Chiebot-Mirror
/
opencv
8
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Merge pull request #21259 from rogday:random_fixes

Browse Source
pull/21261/head
Alexander Alekhin 3 years ago
parent 19cfaa2be7 e97c7e042b
commit e7c5120682
3 changed files with 49 additions and 13 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 9
      modules/dnn/src/layers/padding_layer.cpp
  2. 48
      modules/dnn/src/onnx/onnx_importer.cpp
  3. 5
      modules/dnn/test/test_onnx_conformance_layer_parser_denylist.inl.hpp

9
modules/dnn/src/layers/padding_layer.cpp
Unescape View File

@ -130,12 +130,13 @@ public:
outputs[0].setTo(paddingValue);
inputs[0].copyTo(outputs[0](dstRanges));
}
else if (paddingType == "reflect")
else if (paddingType == "reflect" || paddingType == "edge")
{
CV_Assert(inputs.size() == 1);
CV_Assert(outputs.size() == 1);
CV_Assert(inputs[0].dims == 4);
CV_Assert(outputs[0].dims == 4);
int borderType = paddingType == "reflect" ? BORDER_REFLECT_101 : BORDER_REPLICATE;
if (inputs[0].size[0] != outputs[0].size[0] || inputs[0].size[1] != outputs[0].size[1])
CV_Error(Error::StsNotImplemented, "Only spatial reflection padding is supported.");
@ -148,8 +149,8 @@ public:
const int padBottom = outHeight - dstRanges[2].end;
const int padLeft = dstRanges[3].start;
const int padRight = outWidth - dstRanges[3].end;
CV_CheckLT(padTop, inpHeight, ""); CV_CheckLT(padBottom, inpHeight, "");
CV_CheckLT(padLeft, inpWidth, ""); CV_CheckLT(padRight, inpWidth, "");
CV_CheckLE(padTop, inpHeight, ""); CV_CheckLE(padBottom, inpHeight, "");
CV_CheckLE(padLeft, inpWidth, ""); CV_CheckLE(padRight, inpWidth, "");
for (size_t n = 0; n < inputs[0].size[0]; ++n)
{
@ -158,7 +159,7 @@ public:
copyMakeBorder(getPlane(inputs[0], n, ch),
getPlane(outputs[0], n, ch),
padTop, padBottom, padLeft, padRight,
BORDER_REFLECT_101);
borderType);
}
}
}

