Commit ffea927a authored by Alexander Alekhin's avatar Alexander Alekhin

Merge pull request #15618 from alalek:dnn_test_async_timeout

parents ba0b3983 440a937d
...@@ -169,7 +169,7 @@ class dnn_test(NewOpenCVTests): ...@@ -169,7 +169,7 @@ class dnn_test(NewOpenCVTests):
normAssertDetections(self, ref, out, 0.5, scoresDiff, iouDiff) normAssertDetections(self, ref, out, 0.5, scoresDiff, iouDiff)
def test_async(self): def test_async(self):
timeout = 500*10**6 # in nanoseconds (500ms) timeout = 10*1000*10**6 # in nanoseconds (10 sec)
testdata_required = bool(os.environ.get('OPENCV_DNN_TEST_REQUIRE_TESTDATA', False)) testdata_required = bool(os.environ.get('OPENCV_DNN_TEST_REQUIRE_TESTDATA', False))
proto = self.find_dnn_file('dnn/layers/layer_convolution.prototxt', required=testdata_required) proto = self.find_dnn_file('dnn/layers/layer_convolution.prototxt', required=testdata_required)
model = self.find_dnn_file('dnn/layers/layer_convolution.caffemodel', required=testdata_required) model = self.find_dnn_file('dnn/layers/layer_convolution.caffemodel', required=testdata_required)
......
...@@ -329,7 +329,7 @@ TEST_P(Test_Darknet_nets, TinyYoloVoc) ...@@ -329,7 +329,7 @@ TEST_P(Test_Darknet_nets, TinyYoloVoc)
} }
#ifdef HAVE_INF_ENGINE #ifdef HAVE_INF_ENGINE
static const std::chrono::milliseconds async_timeout(500); static const std::chrono::milliseconds async_timeout(10000);
typedef testing::TestWithParam<tuple<std::string, Target> > Test_Darknet_nets_async; typedef testing::TestWithParam<tuple<std::string, Target> > Test_Darknet_nets_async;
TEST_P(Test_Darknet_nets_async, Accuracy) TEST_P(Test_Darknet_nets_async, Accuracy)
......
...@@ -361,7 +361,7 @@ TEST(Net, forwardAndRetrieve) ...@@ -361,7 +361,7 @@ TEST(Net, forwardAndRetrieve)
} }
#ifdef HAVE_INF_ENGINE #ifdef HAVE_INF_ENGINE
static const std::chrono::milliseconds async_timeout(500); static const std::chrono::milliseconds async_timeout(10000);
// This test runs network in synchronous mode for different inputs and then // This test runs network in synchronous mode for different inputs and then
// runs the same model asynchronously for the same inputs. // runs the same model asynchronously for the same inputs.
......
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