tutorial how to apply neural style transfer to images using OpenCV 4, C++, and deep learning (torch)

Image Processing with Deep Learning
In this tutorial, you will learn how to apply neural style transfer to images using OpenCV 4, C++, and deep learning. By the end of this guide, you’ll be able to generate beautiful works of art with neural style transfer.

#pragma once
#include - iostream -
class styleTransferClass
-
public:
cv::dnn::Net net;
cv::Mat blob;

///farshid
styleTransferClass - - ;
void DLtorchModel - cv::Mat &inputImage, cv::Mat &ouputImage - ;
void DLtorchModelResultOup - cv::Mat &inputImage, cv::Mat &ouputImage - ;
~styleTransferClass - - ;
- ;
#include "styleTransferClass.h"

styleTransferClass::styleTransferClass - -
-
cv::String modelPathN = "C:/opencv4/StyleTransfer/x64/Release/models/eccv16/starry_night.t7";
cv::String modelPathW = "C:/opencv4/StyleTransfer/x64/Release/models/eccv16/the_wave.t7";
cv::String modelPathM = "C:/opencv4/StyleTransfer/x64/Release/models/eccv16/la_muse.t7";
cv::String modelPathV = "C:/opencv4/StyleTransfer/x64/Release/models/eccv16/composition_vii.t7";
net = cv::dnn::readNetFromTorch - modelPathV - ;

-

void styleTransferClass::DLtorchModel - cv::Mat &inputImage, cv::Mat &ouputImage -
-
cv::dnn::blobFromImage - inputImage,blob, 1.0, cv::Size - 600, 600 - , cv::Scalar - 103.939, 116.779, 123.680 - , false, false - ;
DLtorchModelResultOup - prob, ouputImage - ;
-

void styleTransferClass::DLtorchModelResultOup - cv::Mat &inputImage, cv::Mat &ouputImageResult -
-
-

styleTransferClass::~styleTransferClass - -
-
-

int main - void -
-
cv::VideoCapture cap - 0 - ;
cv::Mat frame,outputImage;
styleTransferClass st;
while - true -
-
cap - - frame;
st.DLtorchModel - frame, outputImage - ;
cv::waitKey - 10 - ;
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