Saafke

Google Summer of Code 2019 with OpenCV

Learning-based Super Resolution

Student: Xavier Weber
Mentors: Vladimir Tyan & Yida Wang
Student on the same project: Fanny Monori

Link to accomplished work:

• PR in the opencv_contrib repository: opencv_contrib/pull/2231

Saafke

#include <opencv2/dnn_superres.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>

using namespace std;
using namespace cv;
using namespace dnn;
using namespace dnn_superres;

int main(int argc, char *argv[])

Saafke

% Code created by Xavier Weber

% ============= PART 1: READING AND PADDING THE IMAGE =====================

function [count,im] = countBlobs(img)
%countBlobs Counts the number of blobs: connected regions of positive
%               values - and labels them. 
%   returns:    number of blobs

% Get dimensions

Saafke

% Code created by Xavier Weber

function outimg = padImage(I, pad)
%padImage Pads an image with black pixels (zero-values)
%   Works with single or multi-channels

% Get input dimensions
img_size = size(I);
src_height = img_size(1);
src_width = img_size(2);

Saafke

% Code created by Xavier Weber

% Create an image -- like the one in the GIF.
im = zeros(5,5);

im(1:1,5:5) = 255;

im(2:2,2:2) = 255;
im(3:3,1:1) = 255;

Saafke

import cv2
from cv2 import dnn_superres

# Create an SR object
sr = dnn_superres.DnnSuperResImpl_create()

# Read image
image = cv2.imread('./input.png')

# Read the desired model

Saafke

cmake \
-D CMAKE_BUILD_TYPE=RELEASE \
-D CMAKE_INSTALL_PREFIX=/usr/local \
-D INSTALL_PYTHON_EXAMPLES=ON \
-D INSTALL_C_EXAMPLES=OFF \
-D OPENCV_ENABLE_NONFREE=ON \
-D WITH_CUDA=ON \
-D WITH_CUDNN=ON \
-D OPENCV_DNN_CUDA=ON \
-D ENABLE_FAST_MATH=1 \

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# Read the desired model
path = "EDSR_x3.pb"
sr.readModel(path)

# Set CUDA backend and target to enable GPU inference
sr.setPreferableBackend(cv2.dnn.DNN_BACKEND_CUDA)
sr.setPreferableTarget(cv2.dnn.DNN_TARGET_CUDA)

#etcetera..

Saafke

//Read the desired model
string path = "FSRCNN_x2.pb";
sr.readModel(path);

//Set CUDA backend and target to enable GPU inference
sr.setPreferableBackend(cv::dnn::DNN_BACKEND_CUDA)
sr.setPreferableTarget(cv::dnn::DNN_BACKEND_CUDA)
  
//etcetera..

Saafke

NUMBER_TO_SUBTRACT=217

for file in `ls -1v out*`; do
    echo $file
    NUMBER=${file:3:-4}
    NEW_NUMBER=$[NUMBER-NUMBER_TO_SUBTRACT]

    NEW_FILE_NAME="out${NEW_NUMBER}.png"
    echo $NEW_FILE_NAME