Merge pull request #15216 from dmatveev:dm/ng-0010-g-api-streaming-api

* G-API-NG/Streaming: Introduced a Streaming API

Now a GComputation can be compiled in a special "streaming" way
and then "played" on a video stream.

Currently only VideoCapture is supported as an input source.

* G-API-NG/Streaming: added threading & real streaming

* G-API-NG/Streaming: Added tests & docs on Copy kernel

- Added very simple pipeline tests, not all data types are covered yet
  (in fact, only GMat is tested now);
- Started testing non-OCV backends in the streaming mode;
- Added required fixes to Fluid backend, likely it works OK now;
- Added required fixes to OCL backend, and now it is likely broken
- Also added a UMat-based (OCL) version of Copy kernel

* G-API-NG/Streaming: Added own concurrent queue class

- Used only if TBB is not available

* G-API-NG/Streaming: Fixing various issues

- Added missing header to CMakeLists.txt
- Fixed various CI issues and warnings

* G-API-NG/Streaming: Fixed a compile-time GScalar queue deadlock

- GStreamingExecutor blindly created island's input queues for
  compile-time (value-initialized) GScalars which didn't have any
  producers, making island actor threads wait there forever

* G-API-NG/Streaming: Dropped own version of Copy kernel

One was added into master already

* G-API-NG/Streaming: Addressed GArray<T> review comments

- Added tests on mov()
- Removed unnecessary changes in garray.hpp

* G-API-NG/Streaming: Added Doxygen comments to new public APIs

Also fixed some other comments in the code

* G-API-NG/Streaming: Removed debug info, added some comments & renamed vars

* G-API-NG/Streaming: Fixed own-vs-cv abstraction leak

- Now every island is triggered with own:: (instead of cv::)
  data objects as inputs;
- Changes in Fluid backend required to support cv::Mat/Scalar were
  reverted;

* G-API-NG/Streaming: use holds_alternative<> instead of index/index_of test

- Also fixed regression test comments
- Also added metadata check comments for GStreamingCompiled

* G-API-NG/Streaming: Made start()/stop() more robust

- Fixed various possible deadlocks
- Unified the shutdown code
- Added more tests covering different corner cases on start/stop

* G-API-NG/Streaming: Finally fixed Windows crashes

In fact the problem hasn't been Windows-only.
Island thread popped data from queues without preserving the Cmd
objects and without taking the ownership over data acquired so when
islands started to process the data, this data may be already freed.

Linux version worked only by occasion.

* G-API-NG/Streaming: Fixed (I hope so) Windows warnings

* G-API-NG/Streaming: fixed typos in internal comments

- Also added some more explanation on Streaming/OpenCL status

* G-API-NG/Streaming: Added more unit tests on streaming

- Various start()/stop()/setSource() call flow combinations

* G-API-NG/Streaming: Added tests on own concurrent bounded queue

* G-API-NG/Streaming: Added more tests on various data types, + more

- Vector/Scalar passed as input;
- Vector/Scalar passed in-between islands;
- Some more assertions;
- Also fixed a deadlock problem when inputs are mixed (1 constant, 1 stream)

* G-API-NG/Streaming: Added tests on output data types handling

- Vector
- Scalar

* G-API-NG/Streaming: Fixed test issues with IE + Windows warnings

* G-API-NG/Streaming: Decoupled G-API from videoio

- Now the core G-API doesn't use a cv::VideoCapture directly,
  it comes in via an abstract interface;
- Polished a little bit the setSource()/start()/stop() semantics,
  now setSource() is mandatory before ANY call to start().

* G-API-NG/Streaming: Fix STANDALONE build (errors brought by render)
pull/15746/head
Dmitry Matveev 5 years ago committed by Alexander Alekhin
parent 2ff12c4981
commit 2477103707
  1. 11
      modules/gapi/CMakeLists.txt
  2. 3
      modules/gapi/cmake/standalone.cmake
  3. 9
      modules/gapi/include/opencv2/gapi/core.hpp
  4. 23
      modules/gapi/include/opencv2/gapi/garg.hpp
  5. 15
      modules/gapi/include/opencv2/gapi/garray.hpp
  6. 2
      modules/gapi/include/opencv2/gapi/gcompiled.hpp
  7. 81
      modules/gapi/include/opencv2/gapi/gcomputation.hpp
  8. 1
      modules/gapi/include/opencv2/gapi/gmat.hpp
  9. 231
      modules/gapi/include/opencv2/gapi/gstreaming.hpp
  10. 4
      modules/gapi/include/opencv2/gapi/gtype_traits.hpp
  11. 3
      modules/gapi/include/opencv2/gapi/ocl/goclkernel.hpp
  12. 2
      modules/gapi/include/opencv2/gapi/own/convert.hpp
  13. 79
      modules/gapi/include/opencv2/gapi/streaming/cap.hpp
  14. 57
      modules/gapi/include/opencv2/gapi/streaming/source.hpp
  15. 4
      modules/gapi/src/api/gbackend.cpp
  16. 6
      modules/gapi/src/api/gcomputation.cpp
  17. 1
      modules/gapi/src/api/gproto.cpp
  18. 2
      modules/gapi/src/backends/cpu/gcpucore.cpp
  19. 30
      modules/gapi/src/backends/fluid/gfluidbackend.cpp
  20. 2
      modules/gapi/src/backends/ocl/goclcore.cpp
  21. 31
      modules/gapi/src/compiler/gcompiler.cpp
  22. 6
      modules/gapi/src/compiler/gcompiler.hpp
  23. 16
      modules/gapi/src/compiler/gislandmodel.cpp
  24. 33
      modules/gapi/src/compiler/gislandmodel.hpp
  25. 20
      modules/gapi/src/compiler/gmodel.cpp
  26. 14
      modules/gapi/src/compiler/gmodel.hpp
  27. 11
      modules/gapi/src/compiler/gmodelbuilder.cpp
  28. 148
      modules/gapi/src/compiler/gstreaming.cpp
  29. 51
      modules/gapi/src/compiler/gstreaming_priv.hpp
  30. 24
      modules/gapi/src/compiler/passes/dump_dot.cpp
  31. 2
      modules/gapi/src/compiler/passes/passes.hpp
  32. 84
      modules/gapi/src/compiler/passes/streaming.cpp
  33. 129
      modules/gapi/src/executor/conc_queue.hpp
  34. 771
      modules/gapi/src/executor/gstreamingexecutor.cpp
  35. 132
      modules/gapi/src/executor/gstreamingexecutor.hpp
  36. 3
      modules/gapi/src/precomp.hpp
  37. 2
      modules/gapi/test/common/gapi_core_tests_inl.hpp
  38. 3
      modules/gapi/test/cpu/gapi_core_tests_cpu.cpp
  39. 2
      modules/gapi/test/cpu/gapi_core_tests_fluid.cpp
  40. 24
      modules/gapi/test/gapi_array_tests.cpp
  41. 2
      modules/gapi/test/gpu/gapi_core_tests_gpu.cpp
  42. 1
      modules/gapi/test/infer/gapi_infer_ie_test.cpp
  43. 197
      modules/gapi/test/own/conc_queue_tests.cpp
  44. 827
      modules/gapi/test/streaming/gapi_streaming_tests.cpp

@ -19,6 +19,7 @@ set(the_description "OpenCV G-API Core Module")
ocv_add_module(gapi opencv_imgproc)
file(GLOB gapi_ext_hdrs
"${CMAKE_CURRENT_LIST_DIR}/include/opencv2/*.hpp"
"${CMAKE_CURRENT_LIST_DIR}/include/opencv2/${name}/*.hpp"
@ -30,6 +31,7 @@ file(GLOB gapi_ext_hdrs
"${CMAKE_CURRENT_LIST_DIR}/include/opencv2/${name}/fluid/*.hpp"
"${CMAKE_CURRENT_LIST_DIR}/include/opencv2/${name}/own/*.hpp"
"${CMAKE_CURRENT_LIST_DIR}/include/opencv2/${name}/infer/*.hpp"
"${CMAKE_CURRENT_LIST_DIR}/include/opencv2/${name}/streaming/*.hpp"
)
set(gapi_srcs
@ -57,6 +59,7 @@ set(gapi_srcs
src/compiler/gislandmodel.cpp
src/compiler/gcompiler.cpp
src/compiler/gcompiled.cpp
src/compiler/gstreaming.cpp
src/compiler/passes/helpers.cpp
src/compiler/passes/dump_dot.cpp
src/compiler/passes/islands.cpp
@ -66,9 +69,11 @@ set(gapi_srcs
src/compiler/passes/transformations.cpp
src/compiler/passes/pattern_matching.cpp
src/compiler/passes/perform_substitution.cpp
src/compiler/passes/streaming.cpp
# Executor
src/executor/gexecutor.cpp
src/executor/gstreamingexecutor.cpp
src/executor/gasync.cpp
# CPU Backend (currently built-in)
@ -127,5 +132,11 @@ if(TARGET opencv_test_gapi)
target_link_libraries(opencv_test_gapi PRIVATE ade)
endif()
if(MSVC)
# Disable obsollete warning C4503 popping up on MSVC <<2017
# https://docs.microsoft.com/en-us/cpp/error-messages/compiler-warnings/compiler-warning-level-1-c4503?view=vs-2019
set_target_properties(${the_module} PROPERTIES COMPILE_FLAGS "/wd4503")
endif()
ocv_add_perf_tests()
ocv_add_samples()

@ -39,6 +39,9 @@ if(MSVC)
target_compile_options(${FLUID_TARGET} PUBLIC "/wd4251")
target_compile_options(${FLUID_TARGET} PUBLIC "/wd4275")
target_compile_definitions(${FLUID_TARGET} PRIVATE _CRT_SECURE_NO_DEPRECATE)
# Disable obsollete warning C4503 popping up on MSVC <<2017
# https://docs.microsoft.com/en-us/cpp/error-messages/compiler-warnings/compiler-warning-level-1-c4503?view=vs-2019
set_target_properties(${FLUID_TARGET} PROPERTIES COMPILE_FLAGS "/wd4503")
endif()
target_link_libraries(${FLUID_TARGET} PRIVATE ade)

@ -436,6 +436,7 @@ namespace core {
}
};
// TODO: eliminate the need in this kernel (streaming)
G_TYPED_KERNEL(GCrop, <GMat(GMat, Rect)>, "org.opencv.core.transform.crop") {
static GMatDesc outMeta(GMatDesc in, Rect rc) {
return in.withSize(Size(rc.width, rc.height));
@ -1505,11 +1506,11 @@ Output matrix must be of the same depth as input one, size is specified by given
*/
GAPI_EXPORTS GMat crop(const GMat& src, const Rect& rect);
/** @brief Copies a 2D matrix.
/** @brief Copies a matrix.
The function copies the matrix.
Output matrix must be of the same size and depth as input one.
Copies an input array. Works as a regular Mat::clone but happens in-graph.
Mainly is used to workaround some existing limitations (e.g. to forward an input frame to outputs
in the streaming mode). Will be deprecated and removed in the future.
@note Function textual ID is "org.opencv.core.transform.copy"

@ -23,6 +23,7 @@
#include <opencv2/gapi/gtype_traits.hpp>
#include <opencv2/gapi/gmetaarg.hpp>
#include <opencv2/gapi/own/scalar.hpp>
#include <opencv2/gapi/streaming/source.hpp>
namespace cv {
@ -92,12 +93,33 @@ using GRunArg = util::variant<
cv::Scalar,
cv::UMat,
#endif // !defined(GAPI_STANDALONE)
cv::gapi::wip::IStreamSource::Ptr,
cv::gapi::own::Mat,
cv::gapi::own::Scalar,
cv::detail::VectorRef
>;
using GRunArgs = std::vector<GRunArg>;
namespace gapi
{
namespace wip
{
/**
* @brief This aggregate type represents all types which G-API can handle (via variant).
*
* It only exists to overcome C++ language limitations (where a `using`-defined class can't be forward-declared).
*/
struct Data: public GRunArg
{
using GRunArg::GRunArg;
template <typename T>
Data& operator= (const T& t) { GRunArg::operator=(t); return *this; }
template <typename T>
Data& operator= (T&& t) { GRunArg::operator=(std::move(t)); return *this; }
};
} // namespace wip
} // namespace gapi
using GRunArgP = util::variant<
#if !defined(GAPI_STANDALONE)
cv::Mat*,
@ -110,7 +132,6 @@ using GRunArgP = util::variant<
>;
using GRunArgsP = std::vector<GRunArgP>;
template<typename... Ts> inline GRunArgs gin(const Ts&... args)
{
return GRunArgs{ GRunArg(detail::wrap_host_helper<Ts>::wrap_in(args))... };

@ -114,9 +114,11 @@ namespace detail
std::size_t m_elemSize = 0ul;
cv::GArrayDesc m_desc;
virtual ~BasicVectorRef() {}
virtual void mov(BasicVectorRef &ref) = 0;
};
template<typename T> class VectorRefT: public BasicVectorRef
template<typename T> class VectorRefT final: public BasicVectorRef
{
using empty_t = util::monostate;
using ro_ext_t = const std::vector<T> *;
@ -200,6 +202,12 @@ namespace detail
if (isRWOwn()) return util::get<rw_own_t>(m_ref);
util::throw_error(std::logic_error("Impossible happened"));
}
virtual void mov(BasicVectorRef &v) override {
VectorRefT<T> *tv = dynamic_cast<VectorRefT<T>*>(&v);
GAPI_Assert(tv != nullptr);
wref() = std::move(tv->wref());
}
};
// This class strips type information from VectorRefT<> and makes it usable
@ -245,6 +253,11 @@ namespace detail
return static_cast<VectorRefT<T>&>(*m_ref).rref();
}
void mov(VectorRef &v)
{
m_ref->mov(*v.m_ref);
}
cv::GArrayDesc descr_of() const
{
return m_ref->m_desc;

@ -60,6 +60,8 @@ namespace cv {
* At the same time, two different GCompiled objects produced from the
* single cv::GComputation are completely independent and can be used
* concurrently.
*
* @sa GStreamingCompiled
*/
class GAPI_EXPORTS GCompiled
{

@ -15,6 +15,7 @@
#include <opencv2/gapi/gproto.hpp>
#include <opencv2/gapi/garg.hpp>
#include <opencv2/gapi/gcompiled.hpp>
#include <opencv2/gapi/gstreaming.hpp>
namespace cv {
@ -394,6 +395,77 @@ public:
typename detail::MkSeq<sizeof...(Ts)-1>::type());
}
// FIXME: Document properly in the Doxygen format
// Video-oriented pipeline compilation:
// 1. A generic version
/**
* @brief Compile the computation for streaming mode.
*
* This method triggers compilation process and produces a new
* GStreamingCompiled object which then can process video stream
* data of the given format. Passing a stream in a different
* format to the compiled computation will generate a run-time
* exception.
*
* @param in_metas vector of input metadata configuration. Grab
* metadata from real data objects (like cv::Mat or cv::Scalar)
* using cv::descr_of(), or create it on your own. @param args
* compilation arguments for this compilation process. Compilation
* arguments directly affect what kind of executable object would
* be produced, e.g. which kernels (and thus, devices) would be
* used to execute computation.
*
* @return GStreamingCompiled, a streaming-oriented executable
* computation compiled specifically for the given input
* parameters.
*
* @sa @ref gapi_compile_args
*/
GStreamingCompiled compileStreaming(GMetaArgs &&in_metas, GCompileArgs &&args = {});
// 2. Direct metadata version
/**
* @overload
*
* Takes a variadic parameter pack with metadata
* descriptors for which a compiled object needs to be produced.
*
* @return GStreamingCompiled, a streaming-oriented executable
* computation compiled specifically for the given input
* parameters.
*/
template<typename... Ts>
auto compileStreaming(const Ts&... metas) ->
typename std::enable_if<detail::are_meta_descrs<Ts...>::value, GStreamingCompiled>::type
{
return compileStreaming(GMetaArgs{GMetaArg(metas)...}, GCompileArgs());
}
// 2. Direct metadata + compile arguments version
/**
* @overload
*
* Takes a variadic parameter pack with metadata
* descriptors for which a compiled object needs to be produced,
* followed by GCompileArgs object representing compilation
* arguments for this process.
*
* @return GStreamingCompiled, a streaming-oriented executable
* computation compiled specifically for the given input
* parameters.
*/
template<typename... Ts>
auto compileStreaming(const Ts&... meta_and_compile_args) ->
typename std::enable_if<detail::are_meta_descrs_but_last<Ts...>::value
&& std::is_same<GCompileArgs, detail::last_type_t<Ts...> >::value,
GStreamingCompiled>::type
{
//FIXME: wrapping meta_and_compile_args into a tuple to unwrap them inside a helper function is the overkill
return compileStreaming(std::make_tuple(meta_and_compile_args...),
typename detail::MkSeq<sizeof...(Ts)-1>::type());
}
// Internal use only
/// @private
Priv& priv();
@ -402,7 +474,7 @@ public:
protected:
// 4. Helper method for (3)
// 4. Helper methods for (3)
/// @private
template<typename... Ts, int... IIs>
GCompiled compile(const std::tuple<Ts...> &meta_and_compile_args, detail::Seq<IIs...>)
@ -411,6 +483,13 @@ protected:
GCompileArgs comp_args = std::get<sizeof...(Ts)-1>(meta_and_compile_args);
return compile(std::move(meta_args), std::move(comp_args));
}
template<typename... Ts, int... IIs>
GStreamingCompiled compileStreaming(const std::tuple<Ts...> &meta_and_compile_args, detail::Seq<IIs...>)
{
GMetaArgs meta_args = {GMetaArg(std::get<IIs>(meta_and_compile_args))...};
GCompileArgs comp_args = std::get<sizeof...(Ts)-1>(meta_and_compile_args);
return compileStreaming(std::move(meta_args), std::move(comp_args));
}
/// @private
std::shared_ptr<Priv> m_priv;
};

