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Merge pull request #9406 from Cartucho:update_core_tutorials

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This commit is contained in:
Vadim Pisarevsky
2017-09-13 14:09:39 +00:00
parent f1aa180a40 45afd29b72
commit bc09d1ba3b
16 changed files with 1107 additions and 265 deletions
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samples/cpp/tutorial_code/core/AddingImages/AddingImages.cpp
+1 -2
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@@ -3,7 +3,6 @@
* @brief Simple linear blender ( dst = alpha*src1 + beta*src2 )
* @author OpenCV team
*/
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
@@ -24,7 +23,7 @@ int main( void )
/// Ask the user enter alpha
cout << " Simple Linear Blender " << endl;
cout << "-----------------------" << endl;
cout << "* Enter alpha [0-1]: ";
cout << "* Enter alpha [0.0-1.0]: ";
cin >> input;
// We use the alpha provided by the user if it is between 0 and 1
samples/cpp/tutorial_code/core/Matrix/Drawing_1.cpp
+11 -10
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@@ -1,8 +1,8 @@
/**
* @file Drawing_1.cpp
* @brief Simple sample code
* @brief Simple geometric drawing
* @author OpenCV team
*/
#include <opencv2/core.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>
@@ -83,11 +83,11 @@ int main( void ){
/// Function Declaration
//![myellipse]
/**
* @function MyEllipse
* @brief Draw a fixed-size ellipse with different angles
*/
//![my_ellipse]
void MyEllipse( Mat img, double angle )
{
int thickness = 2;
@@ -103,13 +103,13 @@ void MyEllipse( Mat img, double angle )
thickness,
lineType );
}
//![myellipse]
//![my_ellipse]
//![myfilledcircle]
/**
* @function MyFilledCircle
* @brief Draw a fixed-size filled circle
*/
//![my_filled_circle]
void MyFilledCircle( Mat img, Point center )
{
circle( img,
@@ -119,13 +119,13 @@ void MyFilledCircle( Mat img, Point center )
FILLED,
LINE_8 );
}
//![myfilledcircle]
//![my_filled_circle]
//![mypolygon]
/**
* @function MyPolygon
* @brief Draw a simple concave polygon (rook)
*/
//![my_polygon]
void MyPolygon( Mat img )
{
int lineType = LINE_8;
@@ -163,17 +163,18 @@ void MyPolygon( Mat img )
Scalar( 255, 255, 255 ),
lineType );
}
//![mypolygon]
//![my_polygon]
//![myline]
/**
* @function MyLine
* @brief Draw a simple line
*/
//![my_line]
void MyLine( Mat img, Point start, Point end )
{
int thickness = 2;
int lineType = LINE_8;
line( img,
start,
end,
@@ -181,4 +182,4 @@ void MyLine( Mat img, Point start, Point end )
thickness,
lineType );
}
//![myline]
//![my_line]
samples/cpp/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.cpp
+20 -4
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@@ -8,45 +8,58 @@
using namespace cv;
using namespace std;
static void help(char* progName)
static void help(void)
{
cout << endl
<< "This program demonstrated the use of the discrete Fourier transform (DFT). " << endl
<< "The dft of an image is taken and it's power spectrum is displayed." << endl
<< "Usage:" << endl
<< progName << " [image_name -- default ../data/lena.jpg] " << endl << endl;
<< "./discrete_fourier_transform [image_name -- default ../data/lena.jpg]" << endl;
}
int main(int argc, char ** argv)
{
help(argv[0]);
help();
const char* filename = argc >=2 ? argv[1] : "../data/lena.jpg";
Mat I = imread(filename, IMREAD_GRAYSCALE);
if( I.empty())
if( I.empty()){
cout << "Error opening image" << endl;
return -1;
}
//! [expand]
Mat padded; //expand input image to optimal size
int m = getOptimalDFTSize( I.rows );
int n = getOptimalDFTSize( I.cols ); // on the border add zero values
copyMakeBorder(I, padded, 0, m - I.rows, 0, n - I.cols, BORDER_CONSTANT, Scalar::all(0));
//! [expand]
//! [complex_and_real]
Mat planes[] = {Mat_<float>(padded), Mat::zeros(padded.size(), CV_32F)};
Mat complexI;
merge(planes, 2, complexI); // Add to the expanded another plane with zeros
//! [complex_and_real]
//! [dft]
dft(complexI, complexI); // this way the result may fit in the source matrix
//! [dft]
// compute the magnitude and switch to logarithmic scale
// => log(1 + sqrt(Re(DFT(I))^2 + Im(DFT(I))^2))
//! [magnitude]
split(complexI, planes); // planes[0] = Re(DFT(I), planes[1] = Im(DFT(I))
magnitude(planes[0], planes[1], planes[0]);// planes[0] = magnitude
Mat magI = planes[0];
//! [magnitude]
//! [log]
magI += Scalar::all(1); // switch to logarithmic scale
log(magI, magI);
//! [log]
//! [crop_rearrange]
// crop the spectrum, if it has an odd number of rows or columns
magI = magI(Rect(0, 0, magI.cols & -2, magI.rows & -2));
@@ -67,9 +80,12 @@ int main(int argc, char ** argv)
q1.copyTo(tmp); // swap quadrant (Top-Right with Bottom-Left)
q2.copyTo(q1);
tmp.copyTo(q2);
//! [crop_rearrange]
//! [normalize]
normalize(magI, magI, 0, 1, NORM_MINMAX); // Transform the matrix with float values into a
// viewable image form (float between values 0 and 1).
