From 440a937d24dcc0cbb60edd35d9d764d2041e5744 Mon Sep 17 00:00:00 2001 From: Alexander Alekhin Date: Tue, 1 Oct 2019 13:31:57 +0300 Subject: [PATCH] dnn: increase async test timeout --- modules/dnn/misc/python/test/test_dnn.py | 2 +- modules/dnn/test/test_darknet_importer.cpp | 2 +- modules/dnn/test/test_misc.cpp | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/modules/dnn/misc/python/test/test_dnn.py b/modules/dnn/misc/python/test/test_dnn.py index 600106d19f..c07f8b9591 100644 --- a/modules/dnn/misc/python/test/test_dnn.py +++ b/modules/dnn/misc/python/test/test_dnn.py @@ -169,7 +169,7 @@ class dnn_test(NewOpenCVTests): normAssertDetections(self, ref, out, 0.5, scoresDiff, iouDiff) 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)) 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) diff --git a/modules/dnn/test/test_darknet_importer.cpp b/modules/dnn/test/test_darknet_importer.cpp index e038652e2f..26637ebbe6 100644 --- a/modules/dnn/test/test_darknet_importer.cpp +++ b/modules/dnn/test/test_darknet_importer.cpp @@ -329,7 +329,7 @@ TEST_P(Test_Darknet_nets, TinyYoloVoc) } #ifdef HAVE_INF_ENGINE -static const std::chrono::milliseconds async_timeout(500); +static const std::chrono::milliseconds async_timeout(10000); typedef testing::TestWithParam > Test_Darknet_nets_async; TEST_P(Test_Darknet_nets_async, Accuracy) diff --git a/modules/dnn/test/test_misc.cpp b/modules/dnn/test/test_misc.cpp index 6d2dab1a8b..e2a6af735b 100644 --- a/modules/dnn/test/test_misc.cpp +++ b/modules/dnn/test/test_misc.cpp @@ -361,7 +361,7 @@ TEST(Net, forwardAndRetrieve) } #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 // runs the same model asynchronously for the same inputs.