@ -211,6 +211,7 @@ GAPI_EXPORTS GMatDesc descr_of(const cv::UMat &mat);
/** @} */
// FIXME: WHY??? WHY it is under different namespace?
namespace gapi { namespace own {
GAPI_EXPORTS GMatDesc descr_of(const Mat &mat);
}}//gapi::own

@ -0,0 +1,231 @@
// This file is part of OpenCV project.
// 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) 2018 Intel Corporation
#ifndef OPENCV_GAPI_GSTREAMING_COMPILED_HPP
#define OPENCV_GAPI_GSTREAMING_COMPILED_HPP
#include <vector>
#include <opencv2/gapi/opencv_includes.hpp>
#include <opencv2/gapi/own/assert.hpp>
#include <opencv2/gapi/garg.hpp>
#include <opencv2/gapi/streaming/source.hpp>
namespace cv {
/**
* \addtogroup gapi_main_classes
* @{
*/
/**
* @brief Represents a computation (graph) compiled for streaming.
*
* This class represents a product of graph compilation (calling
* cv::GComputation::compileStreaming()). Objects of this class
* actually do stream processing, and the whole pipeline execution
* complexity is incapsulated into objects of this class. Execution
* model has two levels: at the very top, the execution of a
* heterogeneous graph is aggressively pipelined; at the very bottom
* the execution of every internal block is determined by its
* associated backend. Backends are selected based on kernel packages
* passed via compilation arguments ( see @ref gapi_compile_args,
* GNetworkPackage, GKernelPackage for details).
*
* GStreamingCompiled objects have a "player" semantics -- there are
* methods like start() and stop(). GStreamingCompiled has a full
* control over a videostream and so is stateful. You need to specify the
* input stream data using setSource() and then call start() to
* actually start processing. After that, use pull() or try_pull() to
* obtain next processed data frame from the graph in a blocking or
* non-blocking way, respectively.
*
* Currently a single GStreamingCompiled can process only one video
* streat at time. Produce multiple GStreamingCompiled objects to run the
* same graph on multiple video streams.
*
* @sa GCompiled
*/
class GAPI_EXPORTS GStreamingCompiled
{
public:
class GAPI_EXPORTS Priv;
GStreamingCompiled();
// FIXME: More overloads?
/**
* @brief Specify the input data to GStreamingCompiled for
* processing, a generic version.
*
* Use gin() to create an input parameter vector.
*
* Input vectors must have the same number of elements as defined
* in the cv::GComputation protocol (at the moment of its
* construction). Shapes of elements also must conform to protocol
* (e.g. cv::Mat needs to be passed where cv::GMat has been
* declared as input, and so on). Run-time exception is generated
* on type mismatch.
*
* In contrast with regular GCompiled, user can also pass an
* object of type GVideoCapture for a GMat parameter of the parent
* GComputation. The compiled pipeline will start fetching data
* from that GVideoCapture and feeding it into the
* pipeline. Pipeline stops when a GVideoCapture marks end of the
* stream (or when stop() is called).
*
* Passing a regular Mat for a GMat parameter makes it "infinite"
* source -- pipeline may run forever feeding with this Mat until
* stopped explicitly.
*
* Currently only a single GVideoCapture is supported as input. If
* the parent GComputation is declared with multiple input GMat's,
* one of those can be specified as GVideoCapture but all others
* must be regular Mat objects.
*
* Throws if pipeline is already running. Use stop() and then
* setSource() to run the graph on a new video stream.
*
* @note This method is not thread-safe (with respect to the user
* side) at the moment. Protect the access if
* start()/stop()/setSource() may be called on the same object in
* multiple threads in your application.
*
* @param ins vector of inputs to process.
* @sa gin
*/
void setSource(GRunArgs &&ins);
/**
* @brief Specify an input video stream for a single-input
* computation pipeline.
*
* Throws if pipeline is already running. Use stop() and then
* setSource() to run the graph on a new video stream.
*
* @overload
* @param s a shared pointer to IStreamSource representing the
* input video stream.
*/
void setSource(const gapi::wip::IStreamSource::Ptr& s);
/**
* @brief Start the pipeline execution.
*
* Use pull()/try_pull() to obtain data. Throws an exception if
* a video source was not specified.
*
* setSource() must be called first, even if the pipeline has been
* working already and then stopped (explicitly via stop() or due
* stream completion)
*
* @note This method is not thread-safe (with respect to the user
* side) at the moment. Protect the access if
* start()/stop()/setSource() may be called on the same object in
* multiple threads in your application.
*/
void start();
/**
* @brief Get the next processed frame from the pipeline.
*
* Use gout() to create an output parameter vector.
*
* Output vectors must have the same number of elements as defined
* in the cv::GComputation protocol (at the moment of its
* construction). Shapes of elements also must conform to protocol
* (e.g. cv::Mat needs to be passed where cv::GMat has been
* declared as output, and so on). Run-time exception is generated
* on type mismatch.
*
* This method writes new data into objects passed via output
* vector. If there is no data ready yet, this method blocks. Use
* try_pull() if you need a non-blocking version.
*
* @param outs vector of output parameters to obtain.
* @return true if next result has been obtained,
* false marks end of the stream.
*/
bool pull(cv::GRunArgsP &&outs);
/**
* @brief Try to get the next processed frame from the pipeline.
*
* Use gout() to create an output parameter vector.
*
* This method writes new data into objects passed via output
* vector. If there is no data ready yet, the output vector
* remains unchanged and false is returned.
*
* @return true if data has been obtained, and false if it was
* not. Note: false here doesn't mark the end of the stream.
*/
bool try_pull(cv::GRunArgsP &&outs);
/**
* @brief Stop (abort) processing the pipeline.
*
* Note - it is not pause but a complete stop. Calling start()
* will cause G-API to start processing the stream from the early beginning.
*
* Throws if the pipeline is not running.
*/
void stop();
/**
* @brief Test if the pipeline is running.
*
* @note This method is not thread-safe (with respect to the user
* side) at the moment. Protect the access if
* start()/stop()/setSource() may be called on the same object in
* multiple threads in your application.
*
* @return true if the current stream is not over yet.
*/
bool running() const;
/// @private
Priv& priv();
/**
* @brief Check if compiled object is valid (non-empty)
*
* @return true if the object is runnable (valid), false otherwise
*/
explicit operator bool () const;
/**
* @brief Vector of metadata this graph was compiled for.
*
* @return Unless _reshape_ is not supported, return value is the
* same vector which was passed to cv::GComputation::compile() to
* produce this compiled object. Otherwise, it is the latest
* metadata vector passed to reshape() (if that call was
* successful).
*/
const GMetaArgs& metas() const; // Meta passed to compile()
/**
* @brief Vector of metadata descriptions of graph outputs
*
* @return vector with formats/resolutions of graph's output
* objects, auto-inferred from input metadata vector by
* operations which form this computation.
*
* @note GCompiled objects produced from the same
* cv::GComputiation graph with different input metas may return
* different values in this vector.
*/
const GMetaArgs& outMetas() const;
protected:
/// @private
std::shared_ptr<Priv> m_priv;
};
/** @} */
}
#endif // OPENCV_GAPI_GSTREAMING_COMPILED_HPP

@ -14,6 +14,7 @@
#include <opencv2/gapi/gmat.hpp>
#include <opencv2/gapi/gscalar.hpp>
#include <opencv2/gapi/garray.hpp>
#include <opencv2/gapi/streaming/source.hpp>
#include <opencv2/gapi/gcommon.hpp>
#include <opencv2/gapi/own/convert.hpp>
@ -99,6 +100,9 @@ namespace detail
template<> struct GTypeOf<cv::gapi::own::Mat> { using type = cv::GMat; };
template<> struct GTypeOf<cv::gapi::own::Scalar> { using type = cv::GScalar; };
template<typename U> struct GTypeOf<std::vector<U> > { using type = cv::GArray<U>; };
// FIXME: This is not quite correct since IStreamSource may produce not only Mat but also Scalar
// and vector data. TODO: Extend the type dispatchig on these types too.
template<> struct GTypeOf<cv::gapi::wip::IStreamSource::Ptr> { using type = cv::GMat;};
template<class T> using g_type_of_t = typename GTypeOf<T>::type;
// Marshalling helper for G-types and its Host types. Helps G-API

@ -120,7 +120,8 @@ struct tracked_cv_umat{
//TODO Think if T - API could reallocate UMat to a proper size - how do we handle this ?
//tracked_cv_umat(cv::UMat& m) : r{(m)}, original_data{m.getMat(ACCESS_RW).data} {}
tracked_cv_umat(cv::UMat& m) : r{ (m) }, original_data{ nullptr } {}
cv::UMat r;
cv::UMat &r; // FIXME: It was a value (not a reference) before.
// Actually OCL backend should allocate its internal data!
uchar* original_data;
operator cv::UMat& (){ return r;}

@ -28,6 +28,7 @@ namespace cv
}
cv::gapi::own::Mat to_own(Mat&&) = delete;
inline cv::gapi::own::Mat to_own(Mat const& m) {
return (m.dims == 2)
? cv::gapi::own::Mat{m.rows, m.cols, m.type(), m.data, m.step}
@ -42,7 +43,6 @@ namespace cv
inline cv::gapi::own::Rect to_own (const Rect& r) { return {r.x, r.y, r.width, r.height}; };
namespace gapi
{
namespace own

@ -0,0 +1,79 @@
// This file is part of OpenCV project.
// 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 Intel Corporation
#ifndef OPENCV_GAPI_STREAMING_CAP_HPP
#define OPENCV_GAPI_STREAMING_CAP_HPP
/**
* YOUR ATTENTION PLEASE!
*
* This is a header-only implementation of cv::VideoCapture-based
* Stream source. It is not built by default with G-API as G-API
* doesn't depend on videoio module.
*
* If you want to use it in your application, please make sure
* videioio is available in your OpenCV package and is linked to your
* application.
*
* Note for developers: please don't put videoio dependency in G-API
* because of this file.
*/
#include <opencv2/videoio.hpp>
#include <opencv2/gapi/garg.hpp>
namespace cv {
namespace gapi {
namespace wip {
/**
* @brief OpenCV's VideoCapture-based streaming source.
*
* This class implements IStreamSource interface.
* Its constructor takes the same parameters as cv::VideoCapture does.
*
* Please make sure that videoio OpenCV module is avaiable before using
* this in your application (G-API doesn't depend on it directly).
*
* @note stream sources are passed to G-API via shared pointers, so
* please gapi::make_src<> to create objects and ptr() to pass a
* GCaptureSource to cv::gin().
*/
class GCaptureSource: public IStreamSource
{
public:
explicit GCaptureSource(int id) : cap(id) {}
explicit GCaptureSource(const std::string &path) : cap(path) {}
// TODO: Add more constructor overloads to make it
// fully compatible with VideoCapture's interface.
protected:
cv::VideoCapture cap;
virtual bool pull(cv::gapi::wip::Data &data) override
{
if (!cap.isOpened()) return false;
cv::Mat frame;
if (!cap.read(frame))
{
// end-of-stream happened
return false;
}
// NOTE: Some decode/media VideoCapture backends continue
// owning the video buffer under cv::Mat so in order to
// process it safely in a highly concurrent pipeline, clone()
// is the only right way.
data = frame.clone();
return true;
}
};
} // namespace wip
} // namespace gapi
} // namespace cv
#endif // OPENCV_GAPI_STREAMING_CAP_HPP

@ -0,0 +1,57 @@
// This file is part of OpenCV project.
// 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 Intel Corporation
#ifndef OPENCV_GAPI_STREAMING_SOURCE_HPP
#define OPENCV_GAPI_STREAMING_SOURCE_HPP
#include <memory> // shared_ptr
#include <type_traits> // is_base_of
namespace cv {
namespace gapi {
namespace wip {
struct Data; // "forward-declaration" of GRunArg
/**
* @brief Abstract streaming pipeline source.
*
* Implement this interface if you want customize the way how data is
* streaming into GStreamingCompiled.
*
* Objects implementing this interface can be passes to
* GStreamingCompiled via setSource()/cv::gin(). Regular compiled
* graphs (GCompiled) don't support input objects of this type.
*
* Default cv::VideoCapture-based implementation is available, see
* cv::gapi::GCaptureSource.
*
* @note stream sources are passed to G-API via shared pointers, so
* please use ptr() when passing a IStreamSource implementation to
* cv::gin().
*/
class IStreamSource: public std::enable_shared_from_this<IStreamSource>
{
public:
using Ptr = std::shared_ptr<IStreamSource>;
Ptr ptr() { return shared_from_this(); }
virtual bool pull(Data &data) = 0;
virtual ~IStreamSource() = default;
};
template<class T, class... Args>
IStreamSource::Ptr inline make_src(Args&&... args)
{
static_assert(std::is_base_of<IStreamSource, T>::value,
"T must implement the cv::gapi::IStreamSource interface!");
auto src_ptr = std::make_shared<T>(std::forward<Args>(args)...);
return src_ptr->ptr();
}
} // namespace wip
} // namespace gapi
} // namespace cv
#endif // OPENCV_GAPI_STREAMING_SOURCE_HPP

@ -118,7 +118,7 @@ void bindInArg(Mag& mag, const RcDesc &rc, const GRunArg &arg, bool is_umat)
if (is_umat)
{
auto& mag_umat = mag.template slot<cv::UMat>()[rc.id];
mag_umat = (util::get<cv::UMat>(arg));
mag_umat = util::get<cv::Mat>(arg).getUMat(ACCESS_READ);
}
else
{
@ -185,7 +185,7 @@ void bindOutArg(Mag& mag, const RcDesc &rc, const GRunArgP &arg, bool is_umat)
if (is_umat)
{
auto& mag_umat = mag.template slot<cv::UMat>()[rc.id];
mag_umat = (*util::get<cv::UMat*>(arg));
mag_umat = util::get<cv::Mat*>(arg)->getUMat(ACCESS_RW);
}
else
{

@ -76,6 +76,12 @@ cv::GCompiled cv::GComputation::compile(GMetaArgs &&metas, GCompileArgs &&args)
return comp.compile();
}
cv::GStreamingCompiled cv::GComputation::compileStreaming(GMetaArgs &&metas, GCompileArgs &&args)
{
cv::gimpl::GCompiler comp(*this, std::move(metas), std::move(args));
return comp.compileStreaming();
}
// FIXME: Introduce similar query/test method for GMetaArgs as a building block
// for functions like this?
static bool formats_are_same(const cv::GMetaArgs& metas1, const cv::GMetaArgs& metas2)

