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dnn: use AsyncArray

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This commit is contained in:
Alexander Alekhin
2019-05-01 11:51:12 +00:00
parent 9340af1a8a
commit 132253c9f3
10 changed files with 66 additions and 124 deletions
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modules/dnn/misc/python/test/test_dnn.py
+7 -8
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@@ -69,8 +69,9 @@ def printParams(backend, target):
class dnn_test(NewOpenCVTests):
def __init__(self, *args, **kwargs):
super(dnn_test, self).__init__(*args, **kwargs)
def setUp(self):
super(dnn_test, self).setUp()
self.dnnBackendsAndTargets = [
[cv.dnn.DNN_BACKEND_OPENCV, cv.dnn.DNN_TARGET_CPU],
]
@@ -168,7 +169,7 @@ class dnn_test(NewOpenCVTests):
normAssertDetections(self, ref, out, 0.5, scoresDiff, iouDiff)
def test_async(self):
timeout = 5000 # in milliseconds
timeout = 500*10**6 # in nanoseconds (500ms)
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)
@@ -209,11 +210,9 @@ class dnn_test(NewOpenCVTests):
outs.insert(0, netAsync.forwardAsync())
for i in reversed(range(numInputs)):
ret = outs[i].wait_for(timeout)
if ret == 1:
self.fail("Timeout")
self.assertEqual(ret, 0) # is ready
normAssert(self, refs[i], outs[i].get(), 'Index: %d' % i, 1e-10)
ret, result = outs[i].get(timeoutNs=float(timeout))
self.assertTrue(ret)
normAssert(self, refs[i], result, 'Index: %d' % i, 1e-10)
if __name__ == '__main__':