Add Java and Python code for the following tutorials:

- Changing the contrast and brightness of an image!
      - Operations with images
This commit is contained in:
catree
2018-07-11 19:38:16 +02:00
parent a29d11240e
commit c9fe6f1afe
12 changed files with 1197 additions and 166 deletions
@@ -20,29 +20,32 @@ using namespace cv;
*/
int main( int argc, char** argv )
{
//! [basic-linear-transform-parameters]
double alpha = 1.0; /*< Simple contrast control */
int beta = 0; /*< Simple brightness control */
//! [basic-linear-transform-parameters]
/// Read image given by user
//! [basic-linear-transform-load]
String imageName("../data/lena.jpg"); // by default
if (argc > 1)
CommandLineParser parser( argc, argv, "{@input | ../data/lena.jpg | input image}" );
Mat image = imread( parser.get<String>( "@input" ) );
if( image.empty() )
{
imageName = argv[1];
cout << "Could not open or find the image!\n" << endl;
cout << "Usage: " << argv[0] << " <Input image>" << endl;
return -1;
}
Mat image = imread( imageName );
//! [basic-linear-transform-load]
//! [basic-linear-transform-output]
Mat new_image = Mat::zeros( image.size(), image.type() );
//! [basic-linear-transform-output]
//! [basic-linear-transform-parameters]
double alpha = 1.0; /*< Simple contrast control */
int beta = 0; /*< Simple brightness control */
/// Initialize values
cout << " Basic Linear Transforms " << endl;
cout << "-------------------------" << endl;
cout << "* Enter the alpha value [1.0-3.0]: "; cin >> alpha;
cout << "* Enter the beta value [0-100]: "; cin >> beta;
//! [basic-linear-transform-parameters]
/// Do the operation new_image(i,j) = alpha*image(i,j) + beta
/// Instead of these 'for' loops we could have used simply:
@@ -51,19 +54,15 @@ int main( int argc, char** argv )
//! [basic-linear-transform-operation]
for( int y = 0; y < image.rows; y++ ) {
for( int x = 0; x < image.cols; x++ ) {
for( int c = 0; c < 3; c++ ) {
for( int c = 0; c < image.channels(); c++ ) {
new_image.at<Vec3b>(y,x)[c] =
saturate_cast<uchar>( alpha*( image.at<Vec3b>(y,x)[c] ) + beta );
saturate_cast<uchar>( alpha*image.at<Vec3b>(y,x)[c] + beta );
}
}
}
//! [basic-linear-transform-operation]
//! [basic-linear-transform-display]
/// Create Windows
namedWindow("Original Image", WINDOW_AUTOSIZE);
namedWindow("New Image", WINDOW_AUTOSIZE);
/// Show stuff
imshow("Original Image", image);
imshow("New Image", new_image);
@@ -3,6 +3,8 @@
#include "opencv2/highgui.hpp"
// we're NOT "using namespace std;" here, to avoid collisions between the beta variable and std::beta in c++17
using std::cout;
using std::endl;
using namespace cv;
namespace
@@ -19,12 +21,13 @@ void basicLinearTransform(const Mat &img, const double alpha_, const int beta_)
img.convertTo(res, -1, alpha_, beta_);
hconcat(img, res, img_corrected);
imshow("Brightness and contrast adjustments", img_corrected);
}
void gammaCorrection(const Mat &img, const double gamma_)
{
CV_Assert(gamma_ >= 0);
//![changing-contrast-brightness-gamma-correction]
//! [changing-contrast-brightness-gamma-correction]
Mat lookUpTable(1, 256, CV_8U);
uchar* p = lookUpTable.ptr();
for( int i = 0; i < 256; ++i)
@@ -32,9 +35,10 @@ void gammaCorrection(const Mat &img, const double gamma_)
Mat res = img.clone();
LUT(img, lookUpTable, res);
//![changing-contrast-brightness-gamma-correction]
//! [changing-contrast-brightness-gamma-correction]
hconcat(img, res, img_gamma_corrected);
imshow("Gamma correction", img_gamma_corrected);
}
void on_linear_transform_alpha_trackbar(int, void *)
@@ -60,36 +64,32 @@ void on_gamma_correction_trackbar(int, void *)
int main( int argc, char** argv )
{
String imageName("../data/lena.jpg"); // by default
if (argc > 1)
CommandLineParser parser( argc, argv, "{@input | ../data/lena.jpg | input image}" );
img_original = imread( parser.get<String>( "@input" ) );
if( img_original.empty() )
{
imageName = argv[1];
cout << "Could not open or find the image!\n" << endl;
cout << "Usage: " << argv[0] << " <Input image>" << endl;
return -1;
}
img_original = imread( imageName );
img_corrected = Mat(img_original.rows, img_original.cols*2, img_original.type());
img_gamma_corrected = Mat(img_original.rows, img_original.cols*2, img_original.type());
hconcat(img_original, img_original, img_corrected);
hconcat(img_original, img_original, img_gamma_corrected);
namedWindow("Brightness and contrast adjustments", WINDOW_AUTOSIZE);
namedWindow("Gamma correction", WINDOW_AUTOSIZE);
namedWindow("Brightness and contrast adjustments");
namedWindow("Gamma correction");
createTrackbar("Alpha gain (contrast)", "Brightness and contrast adjustments", &alpha, 500, on_linear_transform_alpha_trackbar);
createTrackbar("Beta bias (brightness)", "Brightness and contrast adjustments", &beta, 200, on_linear_transform_beta_trackbar);
createTrackbar("Gamma correction", "Gamma correction", &gamma_cor, 200, on_gamma_correction_trackbar);
while (true)
{
imshow("Brightness and contrast adjustments", img_corrected);
imshow("Gamma correction", img_gamma_corrected);
on_linear_transform_alpha_trackbar(0, 0);
on_gamma_correction_trackbar(0, 0);
int c = waitKey(30);
if (c == 27)
break;
}
waitKey();
imwrite("linear_transform_correction.png", img_corrected);
imwrite("gamma_correction.png", img_gamma_corrected);