@ -169,6 +169,7 @@ bool cv::can_describe(const GMetaArg& meta, const GRunArg& arg)
util::get<GMatDesc>(meta).canDescribe(util::get<cv::gapi::own::Mat>(arg));
case GRunArg::index_of<cv::gapi::own::Scalar>(): return meta == cv::GMetaArg(descr_of(util::get<cv::gapi::own::Scalar>(arg)));
case GRunArg::index_of<cv::detail::VectorRef>(): return meta == cv::GMetaArg(util::get<cv::detail::VectorRef>(arg).descr_of());
case GRunArg::index_of<cv::gapi::wip::IStreamSource::Ptr>(): return util::holds_alternative<GMatDesc>(meta); // FIXME(?) may be not the best option
default: util::throw_error(std::logic_error("Unsupported GRunArg type"));
}
}

@ -505,7 +505,7 @@ GAPI_OCV_KERNEL(GCPUCopy, cv::gapi::core::GCopy)
{
static void run(const cv::Mat& in, cv::Mat& out)
{
cv::Mat(in).copyTo(out);
in.copyTo(out);
}
};

@ -1243,22 +1243,38 @@ void cv::gimpl::GFluidExecutable::bindInArg(const cv::gimpl::RcDesc &rc, const G
case GShape::GMAT: m_buffers[m_id_map.at(rc.id)].priv().bindTo(util::get<cv::gapi::own::Mat>(arg), true); break;
case GShape::GSCALAR: m_res.slot<cv::gapi::own::Scalar>()[rc.id] = util::get<cv::gapi::own::Scalar>(arg); break;
case GShape::GARRAY: m_res.slot<cv::detail::VectorRef>()[rc.id] = util::get<cv::detail::VectorRef>(arg); break;
default: util::throw_error(std::logic_error("Unsupported GShape type"));
}
}
void cv::gimpl::GFluidExecutable::bindOutArg(const cv::gimpl::RcDesc &rc, const GRunArgP &arg)
{
// Only GMat is supported as return type
using T = GRunArgP;
switch (rc.shape)
{
case GShape::GMAT:
{
cv::GMatDesc desc = m_buffers[m_id_map.at(rc.id)].meta();
auto &bref = m_buffers[m_id_map.at(rc.id)].priv();
switch (arg.index()) {
// FIXME: See the bindInArg comment on Streaming-related changes
case T::index_of<cv::gapi::own::Mat*>(): {
auto &outMat = *util::get<cv::gapi::own::Mat*>(arg);
GAPI_Assert(outMat.data != nullptr);
GAPI_Assert(descr_of(outMat) == desc && "Output argument was not preallocated as it should be ?");
m_buffers[m_id_map.at(rc.id)].priv().bindTo(outMat, false);
bref.bindTo(outMat, false);
} break;
#if !defined(GAPI_STANDALONE)
case T::index_of<cv::Mat*>(): {
auto &outMat = *util::get<cv::Mat*>(arg);
GAPI_Assert(outMat.data != nullptr);
GAPI_Assert(descr_of(outMat) == desc && "Output argument was not preallocated as it should be ?");
bref.bindTo(cv::to_own(outMat), false);
} break;
#endif // GAPI_STANDALONE
default: GAPI_Assert(false);
} // switch(arg.index())
break;
}
default: util::throw_error(std::logic_error("Unsupported return GShape type"));
@ -1446,6 +1462,13 @@ void GFluidBackendImpl::addBackendPasses(ade::ExecutionEngineSetupContext &ectx)
// regardless if it is one fluid island (both writing to and reading from this object)
// or two distinct islands (both fluid)
auto isFluidIsland = [&](const ade::NodeHandle& node) {
// With Streaming, Emitter islands may have no FusedIsland thing in meta.
// FIXME: Probably this is a concept misalignment
if (!gim.metadata(node).contains<FusedIsland>()) {
const auto kind = gim.metadata(node).get<NodeKind>().k;
GAPI_Assert(kind == NodeKind::EMIT || kind == NodeKind::SINK);
return false;
}
const auto isl = gim.metadata(node).get<FusedIsland>().object;
return isl->backend() == cv::gapi::fluid::backend();
};
@ -1456,6 +1479,9 @@ void GFluidBackendImpl::addBackendPasses(ade::ExecutionEngineSetupContext &ectx)
setFluidData(data_node, false);
}
} break; // case::SLOT
case NodeKind::EMIT:
case NodeKind::SINK:
break; // do nothing for Streaming nodes
default: GAPI_Assert(false);
} // switch
} // for (gim.nodes())

@ -486,7 +486,7 @@ GAPI_OCL_KERNEL(GOCLCopy, cv::gapi::core::GCopy)
{
static void run(const cv::UMat& in, cv::UMat& out)
{
cv::UMat(in).copyTo(out);
in.copyTo(out);
}
};

@ -28,21 +28,23 @@
#include "compiler/gmodelbuilder.hpp"
#include "compiler/gcompiler.hpp"
#include "compiler/gcompiled_priv.hpp"
#include "compiler/gstreaming_priv.hpp"
#include "compiler/passes/passes.hpp"
#include "compiler/passes/pattern_matching.hpp"
#include "executor/gexecutor.hpp"
#include "executor/gstreamingexecutor.hpp"
#include "backends/common/gbackend.hpp"
// <FIXME:>
#if !defined(GAPI_STANDALONE)
#include <opencv2/gapi/cpu/core.hpp> // Also directly refer to Core
#include <opencv2/gapi/cpu/imgproc.hpp> // ...and Imgproc kernel implementations
#include <opencv2/gapi/render/render.hpp> // render::ocv::backend()
#endif // !defined(GAPI_STANDALONE)
// </FIXME:>
#include <opencv2/gapi/gcompoundkernel.hpp> // compound::backend()
#include <opencv2/gapi/render/render.hpp> // render::ocv::backend()
#include "logger.hpp"
@ -272,6 +274,12 @@ cv::gimpl::GCompiler::GCompiler(const cv::GComputation &c,
m_e.addPass("exec", "fuse_islands", passes::fuseIslands);
m_e.addPass("exec", "sync_islands", passes::syncIslandTags);
// FIXME: Since a set of passes is shared between
// GCompiled/GStreamingCompiled, this pass is added here unconditionally
// (even if it is not actually required to produce a GCompiled).
// FIXME: add a better way to do that!
m_e.addPass("exec", "add_streaming", passes::addStreaming);
if (dump_path.has_value())
{
m_e.addPass("exec", "dump_dot", std::bind(passes::dumpGraph, _1,
@ -407,6 +415,17 @@ cv::GCompiled cv::gimpl::GCompiler::produceCompiled(GPtr &&pg)
return compiled;
}
cv::GStreamingCompiled cv::gimpl::GCompiler::produceStreamingCompiled(GPtr &&pg)
{
const auto &outMetas = GModel::ConstGraph(*pg).metadata()
.get<OutputMeta>().outMeta;
std::unique_ptr<GStreamingExecutor> pE(new GStreamingExecutor(std::move(pg)));
GStreamingCompiled compiled;
compiled.priv().setup(m_metas, outMetas, std::move(pE));
return compiled;
}
cv::GCompiled cv::gimpl::GCompiler::compile()
{
std::unique_ptr<ade::Graph> pG = generateGraph();
@ -414,3 +433,13 @@ cv::GCompiled cv::gimpl::GCompiler::compile()
compileIslands(*pG);
return produceCompiled(std::move(pG));
}
cv::GStreamingCompiled cv::gimpl::GCompiler::compileStreaming()
{
// FIXME: self-note to DM: now keep these compile()/compileStreaming() in sync!
std::unique_ptr<ade::Graph> pG = generateGraph();
GModel::Graph(*pG).metadata().set(Streaming{});
runPasses(*pG);
compileIslands(*pG);
return produceStreamingCompiled(std::move(pG));
}

@ -42,12 +42,16 @@ public:
// The method which does everything...
GCompiled compile();
// But is actually composed of this:
// This too.
GStreamingCompiled compileStreaming();
// But those are actually composed of this:
using GPtr = std::unique_ptr<ade::Graph>;
GPtr generateGraph(); // Unroll GComputation into a GModel
void runPasses(ade::Graph &g); // Apply all G-API passes on a GModel
void compileIslands(ade::Graph &g); // Instantiate GIslandExecutables in GIslandModel
GCompiled produceCompiled(GPtr &&pg); // Produce GCompiled from processed GModel
GStreamingCompiled produceStreamingCompiled(GPtr &&pg); // Produce GStreamingCompiled from processed GMbodel
};
}}

@ -215,6 +215,22 @@ ade::NodeHandle GIslandModel::mkIslandNode(Graph &g, std::shared_ptr<GIsland>&&
return nh;
}
ade::NodeHandle GIslandModel::mkEmitNode(Graph &g, std::size_t in_idx)
{
ade::NodeHandle nh = g.createNode();
g.metadata(nh).set(cv::gimpl::NodeKind{cv::gimpl::NodeKind::EMIT});
g.metadata(nh).set(cv::gimpl::Emitter{in_idx, {}});
return nh;
}
ade::NodeHandle GIslandModel::mkSinkNode(Graph &g, std::size_t out_idx)
{
ade::NodeHandle nh = g.createNode();
g.metadata(nh).set(cv::gimpl::NodeKind{cv::gimpl::NodeKind::SINK});
g.metadata(nh).set(cv::gimpl::Sink{out_idx});
return nh;
}
void GIslandModel::syncIslandTags(Graph &g, ade::Graph &orig_g)
{
GModel::Graph gm(orig_g);

@ -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) 2018 Intel Corporation
// Copyright (C) 2018-2019 Intel Corporation
#ifndef OPENCV_GAPI_GISLANDMODEL_HPP
@ -115,13 +115,21 @@ public:
virtual ~GIslandExecutable() = default;
};
// GIslandEmitter - a backend-specific thing which feeds data into
// the pipeline. This one is just an interface, implementations are executor-defined.
class GIslandEmitter
{
public:
// Obtain next value from the emitter
virtual bool pull(GRunArg &) = 0;
virtual ~GIslandEmitter() = default;
};
// Couldn't reuse NodeType here - FIXME unify (move meta to a shared place)
struct NodeKind
{
static const char *name() { return "NodeKind"; }
enum { ISLAND, SLOT} k;
enum { ISLAND, SLOT, EMIT, SINK} k;
};
// FIXME: Rename to Island (as soon as current GModel::Island is renamed
@ -144,6 +152,19 @@ struct IslandExec
std::shared_ptr<GIslandExecutable> object;
};
struct Emitter
{
static const char *name() { return "Emitter"; }
std::size_t proto_index;
std::shared_ptr<GIslandEmitter> object;
};
struct Sink
{
static const char *name() { return "Sink"; }
std::size_t proto_index;
};
namespace GIslandModel
{
using Graph = ade::TypedGraph
@ -151,6 +172,8 @@ namespace GIslandModel
, FusedIsland
, DataSlot
, IslandExec
, Emitter
, Sink
, ade::passes::TopologicalSortData
>;
@ -160,6 +183,8 @@ namespace GIslandModel
, FusedIsland
, DataSlot
, IslandExec
, Emitter
, Sink
, ade::passes::TopologicalSortData
>;
@ -169,6 +194,8 @@ namespace GIslandModel
ade::NodeHandle mkSlotNode(Graph &g, const ade::NodeHandle &data_nh);
ade::NodeHandle mkIslandNode(Graph &g, const gapi::GBackend &bknd, const ade::NodeHandle &op_nh, const ade::Graph &orig_g);
ade::NodeHandle mkIslandNode(Graph &g, std::shared_ptr<GIsland>&& isl);
ade::NodeHandle mkEmitNode(Graph &g, std::size_t in_idx); // streaming-related
ade::NodeHandle mkSinkNode(Graph &g, std::size_t out_idx); // streaming-related
// GIslandModel API
void syncIslandTags(Graph &g, ade::Graph &orig_g);

@ -50,21 +50,11 @@ ade::NodeHandle GModel::mkDataNode(GModel::Graph &g, const GOrigin& origin)
storage = Data::Storage::CONST_VAL;
g.metadata(data_h).set(ConstValue{value});
}
g.metadata(data_h).set(Data{origin.shape, id, meta, origin.ctor, storage});
return data_h;
}
ade::NodeHandle GModel::mkDataNode(GModel::Graph &g, const GShape shape)
{
ade::NodeHandle data_h = g.createNode();
g.metadata(data_h).set(NodeType{NodeType::DATA});
const auto id = g.metadata().get<DataObjectCounter>().GetNewId(shape);
GMetaArg meta;
HostCtor ctor;
Data::Storage storage = Data::Storage::INTERNAL; // By default, all objects are marked INTERNAL
g.metadata(data_h).set(Data{shape, id, meta, ctor, storage});
// FIXME: Sometimes a GArray-related node may be created w/o the
// associated host-type constructor (e.g. when the array is
// somewhere in the middle of the graph).
auto ctor_copy = origin.ctor;
g.metadata(data_h).set(Data{origin.shape, id, meta, ctor_copy, storage});
return data_h;
}

@ -145,6 +145,16 @@ struct ActiveBackends
std::unordered_set<cv::gapi::GBackend> backends;
};
// This is a graph-global flag indicating this graph is compiled for
// the streaming case. Streaming-neutral passes (i.e. nearly all of
// them) can ignore this flag safely.
//
// FIXME: Probably a better design can be suggested.
struct Streaming
{
static const char *name() { return "StreamingFlag"; }
};
// Backend-specific inference parameters for a neural network.
// Since these parameters are set on compilation stage (not
// on a construction stage), these parameters are bound lately
@ -190,6 +200,7 @@ namespace GModel
, IslandModel
, ActiveBackends
, CustomMetaFunction
, Streaming
>;
// FIXME: How to define it based on GModel???
@ -209,6 +220,7 @@ namespace GModel
, IslandModel
, ActiveBackends
, CustomMetaFunction
, Streaming
>;
// FIXME:
@ -220,8 +232,6 @@ namespace GModel
GAPI_EXPORTS ade::NodeHandle mkOpNode(Graph &g, const GKernel &k, const std::vector<GArg>& args, const std::string &island);
GAPI_EXPORTS ade::NodeHandle mkDataNode(Graph &g, const GShape shape);
// Adds a string message to a node. Any node can be subject of log, messages then
// appear in the dumped .dot file.x
GAPI_EXPORTS void log(Graph &g, ade::NodeHandle op, std::string &&message, ade::NodeHandle updater = ade::NodeHandle());

@ -303,5 +303,14 @@ ade::NodeHandle cv::gimpl::GModelBuilder::put_DataNode(const GOrigin &origin)
m_graph_data[origin] = nh;
return nh;
}
else return it->second;
else
{
// FIXME: One of the ugliest workarounds ever
if (it->first.ctor.index() == it->first.ctor.index_of<cv::util::monostate>()
&& origin.ctor.index() != origin.ctor.index_of<cv::util::monostate>()) {
// meanwhile update existing object
m_gm.metadata(it->second).get<Data>().ctor = origin.ctor;
}
return it->second;
}
}

