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dnn(onnx): fix Resize inputs handling
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@ -2348,6 +2348,7 @@ void ONNXImporter::parseConcat(LayerParams& layerParams, const opencv_onnx::Node
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addLayer(layerParams, node_proto);
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}
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// https://github.com/onnx/onnx/blob/master/docs/Operators.md#Resize
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void ONNXImporter::parseResize(LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto)
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{
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for (int i = 1; i < node_proto.input_size(); i++)
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@ -2368,30 +2369,38 @@ void ONNXImporter::parseResize(LayerParams& layerParams, const opencv_onnx::Node
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if (layerParams.get<String>("mode") == "linear" && framework_name == "pytorch")
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layerParams.set("mode", "opencv_linear");
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// input = [X, scales], [X, roi, scales] or [x, roi, scales, sizes]
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int foundScaleId = hasDynamicShapes ? node_proto.input_size() - 1
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: node_proto.input_size() > 2 ? 2 : 1;
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// opset-10: input = [X, scales]
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// opset-11: input = [X, roi, scales] or [x, roi, scales, sizes]
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int scalesInputId = node_proto.input_size() == 2 ? 1 : 2;
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Mat scales = getBlob(node_proto, foundScaleId);
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if (scales.total() == 4)
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Mat scales = getBlob(node_proto, scalesInputId);
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if (!scales.empty())
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{
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CV_CheckEQ(scales.total(), (size_t)4, "HCHW layout is expected");
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layerParams.set("zoom_factor_y", scales.at<float>(2));
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layerParams.set("zoom_factor_x", scales.at<float>(3));
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}
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else
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else if (node_proto.input_size() >= 4) // opset-11
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{
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const std::string& inputLast = node_proto.input(node_proto.input_size() - 1);
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if (constBlobs.find(inputLast) != constBlobs.end())
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const std::string& inputSizes = node_proto.input(3);
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if (constBlobs.find(inputSizes) != constBlobs.end())
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{
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Mat shapes = getBlob(inputLast);
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CV_CheckEQ(shapes.size[0], 4, "");
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CV_CheckEQ(shapes.size[1], 1, "");
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Mat shapes = getBlob(inputSizes);
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CV_CheckEQ(shapes.total(), (size_t)4, "HCHW layout is expected");
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CV_CheckDepth(shapes.depth(), shapes.depth() == CV_32S || shapes.depth() == CV_32F, "");
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if (shapes.depth() == CV_32F)
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shapes.convertTo(shapes, CV_32S);
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layerParams.set("width", shapes.at<int>(3));
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layerParams.set("height", shapes.at<int>(2));
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}
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else
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{
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CV_Error(Error::StsNotImplemented, cv::format("ONNX/Resize: doesn't support dynamic non-constant 'sizes' input: %s", inputSizes.c_str()));
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}
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}
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else
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{
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CV_Error(Error::StsNotImplemented, "ONNX/Resize: can't find neither 'scale' nor destination sizes parameters");
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}
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replaceLayerParam(layerParams, "mode", "interpolation");
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addLayer(layerParams, node_proto);
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