d6/d39/samples_2dnn_2colorization_8cpp-example.html

// This file is part of OpenCV project.

// It is subject to the license terms in the LICENSE file found in the top-level directory

// of this distribution and at http://opencv.org/license.html


#include <opencv2/dnn.hpp>

#include <opencv2/imgproc.hpp>

#include <opencv2/highgui.hpp>

#include <iostream>


using namespace cv;

using namespace cv::dnn;

using namespace std;


// the 313 ab cluster centers from pts_in_hull.npy (already transposed)

static float hull_pts[] = {

    -90., -90., -90., -90., -90., -80., -80., -80., -80., -80., -80., -80., -80., -70., -70., -70., -70., -70., -70., -70., -70.,

    -70., -70., -60., -60., -60., -60., -60., -60., -60., -60., -60., -60., -60., -60., -50., -50., -50., -50., -50., -50., -50., -50.,

    -50., -50., -50., -50., -50., -50., -40., -40., -40., -40., -40., -40., -40., -40., -40., -40., -40., -40., -40., -40., -40., -30.,

    -30., -30., -30., -30., -30., -30., -30., -30., -30., -30., -30., -30., -30., -30., -30., -20., -20., -20., -20., -20., -20., -20.,

    -20., -20., -20., -20., -20., -20., -20., -20., -20., -10., -10., -10., -10., -10., -10., -10., -10., -10., -10., -10., -10., -10.,

    -10., -10., -10., -10., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 10., 10., 10., 10., 10., 10., 10.,

    10., 10., 10., 10., 10., 10., 10., 10., 10., 10., 10., 20., 20., 20., 20., 20., 20., 20., 20., 20., 20., 20., 20., 20., 20., 20.,

    20., 20., 20., 30., 30., 30., 30., 30., 30., 30., 30., 30., 30., 30., 30., 30., 30., 30., 30., 30., 30., 30., 40., 40., 40., 40.,

    40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 40., 50., 50., 50., 50., 50., 50., 50., 50., 50., 50.,

    50., 50., 50., 50., 50., 50., 50., 50., 50., 60., 60., 60., 60., 60., 60., 60., 60., 60., 60., 60., 60., 60., 60., 60., 60., 60.,

    60., 60., 60., 70., 70., 70., 70., 70., 70., 70., 70., 70., 70., 70., 70., 70., 70., 70., 70., 70., 70., 70., 70., 80., 80., 80.,

    80., 80., 80., 80., 80., 80., 80., 80., 80., 80., 80., 80., 80., 80., 80., 80., 90., 90., 90., 90., 90., 90., 90., 90., 90., 90.,

    90., 90., 90., 90., 90., 90., 90., 90., 90., 100., 100., 100., 100., 100., 100., 100., 100., 100., 100., 50., 60., 70., 80., 90.,

    20., 30., 40., 50., 60., 70., 80., 90., 0., 10., 20., 30., 40., 50., 60., 70., 80., 90., -20., -10., 0., 10., 20., 30., 40., 50.,

    60., 70., 80., 90., -30., -20., -10., 0., 10., 20., 30., 40., 50., 60., 70., 80., 90., 100., -40., -30., -20., -10., 0., 10., 20.,

    30., 40., 50., 60., 70., 80., 90., 100., -50., -40., -30., -20., -10., 0., 10., 20., 30., 40., 50., 60., 70., 80., 90., 100., -50.,

    -40., -30., -20., -10., 0., 10., 20., 30., 40., 50., 60., 70., 80., 90., 100., -60., -50., -40., -30., -20., -10., 0., 10., 20.,

    30., 40., 50., 60., 70., 80., 90., 100., -70., -60., -50., -40., -30., -20., -10., 0., 10., 20., 30., 40., 50., 60., 70., 80., 90.,

    100., -80., -70., -60., -50., -40., -30., -20., -10., 0., 10., 20., 30., 40., 50., 60., 70., 80., 90., -80., -70., -60., -50.,