//! [normalize]
imshow("Input Image" , I ); // Show the result
imshow("spectrum magnitude", magI);
samples/java/tutorial_code/core/AddingImages/AddingImages.java
+51
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@@ -0,0 +1,51 @@
import org.opencv.core.*;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import java.util.Locale;
import java.util.Scanner;
class AddingImagesRun{
public void run() {
double alpha = 0.5; double beta; double input;
Mat src1, src2, dst = new Mat();
System.out.println(" Simple Linear Blender ");
System.out.println("-----------------------");
System.out.println("* Enter alpha [0.0-1.0]: ");
Scanner scan = new Scanner( System.in ).useLocale(Locale.US);
input = scan.nextDouble();
if( input >= 0.0 && input <= 1.0 )
alpha = input;
//! [load]
src1 = Imgcodecs.imread("../../images/LinuxLogo.jpg");
src2 = Imgcodecs.imread("../../images/WindowsLogo.jpg");
//! [load]
if( src1.empty() == true ){ System.out.println("Error loading src1"); return;}
if( src2.empty() == true ){ System.out.println("Error loading src2"); return;}
//! [blend_images]
beta = ( 1.0 - alpha );
Core.addWeighted( src1, alpha, src2, beta, 0.0, dst);
//! [blend_images]
//![display]
HighGui.imshow("Linear Blend", dst);
HighGui.waitKey(0);
//![display]
System.exit(0);
}
}
public class AddingImages {
public static void main(String[] args) {
// Load the native library.
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
new AddingImagesRun().run();
}
}
samples/java/tutorial_code/core/BasicGeometricDrawing/BasicGeometricDrawing.java
+186
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@@ -0,0 +1,186 @@
import org.opencv.core.*;
import org.opencv.core.Point;
import org.opencv.highgui.HighGui;
import org.opencv.imgproc.Imgproc;
import java.util.*;
import java.util.List;
class GeometricDrawingRun{
private static final int W = 400;
public void run(){
//! [create_images]
/// Windows names
String atom_window = "Drawing 1: Atom";
String rook_window = "Drawing 2: Rook";
/// Create black empty images
Mat atom_image = Mat.zeros( W, W, CvType.CV_8UC3 );
Mat rook_image = Mat.zeros( W, W, CvType.CV_8UC3 );
//! [create_images]
//! [draw_atom]
/// 1. Draw a simple atom:
/// -----------------------
MyEllipse( atom_image, 90.0 );
MyEllipse( atom_image, 0.0 );
MyEllipse( atom_image, 45.0 );
MyEllipse( atom_image, -45.0 );
/// 1.b. Creating circles
MyFilledCircle( atom_image, new Point( W/2, W/2) );
//! [draw_atom]
//! [draw_rook]
/// 2. Draw a rook
/// ------------------
/// 2.a. Create a convex polygon
MyPolygon( rook_image );
//! [rectangle]
/// 2.b. Creating rectangles
Imgproc.rectangle( rook_image,
new Point( 0, 7*W/8 ),
new Point( W, W),
new Scalar( 0, 255, 255 ),
-1,
8,
0 );
//! [rectangle]
/// 2.c. Create a few lines
MyLine( rook_image, new Point( 0, 15*W/16 ), new Point( W, 15*W/16 ) );
MyLine( rook_image, new Point( W/4, 7*W/8 ), new Point( W/4, W ) );
MyLine( rook_image, new Point( W/2, 7*W/8 ), new Point( W/2, W ) );
MyLine( rook_image, new Point( 3*W/4, 7*W/8 ), new Point( 3*W/4, W ) );
//! [draw_rook]
/// 3. Display your stuff!
