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#include <opencv2/dnn.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>
#include <iostream>
#include <string>
#include <cmath>
#include <vector>
using namespace cv;
using namespace cv::dnn;
using namespace std;
class Nafnet {
public:
Nafnet(const string& modelPath) {
loadModel(modelPath);
}
// Function to set up the input image and process it
void process(const Mat& image, Mat& result) {
Mat blob = blobFromImage(image, 0.00392, Size(image.cols, image.rows), Scalar(0, 0, 0), true, false, CV_32F);
net.setInput(blob);
Mat output = net.forward();
postProcess(output, result);
}
private:
Net net;
// Load Model
void loadModel(const string modelPath) {
net = readNetFromONNX(modelPath);
net.setPreferableBackend(DNN_BACKEND_DEFAULT);
net.setPreferableTarget(DNN_TARGET_CPU);
}
void postProcess(const Mat& output, Mat& result) {
Mat output_transposed(3, &output.size[1], CV_32F, const_cast<void*>(reinterpret_cast<const void*>(output.ptr<float>())));
vector<Mat> channels;
for (int i = 0; i < 3; ++i) {
channels.push_back(Mat(output_transposed.size[1], output_transposed.size[2], CV_32F,
output_transposed.ptr<float>(i)));
}
merge(channels, result);
result.convertTo(result, CV_8UC3, 255.0);
cvtColor(result, result, COLOR_RGB2BGR);
}
};
int main(int argc, char** argv) {
const string about =
"This sample demonstrates deblurring with nafnet deblurring model.\n\n";
const string keys =
"{ help h | | Print help message. }"
"{ input i | example_outputs/licenseplate_motion.jpg | Path to input image.}"
"{ model | deblurring_nafnet_2025may.onnx | Path to the nafnet deblurring onnx model file }";
CommandLineParser parser(argc, argv, keys);
if (parser.has("help"))
{
cout << about << endl;
parser.printMessage();
return -1;
}
parser = CommandLineParser(argc, argv, keys);
string model = parser.get<String>("model");
parser.about(about);
Mat image = imread(parser.get<String>("input"));
if (image.empty()) {
cerr << "Error: Input image could not be loaded." << endl;
return -1;
}
// Create an instance of Dexined
Nafnet nafnet(model);
Mat result;
nafnet.process(image, result);
imshow("Input", image);
imshow("Output", result);
waitKey(0);
destroyAllWindows();
return 0;
}
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