalamanov:at/enable-2d-inputs-giebackend

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[G-API] Enable 2D inputs for GIEBackend

* Enable 2D inputs

* Fix typo
This commit is contained in:
Anatoliy Talamanov
2021-11-16 15:52:42 +03:00
committed by GitHub
parent b19697e3ac
commit c7df82460c
4 changed files with 133 additions and 21 deletions
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modules/gapi/src/backends/ie/giebackend.cpp
+39 -14
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@@ -127,7 +127,6 @@ inline int toCV(IE::Precision prec) {
inline IE::TensorDesc toIE(const cv::Mat &mat, cv::gapi::ie::TraitAs hint) {
const auto &sz = mat.size;
// NB: For some reason RGB image is 2D image
// (since channel component is not counted here).
// Note: regular 2D vectors also fall into this category
@@ -148,7 +147,6 @@ inline IE::TensorDesc toIE(const cv::Mat &mat, cv::gapi::ie::TraitAs hint) {
return IE::TensorDesc(toIE(mat.depth()),
IE::SizeVector{1, channels, height, width}, bdesc);
}
return IE::TensorDesc(toIE(mat.depth()), toIE(sz), toIELayout(sz.dims()));
}
@@ -241,7 +239,10 @@ struct IEUnit {
if (params.kind == cv::gapi::ie::detail::ParamDesc::Kind::Load) {
net = cv::gimpl::ie::wrap::readNetwork(params);
net.setBatchSize(params.batch_size);
// NB: Set batch size only if user asked. (don't set by default)
if (params.batch_size.has_value()) {
net.setBatchSize(params.batch_size.value());
}
} else if (params.kind == cv::gapi::ie::detail::ParamDesc::Kind::Import) {
this_plugin = cv::gimpl::ie::wrap::getPlugin(params);
this_network = cv::gimpl::ie::wrap::importNetwork(this_plugin, params, rctx);
@@ -520,7 +521,9 @@ inline IE::Blob::Ptr extractRemoteBlob(IECallContext& ctx, std::size_t i) {
blob_params->second);
}
inline IE::Blob::Ptr extractBlob(IECallContext& ctx, std::size_t i) {
inline IE::Blob::Ptr extractBlob(IECallContext& ctx,
std::size_t i,
cv::gapi::ie::TraitAs hint) {
if (ctx.uu.rctx != nullptr) {
return extractRemoteBlob(ctx, i);
}
@@ -532,7 +535,7 @@ inline IE::Blob::Ptr extractBlob(IECallContext& ctx, std::size_t i) {
return wrapIE(*(ctx.views.back()), frame.desc());
}
case cv::GShape::GMAT: {
return wrapIE(ctx.inMat(i), cv::gapi::ie::TraitAs::IMAGE);
return wrapIE(ctx.inMat(i), hint);
}
default:
GAPI_Assert("Unsupported input shape for IE backend");
@@ -545,6 +548,9 @@ static void setBlob(InferenceEngine::InferRequest& req,
const std::string& layer_name,
const IE::Blob::Ptr& blob,
const IECallContext& ctx) {
// TODO: Ideally we shouldn't do SetBlob() but GetBlob() instead,
// and redirect our data producers to this memory
// (A memory dialog comes to the picture again)
using namespace cv::gapi::ie::detail;
if (ctx.uu.params.kind == ParamDesc::Kind::Load) {
req.SetBlob(layer_name, blob);
@@ -950,7 +956,14 @@ struct Infer: public cv::detail::KernelTag {
uu.params.layer_names_to_reshape.end()) {
configureInputReshapeByImage(ii, mm, input_reshape_table);
}
ii->getPreProcess().setResizeAlgorithm(IE::RESIZE_BILINEAR);
// NB: Configure resize only for NCHW/NHWC layout,
// since it isn't supposed to work with others.
auto layout = ii->getTensorDesc().getLayout();
if (layout == IE::Layout::NCHW ||
layout == IE::Layout::NHWC) {
ii->getPreProcess().setResizeAlgorithm(IE::RESIZE_BILINEAR);
}
}
// FIXME: This isn't the best place to call reshape function.
@@ -1000,11 +1013,16 @@ struct Infer: public cv::detail::KernelTag {
// non-generic version for now:
// - assumes all inputs/outputs are always Mats
for (auto i : ade::util::iota(ctx->uu.params.num_in)) {
// TODO: Ideally we shouldn't do SetBlob() but GetBlob() instead,
// and redirect our data producers to this memory
// (A memory dialog comes to the picture again)
IE::Blob::Ptr this_blob = extractBlob(*ctx, i);
setBlob(req, ctx->uu.params.input_names[i], this_blob, *ctx);
const auto& layer_name = ctx->uu.params.input_names[i];
auto layout =
ctx->uu.this_network.GetInputsInfo().
at(layer_name)->getTensorDesc().getLayout();
auto hint =
(layout == IE::Layout::NCHW || layout == IE::Layout::NHWC)
? cv::gapi::ie::TraitAs::IMAGE : cv::gapi::ie::TraitAs::TENSOR;
IE::Blob::Ptr this_blob = extractBlob(*ctx, i, hint);
setBlob(req, layer_name, this_blob, *ctx);
}
// FIXME: Should it be done by kernel ?
// What about to do that in RequestPool ?
@@ -1092,7 +1110,10 @@ struct InferROI: public cv::detail::KernelTag {
GAPI_Assert(ctx->uu.params.num_in == 1);
auto&& this_roi = ctx->inArg<cv::detail::OpaqueRef>(0).rref<cv::Rect>();
IE::Blob::Ptr this_blob = extractBlob(*ctx, 1);
// NB: This blob will be used to make roi from its, so
// it should be treated as image
IE::Blob::Ptr this_blob =
extractBlob(*ctx, 1, cv::gapi::ie::TraitAs::IMAGE);
setBlob(req,
*(ctx->uu.params.input_names.begin()),
IE::make_shared_blob(this_blob, toIE(this_roi)),
@@ -1187,7 +1208,9 @@ struct InferList: public cv::detail::KernelTag {
return;
}
IE::Blob::Ptr this_blob = extractBlob(*ctx, 1);
// NB: This blob will be used to make roi from its, so
// it should be treated as image
IE::Blob::Ptr this_blob = extractBlob(*ctx, 1, cv::gapi::ie::TraitAs::IMAGE);
std::vector<std::vector<int>> cached_dims(ctx->uu.params.num_out);
for (auto i : ade::util::iota(ctx->uu.params.num_out)) {
@@ -1331,7 +1354,9 @@ struct InferList2: public cv::detail::KernelTag {
cv::gimpl::ie::RequestPool &reqPool) {
GAPI_Assert(ctx->inArgs().size() > 1u
&& "This operation must have at least two arguments");
IE::Blob::Ptr blob_0 = extractBlob(*ctx, 0);
// NB: This blob will be used to make roi from its, so
// it should be treated as image
IE::Blob::Ptr blob_0 = extractBlob(*ctx, 0, cv::gapi::ie::TraitAs::IMAGE);
const auto list_size = ctx->inArg<cv::detail::VectorRef>(1u).size();
if (list_size == 0u) {
for (auto i : ade::util::iota(ctx->uu.params.num_out)) {