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Fix autodetection of input size for dnn networks
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@ -2506,7 +2506,9 @@ struct Net::Impl
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{
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{
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std::vector<LayerPin>& inputLayerIds = layers[id].inputBlobsId;
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std::vector<LayerPin>& inputLayerIds = layers[id].inputBlobsId;
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if (inOutShapes[0].in[0].empty() && !layers[0].outputBlobs.empty())
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if (id == 0 && inOutShapes[id].in[0].empty())
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{
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if (!layers[0].outputBlobs.empty())
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{
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{
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ShapesVec shapes;
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ShapesVec shapes;
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for (int i = 0; i < layers[0].outputBlobs.size(); i++)
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for (int i = 0; i < layers[0].outputBlobs.size(); i++)
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@ -2517,6 +2519,12 @@ struct Net::Impl
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}
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}
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inOutShapes[0].in = shapes;
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inOutShapes[0].in = shapes;
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}
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}
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else
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{
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inOutShapes[0].out.clear();
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return;
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}
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}
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if (inOutShapes[id].in.empty())
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if (inOutShapes[id].in.empty())
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{
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{
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@ -105,8 +105,7 @@ TEST_P(Test_Model, Classify)
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}
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}
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// disabled: https://github.com/opencv/opencv/pull/15593
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TEST_P(Test_Model, DetectRegion)
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TEST_P(Test_Model, DISABLED_DetectRegion)
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{
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{
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applyTestTag(CV_TEST_TAG_LONG, CV_TEST_TAG_MEMORY_1GB);
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applyTestTag(CV_TEST_TAG_LONG, CV_TEST_TAG_MEMORY_1GB);
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