Upscaling video

In this tutorial you will learn how to use the 'dnn_superres' interface to upscale video via pre-trained neural networks.

Building

When building OpenCV, run the following command to build all the contrib module:

cmake -D OPENCV_EXTRA_MODULES_PATH=<opencv_contrib>/modules/

Or only build the dnn_superres module:

cmake -D OPENCV_EXTRA_MODULES_PATH=<opencv_contrib>/modules/dnn_superres

Or make sure you check the dnn_superres module in the GUI version of CMake: cmake-gui.

Source Code of the sample

// 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 <iostream>
 
#include <opencv2/dnn_superres.hpp>
 
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>
 
using namespace std;
using namespace cv;
using namespace dnn_superres;
 
int main(int argc, char *argv[])
{
 // Check for valid command line arguments, print usage
 // if insufficient arguments were given.
 if (argc < 4) {
 cout << "usage: Arg 1: input video path" << endl;
 cout << "\t Arg 2: output video path" << endl;
 cout << "\t Arg 3: algorithm | edsr, espcn, fsrcnn or lapsrn" << endl;
 cout << "\t Arg 4: scale | 2, 3, 4 or 8 \n";
 cout << "\t Arg 5: path to model file \n";
 return -1;
 }
 
 string input_path = string(argv[1]);
 string output_path = string(argv[2]);
 string algorithm = string(argv[3]);
 int scale = atoi(argv[4]);
 string path = string(argv[5]);
 
 VideoCapture input_video(input_path);
 int ex = static_cast<int>(input_video.get(CAP_PROP_FOURCC));
 Size S = Size((int) input_video.get(CAP_PROP_FRAME_WIDTH) * scale,
 (int) input_video.get(CAP_PROP_FRAME_HEIGHT) * scale);
 
 VideoWriter output_video;
 output_video.open(output_path, ex, input_video.get(CAP_PROP_FPS), S, true);
 
 if (!input_video.isOpened())
 {
 std::cerr << "Could not open the video." << std::endl;
 return -1;
 }
 
 DnnSuperResImpl sr;
 sr.readModel(path);
 sr.setModel(algorithm, scale);
 
 for(;;)
 {
 Mat frame, output_frame;
 input_video >> frame;
 
 if ( frame.empty() )
 break;
 
 sr.upsample(frame, output_frame);
 output_video << output_frame;
 
 namedWindow("Upsampled video", WINDOW_AUTOSIZE);
 imshow("Upsampled video", output_frame);
 
 namedWindow("Original video", WINDOW_AUTOSIZE);
 imshow("Original video", frame);
 
 char c=(char)waitKey(25);
 if(c==27)
 break;
 }
 
 input_video.release();
 output_video.release();
 
 return 0;
}

Explanation

1. Set header and namespaces

   #include <opencv2/dnn_superres.hpp>
   using namespace std;
   using namespace cv;
   using namespace dnn_superres;

2. Create the Dnn Superres object

   DnnSuperResImpl sr;

   Instantiate a dnn super-resolution object.
3. Read the model

   path = "models/ESPCN_x2.pb"
   sr.readModel(path);
   sr.setModel("espcn", 2);

   Read the model from the given path and sets the algorithm and scaling factor.
4. Upscale a video

   for(;;)
   {
    Mat frame, output_frame;
    input_video >> frame;
    if ( frame.empty() )
    break;
    sr.upsample(frame, output_frame);
    ...
   }

   Process and upsample video frame by frame.