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