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Merge pull request #14860 from vonchenplus:ocv_maxpoolgrad

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Alexander Alekhin 2019-07-04 09:57:14 +03:00 committed by GitHub
commit e00b0f6f47
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3 changed files with 36 additions and 5 deletions
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16
modules/dnn/src/layers/max_unpooling_layer.cpp
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@ -43,12 +43,18 @@ public:
std::vector<MatShape> &outputs,
std::vector<MatShape> &internals) const CV_OVERRIDE
{
CV_Assert(inputs.size() == 2);
CV_Assert(inputs.size() == 2 || inputs.size() == 3);
CV_Assert(total(inputs[0]) == total(inputs[1]));
MatShape outShape = inputs[0];
outShape[2] = (outShape[2] - 1) * poolStride.height + poolKernel.height - 2 * poolPad.height;
outShape[3] = (outShape[3] - 1) * poolStride.width + poolKernel.width - 2 * poolPad.width;
MatShape outShape;
if (inputs.size() == 2)
{
outShape = inputs[0];
outShape[2] = (outShape[2] - 1) * poolStride.height + poolKernel.height - 2 * poolPad.height;
outShape[3] = (outShape[3] - 1) * poolStride.width + poolKernel.width - 2 * poolPad.width;
}
else
outShape = inputs[2];
outputs.clear();
outputs.push_back(outShape);
@ -71,7 +77,7 @@ public:
inputs_arr.getMatVector(inputs);
outputs_arr.getMatVector(outputs);
CV_Assert(inputs.size() == 2);
CV_Assert(inputs.size() == 2 || inputs.size() == 3);
Mat& input = inputs[0];
Mat& indices = inputs[1];

18
modules/dnn/src/tensorflow/tf_importer.cpp
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@ -1370,6 +1370,24 @@ void TFImporter::populateNet(Net dstNet)
connectToAllBlobs(layer_id, dstNet, parsePin(layer.input(0)), id, layer.input_size());
}
else if (type == "MaxPoolGrad")
{
CV_Assert(layer.input_size() == 3);
layerParams.set("pool_k_h", 0);
layerParams.set("pool_k_w", 0);
layerParams.set("pool_stride_h", 0);
layerParams.set("pool_stride_w", 0);
layerParams.set("pool_pad_h", 0);
layerParams.set("pool_pad_w", 0);
int id = dstNet.addLayer(name, "MaxUnpool", layerParams);
layer_id[name] = id;
connect(layer_id, dstNet, parsePin(layer.input(2)), id, 0);
connect(layer_id, dstNet, parsePin(layer.input(1) + ":1"), id, 1);
connect(layer_id, dstNet, parsePin(layer.input(0)), id, 2);
}
else if (type == "Placeholder")
{
if (!hasLayerAttr(layer, "dtype") ||

7
modules/dnn/test/test_tf_importer.cpp
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@ -218,6 +218,13 @@ TEST_P(Test_TensorFlow_layers, pooling)
runTensorFlowNet("reduce_mean"); // an average pooling over all spatial dimensions.
}
TEST_P(Test_TensorFlow_layers, max_pool_grad)
{
if (backend == DNN_BACKEND_INFERENCE_ENGINE)
applyTestTag(CV_TEST_TAG_DNN_SKIP_IE);
runTensorFlowNet("max_pool_grad");
}
// TODO: fix tests and replace to pooling
TEST_P(Test_TensorFlow_layers, ave_pool_same)
{