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186 lines
6.1 KiB
C++
186 lines
6.1 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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//
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// Copyright (C) 2019 Intel Corporation
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#include "test_precomp.hpp"
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#include <stdexcept>
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#include <ade/util/iota_range.hpp>
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#include "logger.hpp"
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#include <opencv2/gapi/plaidml/core.hpp>
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#include <opencv2/gapi/plaidml/plaidml.hpp>
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namespace opencv_test
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{
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#ifdef HAVE_PLAIDML
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inline cv::gapi::plaidml::config getConfig()
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{
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auto read_var_from_env = [](const char* env)
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{
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const char* raw = std::getenv(env);
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if (!raw)
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{
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cv::util::throw_error(std::runtime_error(std::string(env) + " is't set"));
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}
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return std::string(raw);
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};
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auto dev_id = read_var_from_env("PLAIDML_DEVICE");
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auto trg_id = read_var_from_env("PLAIDML_TARGET");
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return cv::gapi::plaidml::config{std::move(dev_id),
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std::move(trg_id)};
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}
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TEST(GAPI_PlaidML_Pipelines, SimpleArithmetic)
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{
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cv::Size size(1920, 1080);
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int type = CV_8UC1;
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cv::Mat in_mat1(size, type);
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cv::Mat in_mat2(size, type);
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// NB: What about overflow ? PlaidML doesn't handle it
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cv::randu(in_mat1, cv::Scalar::all(0), cv::Scalar::all(127));
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cv::randu(in_mat2, cv::Scalar::all(0), cv::Scalar::all(127));
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cv::Mat out_mat(size, type, cv::Scalar::all(0));
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cv::Mat ref_mat(size, type, cv::Scalar::all(0));
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////////////////////////////// G-API //////////////////////////////////////
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cv::GMat in1, in2;
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auto out = in1 + in2;
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cv::GComputation comp(cv::GIn(in1, in2), cv::GOut(out));
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comp.apply(cv::gin(in_mat1, in_mat2), cv::gout(out_mat),
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cv::compile_args(getConfig(),
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cv::gapi::use_only{cv::gapi::core::plaidml::kernels()}));
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////////////////////////////// OpenCV /////////////////////////////////////
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cv::add(in_mat1, in_mat2, ref_mat, cv::noArray(), type);
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EXPECT_EQ(0, cv::norm(out_mat, ref_mat));
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}
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// FIXME PlaidML cpu backend does't support bitwise operations
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TEST(GAPI_PlaidML_Pipelines, DISABLED_ComplexArithmetic)
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{
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cv::Size size(1920, 1080);
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int type = CV_8UC1;
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cv::Mat in_mat1(size, type);
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cv::Mat in_mat2(size, type);
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cv::randu(in_mat1, cv::Scalar::all(0), cv::Scalar::all(255));
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cv::randu(in_mat2, cv::Scalar::all(0), cv::Scalar::all(255));
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cv::Mat out_mat(size, type, cv::Scalar::all(0));
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cv::Mat ref_mat(size, type, cv::Scalar::all(0));
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////////////////////////////// G-API //////////////////////////////////////
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cv::GMat in1, in2;
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auto out = in1 | (in2 ^ (in1 & (in2 + (in1 - in2))));
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cv::GComputation comp(cv::GIn(in1, in2), cv::GOut(out));
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comp.apply(cv::gin(in_mat1, in_mat2), cv::gout(out_mat),
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cv::compile_args(getConfig(),
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cv::gapi::use_only{cv::gapi::core::plaidml::kernels()}));
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////////////////////////////// OpenCV /////////////////////////////////////
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cv::subtract(in_mat1, in_mat2, ref_mat, cv::noArray(), type);
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cv::add(in_mat2, ref_mat, ref_mat, cv::noArray(), type);
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cv::bitwise_and(in_mat1, ref_mat, ref_mat);
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cv::bitwise_xor(in_mat2, ref_mat, ref_mat);
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cv::bitwise_or(in_mat1, ref_mat, ref_mat);
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EXPECT_EQ(0, cv::norm(out_mat, ref_mat));
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}
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TEST(GAPI_PlaidML_Pipelines, TwoInputOperations)
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{
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cv::Size size(1920, 1080);
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int type = CV_8UC1;
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constexpr int kNumInputs = 4;
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std::vector<cv::Mat> in_mat(kNumInputs, cv::Mat(size, type));
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for (int i = 0; i < kNumInputs; ++i)
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{
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cv::randu(in_mat[i], cv::Scalar::all(0), cv::Scalar::all(60));
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}
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cv::Mat out_mat(size, type, cv::Scalar::all(0));
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cv::Mat ref_mat(size, type, cv::Scalar::all(0));
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////////////////////////////// G-API //////////////////////////////////////
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cv::GMat in[4];
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auto out = (in[3] - in[0]) + (in[2] - in[1]);
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cv::GComputation comp(cv::GIn(in[0], in[1], in[2], in[3]), cv::GOut(out));
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// FIXME Doesn't work just apply(in_mat, out_mat, ...)