HighGui.imshow( atom_window, atom_image );
HighGui.moveWindow( atom_window, 0, 200 );
HighGui.imshow( rook_window, rook_image );
HighGui.moveWindow( rook_window, W, 200 );
HighGui.waitKey( 0 );
System.exit(0);
}
/// Function Declaration
/**
* @function MyEllipse
* @brief Draw a fixed-size ellipse with different angles
*/
//! [my_ellipse]
private void MyEllipse( Mat img, double angle ) {
int thickness = 2;
int lineType = 8;
int shift = 0;
Imgproc.ellipse( img,
new Point( W/2, W/2 ),
new Size( W/4, W/16 ),
angle,
0.0,
360.0,
new Scalar( 255, 0, 0 ),
thickness,
lineType,
shift );
}
//! [my_ellipse]
/**
* @function MyFilledCircle
* @brief Draw a fixed-size filled circle
*/
//! [my_filled_circle]
private void MyFilledCircle( Mat img, Point center ) {
int thickness = -1;
int lineType = 8;
int shift = 0;
Imgproc.circle( img,
center,
W/32,
new Scalar( 0, 0, 255 ),
thickness,
lineType,
shift );
}
//! [my_filled_circle]
/**
* @function MyPolygon
* @function Draw a simple concave polygon (rook)
*/
//! [my_polygon]
private void MyPolygon( Mat img ) {
int lineType = 8;
int shift = 0;
/** Create some points */
Point[] rook_points = new Point[20];
rook_points[0] = new Point( W/4, 7*W/8 );
rook_points[1] = new Point( 3*W/4, 7*W/8 );
rook_points[2] = new Point( 3*W/4, 13*W/16 );
rook_points[3] = new Point( 11*W/16, 13*W/16 );
rook_points[4] = new Point( 19*W/32, 3*W/8 );
rook_points[5] = new Point( 3*W/4, 3*W/8 );
rook_points[6] = new Point( 3*W/4, W/8 );
rook_points[7] = new Point( 26*W/40, W/8 );
rook_points[8] = new Point( 26*W/40, W/4 );
rook_points[9] = new Point( 22*W/40, W/4 );
rook_points[10] = new Point( 22*W/40, W/8 );
rook_points[11] = new Point( 18*W/40, W/8 );
rook_points[12] = new Point( 18*W/40, W/4 );
rook_points[13] = new Point( 14*W/40, W/4 );
rook_points[14] = new Point( 14*W/40, W/8 );
rook_points[15] = new Point( W/4, W/8 );
rook_points[16] = new Point( W/4, 3*W/8 );
rook_points[17] = new Point( 13*W/32, 3*W/8 );
rook_points[18] = new Point( 5*W/16, 13*W/16 );
rook_points[19] = new Point( W/4, 13*W/16 );
MatOfPoint matPt = new MatOfPoint();
matPt.fromArray(rook_points);
List<MatOfPoint> ppt = new ArrayList<MatOfPoint>();
ppt.add(matPt);
Imgproc.fillPoly(img,
ppt,
new Scalar( 255, 255, 255 ),
lineType,
shift,
new Point(0,0) );
}
//! [my_polygon]
/**
* @function MyLine
* @brief Draw a simple line
*/
//! [my_line]
private void MyLine( Mat img, Point start, Point end ) {
int thickness = 2;
int lineType = 8;
int shift = 0;
Imgproc.line( img,
start,
end,
new Scalar( 0, 0, 0 ),
thickness,
lineType,
shift );
}
//! [my_line]
}
public class BasicGeometricDrawing {
public static void main(String[] args) {
// Load the native library.
