Nearest neighbor resize layer

modules/dnn/include/opencv2/dnn/all_layers.hpp

@@ -539,6 +539,17 @@ CV__DNN_EXPERIMENTAL_NS_BEGIN
         static Ptr<NormalizeBBoxLayer> create(const LayerParams& params);
     };
 
+    /**
+     * @brief Resize input 4-dimensional blob by nearest neghbor strategy.
+     *
+     * Layer is used to support TensorFlow's resize_nearest_neighbor op.
+     */
+    class CV_EXPORTS ResizeNearestNeighborLayer : public Layer
+    {
+    public:
+        static Ptr<ResizeNearestNeighborLayer> create(const LayerParams& params);
+    };
+
 //! @}
 //! @}
 CV__DNN_EXPERIMENTAL_NS_END

modules/dnn/src/init.cpp

@@ -83,6 +83,7 @@ void initializeLayerFactory()
     CV_DNN_REGISTER_LAYER_CLASS(Concat,         ConcatLayer);
     CV_DNN_REGISTER_LAYER_CLASS(Reshape,        ReshapeLayer);
     CV_DNN_REGISTER_LAYER_CLASS(Flatten,        FlattenLayer);
+    CV_DNN_REGISTER_LAYER_CLASS(ResizeNearestNeighbor, ResizeNearestNeighborLayer);
 
     CV_DNN_REGISTER_LAYER_CLASS(Convolution,    ConvolutionLayer);
     CV_DNN_REGISTER_LAYER_CLASS(Deconvolution,  DeconvolutionLayer);

modules/dnn/src/layers/resize_nearest_neighbor_layer.cpp

@@ -0,0 +1,71 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+// Copyright (C) 2017, Intel Corporation, all rights reserved.
+// Third party copyrights are property of their respective owners.
+#include "../precomp.hpp"
+#include "layers_common.hpp"
+#include <opencv2/imgproc.hpp>
+
+namespace cv { namespace dnn {
+
+class ResizeNearestNeighborLayerImpl : public ResizeNearestNeighborLayer
+{
+public:
+    ResizeNearestNeighborLayerImpl(const LayerParams& params)
+    {
+        setParamsFrom(params);
+        CV_Assert(params.has("width"), params.has("height"));
+        outWidth = params.get<float>("width");
+        outHeight = params.get<float>("height");
+        alignCorners = params.get<bool>("align_corners", false);
+        if (alignCorners)
+            CV_Error(Error::StsNotImplemented, "Nearest neighborhood resize with align_corners=true is not implemented");
+    }
+
+    bool getMemoryShapes(const std::vector<MatShape> &inputs,
+                         const int requiredOutputs,
+                         std::vector<MatShape> &outputs,
+                         std::vector<MatShape> &internals) const
+    {
+        CV_Assert(inputs.size() == 1, inputs[0].size() == 4);
+        outputs.resize(1, inputs[0]);
+        outputs[0][2] = outHeight;
+        outputs[0][3] = outWidth;
+        // We can work in-place (do nothing) if input shape == output shape.
+        return (outputs[0][2] == inputs[0][2]) && (outputs[0][3] == inputs[0][3]);
+    }
+
+    void forward(std::vector<Mat*> &inputs, std::vector<Mat> &outputs, std::vector<Mat> &internals)
+    {
+        CV_TRACE_FUNCTION();
+        CV_TRACE_ARG_VALUE(name, "name", name.c_str());
+
+        if (outHeight == inputs[0]->size[2] && outWidth == inputs[0]->size[3])
+            return;
+
+        Mat& inp = *inputs[0];
+        Mat& out = outputs[0];
+        for (size_t n = 0; n < inputs[0]->size[0]; ++n)
+        {
+            for (size_t ch = 0; ch < inputs[0]->size[1]; ++ch)
+            {
+                resize(getPlane(inp, n, ch), getPlane(out, n, ch),
+                       Size(outWidth, outHeight), 0, 0, INTER_NEAREST);
+            }
+        }
+    }
+private:
+    int outWidth, outHeight;
+    bool alignCorners;
+};
+
+
+Ptr<ResizeNearestNeighborLayer> ResizeNearestNeighborLayer::create(const LayerParams& params)
+{
+    return Ptr<ResizeNearestNeighborLayer>(new ResizeNearestNeighborLayerImpl(params));
+}
+
+}  // namespace dnn
+}  // namespace cv

modules/dnn/src/tensorflow/tf_importer.cpp

@@ -1132,6 +1132,22 @@ void TFImporter::populateNet(Net dstNet)
             // one input only
             connect(layer_id, dstNet, parsePin(layer.input(1)), id, 0);
         }
+        else if (type == "ResizeNearestNeighbor")
+        {
+            Mat outSize = getTensorContent(getConstBlob(layer, value_id, 1));
+            CV_Assert(outSize.type() == CV_32SC1, outSize.total() == 2);
+
+            layerParams.set("height", outSize.at<int>(0, 0));
+            layerParams.set("width", outSize.at<int>(0, 1));
+
+            if (hasLayerAttr(layer, "align_corners"))
+                layerParams.set("align_corners", getLayerAttr(layer, "align_corners").b());
+
+            int id = dstNet.addLayer(name, "ResizeNearestNeighbor", layerParams);
+            layer_id[name] = id;
+
+            connect(layer_id, dstNet, parsePin(layer.input(0)), id, 0);
+        }
         else if (type == "Abs" || type == "Tanh" || type == "Sigmoid" ||
                  type == "Relu" || type == "Elu" || type == "Softmax" ||
                  type == "Identity" || type == "Relu6")

modules/dnn/test/test_tf_importer.cpp

@@ -175,4 +175,9 @@ TEST(Test_TensorFlow, split)
     runTensorFlowNet("split_equals");
 }
 
+TEST(Test_TensorFlow, resize_nearest_neighbor)
+{
+    runTensorFlowNet("resize_nearest_neighbor");
+}
+
 }