- OpenCV => 4.4.0
- Operating System / Platform => Windows 64 Bit or Ubuntu 18.04
- Compiler => Visual Studio 2019 or GCC
Detailed description
LeakyReLU is not supported in the OpenCV DNN modules Tensorflow models importer. I am exploring the source code of tf_importer.cpp and I found something similar to the possible LeakyReLU activation read implementation (mentioned from the line 1575):
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else if (type == "Mul" || type == "RealDiv") |
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{ |
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int constId = -1; |
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for(int ii = 0; ii < layer.input_size(); ++ii) |
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{ |
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Pin input = parsePin(layer.input(ii)); |
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if (value_id.find(input.name) != value_id.end()) |
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{ |
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constId = ii; |
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break; |
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} |
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} |
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CV_Assert((constId != -1) || (layer.input_size() == 2)); |
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if (constId != -1) |
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{ |
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// Multiplication by constant. |
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CV_Assert(layer.input_size() == 2); |
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Mat scaleMat = getTensorContent(getConstBlob(layer, value_id)); |
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CV_Assert(scaleMat.type() == CV_32FC1); |
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if (type == "RealDiv") |
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{ |
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if (constId == 0) |
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CV_Error(Error::StsNotImplemented, "Division of constant over variable"); |
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scaleMat = 1.0f / scaleMat; |
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} |
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int id; |
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if (scaleMat.total() == 1) // is a scalar. |
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{ |
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// Try to match with a LeakyRelu: |
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// node { |
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// name: "LeakyRelu/mul" |
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// op: "Mul" |
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// input: "LeakyRelu/alpha" |
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// input: "input" |
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// } |
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// node { |
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// name: "LeakyRelu/Maximum" |
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// op: "Maximum" |
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// input: "LeakyRelu/mul" |
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// input: "input" |
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// } |
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StrIntVector next_layers = getNextLayers(net, name, "Maximum"); |
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if (!next_layers.empty()) |
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{ |
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int maximumLayerIdx = next_layers[0].second; |
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CV_Assert(net.node(maximumLayerIdx).input_size() == 2); |
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// The input from the Mul layer can also be at index 1. |
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int mulInputIdx = (net.node(maximumLayerIdx).input(0) == name) ? 0 : 1; |
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ExcludeLayer(net, maximumLayerIdx, mulInputIdx, false); |
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layers_to_ignore.insert(next_layers[0].first); |
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layerParams.set("negative_slope", scaleMat.at<float>(0)); |
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id = dstNet.addLayer(name, "ReLU", layerParams); |
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} |
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else |
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{ |
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// Just a multiplication. |
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layerParams.set("scale", scaleMat.at<float>(0)); |
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id = dstNet.addLayer(name, "Power", layerParams); |
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} |
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} |
Although, this code is not near the actual activation function section (I am not stating this, LeakyReLU might not necessarily be here :-) ) :
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else if (type == "Abs" || type == "Tanh" || type == "Sigmoid" || |
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type == "Relu" || type == "Elu" || |
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type == "Identity" || type == "Relu6") |
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{ |
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std::string dnnType = type; |
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if (type == "Abs") dnnType = "AbsVal"; |
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else if (type == "Tanh") dnnType = "TanH"; |
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else if (type == "Relu") dnnType = "ReLU"; |
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else if (type == "Relu6") dnnType = "ReLU6"; |
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else if (type == "Elu") dnnType = "ELU"; |
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int id = dstNet.addLayer(name, dnnType, layerParams); |
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layer_id[name] = id; |
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connectToAllBlobs(layer_id, dstNet, parsePin(layer.input(0)), id, layer.input_size()); |
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} |
Maybe there will be a possibility to move/copy that chunk of the code near the activation function 'if/else' section to enhance OpenCV DNN modules Tensorflow reader with LeakyReLU support?
If it would possibly settle in the mentioned place (near activation functions if/else section) I would work on the implementation :)