    -40., -30., -20., -10., 0., 10., 20., 30., 40., 50., 60., 70., 80., 90., -90., -80., -70., -60., -50., -40., -30., -20., -10.,

    0., 10., 20., 30., 40., 50., 60., 70., 80., 90., -100., -90., -80., -70., -60., -50., -40., -30., -20., -10., 0., 10., 20., 30.,

    40., 50., 60., 70., 80., 90., -100., -90., -80., -70., -60., -50., -40., -30., -20., -10., 0., 10., 20., 30., 40., 50., 60., 70.,

    80., -110., -100., -90., -80., -70., -60., -50., -40., -30., -20., -10., 0., 10., 20., 30., 40., 50., 60., 70., 80., -110., -100.,

    -90., -80., -70., -60., -50., -40., -30., -20., -10., 0., 10., 20., 30., 40., 50., 60., 70., 80., -110., -100., -90., -80., -70.,

    -60., -50., -40., -30., -20., -10., 0., 10., 20., 30., 40., 50., 60., 70., -110., -100., -90., -80., -70., -60., -50., -40., -30.,

    -20., -10., 0., 10., 20., 30., 40., 50., 60., 70., -90., -80., -70., -60., -50., -40., -30., -20., -10., 0.

};


int main(int argc, char **argv)

{

    const string about =

        "This sample demonstrates recoloring grayscale images with dnn.\n"

        "This program is based on:\n"

        "  http://richzhang.github.io/colorization\n"

        "  https://github.com/richzhang/colorization\n"

        "Download caffemodel and prototxt files:\n"

        "  http://eecs.berkeley.edu/~rich.zhang/projects/2016_colorization/files/demo_v2/colorization_release_v2.caffemodel\n"

        "  https://raw.githubusercontent.com/richzhang/colorization/caffe/models/colorization_deploy_v2.prototxt\n";

    const string keys =

        "{ h help |                                    | print this help message }"

        "{ proto  | colorization_deploy_v2.prototxt    | model configuration }"

        "{ model  | colorization_release_v2.caffemodel | model weights }"

        "{ image  | space_shuttle.jpg                  | path to image file }"

        "{ opencl |                                    | enable OpenCL }";

    CommandLineParser parser(argc, argv, keys);

    parser.about(about);

    if (parser.has("help"))

    {

        parser.printMessage();

        return 0;

    }

    string modelTxt = samples::findFile(parser.get<string>("proto"));

    string modelBin = samples::findFile(parser.get<string>("model"));

    string imageFile = samples::findFile(parser.get<string>("image"));

    bool useOpenCL = parser.has("opencl");

    if (!parser.check())

    {

        parser.printErrors();

        return 1;

    }


    Mat img = imread(imageFile);

    if (img.empty())

    {

        cout << "Can't read image from file: " << imageFile << endl;

        return 2;

    }


    // fixed input size for the pretrained network

    const int W_in = 224;

    const int H_in = 224;

    Net net = dnn::readNetFromCaffe(modelTxt, modelBin);

    if (useOpenCL)

        net.setPreferableTarget(DNN_TARGET_OPENCL);


    // setup additional layers:

    int sz[] = {2, 313, 1, 1};

    const Mat pts_in_hull(4, sz, CV_32F, hull_pts);

    Ptr<dnn::Layer> class8_ab = net.getLayer("class8_ab");

    class8_ab->blobs.push_back(pts_in_hull);

    Ptr<dnn::Layer> conv8_313_rh = net.getLayer("conv8_313_rh");

    conv8_313_rh->blobs.push_back(Mat(1, 313, CV_32F, Scalar(2.606)));


    // extract L channel and subtract mean

    Mat lab, L, input;

    img.convertTo(img, CV_32F, 1.0/255);

    cvtColor(img, lab, COLOR_BGR2Lab);

    extractChannel(lab, L, 0);

    resize(L, input, Size(W_in, H_in));

    input -= 50;


