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