48
modules/dnn/src/onnx/onnx_importer.cpp
Unescape View File

@ -131,6 +131,7 @@ private:
typedef void (ONNXImporter::*ONNXImporterNodeParser)(LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto);
typedef std::map<std::string, ONNXImporterNodeParser> DispatchMap;
void parseMaxUnpool (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto);
void parseMaxPool (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto);
void parseAveragePool (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto);
void parseReduce (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto);
@ -625,6 +626,41 @@ void setCeilMode(LayerParams& layerParams)
}
}
void ONNXImporter::parseMaxUnpool(LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto)
{
layerParams.type = "MaxUnpool";
DictValue kernel_shape = layerParams.get("kernel_size");
CV_Assert(kernel_shape.size() == 2);
layerParams.set("pool_k_w", kernel_shape.get<int>(0));
layerParams.set("pool_k_h", kernel_shape.get<int>(1));
int pool_pad_w = 0, pool_pad_h = 0;
if (layerParams.has("pad"))
{
DictValue pads = layerParams.get("pad");
CV_CheckEQ(pads.size(), 2, "");
pool_pad_w = pads.get<int>(0);
pool_pad_h = pads.get<int>(1);
}
layerParams.set("pool_pad_w", pool_pad_w);
layerParams.set("pool_pad_h", pool_pad_h);
int pool_stride_w = 1, pool_stride_h = 1;
if (layerParams.has("stride"))
{
DictValue strides = layerParams.get("stride");
CV_CheckEQ(strides.size(), 2, "");
pool_stride_w = strides.get<int>(0);
pool_stride_h = strides.get<int>(1);
}
layerParams.set("pool_stride_w", pool_stride_w);
layerParams.set("pool_stride_h", pool_stride_h);
addLayer(layerParams, node_proto);
}
void ONNXImporter::parseMaxPool(LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto)
{
layerParams.type = "Pooling";
@ -659,11 +695,11 @@ void ONNXImporter::parseReduce(LayerParams& layerParams, const opencv_onnx::Node
pool = "AVE";
layerParams.set("pool", pool);
layerParams.set("global_pooling", !layerParams.has("axes"));
bool keepdims = layerParams.get<int>("keepdims", 1) == 1;
if (layerParams.has("axes") && (layer_type == "ReduceMean" || layer_type == "ReduceSum" || layer_type == "ReduceMax"))
{
MatShape inpShape = outShapes[node_proto.input(0)];
DictValue axes = layerParams.get("axes");
bool keepdims = layerParams.get<int>("keepdims");
MatShape targetShape;
std::vector<bool> shouldDelete(inpShape.size(), false);
for (int i = 0; i < axes.size(); i++) {
@ -771,7 +807,10 @@ void ONNXImporter::parseReduce(LayerParams& layerParams, const opencv_onnx::Node
}
else if (!layerParams.has("axes") && (layer_type == "ReduceMean" || layer_type == "ReduceSum" || layer_type == "ReduceMax"))
{
CV_CheckEQ(layerParams.get<int>("keepdims"), 0, "layer only supports keepdims = false");
IterShape_t shapeIt = outShapes.find(node_proto.input(0));
CV_Assert(shapeIt != outShapes.end());
const size_t dims = keepdims ? shapeIt->second.size() : 1;
LayerParams reshapeLp;
reshapeLp.name = layerParams.name + "/reshape";
reshapeLp.type = "Reshape";
@ -793,8 +832,8 @@ void ONNXImporter::parseReduce(LayerParams& layerParams, const opencv_onnx::Node
addLayer(poolLp, node_proto);
layerParams.type = "Reshape";
int targetShape[] = {1};
layerParams.set("dim", DictValue::arrayInt(&targetShape[0], 1));
std::vector<int> targetShape(dims, 1);
layerParams.set("dim", DictValue::arrayInt(targetShape.data(), targetShape.size()));
node_proto.set_input(0, node_proto.output(0));
node_proto.set_output(0, layerParams.name);
@ -2341,6 +2380,7 @@ const ONNXImporter::DispatchMap ONNXImporter::buildDispatchMap()
{
DispatchMap dispatch;
dispatch["MaxUnpool"] = &ONNXImporter::parseMaxUnpool;
dispatch["MaxPool"] = &ONNXImporter::parseMaxPool;
dispatch["AveragePool"] = &ONNXImporter::parseAveragePool;
dispatch["GlobalAveragePool"] = dispatch["GlobalMaxPool"] = dispatch["ReduceMean"] = dispatch["ReduceSum"] =

5
modules/dnn/test/test_onnx_conformance_layer_parser_denylist.inl.hpp
Unescape View File

@ -277,7 +277,6 @@
"test_max_uint8",
"test_maxpool_2d_uint8",
"test_maxunpool_export_with_output_shape",
"test_maxunpool_export_without_output_shape",
"test_mean_example",
"test_mean_one_input",
"test_mean_two_inputs",
@ -436,10 +435,6 @@
"test_reduce_log_sum_exp_negative_axes_keepdims_example",
"test_reduce_log_sum_exp_negative_axes_keepdims_random",
"test_reduce_log_sum_negative_axes",
"test_reduce_max_default_axes_keepdim_example",
"test_reduce_max_default_axes_keepdims_random",
"test_reduce_mean_default_axes_keepdims_example",
"test_reduce_mean_default_axes_keepdims_random",
"test_reduce_min_default_axes_keepdims_example",
"test_reduce_min_default_axes_keepdims_random",
"test_reduce_min_do_not_keepdims_example",

Write Preview
Loading…
Cancel
Save