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Merge pull request #21608 from zihaomu:depth2space

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DNN: add depth2space and space2depth layer for onnx importer
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OpenCV Pushbot 2022-05-12 08:46:36 +00:00 committed by GitHub
commit dda96264df
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2 changed files with 81 additions and 6 deletions
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81
modules/dnn/src/onnx/onnx_importer.cpp
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@ -175,6 +175,7 @@ private:
void parseSoftMax (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto);
void parseDetectionOutput (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto);
void parseCumSum (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto);
void parseDepthToSpace (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto);
void parseSimpleLayers (LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto);
// Domain: com.microsoft
@ -3183,6 +3184,85 @@ void ONNXImporter::parseCumSum(LayerParams& layerParams, const opencv_onnx::Node
addLayer(layerParams, node_proto);
}
void ONNXImporter::parseDepthToSpace(LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto_)
{
// We parse "DepthToSpace" and "SpaceToDepth" in this function.
opencv_onnx::NodeProto node_proto = node_proto_;
const std::string& layer_type = node_proto.op_type();
CV_Assert(layer_type == "DepthToSpace" || layer_type == "SpaceToDepth");
// Get blocksize
CV_Assert(layerParams.has("blocksize"));
int blocksize = layerParams.get<int>("blocksize");
CV_Assert(blocksize > 0);
// Get mode, only for "DepthToSpace"
std::string modeType = layerParams.get<std::string>("mode", "DCR");
MatShape inpShape = outShapes[node_proto.input(0)];
CV_Assert(inpShape.size() == 4);
int N = inpShape[0], C = inpShape[1], H = inpShape[2], W = inpShape[3];
// Implement DepthToSpace and SpaceToDepth by the Reshape and Permute layer.
std::array<int, 6> shape0, perm;
std::array<int, 4> shape1;
if (layer_type == "DepthToSpace")
{
if (modeType == "DCR")
{
shape0 = {N, blocksize, blocksize, C/(blocksize * blocksize), H, W};
perm = {0, 3, 4, 1, 5, 2};
shape1 = {N, C/(blocksize * blocksize), H * blocksize, W * blocksize};
}
else if (modeType == "CRD")
{
shape0 = {N, C/(blocksize * blocksize), blocksize, blocksize, H, W};
perm = {0, 1, 4, 2, 5, 3};
shape1 = {N, C/(blocksize * blocksize), H * blocksize, W * blocksize};
}
else
CV_Error(Error::StsNotImplemented, "The mode of " + modeType + " in " + layer_type + " Layer is not supported");
}
else // SpaceToDepth
{
shape0 = {N, C, H/blocksize, blocksize, W/blocksize, blocksize};
perm = {0, 3, 5, 1, 2, 4};
shape1 = {N, C * blocksize * blocksize, H/blocksize, W/blocksize};
}
// Step1: Reshape
LayerParams reshapeLp;
reshapeLp.name = layerParams.name + "/reshape";
reshapeLp.type = "Reshape";
CV_Assert(layer_id.find(reshapeLp.name) == layer_id.end());
reshapeLp.set("dim", DictValue::arrayInt(shape0.data(), shape0.size()));
opencv_onnx::NodeProto protoReshape;
protoReshape.add_input(node_proto.input(0));
protoReshape.add_output(reshapeLp.name);
addLayer(reshapeLp, protoReshape);
// Step2: Transpose
LayerParams permuteLp;
permuteLp.name = layerParams.name + "/permute";
permuteLp.type = "Permute";
CV_Assert(layer_id.find(permuteLp.name) == layer_id.end());
permuteLp.set("order", DictValue::arrayInt(perm.data(), perm.size()));
opencv_onnx::NodeProto protoPermute;
protoPermute.add_input(reshapeLp.name);
protoPermute.add_output(permuteLp.name);
addLayer(permuteLp, protoPermute);
// Step3: Reshape
layerParams.type = "Reshape";
layerParams.set("dim", DictValue::arrayInt(shape1.data(), shape1.size()));
node_proto.set_input(0, permuteLp.name);
addLayer(layerParams, node_proto);
}
void ONNXImporter::parseSimpleLayers(LayerParams& layerParams, const opencv_onnx::NodeProto& node_proto)
{
for (int j = 0; j < node_proto.input_size(); j++) {
@ -3672,6 +3752,7 @@ void ONNXImporter::buildDispatchMap_ONNX_AI(int opset_version)
dispatch["SoftMax"] = dispatch["LogSoftmax"] = &ONNXImporter::parseSoftMax;
dispatch["DetectionOutput"] = &ONNXImporter::parseDetectionOutput;
dispatch["CumSum"] = &ONNXImporter::parseCumSum;
dispatch["SpaceToDepth"] = dispatch["DepthToSpace"] = &ONNXImporter::parseDepthToSpace;
std::vector<std::string> simpleLayers{"Acos", "Acosh", "Asin", "Asinh", "Atan", "Atanh", "Ceil", "Celu", "Cos",
"Cosh", "Dropout", "Erf", "Exp", "Floor", "HardSigmoid", "HardSwish",

6
modules/dnn/test/test_onnx_conformance_layer_parser_denylist.inl.hpp
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@ -96,10 +96,6 @@
"test_cumsum_2d_axis_0",
"test_cumsum_2d_axis_1",
"test_cumsum_2d_negative_axis",
"test_depthtospace_crd_mode",
"test_depthtospace_crd_mode_example",
"test_depthtospace_dcr_mode",
"test_depthtospace_example",
"test_dequantizelinear",
"test_dequantizelinear_axis",
"test_det_2d",
@ -490,8 +486,6 @@
"test_slice_neg_steps",
"test_slice_negative_axes",
"test_slice_start_out_of_bounds",
"test_spacetodepth",
"test_spacetodepth_example",
"test_split_variable_parts_1d",
"test_split_variable_parts_2d",
"test_split_variable_parts_default_axis",