@ -0,0 +1,148 @@
// This file is part of OpenCV project.
// 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 Intel Corporation
#include "precomp.hpp"
#if !defined(GAPI_STANDALONE)
#include <ade/graph.hpp>
#include <opencv2/gapi/gproto.hpp> // can_describe
#include <opencv2/gapi/gcompiled.hpp>
#include "compiler/gstreaming_priv.hpp"
#include "backends/common/gbackend.hpp"
// GStreamingCompiled private implementation ///////////////////////////////////
void cv::GStreamingCompiled::Priv::setup(const GMetaArgs &_metaArgs,
const GMetaArgs &_outMetas,
std::unique_ptr<cv::gimpl::GStreamingExecutor> &&_pE)
{
m_metas = _metaArgs;
m_outMetas = _outMetas;
m_exec = std::move(_pE);
}
bool cv::GStreamingCompiled::Priv::isEmpty() const
{
return !m_exec;
}
const cv::GMetaArgs& cv::GStreamingCompiled::Priv::metas() const
{
return m_metas;
}
const cv::GMetaArgs& cv::GStreamingCompiled::Priv::outMetas() const
{
return m_outMetas;
}
// FIXME: What is the reason in having Priv here if Priv actually dispatches
// everything to the underlying executable?? May be this executable may become
// the G*Compiled's priv?
void cv::GStreamingCompiled::Priv::setSource(cv::GRunArgs &&args)
{
// FIXME: This metadata checking should be removed at all
// for the streaming case.
if (!can_describe(m_metas, args))
{
util::throw_error(std::logic_error("This object was compiled "
"for different metadata!"));
}
GAPI_Assert(m_exec != nullptr);
m_exec->setSource(std::move(args));
}
void cv::GStreamingCompiled::Priv::start()
{
m_exec->start();
}
bool cv::GStreamingCompiled::Priv::pull(cv::GRunArgsP &&outs)
{
return m_exec->pull(std::move(outs));
}
bool cv::GStreamingCompiled::Priv::try_pull(cv::GRunArgsP &&outs)
{
return m_exec->try_pull(std::move(outs));
}
void cv::GStreamingCompiled::Priv::stop()
{
m_exec->stop();
}
bool cv::GStreamingCompiled::Priv::running() const
{
return m_exec->running();
}
// GStreamingCompiled public implementation ////////////////////////////////////
cv::GStreamingCompiled::GStreamingCompiled()
: m_priv(new Priv())
{
}
void cv::GStreamingCompiled::setSource(GRunArgs &&ins)
{
// FIXME: verify these input parameters according to the graph input meta
m_priv->setSource(std::move(ins));
}
void cv::GStreamingCompiled::setSource(const cv::gapi::wip::IStreamSource::Ptr &s)
{
setSource(cv::gin(s));
}
void cv::GStreamingCompiled::start()
{
m_priv->start();
}
bool cv::GStreamingCompiled::pull(cv::GRunArgsP &&outs)
{
return m_priv->pull(std::move(outs));
}
bool cv::GStreamingCompiled::try_pull(cv::GRunArgsP &&outs)
{
return m_priv->try_pull(std::move(outs));
}
void cv::GStreamingCompiled::stop()
{
m_priv->stop();
}
bool cv::GStreamingCompiled::running() const
{
return m_priv->running();
}
cv::GStreamingCompiled::operator bool() const
{
return !m_priv->isEmpty();
}
const cv::GMetaArgs& cv::GStreamingCompiled::metas() const
{
return m_priv->metas();
}
const cv::GMetaArgs& cv::GStreamingCompiled::outMetas() const
{
return m_priv->outMetas();
}
cv::GStreamingCompiled::Priv& cv::GStreamingCompiled::priv()
{
return *m_priv;
}
#endif // GAPI_STANDALONE

@ -0,0 +1,51 @@
// This file is part of OpenCV project.
// 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 Intel Corporation
#ifndef OPENCV_GAPI_GSTREAMING_COMPILED_PRIV_HPP
#define OPENCV_GAPI_GSTREAMING_COMPILED_PRIV_HPP
#include <memory> // unique_ptr
#include "executor/gstreamingexecutor.hpp"
namespace cv {
namespace gimpl
{
struct GRuntimeArgs;
};
// FIXME: GAPI_EXPORTS is here only due to tests and Windows linker issues
// FIXME: It seems it clearly duplicates the GStreamingCompiled and
// GStreamingExecutable APIs so is highly redundant now.
// Same applies to GCompiled/GCompiled::Priv/GExecutor.
class GAPI_EXPORTS GStreamingCompiled::Priv
{
GMetaArgs m_metas; // passed by user
GMetaArgs m_outMetas; // inferred by compiler
std::unique_ptr<cv::gimpl::GStreamingExecutor> m_exec;
public:
void setup(const GMetaArgs &metaArgs,
const GMetaArgs &outMetas,
std::unique_ptr<cv::gimpl::GStreamingExecutor> &&pE);
bool isEmpty() const;
const GMetaArgs& metas() const;
const GMetaArgs& outMetas() const;
void setSource(GRunArgs &&args);
void start();
bool pull(cv::GRunArgsP &&outs);
bool try_pull(cv::GRunArgsP &&outs);
void stop();
bool running() const;
};
} // namespace cv
#endif // OPENCV_GAPI_GSTREAMING_COMPILED_PRIV_HPP

@ -172,20 +172,40 @@ void dumpDot(const ade::Graph &g, std::ostream& os)
}
}
break;
case NodeKind::SLOT:
{
const auto obj_name = format_obj(gim.metadata(nh).get<DataSlot>()
.original_data_node);
for (auto cons_nh : nh->outNodes())
{
if (gim.metadata(cons_nh).get<NodeKind>().k == NodeKind::ISLAND) {
os << "\"slot:" << obj_name << "\" -> \""
<< gim.metadata(cons_nh).get<FusedIsland>().object->name()
<< "\"\n";
} // other data consumers -- sinks -- are processed separately
}
}
break;
case NodeKind::EMIT:
{
for (auto out_nh : nh->outNodes())
{
const auto obj_name = format_obj(gim.metadata(out_nh).get<DataSlot>()
.original_data_node);
os << "\"emit:" << nh << "\" -> \"slot:" << obj_name << "\"\n";
}
}
break;
case NodeKind::SINK:
{
for (auto in_nh : nh->inNodes())
{
const auto obj_name = format_obj(gim.metadata(in_nh).get<DataSlot>()
.original_data_node);
os << "\"slot:" << obj_name << "\" -> \"sink:" << nh << "\"\n";
}
}
break;
default:
GAPI_Assert(false);
break;

@ -63,6 +63,8 @@ void applyTransformations(ade::passes::PassContext &ctx,
const gapi::GKernelPackage &pkg,
const std::vector<std::unique_ptr<ade::Graph>> &preGeneratedPatterns);
void addStreaming(ade::passes::PassContext &ctx);
}} // namespace gimpl::passes
} // namespace cv

@ -0,0 +1,84 @@
// This file is part of OpenCV project.
// 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 Intel Corporation
#include "precomp.hpp"
#include <iostream> // cout
#include <sstream> // stringstream
#include <fstream> // ofstream
#include <map>
#include <ade/passes/check_cycles.hpp>
#include <ade/util/zip_range.hpp> // indexed()
#include <opencv2/gapi/gproto.hpp>
#include "compiler/gmodel.hpp"
#include "compiler/gislandmodel.hpp"
#include "compiler/passes/passes.hpp"
namespace cv { namespace gimpl { namespace passes {
/**
* This pass extends a GIslandModel with streaming-oriented
* information.
*
* Every input data object (according to the protocol) is connected to
* a new "Emitter" node which becomes its _consumer_.
*
* Every output data object (again, according to the protocol) is
* connected to a new "Sink" node which becomes its _consumer_.
*
* These extra nodes are required to streamline the queues
* initialization by the GStreamingExecutable and its derivatives.
*/
void addStreaming(ade::passes::PassContext &ctx)
{
GModel::Graph gm(ctx.graph);
if (!gm.metadata().contains<Streaming>()) {
return;
}
// Note: This pass is working on a GIslandModel.
// FIXME: May be introduce a new variant of GIslandModel to
// deal with streams?
auto igr = gm.metadata().get<IslandModel>().model;
GIslandModel::Graph igm(*igr);
// First collect all data slots & their respective original
// data objects
using M = std::unordered_map
< ade::NodeHandle // key: a GModel's data object node
, ade::NodeHandle // value: an appropriate GIslandModel's slot node
, ade::HandleHasher<ade::Node>
>;
M orig_to_isl;
for (auto &&nh : igm.nodes()) {
if (igm.metadata(nh).get<NodeKind>().k == NodeKind::SLOT) {
const auto &orig_nh = igm.metadata(nh).get<DataSlot>().original_data_node;
orig_to_isl[orig_nh] = nh;
}
}
// Now walk through the list of input slots and connect those
// to a Streaming source.
const auto proto = gm.metadata().get<Protocol>();
for (auto &&it : ade::util::indexed(proto.in_nhs)) {
const auto in_idx = ade::util::index(it);
const auto in_nh = ade::util::value(it);
auto emit_nh = GIslandModel::mkEmitNode(igm, in_idx);
igm.link(emit_nh, orig_to_isl.at(in_nh));
}
// Same for output slots
for (auto &&it : ade::util::indexed(proto.out_nhs)) {
const auto out_idx = ade::util::index(it);
const auto out_nh = ade::util::value(it);
auto sink_nh = GIslandModel::mkSinkNode(igm, out_idx);
igm.link(orig_to_isl.at(out_nh), sink_nh);
}
}
}}} // cv::gimpl::passes

@ -0,0 +1,129 @@
// This file is part of OpenCV project.
// 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 Intel Corporation
#ifndef OPENCV_GAPI_EXECUTOR_CONC_QUEUE_HPP
#define OPENCV_GAPI_EXECUTOR_CONC_QUEUE_HPP
#include <queue>
#include <mutex>
#include <condition_variable>
#include <opencv2/gapi/own/assert.hpp>
namespace cv {
namespace gapi {
namespace own {
// This class implements a bare minimum interface of TBB's
// concurrent_bounded_queue with only std:: stuff to make streaming
// API work without TBB.
//
// Highly inefficient, please use it as a last resort if TBB is not
// available in the build.
template<class T>
class concurrent_bounded_queue {
std::queue<T> m_data;
std::size_t m_capacity;
std::mutex m_mutex;
std::condition_variable m_cond_empty;
std::condition_variable m_cond_full;
void unsafe_pop(T &t);
public:
concurrent_bounded_queue() : m_capacity(0) {}
concurrent_bounded_queue(const concurrent_bounded_queue<T> &cc)
: m_data(cc.m_data), m_capacity(cc.m_capacity) {
// FIXME: what to do with all that locks, etc?
}
concurrent_bounded_queue(concurrent_bounded_queue<T> &&cc)
: m_data(std::move(cc.m_data)), m_capacity(cc.m_capacity) {
// FIXME: what to do with all that locks, etc?
}
// FIXME: && versions
void push(const T &t);
void pop(T &t);
bool try_pop(T &t);
void set_capacity(std::size_t capacity);
// Not thread-safe - as in TBB
void clear();
};
// Internal: do shared pop things assuming the lock is already there
template<typename T>
void concurrent_bounded_queue<T>::unsafe_pop(T &t) {
GAPI_Assert(!m_data.empty());
t = m_data.front();
m_data.pop();
}
// Push an element to the queue. Blocking if there's no space left
template<typename T>
void concurrent_bounded_queue<T>::push(const T& t) {
std::unique_lock<std::mutex> lock(m_mutex);
if (m_capacity && m_capacity == m_data.size()) {
// if there is a limit and it is reached, wait
m_cond_full.wait(lock, [&](){return m_capacity > m_data.size();});
GAPI_Assert(m_capacity > m_data.size());
}
m_data.push(t);
lock.unlock();
m_cond_empty.notify_one();
}
// Pop an element from the queue. Blocking if there's no items
template<typename T>
void concurrent_bounded_queue<T>::pop(T &t) {
std::unique_lock<std::mutex> lock(m_mutex);
if (m_data.empty()) {
// if there is no data, wait
m_cond_empty.wait(lock, [&](){return !m_data.empty();});
}
unsafe_pop(t);
lock.unlock();
m_cond_full.notify_one();
}
// Try pop an element from the queue. Returns false if queue is empty
template<typename T>
bool concurrent_bounded_queue<T>::try_pop(T &t) {
std::unique_lock<std::mutex> lock(m_mutex);
if (m_data.empty()) {
// if there is no data, return
return false;
}
unsafe_pop(t);
lock.unlock();
m_cond_full.notify_one();
return true;
}
// Specify the upper limit to the queue. Assumed to be called after
// queue construction but before any real use, any other case is UB
template<typename T>
void concurrent_bounded_queue<T>::set_capacity(std::size_t capacity) {
GAPI_Assert(m_data.empty());
GAPI_Assert(m_capacity == 0u);
GAPI_Assert(capacity != 0u);
m_capacity = capacity;
}
// Clear the queue. Similar to the TBB version, this method is not
// thread-safe.
template<typename T>
void concurrent_bounded_queue<T>::clear()
{
m_data = std::queue<T>{};
}
}}} // namespace cv::gapi::own
#endif // OPENCV_GAPI_EXECUTOR_CONC_QUEUE_HPP

