Replace DNNTarget and DNNBackend in tests

Author: dkurt

modules/dnn/test/test_backends.cpp

@@ -10,9 +10,6 @@
 
 namespace opencv_test { namespace {
 
-CV_ENUM(DNNBackend, DNN_BACKEND_DEFAULT, DNN_BACKEND_HALIDE, DNN_BACKEND_INFERENCE_ENGINE)
-CV_ENUM(DNNTarget, DNN_TARGET_CPU, DNN_TARGET_OPENCL)
-
 static void loadNet(const std::string& weights, const std::string& proto,
                     const std::string& framework, Net* net)
 {

modules/dnn/test/test_caffe_importer.cpp

@@ -42,26 +42,9 @@
 #include "test_precomp.hpp"
 #include "npy_blob.hpp"
 #include <opencv2/dnn/shape_utils.hpp>
-#include <opencv2/core/ocl.hpp>
-#include <opencv2/ts/ocl_test.hpp>
 
 namespace opencv_test { namespace {
 
-CV_ENUM(DNNTarget, DNN_TARGET_CPU, DNN_TARGET_OPENCL)
-static testing::internal::ParamGenerator<DNNTarget> availableBackends()
-{
-    static std::vector<DNNTarget> targets;
-    if (targets.empty())
-    {
-        targets.push_back(DNN_TARGET_CPU);
-#ifdef HAVE_OPENCL
-        if (cv::ocl::useOpenCL())
-            targets.push_back(DNN_TARGET_OPENCL);
-#endif
-    }
-    return testing::ValuesIn(targets);
-}
-
 template<typename TString>
 static std::string _tf(TString filename)
 {
@@ -132,7 +115,7 @@ TEST_P(Reproducibility_AlexNet, Accuracy)
     normAssert(ref, out);
 }
 
-INSTANTIATE_TEST_CASE_P(/**/, Reproducibility_AlexNet, Combine(testing::Bool(), availableBackends()));
+INSTANTIATE_TEST_CASE_P(/**/, Reproducibility_AlexNet, Combine(testing::Bool(), availableDnnTargets()));
 
 #if !defined(_WIN32) || defined(_WIN64)
 TEST(Reproducibility_FCN, Accuracy)
@@ -232,7 +215,7 @@ TEST_P(Reproducibility_MobileNet_SSD, Accuracy)
     normAssert(outBatch.rowRange(0, numDetections), ref);
     normAssert(outBatch.rowRange(numDetections, 2 * numDetections).colRange(1, 7), ref.colRange(1, 7));
 }
-INSTANTIATE_TEST_CASE_P(/**/, Reproducibility_MobileNet_SSD, availableBackends());
+INSTANTIATE_TEST_CASE_P(/**/, Reproducibility_MobileNet_SSD, availableDnnTargets());
 
 typedef testing::TestWithParam<DNNTarget> Reproducibility_ResNet50;
 TEST_P(Reproducibility_ResNet50, Accuracy)
@@ -263,7 +246,7 @@ TEST_P(Reproducibility_ResNet50, Accuracy)
         normAssert(ref, out_umats[0], "out_umat_vector");
     }
 }
-INSTANTIATE_TEST_CASE_P(/**/, Reproducibility_ResNet50, availableBackends());
+INSTANTIATE_TEST_CASE_P(/**/, Reproducibility_ResNet50, availableDnnTargets());
 
 typedef testing::TestWithParam<DNNTarget> Reproducibility_SqueezeNet_v1_1;
 TEST_P(Reproducibility_SqueezeNet_v1_1, Accuracy)
@@ -291,7 +274,7 @@ TEST_P(Reproducibility_SqueezeNet_v1_1, Accuracy)
     Mat ref = blobFromNPY(_tf("squeezenet_v1.1_prob.npy"));
     normAssert(ref, out);
 }
-INSTANTIATE_TEST_CASE_P(/**/, Reproducibility_SqueezeNet_v1_1, availableBackends());
+INSTANTIATE_TEST_CASE_P(/**/, Reproducibility_SqueezeNet_v1_1, availableDnnTargets());
 
 TEST(Reproducibility_AlexNet_fp16, Accuracy)
 {

modules/dnn/test/test_precomp.hpp

@@ -44,12 +44,31 @@
 #include "opencv2/ts.hpp"
 #include "opencv2/ts/ts_perf.hpp"
 #include "opencv2/core/utility.hpp"
+#include "opencv2/core/ocl.hpp"
 
