Merge pull request #1017 from arrybn:unpool_layer_fix

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

@@ -412,7 +412,7 @@ namespace dnn
     class CV_EXPORTS_W MaxUnpoolLayer : public Layer
     {
     public:
-        static CV_WRAP Ptr<MaxUnpoolLayer> create(Size unpoolSize);
+        static CV_WRAP Ptr<MaxUnpoolLayer> create(Size poolKernel, Size poolPad, Size poolStride);
     };
 
     class CV_EXPORTS_W ScaleLayer : public Layer

modules/dnn/src/caffe/layer_loaders.cpp

@@ -336,9 +336,10 @@ Ptr<Layer> createLayerFromCaffe<ChannelsPReLULayer>(LayerParams& params)
 template<> //MaxUnpoolLayer specialization
 Ptr<Layer> createLayerFromCaffe<MaxUnpoolLayer>(LayerParams& params)
 {
-   Size outSize(params.get<int>("out_w"),
-                params.get<int>("out_h"));
-   Ptr<MaxUnpoolLayer> l = MaxUnpoolLayer::create(outSize);
+   Size poolKernel(params.get<int>("pool_k_w"), params.get<int>("pool_k_h")),
+        poolPad(params.get<int>("pool_pad_w"), params.get<int>("pool_pad_h")),
+        poolStride(params.get<int>("pool_stride_w"), params.get<int>("pool_stride_h"));
+   Ptr<MaxUnpoolLayer> l = MaxUnpoolLayer::create(poolKernel, poolPad, poolStride);
    l->setParamsFrom(params);
 
    return Ptr<Layer>(l);

modules/dnn/src/layers/max_unpooling_layer.cpp

@@ -16,19 +16,20 @@ namespace cv
 namespace dnn
 {
 
-MaxUnpoolLayerImpl::MaxUnpoolLayerImpl(Size outSize_):
-    outSize(outSize_)
+MaxUnpoolLayerImpl::MaxUnpoolLayerImpl(Size poolKernel_, Size poolPad_, Size poolStride_):
+    poolKernel(poolKernel_),
+    poolPad(poolPad_),
+    poolStride(poolStride_)
 {}
 
 void MaxUnpoolLayerImpl::allocate(const std::vector<Blob*> &inputs, std::vector<Blob> &outputs)
 {
     CV_Assert(inputs.size() == 2);
+    CV_Assert(inputs[0]->total() == inputs[1]->total());
 
     BlobShape outShape = inputs[0]->shape();
-    outShape[2] = outSize.height;
-    outShape[3] = outSize.width;
-
-    CV_Assert(inputs[0]->total() == inputs[1]->total());
+    outShape[2] = (outShape[2] - 1) * poolStride.height + poolKernel.height - 2 * poolPad.height;
+    outShape[3] = (outShape[3] - 1) * poolStride.width + poolKernel.width - 2 * poolPad.width;
 
     outputs.resize(1);
     outputs[0].create(outShape);
@@ -63,9 +64,9 @@ void MaxUnpoolLayerImpl::forward(std::vector<Blob*> &inputs, std::vector<Blob> &
     }
 }
 
-Ptr<MaxUnpoolLayer> MaxUnpoolLayer::create(Size unpoolSize)
+Ptr<MaxUnpoolLayer> MaxUnpoolLayer::create(Size poolKernel, Size poolPad, Size poolStride)
 {
-    return Ptr<MaxUnpoolLayer>(new MaxUnpoolLayerImpl(unpoolSize));
+    return Ptr<MaxUnpoolLayer>(new MaxUnpoolLayerImpl(poolKernel, poolPad, poolStride));
 }
 
 }

modules/dnn/src/layers/max_unpooling_layer.hpp

@@ -22,14 +22,16 @@ namespace dnn
 class MaxUnpoolLayerImpl : public MaxUnpoolLayer
 {
 public:
-    MaxUnpoolLayerImpl(Size outSize_);
+    MaxUnpoolLayerImpl(Size poolKernel_, Size poolPad_, Size poolStride_);
 
     void allocate(const std::vector<Blob*> &inputs, std::vector<Blob> &outputs);
 
     void forward(std::vector<Blob*> &inputs, std::vector<Blob> &outputs);
 
 private:
-    Size outSize;
+    Size poolKernel;
+    Size poolPad;
+    Size poolStride;
 };
 
 }

modules/dnn/src/torch/torch_importer.cpp

@@ -737,14 +737,8 @@ struct TorchImporter : public ::cv::dnn::Importer
             else if (nnName == "SpatialMaxUnpooling")
             {
                 readTorchTable(scalarParams, tensorParams);
-
-                CV_Assert(scalarParams.has("oheight") &&
-                          scalarParams.has("owidth"));
-
                 CV_Assert(tensorParams.count("indices"));
 
-                layerParams.set("out_h", static_cast<int>(scalarParams.get<double>("oheight")));
-                layerParams.set("out_w", static_cast<int>(scalarParams.get<double>("owidth"))/2);
                 layerParams.set("indices_blob_id", tensorParams["indices"].first);
                 curModule->modules.push_back(newModule);
             }
@@ -908,13 +902,10 @@ struct TorchImporter : public ::cv::dnn::Importer
                 return id;
             }
             else if (module->thName == "SpatialMaxUnpooling") {
-                String name = generateLayerName("torchMaxUnpooling");
-                int id = net.addLayer(name, "MaxUnpool", module->params);
-                net.connect(prevLayerId, 0, id, 0);
-
                 CV_Assert(module->params.has("indices_blob_id"));
-
                 int indicesBlobId = module->params.get<int>("indices_blob_id");
+                std::pair<int, Module*> poolingLayer;
+                poolingLayer.first = -1;
 
                 for(int i = 0; i < addedModules.size(); i++)
                 {
@@ -922,11 +913,25 @@ struct TorchImporter : public ::cv::dnn::Importer
                         addedModules[i].second->params.has("indices_blob_id") &&
                         addedModules[i].second->params.get<int>("indices_blob_id") == indicesBlobId)
                     {
-                        net.connect(addedModules[i].first, 1, id, 1);
+                        poolingLayer = addedModules[i];
                         break;
                     }
                 }
 
+                module->params.set("pool_k_h", poolingLayer.second->params.get<int>("kernel_h"));
+                module->params.set("pool_k_w", poolingLayer.second->params.get<int>("kernel_w"));
+                module->params.set("pool_stride_h", poolingLayer.second->params.get<int>("stride_h"));
+                module->params.set("pool_stride_w", poolingLayer.second->params.get<int>("stride_w"));
+                module->params.set("pool_pad_h", poolingLayer.second->params.get<int>("pad_h"));
+                module->params.set("pool_pad_w", poolingLayer.second->params.get<int>("pad_w"));
+
+                String name = generateLayerName("torchMaxUnpooling");
+                int id = net.addLayer(name, "MaxUnpool", module->params);
+                net.connect(prevLayerId, 0, id, 0);
+
+                CV_Assert(poolingLayer.first != -1);
+                net.connect(poolingLayer.first, 1, id, 1);
+
                 return id;
             }
         }