@ -0,0 +1,771 @@
// This file is part of OpenCV project.
// 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 Intel Corporation
#include "precomp.hpp"
#include <iostream>
#include <ade/util/zip_range.hpp>
#include <opencv2/gapi/opencv_includes.hpp>
#include "executor/gstreamingexecutor.hpp"
#include "compiler/passes/passes.hpp"
#include "backends/common/gbackend.hpp" // createMat
namespace
{
using namespace cv::gimpl::stream;
#if !defined(GAPI_STANDALONE)
class VideoEmitter final: public cv::gimpl::GIslandEmitter {
cv::gapi::wip::IStreamSource::Ptr src;
virtual bool pull(cv::GRunArg &arg) override {
// FIXME: probably we can maintain a pool of (then) pre-allocated
// buffers to avoid runtime allocations.
// Pool size can be determined given the internal queue size.
cv::gapi::wip::Data newData;
if (!src->pull(newData)) {
return false;
}
arg = std::move(static_cast<cv::GRunArg&>(newData));
return true;
}
public:
explicit VideoEmitter(const cv::GRunArg &arg) {
src = cv::util::get<cv::gapi::wip::IStreamSource::Ptr>(arg);
}
};
#endif // GAPI_STANDALONE
class ConstEmitter final: public cv::gimpl::GIslandEmitter {
cv::GRunArg m_arg;
virtual bool pull(cv::GRunArg &arg) override {
arg = const_cast<const cv::GRunArg&>(m_arg); // FIXME: variant workaround
return true;
}
public:
explicit ConstEmitter(const cv::GRunArg &arg) : m_arg(arg) {
}
};
struct DataQueue {
static const char *name() { return "StreamingDataQueue"; }
explicit DataQueue(std::size_t capacity) {
if (capacity) {
q.set_capacity(capacity);
}
}
cv::gimpl::stream::Q q;
};
std::vector<cv::gimpl::stream::Q*> reader_queues( ade::Graph &g,
const ade::NodeHandle &obj)
{
ade::TypedGraph<DataQueue> qgr(g);
std::vector<cv::gimpl::stream::Q*> result;
for (auto &&out_eh : obj->outEdges())
{
result.push_back(&qgr.metadata(out_eh).get<DataQueue>().q);
}
return result;
}
std::vector<cv::gimpl::stream::Q*> input_queues( ade::Graph &g,
const ade::NodeHandle &obj)
{
ade::TypedGraph<DataQueue> qgr(g);
std::vector<cv::gimpl::stream::Q*> result;
for (auto &&in_eh : obj->inEdges())
{
result.push_back(qgr.metadata(in_eh).contains<DataQueue>()
? &qgr.metadata(in_eh).get<DataQueue>().q
: nullptr);
}
return result;
}
void sync_data(cv::GRunArgs &results, cv::GRunArgsP &outputs)
{
namespace own = cv::gapi::own;
for (auto && it : ade::util::zip(ade::util::toRange(outputs),
ade::util::toRange(results)))
{
auto &out_obj = std::get<0>(it);
auto &res_obj = std::get<1>(it);
// FIXME: this conversion should be unified
using T = cv::GRunArgP;
switch (out_obj.index())
{
#if !defined(GAPI_STANDALONE)
case T::index_of<cv::Mat*>():
*cv::util::get<cv::Mat*>(out_obj) = std::move(cv::util::get<cv::Mat>(res_obj));
break;
case T::index_of<cv::Scalar*>():
*cv::util::get<cv::Scalar*>(out_obj) = std::move(cv::util::get<cv::Scalar>(res_obj));
break;
#endif // !GAPI_STANDALONE
case T::index_of<own::Mat*>():
*cv::util::get<own::Mat*>(out_obj) = std::move(cv::util::get<own::Mat>(res_obj));
break;
case T::index_of<own::Scalar*>():
*cv::util::get<own::Scalar*>(out_obj) = std::move(cv::util::get<own::Scalar>(res_obj));
break;
case T::index_of<cv::detail::VectorRef>():
cv::util::get<cv::detail::VectorRef>(out_obj).mov(cv::util::get<cv::detail::VectorRef>(res_obj));
break;
default:
GAPI_Assert(false && "This value type is not supported!"); // ...maybe because of STANDALONE mode.
break;
}
}
}
// This thread is a plain dump source actor. What it do is just:
// - Check input queue (the only one) for a control command
// - Depending on the state, obtains next data object and pushes it to the
// pipeline.
void emitterActorThread(std::shared_ptr<cv::gimpl::GIslandEmitter> emitter,
Q& in_queue,
std::vector<Q*> out_queues,
std::function<void()> cb_completion)
{
// Wait for the explicit Start command.
// ...or Stop command, this also happens.
Cmd cmd;
in_queue.pop(cmd);
GAPI_Assert( cv::util::holds_alternative<Start>(cmd)
|| cv::util::holds_alternative<Stop>(cmd));
if (cv::util::holds_alternative<Stop>(cmd))
{
for (auto &&oq : out_queues) oq->push(cmd);
return;
}
// Now start emitting the data from the source to the pipeline.
while (true)
{
Cmd cancel;
if (in_queue.try_pop(cancel))
{
// if we just popped a cancellation command...
GAPI_Assert(cv::util::holds_alternative<Stop>(cancel));
// Broadcast it to the readers and quit.
for (auto &&oq : out_queues) oq->push(cancel);
return;
}
// Try to obrain next data chunk from the source
cv::GRunArg data;
if (emitter->pull(data))
{
// // On success, broadcast it to our readers
for (auto &&oq : out_queues)
{
// FIXME: FOR SOME REASON, oq->push(Cmd{data}) doesn't work!!
// empty mats are arrived to the receivers!
// There may be a fatal bug in our variant!
const auto tmp = data;
oq->push(Cmd{tmp});
}
}
else
{
// Otherwise, broadcast STOP message to our readers and quit.
// This usually means end-of-stream, so trigger a callback
for (auto &&oq : out_queues) oq->push(Cmd{Stop{}});
if (cb_completion) cb_completion();
return;
}
}
}
// This thread is a plain dumb processing actor. What it do is just:
// - Reads input from the input queue(s), sleeps if there's nothing to read
// - Once a full input vector is obtained, passes it to the underlying island
// executable for processing.
// - Pushes processing results down to consumers - to the subsequent queues.
// Note: Every data object consumer has its own queue.
void islandActorThread(std::vector<cv::gimpl::RcDesc> in_rcs, // FIXME: this is...
std::vector<cv::gimpl::RcDesc> out_rcs, // FIXME: ...basically just...
cv::GMetaArgs out_metas, // ...
std::shared_ptr<cv::gimpl::GIslandExecutable> island, // FIXME: ...a copy of OpDesc{}.
std::vector<Q*> in_queues,
std::vector<cv::GRunArg> in_constants,
std::vector< std::vector<Q*> > out_queues)
{
GAPI_Assert(in_queues.size() == in_rcs.size());
GAPI_Assert(out_queues.size() == out_rcs.size());
GAPI_Assert(out_queues.size() == out_metas.size());
while (true)
{
std::vector<cv::gimpl::GIslandExecutable::InObj> isl_inputs;
isl_inputs.resize(in_rcs.size());
// Try to obtain the full input vector.
// Note this may block us. We also may get Stop signal here
// and then exit the thread.
// NOTE: in order to maintain the GRunArg's underlying object
// lifetime, keep the whole cmd vector (of size == # of inputs)
// in memory.
std::vector<Cmd> cmd(in_queues.size());
for (auto &&it : ade::util::indexed(in_queues))
{
auto id = ade::util::index(it);
auto &q = ade::util::value(it);
isl_inputs[id].first = in_rcs[id];
if (q == nullptr)
{
// NULL queue means a graph-constant value
// (like a value-initialized scalar)
// FIXME: Variant move problem
isl_inputs[id].second = const_cast<const cv::GRunArg&>(in_constants[id]);
}
else
{
q->pop(cmd[id]);
if (cv::util::holds_alternative<Stop>(cmd[id]))
{
// FIXME: This logic must be unified with what collectorThread is doing!
// Just got a stop sign. Reiterate through all queues
// and rewind data to every Stop sign per queue
for (auto &&qit : ade::util::indexed(in_queues))
{
auto id2 = ade::util::index(qit);
auto &q2 = ade::util::value(qit);
if (id == id2) continue;
Cmd cmd2;
while (q2 && !cv::util::holds_alternative<Stop>(cmd2))
q2->pop(cmd2);
}
// Broadcast Stop down to the pipeline and quit
for (auto &&out_qq : out_queues)
{
for (auto &&out_q : out_qq) out_q->push(Cmd{Stop{}});
}
return;
}
// FIXME: MOVE PROBLEM
const cv::GRunArg &in_arg = cv::util::get<cv::GRunArg>(cmd[id]);
#if defined(GAPI_STANDALONE)
// Standalone mode - simply store input argument in the vector as-is
isl_inputs[id].second = in_arg;
#else
// Make Islands operate on own:: data types (i.e. in the same
// environment as GExecutor provides)
// This way several backends (e.g. Fluid) remain OpenCV-independent.
switch (in_arg.index()) {
case cv::GRunArg::index_of<cv::Mat>():
isl_inputs[id].second = cv::GRunArg{cv::to_own(cv::util::get<cv::Mat>(in_arg))};
break;
case cv::GRunArg::index_of<cv::Scalar>():
isl_inputs[id].second = cv::GRunArg{cv::to_own(cv::util::get<cv::Scalar>(in_arg))};
break;
default:
isl_inputs[id].second = in_arg;
break;
}
#endif // GAPI_STANDALONE
}
}
// Once the vector is obtained, prepare data for island execution
// Note - we first allocate output vector via GRunArg!
// Then it is converted to a GRunArgP.
std::vector<cv::gimpl::GIslandExecutable::OutObj> isl_outputs;
std::vector<cv::GRunArg> out_data;
isl_outputs.resize(out_rcs.size());
out_data.resize(out_rcs.size());
for (auto &&it : ade::util::indexed(out_rcs))
{
auto id = ade::util::index(it);
auto &r = ade::util::value(it);
#if !defined(GAPI_STANDALONE)
using MatType = cv::Mat;
using SclType = cv::Scalar;
#else
using MatType = cv::gapi::own::Mat;
using SclType = cv::gapi::own::Scalar;
#endif // GAPI_STANDALONE
switch (r.shape) {
// Allocate a data object based on its shape & meta, and put it into our vectors.
// Yes, first we put a cv::Mat GRunArg, and then specify _THAT_
// pointer as an output parameter - to make sure that after island completes,
// our GRunArg still has the right (up-to-date) value.
// Same applies to other types.
// FIXME: This is absolutely ugly but seem to work perfectly for its purpose.
case cv::GShape::GMAT:
{
MatType newMat;
cv::gimpl::createMat(cv::util::get<cv::GMatDesc>(out_metas[id]), newMat);
out_data[id] = cv::GRunArg(std::move(newMat));
isl_outputs[id] = { r, cv::GRunArgP(&cv::util::get<MatType>(out_data[id])) };
}
break;
case cv::GShape::GSCALAR:
{
SclType newScl;
out_data[id] = cv::GRunArg(std::move(newScl));
isl_outputs[id] = { r, cv::GRunArgP(&cv::util::get<SclType>(out_data[id])) };
}
break;
case cv::GShape::GARRAY:
{
cv::detail::VectorRef newVec;
cv::util::get<cv::detail::ConstructVec>(r.ctor)(newVec);
out_data[id] = cv::GRunArg(std::move(newVec));
// VectorRef is implicitly shared so no pointer is taken here
const auto &rr = cv::util::get<cv::detail::VectorRef>(out_data[id]); // FIXME: that variant MOVE problem again
isl_outputs[id] = { r, cv::GRunArgP(rr) };
}
break;
default:
cv::util::throw_error(std::logic_error("Unsupported GShape"));
break;
}
}
// Now ask Island to execute on this data
island->run(std::move(isl_inputs), std::move(isl_outputs));
// Once executed, dispatch our results down to the pipeline.
for (auto &&it : ade::util::zip(ade::util::toRange(out_queues),
ade::util::toRange(out_data)))
{
for (auto &&q : std::get<0>(it))
{
// FIXME: FATAL VARIANT ISSUE!!
const auto tmp = std::get<1>(it);
q->push(Cmd{tmp});
}
}
}
}
// The idea of collectorThread is easy. If there're multiple outputs
// in the graph, we need to pull an object from every associated queue
// and then put the resulting vector into one single queue. While it
// looks redundant, it simplifies dramatically the way how try_pull()
// is implemented - we need to check one queue instead of many.
void collectorThread(std::vector<Q*> in_queues,
Q& out_queue)
{
while (true)
{
cv::GRunArgs this_result(in_queues.size());
for (auto &&it : ade::util::indexed(in_queues))
{
Cmd cmd;
ade::util::value(it)->pop(cmd);
if (cv::util::holds_alternative<Stop>(cmd))
{
// FIXME: Unify this code with island thread
for (auto &&qit : ade::util::indexed(in_queues))
{
if (ade::util::index(qit) == ade::util::index(it)) continue;
Cmd cmd2;
while (!cv::util::holds_alternative<Stop>(cmd2))
ade::util::value(qit)->pop(cmd2);
}
out_queue.push(Cmd{Stop{}});
return;
}
else
{
// FIXME: MOVE_PROBLEM
const cv::GRunArg &in_arg = cv::util::get<cv::GRunArg>(cmd);
this_result[ade::util::index(it)] = in_arg;
// FIXME: Check for other message types.
}
}
out_queue.push(Cmd{this_result});
}
}
} // anonymous namespace
cv::gimpl::GStreamingExecutor::GStreamingExecutor(std::unique_ptr<ade::Graph> &&g_model)
: m_orig_graph(std::move(g_model))
, m_island_graph(GModel::Graph(*m_orig_graph).metadata()
.get<IslandModel>().model)
, m_gim(*m_island_graph)
{
GModel::Graph gm(*m_orig_graph);
// NB: Right now GIslandModel is acyclic, and all the below code assumes that.
// NB: This naive execution code is taken from GExecutor nearly "as-is"
const auto proto = gm.metadata().get<Protocol>();
m_emitters .resize(proto.in_nhs.size());
m_emitter_queues.resize(proto.in_nhs.size());
m_sinks .resize(proto.out_nhs.size());
m_sink_queues .resize(proto.out_nhs.size());
// Very rough estimation to limit internal queue sizes.
// Pipeline depth is equal to number of its (pipeline) steps.
const auto queue_capacity = std::count_if
(m_gim.nodes().begin(),
m_gim.nodes().end(),
[&](ade::NodeHandle nh) {
return m_gim.metadata(nh).get<NodeKind>().k == NodeKind::ISLAND;
});
auto sorted = m_gim.metadata().get<ade::passes::TopologicalSortData>();
for (auto nh : sorted.nodes())
{
switch (m_gim.metadata(nh).get<NodeKind>().k)
{
case NodeKind::ISLAND:
{
std::vector<RcDesc> input_rcs;
std::vector<RcDesc> output_rcs;
std::vector<GRunArg> in_constants;
cv::GMetaArgs output_metas;
input_rcs.reserve(nh->inNodes().size());
in_constants.reserve(nh->inNodes().size()); // FIXME: Ugly
output_rcs.reserve(nh->outNodes().size());
output_metas.reserve(nh->outNodes().size());
std::unordered_set<ade::NodeHandle, ade::HandleHasher<ade::Node> > const_ins;
// FIXME: THIS ORDER IS IRRELEVANT TO PROTOCOL OR ANY OTHER ORDER!
// FIXME: SAME APPLIES TO THE REGULAR GEEXECUTOR!!
auto xtract_in = [&](ade::NodeHandle slot_nh, std::vector<RcDesc> &vec) {
const auto orig_data_nh
= m_gim.metadata(slot_nh).get<DataSlot>().original_data_node;
const auto &orig_data_info
= gm.metadata(orig_data_nh).get<Data>();
if (orig_data_info.storage == Data::Storage::CONST_VAL) {
const_ins.insert(slot_nh);
// FIXME: Variant move issue
in_constants.push_back(const_cast<const cv::GRunArg&>(gm.metadata(orig_data_nh).get<ConstValue>().arg));
} else in_constants.push_back(cv::GRunArg{}); // FIXME: Make it in some smarter way pls
if (orig_data_info.shape == GShape::GARRAY) {
// FIXME: GArray lost host constructor problem
GAPI_Assert(!cv::util::holds_alternative<cv::util::monostate>(orig_data_info.ctor));
}
vec.emplace_back(RcDesc{ orig_data_info.rc
, orig_data_info.shape
, orig_data_info.ctor});
};
auto xtract_out = [&](ade::NodeHandle slot_nh, std::vector<RcDesc> &vec, cv::GMetaArgs &metas) {
const auto orig_data_nh
= m_gim.metadata(slot_nh).get<DataSlot>().original_data_node;
const auto &orig_data_info
= gm.metadata(orig_data_nh).get<Data>();
if (orig_data_info.shape == GShape::GARRAY) {
// FIXME: GArray lost host constructor problem
GAPI_Assert(!cv::util::holds_alternative<cv::util::monostate>(orig_data_info.ctor));
}
vec.emplace_back(RcDesc{ orig_data_info.rc
, orig_data_info.shape
, orig_data_info.ctor});
metas.emplace_back(orig_data_info.meta);
};
// FIXME: JEZ IT WAS SO AWFUL!!!!
for (auto in_slot_nh : nh->inNodes()) xtract_in(in_slot_nh, input_rcs);
for (auto out_slot_nh : nh->outNodes()) xtract_out(out_slot_nh, output_rcs, output_metas);
m_ops.emplace_back(OpDesc{ std::move(input_rcs)
, std::move(output_rcs)
, std::move(output_metas)
, nh
, in_constants
, m_gim.metadata(nh).get<IslandExec>().object});
// Initialize queues for every operation's input
ade::TypedGraph<DataQueue> qgr(*m_island_graph);
for (auto eh : nh->inEdges())
{
// ...only if the data is not compile-const
if (const_ins.count(eh->srcNode()) == 0) {
qgr.metadata(eh).set(DataQueue(queue_capacity));
m_internal_queues.insert(&qgr.metadata(eh).get<DataQueue>().q);
}
}
}
break;
case NodeKind::SLOT:
{
const auto orig_data_nh
= m_gim.metadata(nh).get<DataSlot>().original_data_node;
m_slots.emplace_back(DataDesc{nh, orig_data_nh});
}
break;
case NodeKind::EMIT:
{
const auto emitter_idx
= m_gim.metadata(nh).get<Emitter>().proto_index;
GAPI_Assert(emitter_idx < m_emitters.size());
m_emitters[emitter_idx] = nh;
}
break;
case NodeKind::SINK:
{
const auto sink_idx
= m_gim.metadata(nh).get<Sink>().proto_index;
GAPI_Assert(sink_idx < m_sinks.size());
m_sinks[sink_idx] = nh;
// Also initialize Sink's input queue
ade::TypedGraph<DataQueue> qgr(*m_island_graph);
GAPI_Assert(nh->inEdges().size() == 1u);
qgr.metadata(nh->inEdges().front()).set(DataQueue(queue_capacity));
m_sink_queues[sink_idx] = &qgr.metadata(nh->inEdges().front()).get<DataQueue>().q;
}
break;
default:
GAPI_Assert(false);
break;
} // switch(kind)
} // for(gim nodes)
m_out_queue.set_capacity(queue_capacity);
}
cv::gimpl::GStreamingExecutor::~GStreamingExecutor()
{
if (state == State::READY || state == State::RUNNING)
stop();
}
void cv::gimpl::GStreamingExecutor::setSource(GRunArgs &&ins)
{
GAPI_Assert(state == State::READY || state == State::STOPPED);
const auto is_video = [](const GRunArg &arg) {
return util::holds_alternative<cv::gapi::wip::IStreamSource::Ptr>(arg);
};
const auto num_videos = std::count_if(ins.begin(), ins.end(), is_video);
if (num_videos > 1u)
{
// See below why (another reason - no documented behavior
// on handling videos streams of different length)
util::throw_error(std::logic_error("Only one video source is"
" currently supported!"));
}
// Walk through the protocol, set-up emitters appropriately
// There's a 1:1 mapping between emitters and corresponding data inputs.
for (auto it : ade::util::zip(ade::util::toRange(m_emitters),
ade::util::toRange(ins),
ade::util::iota(m_emitters.size())))
{
auto emit_nh = std::get<0>(it);
auto& emit_arg = std::get<1>(it);
auto emit_idx = std::get<2>(it);
auto& emitter = m_gim.metadata(emit_nh).get<Emitter>().object;
using T = GRunArg;
switch (emit_arg.index())
{
// Create a streaming emitter.
// Produces the next video frame when pulled.
case T::index_of<cv::gapi::wip::IStreamSource::Ptr>():
#if !defined(GAPI_STANDALONE)
emitter.reset(new VideoEmitter{emit_arg});
#else
util::throw_error(std::logic_error("Video is not supported in the "
"standalone mode"));
#endif
break;
default:
// Create a constant emitter.
// Produces always the same ("constant") value when pulled.
emitter.reset(new ConstEmitter{emit_arg});
m_const_emitter_queues.push_back(&m_emitter_queues[emit_idx]);
break;
}
}
// FIXME: The below code assumes our graph may have only one
// real video source (and so, only one stream which may really end)
// all other inputs are "constant" generators.
// Craft here a completion callback to notify Const emitters that
// a video source is over
auto real_video_completion_cb = [this]() {
for (auto q : m_const_emitter_queues) q->push(Cmd{Stop{}});
};
// FIXME: ONLY now, after all executable objects are created,
// we can set up our execution threads. Let's do it.
// First create threads for all the emitters.
// FIXME: One way to avoid this may be including an Emitter object as a part of
// START message. Why not?
if (state == State::READY)
{
stop();
}
for (auto it : ade::util::indexed(m_emitters))
{
const auto id = ade::util::index(it); // = index in GComputation's protocol
const auto eh = ade::util::value(it);
// Prepare emitter thread parameters
auto emitter = m_gim.metadata(eh).get<Emitter>().object;
// Collect all reader queues from the emitter's the only output object
auto out_queues = reader_queues(*m_island_graph, eh->outNodes().front());
m_threads.emplace_back(emitterActorThread,
emitter,
std::ref(m_emitter_queues[id]),
out_queues,
real_video_completion_cb);
}
// Now do this for every island (in a topological order)
for (auto &&op : m_ops)
{
// Prepare island thread parameters
auto island = m_gim.metadata(op.nh).get<IslandExec>().object;
// Collect actor's input queues
auto in_queues = input_queues(*m_island_graph, op.nh);
// Collect actor's output queues.
// This may be tricky...
std::vector< std::vector<stream::Q*> > out_queues;
for (auto &&out_eh : op.nh->outNodes()) {
out_queues.push_back(reader_queues(*m_island_graph, out_eh));
}
m_threads.emplace_back(islandActorThread,
op.in_objects,
op.out_objects,
op.out_metas,
island,
in_queues,
op.in_constants,
out_queues);
}
// Finally, start a collector thread.
m_threads.emplace_back(collectorThread,
m_sink_queues,
std::ref(m_out_queue));
state = State::READY;
}
void cv::gimpl::GStreamingExecutor::start()
{
if (state == State::STOPPED)
{
util::throw_error(std::logic_error("Please call setSource() before start() "
"if the pipeline has been already stopped"));
}
GAPI_Assert(state == State::READY);
// Currently just trigger our emitters to work
state = State::RUNNING;
for (auto &q : m_emitter_queues)
{
q.push(stream::Cmd{stream::Start{}});
}
}
void cv::gimpl::GStreamingExecutor::wait_shutdown()
{
// This utility is used by pull/try_pull/stop() to uniformly
// shutdown the worker threads.
// FIXME: Of course it can be designed much better
for (auto &t : m_threads) t.join();
m_threads.clear();
// Clear all queues
// If there are constant emitters, internal queues
// may be polluted with constant values and have extra
// data at the point of shutdown.
// It usually happens when there's multiple inputs,
// one constant and one is not, and the latter ends (e.g.
// with end-of-stream).
for (auto &q : m_emitter_queues) q.clear();
for (auto &q : m_sink_queues) q->clear();
for (auto &q : m_internal_queues) q->clear();
m_out_queue.clear();
state = State::STOPPED;
}
bool cv::gimpl::GStreamingExecutor::pull(cv::GRunArgsP &&outs)
{
if (state == State::STOPPED)
return false;
GAPI_Assert(state == State::RUNNING);
GAPI_Assert(m_sink_queues.size() == outs.size());
Cmd cmd;
m_out_queue.pop(cmd);
if (cv::util::holds_alternative<Stop>(cmd))
{
wait_shutdown();
return false;
}
GAPI_Assert(cv::util::holds_alternative<cv::GRunArgs>(cmd));
cv::GRunArgs &this_result = cv::util::get<cv::GRunArgs>(cmd);
sync_data(this_result, outs);
return true;
}
bool cv::gimpl::GStreamingExecutor::try_pull(cv::GRunArgsP &&outs)
{
if (state == State::STOPPED)
return false;
GAPI_Assert(m_sink_queues.size() == outs.size());
Cmd cmd;
if (!m_out_queue.try_pop(cmd)) {
return false;
}
if (cv::util::holds_alternative<Stop>(cmd))
{
wait_shutdown();
return false;
}
GAPI_Assert(cv::util::holds_alternative<cv::GRunArgs>(cmd));
cv::GRunArgs &this_result = cv::util::get<cv::GRunArgs>(cmd);
sync_data(this_result, outs);
return true;
}
void cv::gimpl::GStreamingExecutor::stop()
{
if (state == State::STOPPED)
return;
// FIXME: ...and how to deal with still-unread data then?
// Push a Stop message to the every emitter,
// wait until it broadcasts within the pipeline,
// FIXME: worker threads could stuck on push()!
// need to read the output queues until Stop!
for (auto &q : m_emitter_queues) {
q.push(stream::Cmd{stream::Stop{}});
}
// Pull messages from the final queue to ensure completion
Cmd cmd;
while (!cv::util::holds_alternative<Stop>(cmd))
{
m_out_queue.pop(cmd);
}
GAPI_Assert(cv::util::holds_alternative<Stop>(cmd));
wait_shutdown();
}
bool cv::gimpl::GStreamingExecutor::running() const
{
return (state == State::RUNNING);
}

