From 54f0616a13b9bde2c17d71096303ba3faab0f555 Mon Sep 17 00:00:00 2001
From: Dmitry Kurtaev <dmitry.kurtaev+github@gmail.com>
Date: Fri, 11 Aug 2017 16:23:41 +0300
Subject: [PATCH] Deconvolution layer from TensorFlow

---
 modules/dnn/src/tensorflow/tf_importer.cpp | 44 ++++++++++++++++++++++
 modules/dnn/test/test_tf_importer.cpp      |  5 +++
 2 files changed, 49 insertions(+)

diff --git a/modules/dnn/src/tensorflow/tf_importer.cpp b/modules/dnn/src/tensorflow/tf_importer.cpp
index 0f07f33d3d..6c5faa4caa 100644
--- a/modules/dnn/src/tensorflow/tf_importer.cpp
+++ b/modules/dnn/src/tensorflow/tf_importer.cpp
@@ -863,6 +863,50 @@ void TFImporter::populateNet(Net dstNet)
             // one input only
             connect(layer_id, dstNet, parsePin(layer.input(0)), id, 0);
         }
+        else if (type == "Conv2DBackpropInput")
+        {
+            // op: "Conv2DBackpropInput"
+            // input: "conv2d_transpose/output_shape"
+            // input: "weights"
+            // input: "input"
+            if (layer.input_size() != 3)
+                CV_Error(Error::StsNotImplemented,
+                         "Expected output shape, weights and input nodes");
+
+            layerParams.set("bias_term", false);
+            layerParams.blobs.resize(1);
+
+            StrIntVector next_layers = getNextLayers(net, name, "BiasAdd");
+            if (next_layers.size() == 1)
+            {
+                layerParams.set("bias_term", true);
+                layerParams.blobs.resize(2);
+
+                int weights_layer_index = next_layers[0].second;
+
+                blobFromTensor(getConstBlob(net.node(weights_layer_index), value_id), layerParams.blobs[1]);
+                ExcludeLayer(net, weights_layer_index, 0, false);
+                layers_to_ignore[weights_layer_index] = next_layers[0].first;
+            }
+
+            kernelFromTensor(getConstBlob(layer, value_id, 1), layerParams.blobs[0]);
+            // Swap just numbers of input and output channels.
+            std::swap(layerParams.blobs[0].size[0], layerParams.blobs[0].size[1]);
+
+            const int* kshape = layerParams.blobs[0].size.p;
+            layerParams.set("kernel_h", kshape[2]);
+            layerParams.set("kernel_w", kshape[3]);
+            layerParams.set("num_output", kshape[0]);
+
+            setStrides(layerParams, layer);
+            setPadding(layerParams, layer);
+
+            int id = dstNet.addLayer(name, "Deconvolution", layerParams);
+            layer_id[name] = id;
+
+            // one input only
+            connect(layer_id, dstNet, parsePin(layer.input(2)), id, 0);
+        }
         else if (type == "Abs" || type == "Tanh" || type == "Sigmoid" ||
                  type == "Relu" || type == "Elu" || type == "Softmax" ||
                  type == "Identity")
diff --git a/modules/dnn/test/test_tf_importer.cpp b/modules/dnn/test/test_tf_importer.cpp
index 8a6d495584..9df211cfbc 100644
--- a/modules/dnn/test/test_tf_importer.cpp
+++ b/modules/dnn/test/test_tf_importer.cpp
@@ -125,4 +125,9 @@ TEST(Test_TensorFlow, pooling)
     runTensorFlowNet("max_pool_odd_same");
 }
 
+TEST(Test_TensorFlow, deconvolution)
+{
+    runTensorFlowNet("deconvolution");
+}
+
 }