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
new GeometricDrawingRun().run();
}
}
samples/java/tutorial_code/core/discrete_fourier_transform/DiscreteFourierTransform.java
+109
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@@ -0,0 +1,109 @@
import org.opencv.core.*;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import java.util.List;
import java.util.*;
class DiscreteFourierTransformRun{
private void help() {
System.out.println("" +
"This program demonstrated the use of the discrete Fourier transform (DFT). \n" +
"The dft of an image is taken and it's power spectrum is displayed.\n" +
"Usage:\n" +
"./DiscreteFourierTransform [image_name -- default ../data/lena.jpg]");
}
public void run(String[] args){
help();
String filename = ((args.length > 0) ? args[0] : "../data/lena.jpg");
Mat I = Imgcodecs.imread(filename, Imgcodecs.IMREAD_GRAYSCALE);
if( I.empty() ) {
System.out.println("Error opening image");
System.exit(-1);
}
//! [expand]
Mat padded = new Mat(); //expand input image to optimal size
int m = Core.getOptimalDFTSize( I.rows() );
int n = Core.getOptimalDFTSize( I.cols() ); // on the border add zero values
Core.copyMakeBorder(I, padded, 0, m - I.rows(), 0, n - I.cols(), Core.BORDER_CONSTANT, Scalar.all(0));
//! [expand]
//! [complex_and_real]
List<Mat> planes = new ArrayList<Mat>();
padded.convertTo(padded, CvType.CV_32F);
planes.add(padded);
planes.add(Mat.zeros(padded.size(), CvType.CV_32F));
Mat complexI = new Mat();
Core.merge(planes, complexI); // Add to the expanded another plane with zeros
//! [complex_and_real]
//! [dft]
Core.dft(complexI, complexI); // this way the result may fit in the source matrix
//! [dft]
// compute the magnitude and switch to logarithmic scale
// => log(1 + sqrt(Re(DFT(I))^2 + Im(DFT(I))^2))
//! [magnitude]
Core.split(complexI, planes); // planes.get(0) = Re(DFT(I)
// planes.get(1) = Im(DFT(I))
Core.magnitude(planes.get(0), planes.get(1), planes.get(0));// planes.get(0) = magnitude
Mat magI = planes.get(0);
//! [magnitude]
//! [log]
Mat matOfOnes = Mat.ones(magI.size(), magI.type());
Core.add(matOfOnes, magI, magI); // switch to logarithmic scale
Core.log(magI, magI);
//! [log]
//! [crop_rearrange]
// crop the spectrum, if it has an odd number of rows or columns
magI = magI.submat(new Rect(0, 0, magI.cols() & -2, magI.rows() & -2));
// rearrange the quadrants of Fourier image so that the origin is at the image center
int cx = magI.cols()/2;
int cy = magI.rows()/2;
Mat q0 = new Mat(magI, new Rect(0, 0, cx, cy)); // Top-Left - Create a ROI per quadrant
Mat q1 = new Mat(magI, new Rect(cx, 0, cx, cy)); // Top-Right
Mat q2 = new Mat(magI, new Rect(0, cy, cx, cy)); // Bottom-Left
Mat q3 = new Mat(magI, new Rect(cx, cy, cx, cy)); // Bottom-Right
Mat tmp = new Mat(); // swap quadrants (Top-Left with Bottom-Right)
q0.copyTo(tmp);
q3.copyTo(q0);
tmp.copyTo(q3);
q1.copyTo(tmp); // swap quadrant (Top-Right with Bottom-Left)
q2.copyTo(q1);
tmp.copyTo(q2);
//! [crop_rearrange]
magI.convertTo(magI, CvType.CV_8UC1);
//! [normalize]
Core.normalize(magI, magI, 0, 255, Core.NORM_MINMAX, CvType.CV_8UC1); // Transform the matrix with float values
// into a viewable image form (float between
// values 0 and 255).
//! [normalize]
HighGui.imshow("Input Image" , I ); // Show the result
HighGui.imshow("Spectrum Magnitude", magI);
HighGui.waitKey();
System.exit(0);
}
}
public class DiscreteFourierTransform {
public static void main(String[] args) {
// Load the native library.