@ -0,0 +1,132 @@
// This file is part of OpenCV project.
// 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 Intel Corporation
#ifndef OPENCV_GAPI_GSTREAMING_EXECUTOR_HPP
#define OPENCV_GAPI_GSTREAMING_EXECUTOR_HPP
#ifdef _MSC_VER
#pragma warning(disable: 4503) // "decorated name length exceeded"
// on concurrent_bounded_queue
#endif
#include <memory> // unique_ptr, shared_ptr
#include <thread> // thread
#if defined(HAVE_TBB)
# include <tbb/concurrent_queue.h> // FIXME: drop it from here!
template<typename T> using QueueClass = tbb::concurrent_bounded_queue<T>;
#else
# include "executor/conc_queue.hpp"
template<typename T> using QueueClass = cv::gapi::own::concurrent_bounded_queue<T>;
#endif // TBB
#include <ade/graph.hpp>
#include "backends/common/gbackend.hpp"
namespace cv {
namespace gimpl {
namespace stream {
struct Start {};
struct Stop {};
using Cmd = cv::util::variant
< cv::util::monostate
, Start // Tells emitters to start working. Not broadcasted to workers.
, Stop // Tells emitters to stop working. Broadcasted to workers.
, cv::GRunArg // Workers data payload to process.
, cv::GRunArgs // Full results vector
>;
using Q = QueueClass<Cmd>;
} // namespace stream
// FIXME: Currently all GExecutor comments apply also
// to this one. Please document it separately in the future.
class GStreamingExecutor final
{
protected:
// GStreamingExecutor is a state machine described as follows
//
// setSource() called
// STOPPED: - - - - - - - - - ->READY:
// -------- ------
// Initial state Input data specified
// No threads running Threads are created and IDLE
// ^ (Currently our emitter threads
// : are bounded to input data)
// : stop() called No processing happending
// : OR :
// : end-of-stream reached : start() called
// : during pull()/try_pull() V
// : RUNNING:
// : --------
// : Actual pipeline execution
// - - - - - - - - - - - - - - Threads are running
//
enum class State {
STOPPED,
READY,
RUNNING,
} state = State::STOPPED;
std::unique_ptr<ade::Graph> m_orig_graph;
std::shared_ptr<ade::Graph> m_island_graph;
cv::gimpl::GIslandModel::Graph m_gim; // FIXME: make const?
// FIXME: Naive executor details are here for now
// but then it should be moved to another place
struct OpDesc
{
std::vector<RcDesc> in_objects;
std::vector<RcDesc> out_objects;
cv::GMetaArgs out_metas;
ade::NodeHandle nh;
std::vector<GRunArg> in_constants;
// FIXME: remove it as unused
std::shared_ptr<GIslandExecutable> isl_exec;
};
std::vector<OpDesc> m_ops;
struct DataDesc
{
ade::NodeHandle slot_nh;
ade::NodeHandle data_nh;
};
std::vector<DataDesc> m_slots;
// Order in these vectors follows the GComputaion's protocol
std::vector<ade::NodeHandle> m_emitters;
std::vector<ade::NodeHandle> m_sinks;
std::vector<std::thread> m_threads;
std::vector<stream::Q> m_emitter_queues;
std::vector<stream::Q*> m_const_emitter_queues; // a view over m_emitter_queues
std::vector<stream::Q*> m_sink_queues;
std::unordered_set<stream::Q*> m_internal_queues;
stream::Q m_out_queue;
void wait_shutdown();
public:
explicit GStreamingExecutor(std::unique_ptr<ade::Graph> &&g_model);
~GStreamingExecutor();
void setSource(GRunArgs &&args);
void start();
bool pull(cv::GRunArgsP &&outs);
bool try_pull(cv::GRunArgsP &&outs);
void stop();
bool running() const;
};
} // namespace gimpl
} // namespace cv
#endif // OPENCV_GAPI_GSTREAMING_EXECUTOR_HPP

@ -18,4 +18,7 @@
#include <opencv2/gapi.hpp>
#include <opencv2/gapi/gkernel.hpp>
// FIXME: Should this file be extended with our new headers?
// (which sometimes may be implicitly included here already?)
#endif // __OPENCV_GAPI_PRECOMP_HPP__

@ -1293,6 +1293,8 @@ TEST_P(NormalizeTest, Test)
}
}
// PLEASE DO NOT PUT NEW ACCURACY TESTS BELOW THIS POINT! //////////////////////
TEST_P(BackendOutputAllocationTest, EmptyOutput)
{
// G-API code //////////////////////////////////////////////////////////////

@ -447,6 +447,8 @@ INSTANTIATE_TEST_CASE_P(NormalizeTestCPU, NormalizeTest,
Values(NORM_MINMAX, NORM_INF, NORM_L1, NORM_L2),
Values(-1, CV_8U, CV_16U, CV_16S, CV_32F)));
// PLEASE DO NOT PUT NEW ACCURACY TESTS BELOW THIS POINT! //////////////////////
INSTANTIATE_TEST_CASE_P(BackendOutputAllocationTestCPU, BackendOutputAllocationTest,
Combine(Values(CV_8UC3, CV_16SC2, CV_32FC1),
Values(cv::Size(50, 50)),
@ -467,4 +469,5 @@ INSTANTIATE_TEST_CASE_P(ReInitOutTestCPU, ReInitOutTest,
Values(CORE_CPU),
Values(cv::Size(640, 400),
cv::Size(10, 480))));
}

@ -518,6 +518,8 @@ INSTANTIATE_TEST_CASE_P(LUTTestCustomCPU, LUTTest,
cv::Size(128, 128)),
/*init output matrices or not*/ Values(true)));
// PLEASE DO NOT PUT NEW ACCURACY TESTS BELOW THIS POINT! //////////////////////
INSTANTIATE_TEST_CASE_P(ConvertToCPU, ConvertToTest,
Combine(Values(CV_8UC3, CV_8UC1, CV_16UC1, CV_32FC1),
Values(CV_8U, CV_16U, CV_32F),

@ -163,4 +163,28 @@ TEST(GArray, TestIntermediateOutput)
EXPECT_EQ(10u, out_points.size());
EXPECT_EQ(10, out_count[0]);
}
TEST(GArray_VectorRef, TestMov)
{
// Warning: this test is testing some not-very-public APIs
// Test how VectorRef's mov() (aka poor man's move()) is working.
using I = int;
using V = std::vector<I>;
const V vgold = { 1, 2, 3};
V vtest = vgold;
const I* vptr = vtest.data();
cv::detail::VectorRef vref(vtest);
cv::detail::VectorRef vmov;
vmov.reset<I>();
EXPECT_EQ(vgold, vref.rref<I>());
vmov.mov(vref);
EXPECT_EQ(vgold, vmov.rref<I>());
EXPECT_EQ(vptr, vmov.rref<I>().data());
EXPECT_EQ(V{}, vref.rref<I>());
EXPECT_EQ(V{}, vtest);
}
} // namespace opencv_test

@ -390,6 +390,8 @@ INSTANTIATE_TEST_CASE_P(ConcatVertTestGPU, ConcatVertTest,
Values(-1),
Values(CORE_GPU)));
// PLEASE DO NOT PUT NEW ACCURACY TESTS BELOW THIS POINT! //////////////////////
INSTANTIATE_TEST_CASE_P(BackendOutputAllocationTestGPU, BackendOutputAllocationTest,
Combine(Values(CV_8UC3, CV_16SC2, CV_32FC1),
Values(cv::Size(50, 50)),

@ -101,7 +101,6 @@ TEST(TestAgeGenderIE, InferBasicTensor)
const auto &iedims = net.getInputsInfo().begin()->second->getTensorDesc().getDims();
auto cvdims = cv::gapi::ie::util::to_ocv(iedims);
std::reverse(cvdims.begin(), cvdims.end());
in_mat.create(cvdims, CV_32F);
cv::randu(in_mat, -1, 1);

@ -0,0 +1,197 @@
// This file is part of OpenCV project.
// 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 Intel Corporation
#include "../test_precomp.hpp"
#include <unordered_set>
#include <thread>
#include "executor/conc_queue.hpp"
namespace opencv_test
{
using namespace cv::gapi;
TEST(ConcQueue, PushPop)
{
own::concurrent_bounded_queue<int> q;
for (int i = 0; i < 100; i++)
{
q.push(i);
}
for (int i = 0; i < 100; i++)
{
int x;
q.pop(x);
EXPECT_EQ(x, i);
}
}
TEST(ConcQueue, TryPop)
{
own::concurrent_bounded_queue<int> q;
int x = 0;
EXPECT_FALSE(q.try_pop(x));
q.push(1);
EXPECT_TRUE(q.try_pop(x));
EXPECT_EQ(1, x);
}
TEST(ConcQueue, Clear)
{
own::concurrent_bounded_queue<int> q;
for (int i = 0; i < 10; i++)
{
q.push(i);
}
q.clear();
int x = 0;
EXPECT_FALSE(q.try_pop(x));
}
// In this test, every writer thread produce its own range of integer
// numbers, writing those to a shared queue.
//
// Every reader thread pops elements from the queue (until -1 is
// reached) and stores those in its own associated set.
//
// Finally, the master thread waits for completion of all other
// threads and verifies that all the necessary data is
// produced/obtained.
using StressParam = std::tuple<int // Num writer threads
,int // Num elements per writer
,int // Num reader threads
,std::size_t>; // Queue capacity
namespace
{
constexpr int STOP_SIGN = -1;
constexpr int BASE = 1000;
}
struct ConcQueue_: public ::testing::TestWithParam<StressParam>
{
using Q = own::concurrent_bounded_queue<int>;
using S = std::unordered_set<int>;
static void writer(int base, int writes, Q& q)
{
for (int i = 0; i < writes; i++)
{
q.push(base + i);
}
q.push(STOP_SIGN);
}
static void reader(Q& q, S& s)
{
int x = 0;
while (true)
{
q.pop(x);
if (x == STOP_SIGN) return;
s.insert(x);
}
}
};
TEST_P(ConcQueue_, Test)
{
int num_writers = 0;
int num_writes = 0;
int num_readers = 0;
std::size_t capacity = 0u;
std::tie(num_writers, num_writes, num_readers, capacity) = GetParam();
CV_Assert(num_writers < 20);
CV_Assert(num_writes < BASE);
Q q;
if (capacity)
{
// see below (2)
CV_Assert(static_cast<int>(capacity) > (num_writers - num_readers));
q.set_capacity(capacity);
}
// Start reader threads
std::vector<S> storage(num_readers);
std::vector<std::thread> readers;
for (S& s : storage)
{
readers.emplace_back(reader, std::ref(q), std::ref(s));
}
// Start writer threads, also pre-generate reference numbers
S reference;
std::vector<std::thread> writers;
for (int w = 0; w < num_writers; w++)
{
writers.emplace_back(writer, w*BASE, num_writes, std::ref(q));
for (int r = 0; r < num_writes; r++)
{
reference.insert(w*BASE + r);
}
}
// Every writer puts a STOP_SIGN at the end,
// There are three cases:
// 1) num_writers == num_readers
// every reader should get its own STOP_SIGN from any
// of the writers
//
// 2) num_writers > num_readers
// every reader will get a STOP_SIGN but there're more
// STOP_SIGNs may be pushed to the queue - and if this
// number exceeds capacity, writers block (to a deadlock).
// The latter situation must be avoided at parameters level.
// [a] Also not every data produced by writers will be consumed
// by a reader in this case. Master thread will read the rest
//
// 3) num_readers > num_writers
// in this case, some readers will stuck and will never get
// a STOP_SIGN. Master thread will push extra STOP_SIGNs to the
// queue.
// Solution to (2a)
S remnants;
if (num_writers > num_readers)
{
int extra = num_writers - num_readers;
while (extra)
{
int x = 0;
q.pop(x);
if (x == STOP_SIGN) extra--;
else remnants.insert(x);
}
}
// Solution to (3)
if (num_readers > num_writers)
{
int extra = num_readers - num_writers;
while (extra--) q.push(STOP_SIGN);
}
// Wait for completions
for (auto &t : readers) t.join();
for (auto &t : writers) t.join();
// Accumulate and validate the result
S result(remnants.begin(), remnants.end());
for (const auto &s : storage) result.insert(s.begin(), s.end());
EXPECT_EQ(reference, result);
}
INSTANTIATE_TEST_CASE_P(ConcQueueStress, ConcQueue_,
Combine( Values(1, 2, 4, 8, 16) // writers
, Values(1, 32, 96, 256) // writes
, Values(1, 2, 10) // readers
, Values(0u, 16u, 32u))); // capacity
} // namespace opencv_test