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comp.apply(cv::gin(in_mat[0], in_mat[1], in_mat[2], in_mat[3]), cv::gout(out_mat),
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cv::compile_args(getConfig(),
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cv::gapi::use_only{cv::gapi::core::plaidml::kernels()}));
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////////////////////////////// OpenCV /////////////////////////////////////
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cv::subtract(in_mat[3], in_mat[0], ref_mat, cv::noArray(), type);
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cv::add(ref_mat, in_mat[2], ref_mat, cv::noArray(), type);
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cv::subtract(ref_mat, in_mat[1], ref_mat, cv::noArray(), type);
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EXPECT_EQ(0, cv::norm(out_mat, ref_mat));
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}
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TEST(GAPI_PlaidML_Pipelines, TwoOutputOperations)
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{
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cv::Size size(1920, 1080);
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int type = CV_8UC1;
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constexpr int kNumInputs = 4;
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std::vector<cv::Mat> in_mat(kNumInputs, cv::Mat(size, type));
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for (int i = 0; i < kNumInputs; ++i)
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{
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cv::randu(in_mat[i], cv::Scalar::all(0), cv::Scalar::all(60));
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}
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std::vector<cv::Mat> out_mat(kNumInputs, cv::Mat(size, type, cv::Scalar::all(0)));
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std::vector<cv::Mat> ref_mat(kNumInputs, cv::Mat(size, type, cv::Scalar::all(0)));
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////////////////////////////// G-API //////////////////////////////////////
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cv::GMat in[4], out[2];
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out[0] = in[0] + in[3];
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out[1] = in[1] + in[2];
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cv::GComputation comp(cv::GIn(in[0], in[1], in[2], in[3]), cv::GOut(out[0], out[1]));
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// FIXME Doesn't work just apply(in_mat, out_mat, ...)
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comp.apply(cv::gin(in_mat[0], in_mat[1], in_mat[2], in_mat[3]),
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cv::gout(out_mat[0], out_mat[1]),
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cv::compile_args(getConfig(),
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cv::gapi::use_only{cv::gapi::core::plaidml::kernels()}));
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////////////////////////////// OpenCV /////////////////////////////////////
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cv::add(in_mat[0], in_mat[3], ref_mat[0], cv::noArray(), type);
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cv::add(in_mat[1], in_mat[2], ref_mat[1], cv::noArray(), type);
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EXPECT_EQ(0, cv::norm(out_mat[0], ref_mat[0]));
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EXPECT_EQ(0, cv::norm(out_mat[1], ref_mat[1]));
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}
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#else // HAVE_PLAIDML
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TEST(GAPI_PlaidML_Pipelines, ThrowIfPlaidMLNotFound)
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{
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ASSERT_ANY_THROW(cv::gapi::core::plaidml::kernels());
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}
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#endif // HAVE_PLAIDML
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} // namespace opencv_test
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