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
new DiscreteFourierTransformRun().run(args);
}
}
samples/java/tutorial_code/core/mat_mask_operations/MatMaskOperations.java
+13 -38
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@@ -2,14 +2,10 @@ import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.core.Scalar;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import javax.swing.*;
import java.awt.*;
import java.awt.image.BufferedImage;
import java.awt.image.DataBufferByte;
class MatMaskOperationsRun {
public void run(String[] args) {
@@ -31,8 +27,10 @@ class MatMaskOperationsRun {
System.exit(-1);
}
Image img = toBufferedImage(src);
displayImage("Input", img, 0, 200);
HighGui.namedWindow("Input", HighGui.WINDOW_AUTOSIZE);
HighGui.namedWindow("Output", HighGui.WINDOW_AUTOSIZE);
HighGui.imshow( "Input", src );
double t = System.currentTimeMillis();
Mat dst0 = sharpen(src, new Mat());
@@ -40,8 +38,9 @@ class MatMaskOperationsRun {
t = ((double) System.currentTimeMillis() - t) / 1000;
System.out.println("Hand written function time passed in seconds: " + t);
Image img2 = toBufferedImage(dst0);
displayImage("Output", img2, 400, 400);
HighGui.imshow( "Output", dst0 );
HighGui.moveWindow("Output", 400, 400);
HighGui.waitKey();
//![kern]
Mat kern = new Mat(3, 3, CvType.CV_8S);
@@ -58,8 +57,10 @@ class MatMaskOperationsRun {
t = ((double) System.currentTimeMillis() - t) / 1000;
System.out.println("Built-in filter2D time passed in seconds: " + t);
Image img3 = toBufferedImage(dst1);
displayImage("Output", img3, 800, 400);
HighGui.imshow( "Output", dst1 );
HighGui.waitKey();
System.exit(0);
}
//! [basic_method]
@@ -108,38 +109,12 @@ class MatMaskOperationsRun {
return Result;
}
//! [basic_method]
public Image toBufferedImage(Mat m) {
int type = BufferedImage.TYPE_BYTE_GRAY;
if (m.channels() > 1) {
type = BufferedImage.TYPE_3BYTE_BGR;
}
int bufferSize = m.channels() * m.cols() * m.rows();
byte[] b = new byte[bufferSize];
m.get(0, 0, b); // get all the pixels
BufferedImage image = new BufferedImage(m.cols(), m.rows(), type);
final byte[] targetPixels = ((DataBufferByte) image.getRaster().getDataBuffer()).getData();
System.arraycopy(b, 0, targetPixels, 0, b.length);
return image;
}
public void displayImage(String title, Image img, int x, int y) {
ImageIcon icon = new ImageIcon(img);
JFrame frame = new JFrame(title);
JLabel lbl = new JLabel(icon);
frame.add(lbl);
frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
frame.pack();
frame.setLocation(x, y);
frame.setVisible(true);
}
}
public class MatMaskOperations {
public static void main(String[] args) {
// Load the native library.
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
new MatMaskOperationsRun().run(args); // run code
new MatMaskOperationsRun().run(args);
}
}
samples/python/tutorial_code/core/AddingImages/adding_images.py
+35
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@@ -0,0 +1,35 @@
from __future__ import print_function
import sys
import cv2
alpha = 0.5
print(''' Simple Linear Blender
-----------------------
* Enter alpha [0.0-1.0]: ''')
if sys.version_info >= (3, 0): # If Python 3.x
input_alpha = float(input())
else:
input_alpha = float(raw_input())
if 0 <= alpha <= 1:
alpha = input_alpha
## [load]
src1 = cv2.imread('../../../../data/LinuxLogo.jpg')
src2 = cv2.imread('../../../../data/WindowsLogo.jpg')
## [load]
if src1 is None:
print ("Error loading src1")
exit(-1)
elif src2 is None:
print ("Error loading src2")
exit(-1)
## [blend_images]
beta = (1.0 - alpha)
dst = cv2.addWeighted(src1, alpha, src2, beta, 0.0)