@ -0,0 +1,827 @@
// This file is part of OpenCV project.
// 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 Intel Corporation
#include "../test_precomp.hpp"
#include <opencv2/gapi/cpu/core.hpp>
#include <opencv2/gapi/cpu/imgproc.hpp>
#include <opencv2/gapi/fluid/core.hpp>
#include <opencv2/gapi/fluid/imgproc.hpp>
#include <opencv2/gapi/fluid/gfluidkernel.hpp>
#include <opencv2/gapi/ocl/core.hpp>
#include <opencv2/gapi/ocl/imgproc.hpp>
#include <opencv2/gapi/streaming/cap.hpp>
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");
GAPI_Assert(testDataPath != nullptr);
cvtest::addDataSearchPath(testDataPath);
initialized = true;
}
#endif // WINRT
}
cv::gapi::GKernelPackage OCV_KERNELS()
{
static cv::gapi::GKernelPackage pkg =
cv::gapi::combine(cv::gapi::core::cpu::kernels(),
cv::gapi::imgproc::cpu::kernels());
return pkg;
}
cv::gapi::GKernelPackage OCV_FLUID_KERNELS()
{
static cv::gapi::GKernelPackage pkg =
cv::gapi::combine(OCV_KERNELS(),
cv::gapi::core::fluid::kernels());
return pkg;
}
#if 0
// FIXME: OpenCL backend seem to work fine with Streaming
// however the results are not very bit exact with CPU
// It may be a problem but may be just implementation innacuracy.
// Need to customize the comparison function in tests where OpenCL
// is involved.
cv::gapi::GKernelPackage OCL_KERNELS()
{
static cv::gapi::GKernelPackage pkg =
cv::gapi::combine(cv::gapi::core::ocl::kernels(),
cv::gapi::imgproc::ocl::kernels());
return pkg;
}
cv::gapi::GKernelPackage OCL_FLUID_KERNELS()
{
static cv::gapi::GKernelPackage pkg =
cv::gapi::combine(OCL_KERNELS(),
cv::gapi::core::fluid::kernels());
return pkg;
}
#endif // 0
struct GAPI_Streaming: public ::testing::TestWithParam<cv::gapi::GKernelPackage> {
GAPI_Streaming() { initTestDataPath(); }
};
} // anonymous namespace
TEST_P(GAPI_Streaming, SmokeTest_ConstInput_GMat)
{
// This graph models the following use-case:
// Canny here is used as some "feature detector"
//
// Island/device layout may be different given the contents
// of the passed kernel package.
//
// The expectation is that we get as much islands in the
// graph as backends the GKernelPackage contains.
//
// [Capture] --> Crop --> Resize --> Canny --> [out]
const auto crop_rc = cv::Rect(13, 75, 377, 269);
const auto resample_sz = cv::Size(224, 224);
const auto thr_lo = 64.;
const auto thr_hi = 192.;
cv::GMat in;
auto roi = cv::gapi::crop(in, crop_rc);
auto res = cv::gapi::resize(roi, resample_sz);
auto out = cv::gapi::Canny(res, thr_lo, thr_hi);
cv::GComputation c(in, out);
// Input data
cv::Mat in_mat = cv::imread(findDataFile("cv/edgefilter/kodim23.png"));
cv::Mat out_mat_gapi;
// OpenCV reference image
cv::Mat out_mat_ocv;
{
cv::Mat tmp;
cv::resize(in_mat(crop_rc), tmp, resample_sz);
cv::Canny(tmp, out_mat_ocv, thr_lo, thr_hi);
}
// Compilation & testing
auto ccomp = c.compileStreaming(cv::descr_of(in_mat),
cv::compile_args(cv::gapi::use_only{GetParam()}));
EXPECT_TRUE(ccomp);
EXPECT_FALSE(ccomp.running());
ccomp.setSource(cv::gin(in_mat));
ccomp.start();
EXPECT_TRUE(ccomp.running());
// Fetch the result 15 times
for (int i = 0; i < 15; i++) {
// With constant inputs, the stream is endless so
// the blocking pull() should never return `false`.
EXPECT_TRUE(ccomp.pull(cv::gout(out_mat_gapi)));
EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
}
EXPECT_TRUE(ccomp.running());
ccomp.stop();
EXPECT_FALSE(ccomp.running());
}
TEST_P(GAPI_Streaming, SmokeTest_VideoInput_GMat)
{
const auto crop_rc = cv::Rect(13, 75, 377, 269);
const auto resample_sz = cv::Size(224, 224);
const auto thr_lo = 64.;
const auto thr_hi = 192.;
cv::GMat in;
auto roi = cv::gapi::crop(in, crop_rc);
auto res = cv::gapi::resize(roi, resample_sz);
auto out = cv::gapi::Canny(res, thr_lo, thr_hi);
cv::GComputation c(cv::GIn(in), cv::GOut(cv::gapi::copy(in), out));
// OpenCV reference image code
auto opencv_ref = [&](const cv::Mat &in_mat, cv::Mat &out_mat) {
cv::Mat tmp;
cv::resize(in_mat(crop_rc), tmp, resample_sz);
cv::Canny(tmp, out_mat, thr_lo, thr_hi);
};
// Compilation & testing
auto ccomp = c.compileStreaming(cv::GMatDesc{CV_8U,3,cv::Size{768,576}},
cv::compile_args(cv::gapi::use_only{GetParam()}));
EXPECT_TRUE(ccomp);
EXPECT_FALSE(ccomp.running());
ccomp.setSource(gapi::wip::make_src<cv::gapi::wip::GCaptureSource>(findDataFile("cv/video/768x576.avi")));
ccomp.start();
EXPECT_TRUE(ccomp.running());
// Process the full video
cv::Mat in_mat_gapi, out_mat_gapi;
std::size_t frames = 0u;
while (ccomp.pull(cv::gout(in_mat_gapi, out_mat_gapi))) {
frames++;
cv::Mat out_mat_ocv;
opencv_ref(in_mat_gapi, out_mat_ocv);
EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
}
EXPECT_LT(0u, frames);
EXPECT_FALSE(ccomp.running());
// Stop can be called at any time (even if the pipeline is not running)
ccomp.stop();
EXPECT_FALSE(ccomp.running());
}
TEST_P(GAPI_Streaming, Regression_CompileTimeScalar)
{
// There was a bug with compile-time GScalars. Compile-time
// GScalars generate their own DATA nodes at GModel/GIslandModel
// level, resulting in an extra link at the GIslandModel level, so
// GStreamingExecutor automatically assigned an input queue to
// such edges. Since there were no in-graph producer for that
// data, no data were pushed to such queue what lead to a
// deadlock.
cv::GMat in;
cv::GMat tmp = cv::gapi::copy(in);
for (int i = 0; i < 3; i++) {
tmp = tmp & cv::gapi::blur(in, cv::Size(3,3));
}
cv::GComputation c(cv::GIn(in), cv::GOut(tmp, tmp + 1));
auto ccomp = c.compileStreaming(cv::GMatDesc{CV_8U,3,cv::Size{768,512}},
cv::compile_args(cv::gapi::use_only{GetParam()}));
cv::Mat in_mat = cv::imread(findDataFile("cv/edgefilter/kodim23.png"));
cv::Mat out_mat1, out_mat2;
// Fetch the result 15 times
ccomp.setSource(cv::gin(in_mat));
ccomp.start();
for (int i = 0; i < 15; i++) {
EXPECT_TRUE(ccomp.pull(cv::gout(out_mat1, out_mat2)));
}
ccomp.stop();
}
TEST_P(GAPI_Streaming, SmokeTest_StartRestart)
{
cv::GMat in;
auto res = cv::gapi::resize(in, cv::Size{300,200});
auto out = cv::gapi::Canny(res, 95, 220);
cv::GComputation c(cv::GIn(in), cv::GOut(cv::gapi::copy(in), out));
auto ccomp = c.compileStreaming(cv::GMatDesc{CV_8U,3,cv::Size{768,576}},
cv::compile_args(cv::gapi::use_only{GetParam()}));
EXPECT_TRUE(ccomp);
EXPECT_FALSE(ccomp.running());
// Run 1
std::size_t num_frames1 = 0u;
ccomp.setSource(gapi::wip::make_src<cv::gapi::wip::GCaptureSource>(findDataFile("cv/video/768x576.avi")));
ccomp.start();
EXPECT_TRUE(ccomp.running());
cv::Mat out1, out2;
while (ccomp.pull(cv::gout(out1, out2))) num_frames1++;
EXPECT_FALSE(ccomp.running());
// Run 2
std::size_t num_frames2 = 0u;
ccomp.setSource(gapi::wip::make_src<cv::gapi::wip::GCaptureSource>(findDataFile("cv/video/768x576.avi")));
ccomp.start();
EXPECT_TRUE(ccomp.running());
while (ccomp.pull(cv::gout(out1, out2))) num_frames2++;
EXPECT_FALSE(ccomp.running());
EXPECT_LT(0u, num_frames1);
EXPECT_LT(0u, num_frames2);
EXPECT_EQ(num_frames1, num_frames2);
}
TEST_P(GAPI_Streaming, SmokeTest_VideoConstSource_NoHang)
{
// A video source is a finite one, while const source is not.
// Check that pipeline completes when a video source completes.
auto refc = cv::GComputation([](){
cv::GMat in;
return cv::GComputation(in, cv::gapi::copy(in));
}).compileStreaming(cv::GMatDesc{CV_8U,3,cv::Size{768,576}},
cv::compile_args(cv::gapi::use_only{GetParam()}));
refc.setSource(gapi::wip::make_src<cv::gapi::wip::GCaptureSource>(findDataFile("cv/video/768x576.avi")));
refc.start();
std::size_t ref_frames = 0u;
cv::Mat tmp;
while (refc.pull(cv::gout(tmp))) ref_frames++;
EXPECT_EQ(100u, ref_frames);
cv::GMat in;
cv::GMat in2;
cv::GMat roi = cv::gapi::crop(in2, cv::Rect{1,1,256,256});
cv::GMat blr = cv::gapi::blur(roi, cv::Size(3,3));
cv::GMat out = blr - in;
auto testc = cv::GComputation(cv::GIn(in, in2), cv::GOut(out))
.compileStreaming(cv::GMatDesc{CV_8U,3,cv::Size{256,256}},
cv::GMatDesc{CV_8U,3,cv::Size{768,576}},
cv::compile_args(cv::gapi::use_only{GetParam()}));
cv::Mat in_const = cv::Mat::eye(cv::Size(256,256), CV_8UC3);
testc.setSource(cv::gin(in_const,
gapi::wip::make_src<cv::gapi::wip::GCaptureSource>(findDataFile("cv/video/768x576.avi"))));
testc.start();
std::size_t test_frames = 0u;
while (testc.pull(cv::gout(tmp))) test_frames++;
EXPECT_EQ(ref_frames, test_frames);
}
INSTANTIATE_TEST_CASE_P(TestStreaming, GAPI_Streaming,
Values( OCV_KERNELS()
//, OCL_KERNELS() // FIXME: Fails bit-exactness check, maybe relax it?
, OCV_FLUID_KERNELS()
//, OCL_FLUID_KERNELS() // FIXME: Fails bit-exactness check, maybe relax it?
));
namespace TypesTest
{
G_API_OP(SumV, <cv::GArray<int>(cv::GMat)>, "test.gapi.sumv") {
static cv::GArrayDesc outMeta(const cv::GMatDesc &) {
return cv::empty_array_desc();
}
};
G_API_OP(AddV, <cv::GMat(cv::GMat,cv::GArray<int>)>, "test.gapi.addv") {
static cv::GMatDesc outMeta(const cv::GMatDesc &in, const cv::GArrayDesc &) {
return in;
}
};
GAPI_OCV_KERNEL(OCVSumV, SumV) {
static void run(const cv::Mat &in, std::vector<int> &out) {
CV_Assert(in.depth() == CV_8U);
const auto length = in.cols * in.channels();
out.resize(length);
const uchar *ptr = in.ptr(0);
for (int c = 0; c < length; c++) {
out[c] = ptr[c];
}
for (int r = 1; r < in.rows; r++) {
ptr = in.ptr(r);
for (int c = 0; c < length; c++) {
out[c] += ptr[c];
}
}
}
};
GAPI_OCV_KERNEL(OCVAddV, AddV) {
static void run(const cv::Mat &in, const std::vector<int> &inv, cv::Mat &out) {
CV_Assert(in.depth() == CV_8U);
const auto length = in.cols * in.channels();
CV_Assert(length == static_cast<int>(inv.size()));
for (int r = 0; r < in.rows; r++) {
const uchar *in_ptr = in.ptr(r);
uchar *out_ptr = out.ptr(r);
for (int c = 0; c < length; c++) {
out_ptr[c] = cv::saturate_cast<uchar>(in_ptr[c] + inv[c]);
}
}
}
};
GAPI_FLUID_KERNEL(FluidAddV, AddV, false) {
static const int Window = 1;
static void run(const cv::gapi::fluid::View &in,
const std::vector<int> &inv,
cv::gapi::fluid::Buffer &out) {
const uchar *in_ptr = in.InLineB(0);
uchar *out_ptr = out.OutLineB(0);
const auto length = in.meta().size.width * in.meta().chan;
CV_Assert(length == static_cast<int>(inv.size()));
for (int c = 0; c < length; c++) {
out_ptr[c] = cv::saturate_cast<uchar>(in_ptr[c] + inv[c]);
}
}
};
} // namespace TypesTest
TEST(GAPI_Streaming_Types, InputScalar)
{
// This test verifies if Streaming works with Scalar data @ input.
cv::GMat in_m;
cv::GScalar in_s;
cv::GMat out_m = in_m * in_s;
cv::GComputation c(cv::GIn(in_m, in_s), cv::GOut(out_m));
// Input data
cv::Mat in_mat = cv::Mat::eye(256, 256, CV_8UC1);
cv::Scalar in_scl = 32;
// Run pipeline
auto sc = c.compileStreaming(cv::descr_of(in_mat), cv::descr_of(in_scl));
sc.setSource(cv::gin(in_mat, in_scl));
sc.start();
for (int i = 0; i < 10; i++)
{
cv::Mat out;
EXPECT_TRUE(sc.pull(cv::gout(out)));
EXPECT_EQ(0., cv::norm(out, in_mat.mul(in_scl), cv::NORM_INF));
}
}
TEST(GAPI_Streaming_Types, InputVector)
{
// This test verifies if Streaming works with Vector data @ input.
cv::GMat in_m;
cv::GArray<int> in_v;
cv::GMat out_m = TypesTest::AddV::on(in_m, in_v) - in_m;
cv::GComputation c(cv::GIn(in_m, in_v), cv::GOut(out_m));
// Input data
cv::Mat in_mat = cv::Mat::eye(256, 256, CV_8UC1);
std::vector<int> in_vec;
TypesTest::OCVSumV::run(in_mat, in_vec);
EXPECT_EQ(std::vector<int>(256,1), in_vec); // self-sanity-check