    // run the L channel through the network

    Mat inputBlob = blobFromImage(input);

    net.setInput(inputBlob);

    Mat result = net.forward();


    // retrieve the calculated a,b channels from the network output

    Size siz(result.size[2], result.size[3]);

    Mat a = Mat(siz, CV_32F, result.ptr(0,0));

    Mat b = Mat(siz, CV_32F, result.ptr(0,1));

    resize(a, a, img.size());

    resize(b, b, img.size());


    // merge, and convert back to BGR

    Mat color, chn[] = {L, a, b};

    merge(chn, 3, lab);

    cvtColor(lab, color, COLOR_Lab2BGR);


    imshow("color", color);

    imshow("original", img);

    waitKey();

    return 0;

}

cv::CommandLineParser
Designed for command line parsing.
Definition utility.hpp:890

cv::Mat
n-dimensional dense array class
Definition mat.hpp:828

cv::Mat::size
MatSize size
Definition mat.hpp:2176

cv::Mat::ptr
uchar * ptr(int i0=0)
Returns a pointer to the specified matrix row.

cv::Mat::empty
bool empty() const
Returns true if the array has no elements.

cv::Mat::convertTo
void convertTo(OutputArray m, int rtype, double alpha=1, double beta=0) const
Converts an array to another data type with optional scaling.

cv::Scalar_< double >

cv::Size_
Template class for specifying the size of an image or rectangle.
Definition types.hpp:335

cv::dnn::Net
This class allows to create and manipulate comprehensive artificial neural networks.
Definition dnn.hpp:475

cv::dnn::Net::setInput
void setInput(CV_ND InputArray blob, const String &name="", double scalefactor=1.0, const Scalar &mean=Scalar())
Sets the new input value for the network.

cv::dnn::Net::forward
Mat forward(const String &outputName=String())
Runs forward pass to compute output of layer with name outputName.

cv::dnn::Net::setPreferableTarget
void setPreferableTarget(int targetId)
Ask network to make computations on specific target device.

cv::dnn::Net::getLayer
Ptr< Layer > getLayer(int layerId) const
Returns pointer to layer with specified id or name which the network use.

dnn.hpp

cv::merge
void merge(const Mat *mv, size_t count, OutputArray dst)
Creates one multi-channel array out of several single-channel ones.

cv::extractChannel
void extractChannel(InputArray src, OutputArray dst, int coi)
Extracts a single channel from src (coi is 0-based index)

cv::Ptr
std::shared_ptr< _Tp > Ptr
Definition cvstd_wrapper.hpp:23

CV_32F
#define CV_32F
Definition interface.h:78

cv::ocl::useOpenCL
bool useOpenCL()

cv::dnn::blobFromImage
Mat blobFromImage(InputArray image, double scalefactor=1.0, const Size &size=Size(), const Scalar &mean=Scalar(), bool swapRB=false, bool crop=false, int ddepth=CV_32F)
Creates 4-dimensional blob from image. Optionally resizes and crops image from center,...

cv::imshow
void imshow(const String &winname, InputArray mat)
Displays an image in the specified window.

cv::waitKey
int waitKey(int delay=0)
Waits for a pressed key.

cv::imread
CV_EXPORTS_W Mat imread(const String &filename, int flags=IMREAD_COLOR_BGR)
Loads an image from a file.

cv::cvtColor
void cvtColor(InputArray src, OutputArray dst, int code, int dstCn=0, AlgorithmHint hint=cv::ALGO_HINT_DEFAULT)
Converts an image from one color space to another.

cv::resize
void resize(InputArray src, OutputArray dst, Size dsize, double fx=0, double fy=0, int interpolation=INTER_LINEAR)
Resizes an image.

highgui.hpp

main
int main(int argc, char *argv[])
Definition highgui_qt.cpp:3

imgproc.hpp

cv::dnn
Definition all_layers.hpp:47

cv
Definition core.hpp:107

std
STL namespace.