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/*
* Copyright (C) 2016-2017 Samuel Audet
*
* Licensed either under the Apache License, Version 2.0, or (at your option)
* under the terms of the GNU General Public License as published by
* the Free Software Foundation (subject to the "Classpath" exception),
* either version 2, or any later version (collectively, the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
* http://www.gnu.org/licenses/
* http://www.gnu.org/software/classpath/license.html
*
* or as provided in the LICENSE.txt file that accompanied this code.
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.bytedeco.javacpp.presets;
import org.bytedeco.javacpp.annotation.Platform;
import org.bytedeco.javacpp.annotation.Properties;
import org.bytedeco.javacpp.tools.Info;
import org.bytedeco.javacpp.tools.InfoMap;
import org.bytedeco.javacpp.tools.InfoMapper;
/**
*
* @author Samuel Audet
*/
@Properties(inherit = opencv_imgproc.class, value = {
@Platform(include = {"", "","",
"", "", ""},
link = "[email protected]"),
@Platform(value = "windows", link = "opencv_dnn340")},
target = "org.bytedeco.javacpp.opencv_dnn")
public class opencv_dnn implements InfoMapper {
public void map(InfoMap infoMap) {
infoMap.put(new Info("CV__DNN_EXPERIMENTAL_NS_BEGIN", "CV__DNN_EXPERIMENTAL_NS_END").cppTypes().annotations())
.put(new Info("is_neg").javaNames("is_neg").annotations("@Namespace(\"cv::dnn\")"))
.put(new Info("cv::dnn::MatShape").annotations("@StdVector").pointerTypes("IntPointer"))
.put(new Info("std::vector").pointerTypes("MatShapeVector").define())
.put(new Info("std::vector >").pointerTypes("MatShapeVectorVector").define())
.put(new Info("std::vector >").pointerTypes("RangeVectorVector").define())
.put(new Info("cv::dnn::LRNLayer::type").javaNames("lrnType"))
.put(new Info("cv::dnn::PoolingLayer::type").javaNames("poolingType"))
.put(new Info("cv::dnn::BlankLayer", "cv::dnn::LSTMLayer", "cv::dnn::RNNLayer", "cv::dnn::BaseConvolutionLayer",
"cv::dnn::ConvolutionLayer", "cv::dnn::DeconvolutionLayer", "cv::dnn::LRNLayer", "cv::dnn::PoolingLayer",
"cv::dnn::SoftmaxLayer", "cv::dnn::InnerProductLayer", "cv::dnn::MVNLayer", "cv::dnn::ReshapeLayer",
"cv::dnn::FlattenLayer", "cv::dnn::ConcatLayer", "cv::dnn::SplitLayer", "cv::dnn::SliceLayer",
"cv::dnn::PermuteLayer", "cv::dnn::PaddingLayer", "cv::dnn::ActivationLayer", "cv::dnn::ReLULayer",
"cv::dnn::ChannelsPReLULayer", "cv::dnn::ELULayer", "cv::dnn::TanHLayer", "cv::dnn::SigmoidLayer",
"cv::dnn::BNLLLayer", "cv::dnn::AbsLayer", "cv::dnn::PowerLayer", "cv::dnn::CropLayer", "cv::dnn::EltwiseLayer",
"cv::dnn::BatchNormLayer", "cv::dnn::MaxUnpoolLayer", "cv::dnn::ScaleLayer", "cv::dnn::ShiftLayer",
"cv::dnn::PriorBoxLayer", "cv::dnn::DetectionOutputLayer", "cv::dnn::NormalizeBBoxLayer", "cv::dnn::ProposalLayer",
"cv::dnn::ReLU6Layer", "cv::dnn::ReorgLayer", "cv::dnn::RegionLayer", "cv::dnn::ResizeNearestNeighborLayer").purify())
.put(new Info("cv::dnn::Net::forward(cv::dnn::Net::LayerId, cv::dnn::Net::LayerId)",
"cv::dnn::Net::forward(cv::dnn::Net::LayerId*, cv::dnn::Net::LayerId*)",
"cv::dnn::Net::forwardOpt(cv::dnn::Net::LayerId)",
"cv::dnn::Net::forwardOpt(cv::dnn::Net::LayerId*)").skip())
.put(new Info("std::vector").pointerTypes("MatPointerVector").define())
.put(new Info("cv::dnn::Layer* (*)(cv::dnn::LayerParams&)").annotations("@Convention(value=\"\", extern=\"C++\")"));
}
}