auto opencv_ref = [&](const cv::Mat &in, const std::vector<int> &inv, cv::Mat &out) {
cv::Mat tmp = in_mat.clone(); // allocate the same amount of memory as graph does
TypesTest::OCVAddV::run(in, inv, tmp);
out = tmp - in;
};
// Run pipeline
auto sc = c.compileStreaming(cv::descr_of(in_mat),
cv::descr_of(in_vec),
cv::compile_args(cv::gapi::kernels<TypesTest::OCVAddV>()));
sc.setSource(cv::gin(in_mat, in_vec));
sc.start();
for (int i = 0; i < 10; i++)
{
cv::Mat out_mat;
EXPECT_TRUE(sc.pull(cv::gout(out_mat)));
cv::Mat ref_mat;
opencv_ref(in_mat, in_vec, ref_mat);
EXPECT_EQ(0., cv::norm(ref_mat, out_mat, cv::NORM_INF));
}
}
TEST(GAPI_Streaming_Types, XChangeScalar)
{
// This test verifies if Streaming works when pipeline steps
// (islands) exchange Scalar data.
initTestDataPath();
cv::GMat in;
cv::GScalar m = cv::gapi::mean(in);
cv::GMat tmp = cv::gapi::convertTo(in, CV_32F) - m;
cv::GMat out = cv::gapi::blur(tmp, cv::Size(3,3));
cv::GComputation c(cv::GIn(in), cv::GOut(cv::gapi::copy(in),
cv::gapi::convertTo(out, CV_8U)));
auto ocv_ref = [](const cv::Mat &in_mat, cv::Mat &out_mat) {
cv::Scalar ocv_m = cv::mean(in_mat);
cv::Mat ocv_tmp;
in_mat.convertTo(ocv_tmp, CV_32F);
ocv_tmp -= ocv_m;
cv::blur(ocv_tmp, ocv_tmp, cv::Size(3,3));
ocv_tmp.convertTo(out_mat, CV_8U);
};
// Here we want mean & convertTo run on OCV
// and subC & blur3x3 on Fluid.
// FIXME: With the current API it looks quite awful:
auto ocv_kernels = cv::gapi::core::cpu::kernels(); // convertTo
ocv_kernels.remove<cv::gapi::core::GSubC>();
auto fluid_kernels = cv::gapi::combine(cv::gapi::core::fluid::kernels(), // subC
cv::gapi::imgproc::fluid::kernels()); // box3x3
fluid_kernels.remove<cv::gapi::core::GConvertTo>();
fluid_kernels.remove<cv::gapi::core::GMean>();
// FIXME: Now
// - fluid kernels take over ocv kernels (including Copy, SubC, & Box3x3)
// - selected kernels (which were removed from the fluid package) remain in OCV
// (ConvertTo + some others)
// FIXME: This is completely awful. User should easily pick up specific kernels
// to an empty kernel package to craft his own but not do it via exclusion.
// Need to expose kernel declarations to public headers to enable kernels<..>()
// on user side.
auto kernels = cv::gapi::combine(ocv_kernels, fluid_kernels);
// Compile streaming pipeline
auto sc = c.compileStreaming(cv::GMatDesc{CV_8U,3,cv::Size{768,576}},
cv::compile_args(cv::gapi::use_only{kernels}));
sc.setSource(gapi::wip::make_src<cv::gapi::wip::GCaptureSource>(findDataFile("cv/video/768x576.avi")));
sc.start();
cv::Mat in_frame;
cv::Mat out_mat_gapi;
cv::Mat out_mat_ref;
std::size_t num_frames = 0u;
while (sc.pull(cv::gout(in_frame, out_mat_gapi))) {
num_frames++;
ocv_ref(in_frame, out_mat_ref);
EXPECT_EQ(0., cv::norm(out_mat_gapi, out_mat_ref, cv::NORM_INF));
}
EXPECT_LT(0u, num_frames);
}
TEST(GAPI_Streaming_Types, XChangeVector)
{
// This test verifies if Streaming works when pipeline steps
// (islands) exchange Vector data.
initTestDataPath();
cv::GMat in1, in2;
cv::GMat in = cv::gapi::crop(in1, cv::Rect{0,0,576,576});
cv::GScalar m = cv::gapi::mean(in);
cv::GArray<int> s = TypesTest::SumV::on(in2); // (in2 = eye, so s = [1,0,0,1,..])
cv::GMat out = TypesTest::AddV::on(in - m, s);
cv::GComputation c(cv::GIn(in1, in2), cv::GOut(cv::gapi::copy(in), out));
auto ocv_ref = [](const cv::Mat &in_mat1, const cv::Mat &in_mat2, cv::Mat &out_mat) {
cv::Mat in_roi = in_mat1(cv::Rect{0,0,576,576});
cv::Scalar ocv_m = cv::mean(in_roi);
std::vector<int> ocv_v;
TypesTest::OCVSumV::run(in_mat2, ocv_v);
out_mat.create(cv::Size(576,576), CV_8UC3);
cv::Mat in_tmp = in_roi - ocv_m;
TypesTest::OCVAddV::run(in_tmp, ocv_v, out_mat);
};
// Let crop/mean/sumV be calculated via OCV,
// and AddV/subC be calculated via Fluid
auto ocv_kernels = cv::gapi::core::cpu::kernels();
ocv_kernels.remove<cv::gapi::core::GSubC>();
ocv_kernels.include<TypesTest::OCVSumV>();
auto fluid_kernels = cv::gapi::core::fluid::kernels();
fluid_kernels.include<TypesTest::FluidAddV>();
// Here OCV takes precedense over Fluid, whith SubC & SumV remaining
// in Fluid.
auto kernels = cv::gapi::combine(fluid_kernels, ocv_kernels);
// Compile streaming pipeline
cv::Mat in_eye = cv::Mat::eye(cv::Size(576, 576), CV_8UC3);
auto sc = c.compileStreaming(cv::GMatDesc{CV_8U,3,cv::Size{768,576}},
cv::GMatDesc{CV_8U,3,cv::Size{576,576}},
cv::compile_args(cv::gapi::use_only{kernels}));
sc.setSource(cv::gin(gapi::wip::make_src<cv::gapi::wip::GCaptureSource>(findDataFile("cv/video/768x576.avi")),
in_eye));
sc.start();
cv::Mat in_frame;
cv::Mat out_mat_gapi;
cv::Mat out_mat_ref;
std::size_t num_frames = 0u;
while (sc.pull(cv::gout(in_frame, out_mat_gapi))) {
num_frames++;
ocv_ref(in_frame, in_eye, out_mat_ref);
EXPECT_EQ(0., cv::norm(out_mat_gapi, out_mat_ref, cv::NORM_INF));
}
EXPECT_LT(0u, num_frames);
}
TEST(GAPI_Streaming_Types, OutputScalar)
{
// This test verifies if Streaming works when pipeline
// produces scalar data only
initTestDataPath();
cv::GMat in;
cv::GScalar out = cv::gapi::mean(in);
auto sc = cv::GComputation(cv::GIn(in), cv::GOut(out))
.compileStreaming(cv::GMatDesc{CV_8U,3,cv::Size{768,576}});
const auto video_path = findDataFile("cv/video/768x576.avi");
sc.setSource(gapi::wip::make_src<cv::gapi::wip::GCaptureSource>(video_path));
sc.start();
cv::VideoCapture cap;
cap.open(video_path);
cv::Mat tmp;
cv::Scalar out_scl;
std::size_t num_frames = 0u;
while (sc.pull(cv::gout(out_scl)))
{
num_frames++;
cap >> tmp;
cv::Scalar out_ref = cv::mean(tmp);
EXPECT_EQ(out_ref, out_scl);
}
EXPECT_LT(0u, num_frames);
}
TEST(GAPI_Streaming_Types, OutputVector)
{
// This test verifies if Streaming works when pipeline
// produces vector data only
initTestDataPath();
auto pkg = cv::gapi::kernels<TypesTest::OCVSumV>();
cv::GMat in1, in2;
cv::GMat roi = cv::gapi::crop(in2, cv::Rect(3,3,256,256));
cv::GArray<int> out = TypesTest::SumV::on(cv::gapi::mul(roi, in1));
auto sc = cv::GComputation(cv::GIn(in1, in2), cv::GOut(out))
.compileStreaming(cv::GMatDesc{CV_8U,3,cv::Size{256,256}},
cv::GMatDesc{CV_8U,3,cv::Size{768,576}},
cv::compile_args(pkg));
auto ocv_ref = [](const cv::Mat &ocv_in1,
const cv::Mat &ocv_in2,
std::vector<int> &ocv_out) {
auto ocv_roi = ocv_in2(cv::Rect{3,3,256,256});
TypesTest::OCVSumV::run(ocv_roi.mul(ocv_in1), ocv_out);
};
cv::Mat in_eye = cv::Mat::eye(cv::Size(256, 256), CV_8UC3);
const auto video_path = findDataFile("cv/video/768x576.avi");
sc.setSource(cv::gin(in_eye, gapi::wip::make_src<cv::gapi::wip::GCaptureSource>(video_path)));
sc.start();
cv::VideoCapture cap;
cap.open(video_path);
cv::Mat tmp;
std::vector<int> ref_vec;
std::vector<int> out_vec;
std::size_t num_frames = 0u;
while (sc.pull(cv::gout(out_vec)))
{
num_frames++;
cap >> tmp;
ref_vec.clear();
ocv_ref(in_eye, tmp, ref_vec);
EXPECT_EQ(ref_vec, out_vec);
}
EXPECT_LT(0u, num_frames);
}
struct GAPI_Streaming_Unit: public ::testing::Test {
cv::Mat m;
cv::GComputation cc;
cv::GStreamingCompiled sc;
cv::GCompiled ref;
GAPI_Streaming_Unit()
: m(cv::Mat::ones(224,224,CV_8UC3))
, cc([]{
cv::GMat a, b;
cv::GMat c = a + b*2;
return cv::GComputation(cv::GIn(a, b), cv::GOut(c));
})
{
initTestDataPath();
const auto a_desc = cv::descr_of(m);
const auto b_desc = cv::descr_of(m);
sc = cc.compileStreaming(a_desc, b_desc);
ref = cc.compile(a_desc, b_desc);
}
};
TEST_F(GAPI_Streaming_Unit, TestTwoVideoSourcesFail)
{
// FIXME: Meta check doesn't fail here (but ideally it should)
const auto c_ptr = gapi::wip::make_src<cv::gapi::wip::GCaptureSource>(findDataFile("cv/video/768x576.avi"));
EXPECT_NO_THROW(sc.setSource(cv::gin(c_ptr, m)));
EXPECT_NO_THROW(sc.setSource(cv::gin(m, c_ptr)));
EXPECT_ANY_THROW(sc.setSource(cv::gin(c_ptr, c_ptr)));
}
TEST_F(GAPI_Streaming_Unit, TestStartWithoutnSetSource)
{
EXPECT_ANY_THROW(sc.start());
}
TEST_F(GAPI_Streaming_Unit, TestStopWithoutStart1)
{
// It is ok!
EXPECT_NO_THROW(sc.stop());
}
TEST_F(GAPI_Streaming_Unit, TestStopWithoutStart2)
{
// It should be ok as well
sc.setSource(cv::gin(m, m));
EXPECT_NO_THROW(sc.stop());
}
TEST_F(GAPI_Streaming_Unit, StopStartStop)
{
cv::Mat out;
EXPECT_NO_THROW(sc.stop());
EXPECT_NO_THROW(sc.setSource(cv::gin(m, m)));
EXPECT_NO_THROW(sc.start());
std::size_t i = 0u;
while (i++ < 10u) {EXPECT_TRUE(sc.pull(cv::gout(out)));};
EXPECT_NO_THROW(sc.stop());
}
TEST_F(GAPI_Streaming_Unit, ImplicitStop)
{
EXPECT_NO_THROW(sc.setSource(cv::gin(m, m)));
EXPECT_NO_THROW(sc.start());
// No explicit stop here - pipeline stops successfully at the test exit
}
TEST_F(GAPI_Streaming_Unit, StartStopStart_NoSetSource)
{
EXPECT_NO_THROW(sc.setSource(cv::gin(m, m)));
EXPECT_NO_THROW(sc.start());
EXPECT_NO_THROW(sc.stop());
EXPECT_ANY_THROW(sc.start()); // Should fails since setSource was not called
}
TEST_F(GAPI_Streaming_Unit, StartStopStress_Const)
{
// Runs 100 times with no deadlock - assumed stable (robust) enough
for (int i = 0; i < 100; i++)
{
sc.stop();
sc.setSource(cv::gin(m, m));
sc.start();
cv::Mat out;
for (int j = 0; j < 5; j++) EXPECT_TRUE(sc.pull(cv::gout(out)));
}
}
TEST_F(GAPI_Streaming_Unit, StartStopStress_Video)
{
// Runs 100 times with no deadlock - assumed stable (robust) enough
sc = cc.compileStreaming(cv::GMatDesc{CV_8U,3,cv::Size{768,576}},
cv::GMatDesc{CV_8U,3,cv::Size{768,576}});
m = cv::Mat::eye(cv::Size{768,576}, CV_8UC3);
for (int i = 0; i < 100; i++)
{
auto src = cv::gapi::wip::make_src<cv::gapi::wip::GCaptureSource>(findDataFile("cv/video/768x576.avi"));
sc.stop();
sc.setSource(cv::gin(src, m));
sc.start();
cv::Mat out;
for (int j = 0; j < 5; j++) EXPECT_TRUE(sc.pull(cv::gout(out)));
}
}
TEST_F(GAPI_Streaming_Unit, PullNoStart)
{
sc.setSource(cv::gin(m, m));
cv::Mat out;
EXPECT_ANY_THROW(sc.pull(cv::gout(out)));
}
TEST_F(GAPI_Streaming_Unit, SetSource_Multi_BeforeStart)
{
cv::Mat eye = cv::Mat::eye (224, 224, CV_8UC3);
cv::Mat zrs = cv::Mat::zeros(224, 224, CV_8UC3);
// Call setSource two times, data specified last time
// should be actually processed.
sc.setSource(cv::gin(zrs, zrs));
sc.setSource(cv::gin(eye, eye));
// Run the pipeline, acquire result once
sc.start();
cv::Mat out, out_ref;
EXPECT_TRUE(sc.pull(cv::gout(out)));
sc.stop();
// Pipeline should process `eye` mat, not `zrs`
ref(cv::gin(eye, eye), cv::gout(out_ref));
EXPECT_EQ(0., cv::norm(out, out_ref, cv::NORM_INF));
}
TEST_F(GAPI_Streaming_Unit, SetSource_During_Execution)
{
cv::Mat zrs = cv::Mat::zeros(224, 224, CV_8UC3);
sc.setSource(cv::gin(m, m));
sc.start();
EXPECT_ANY_THROW(sc.setSource(cv::gin(zrs, zrs)));
EXPECT_ANY_THROW(sc.setSource(cv::gin(zrs, zrs)));
EXPECT_ANY_THROW(sc.setSource(cv::gin(zrs, zrs)));
sc.stop();
}
TEST_F(GAPI_Streaming_Unit, SetSource_After_Completion)
{
sc.setSource(cv::gin(m, m));
// Test pipeline with `m` input
sc.start();
cv::Mat out, out_ref;
EXPECT_TRUE(sc.pull(cv::gout(out)));
sc.stop();
// Test against ref
ref(cv::gin(m, m), cv::gout(out_ref));
EXPECT_EQ(0., cv::norm(out, out_ref, cv::NORM_INF));
// Now set another source
cv::Mat eye = cv::Mat::eye(224, 224, CV_8UC3);
sc.setSource(cv::gin(eye, m));
sc.start();
EXPECT_TRUE(sc.pull(cv::gout(out)));
sc.stop();
// Test against new ref
ref(cv::gin(eye, m), cv::gout(out_ref));
EXPECT_EQ(0., cv::norm(out, out_ref, cv::NORM_INF));
}
} // namespace opencv_test
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