 #include "opencv2/dnn.hpp"
 #include "test_common.hpp"
 
 namespace opencv_test {
 using namespace cv::dnn;
+
+CV_ENUM(DNNBackend, DNN_BACKEND_DEFAULT, DNN_BACKEND_HALIDE, DNN_BACKEND_INFERENCE_ENGINE)
+CV_ENUM(DNNTarget, DNN_TARGET_CPU, DNN_TARGET_OPENCL)
+
+static testing::internal::ParamGenerator<DNNTarget> availableDnnTargets()
+{
+    static std::vector<DNNTarget> targets;
+    if (targets.empty())
+    {
+        targets.push_back(DNN_TARGET_CPU);
+#ifdef HAVE_OPENCL
+        if (cv::ocl::useOpenCL())
+            targets.push_back(DNN_TARGET_OPENCL);
+#endif
+    }
+    return testing::ValuesIn(targets);
+}
+
 }
 
 #endif

modules/dnn/test/test_tf_importer.cpp

@@ -11,8 +11,6 @@ Test for Tensorflow models loading
 
 #include "test_precomp.hpp"
 #include "npy_blob.hpp"
-#include <opencv2/core/ocl.hpp>
-#include <opencv2/ts/ocl_test.hpp>
 
 namespace opencv_test
 {
@@ -26,21 +24,6 @@ static std::string _tf(TString filename)
     return (getOpenCVExtraDir() + "/dnn/") + filename;
 }
 
-CV_ENUM(DNNTarget, DNN_TARGET_CPU, DNN_TARGET_OPENCL)
-static testing::internal::ParamGenerator<DNNTarget> availableBackends()
-{
-    static std::vector<DNNTarget> targets;
-    if (targets.empty())
-    {
-        targets.push_back(DNN_TARGET_CPU);
-#ifdef HAVE_OPENCL
-        if (cv::ocl::useOpenCL())
-            targets.push_back(DNN_TARGET_OPENCL);
-#endif
-    }
-    return testing::ValuesIn(targets);
-}
-
 TEST(Test_TensorFlow, read_inception)
 {
     Net net;
@@ -204,7 +187,7 @@ TEST_P(Test_TensorFlow_layers, reshape)
     runTensorFlowNet("flatten", targetId, true);
 }
 
-INSTANTIATE_TEST_CASE_P(/**/, Test_TensorFlow_layers, availableBackends());
+INSTANTIATE_TEST_CASE_P(/**/, Test_TensorFlow_layers, availableDnnTargets());
 
 typedef testing::TestWithParam<DNNTarget> Test_TensorFlow_nets;
 
@@ -302,7 +285,7 @@ TEST_P(Test_TensorFlow_nets, opencv_face_detector_uint8)
     normAssert(out.reshape(1, out.total() / 7).rowRange(0, 6).colRange(2, 7), ref, "", 2.8e-4, 3.4e-3);
 }
 
-INSTANTIATE_TEST_CASE_P(/**/, Test_TensorFlow_nets, availableBackends());
+INSTANTIATE_TEST_CASE_P(/**/, Test_TensorFlow_nets, availableDnnTargets());
 
 TEST(Test_TensorFlow, defun)
 {

modules/dnn/test/test_torch_importer.cpp

@@ -42,7 +42,6 @@
 #include "test_precomp.hpp"
 #include "npy_blob.hpp"
 #include <opencv2/dnn/shape_utils.hpp>
-#include <opencv2/ts/ocl_test.hpp>
 
 namespace opencv_test
 {
@@ -62,21 +61,6 @@ static std::string _tf(TStr filename, bool inTorchDir = true)
     return findDataFile(path, false);
 }
 
-CV_ENUM(DNNTarget, DNN_TARGET_CPU, DNN_TARGET_OPENCL)
-static testing::internal::ParamGenerator<DNNTarget> availableBackends()
-{
-    static std::vector<DNNTarget> targets;
-    if (targets.empty())
-    {
-        targets.push_back(DNN_TARGET_CPU);
-#ifdef HAVE_OPENCL
-        if (cv::ocl::useOpenCL())
-            targets.push_back(DNN_TARGET_OPENCL);
-#endif
-    }
-    return testing::ValuesIn(targets);
-}
-
 TEST(Torch_Importer, simple_read)
 {
     Net net;
@@ -221,7 +205,7 @@ TEST_P(Test_Torch_layers, net_non_spatial)
     runTorchNet("net_non_spatial", GetParam(), "", false, true);
 }
 
-INSTANTIATE_TEST_CASE_P(/**/, Test_Torch_layers, availableBackends());
+INSTANTIATE_TEST_CASE_P(/**/, Test_Torch_layers, availableDnnTargets());
 
 typedef testing::TestWithParam<DNNTarget> Test_Torch_nets;
 
@@ -323,7 +307,7 @@ TEST_P(Test_Torch_nets, FastNeuralStyle_accuracy)
     }
 }
 
-INSTANTIATE_TEST_CASE_P(/**/, Test_Torch_nets, availableBackends());
+INSTANTIATE_TEST_CASE_P(/**/, Test_Torch_nets, availableDnnTargets());
 
 // TODO: fix OpenCL and add to the rest of tests
 TEST(Torch_Importer, run_paralel)