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• ConvolutionLayer.java

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org.bytedeco.opencv.opencv_dnn.ConvolutionLayer Maven / Gradle / Ivy

// Targeted by JavaCPP version 1.5.10: DO NOT EDIT THIS FILE

package org.bytedeco.opencv.opencv_dnn;

import java.nio.*;
import org.bytedeco.javacpp.*;
import org.bytedeco.javacpp.annotation.*;

import static org.bytedeco.javacpp.presets.javacpp.*;
import static org.bytedeco.openblas.global.openblas_nolapack.*;
import static org.bytedeco.openblas.global.openblas.*;
import org.bytedeco.opencv.opencv_core.*;
import static org.bytedeco.opencv.global.opencv_core.*;
import org.bytedeco.opencv.opencv_imgproc.*;
import static org.bytedeco.opencv.global.opencv_imgproc.*;

import static org.bytedeco.opencv.global.opencv_dnn.*;


    @Namespace("cv::dnn") @NoOffset @Properties(inherit = org.bytedeco.opencv.presets.opencv_dnn.class)
public class ConvolutionLayer extends BaseConvolutionLayer {
        static { Loader.load(); }
        /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
        public ConvolutionLayer(Pointer p) { super(p); }
    
        public static native @Ptr BaseConvolutionLayer create(@Const @ByRef LayerParams params);
        public native @Cast("bool") boolean fusedActivation(); public native ConvolutionLayer fusedActivation(boolean setter);
        public native @Cast("bool") boolean fusedAdd(); public native ConvolutionLayer fusedAdd(boolean setter);
        public native @Cast("bool") boolean useWinograd(); public native ConvolutionLayer useWinograd(boolean setter); // Flag whether to use Winograd to speed up 3x3 convolution.
    }