## [blend_images]
## [display]
cv2.imshow('dst', dst)
cv2.waitKey(0)
## [display]
cv2.destroyAllWindows()
samples/python/tutorial_code/core/BasicGeometricDrawing/basic_geometric_drawing.py
+115
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@@ -0,0 +1,115 @@
import cv2
import numpy as np
W = 400
## [my_ellipse]
def my_ellipse(img, angle):
thickness = 2
line_type = 8
cv2.ellipse(img,
(W / 2, W / 2),
(W / 4, W / 16),
angle,
0,
360,
(255, 0, 0),
thickness,
line_type)
## [my_ellipse]
## [my_filled_circle]
def my_filled_circle(img, center):
thickness = -1
line_type = 8
cv2.circle(img,
center,
W / 32,
(0, 0, 255),
thickness,
line_type)
## [my_filled_circle]
## [my_polygon]
def my_polygon(img):
line_type = 8
# Create some points
ppt = np.array([[W / 4, 7 * W / 8], [3 * W / 4, 7 * W / 8],
[3 * W / 4, 13 * W / 16], [11 * W / 16, 13 * W / 16],
[19 * W / 32, 3 * W / 8], [3 * W / 4, 3 * W / 8],
[3 * W / 4, W / 8], [26 * W / 40, W / 8],
[26 * W / 40, W / 4], [22 * W / 40, W / 4],
[22 * W / 40, W / 8], [18 * W / 40, W / 8],
[18 * W / 40, W / 4], [14 * W / 40, W / 4],
[14 * W / 40, W / 8], [W / 4, W / 8],
[W / 4, 3 * W / 8], [13 * W / 32, 3 * W / 8],
[5 * W / 16, 13 * W / 16], [W / 4, 13 * W / 16]], np.int32)
ppt = ppt.reshape((-1, 1, 2))
cv2.fillPoly(img, [ppt], (255, 255, 255), line_type)
# Only drawind the lines would be:
# cv2.polylines(img, [ppt], True, (255, 0, 255), line_type)
## [my_polygon]
## [my_line]
def my_line(img, start, end):
thickness = 2
line_type = 8
cv2.line(img,
start,
end,
(0, 0, 0),
thickness,
line_type)
## [my_line]
## [create_images]
# Windows names
atom_window = "Drawing 1: Atom"
rook_window = "Drawing 2: Rook"
# Create black empty images
size = W, W, 3
atom_image = np.zeros(size, dtype=np.uint8)
rook_image = np.zeros(size, dtype=np.uint8)
## [create_images]
## [draw_atom]
# 1. Draw a simple atom:
# -----------------------
# 1.a. Creating ellipses
my_ellipse(atom_image, 90)
my_ellipse(atom_image, 0)
my_ellipse(atom_image, 45)
my_ellipse(atom_image, -45)
# 1.b. Creating circles
my_filled_circle(atom_image, (W / 2, W / 2))
## [draw_atom]
## [draw_rook]
# 2. Draw a rook
# ------------------
# 2.a. Create a convex polygon
my_polygon(rook_image)
## [rectangle]
# 2.b. Creating rectangles
cv2.rectangle(rook_image,
(0, 7 * W / 8),
(W, W),
(0, 255, 255),
-1,
8)
## [rectangle]
# 2.c. Create a few lines
my_line(rook_image, (0, 15 * W / 16), (W, 15 * W / 16))
my_line(rook_image, (W / 4, 7 * W / 8), (W / 4, W))
my_line(rook_image, (W / 2, 7 * W / 8), (W / 2, W))
my_line(rook_image, (3 * W / 4, 7 * W / 8), (3 * W / 4, W))
## [draw_rook]
cv2.imshow(atom_window, atom_image)
cv2.moveWindow(atom_window, 0, 200)
cv2.imshow(rook_window, rook_image)
cv2.moveWindow(rook_window, W, 200)
cv2.waitKey(0)
cv2.destroyAllWindows()
samples/python/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.py
+80
View File
@@ -0,0 +1,80 @@
from __future__ import print_function
import sys
import cv2
import numpy as np
def print_help():
print('''
This program demonstrated the use of the discrete Fourier transform (DFT).
The dft of an image is taken and it's power spectrum is displayed.
Usage:
discrete_fourier_transform.py [image_name -- default ../../../../data/lena.jpg]''')
def main(argv):
print_help()
filename = argv[0] if len(argv) > 0 else "../../../../data/lena.jpg"
I = cv2.imread(filename, cv2.IMREAD_GRAYSCALE)
if I is None:
print('Error opening image')
return -1
## [expand]
rows, cols = I.shape
m = cv2.getOptimalDFTSize( rows )
n = cv2.getOptimalDFTSize( cols )
padded = cv2.copyMakeBorder(I, 0, m - rows, 0, n - cols, cv2.BORDER_CONSTANT, value=[0, 0, 0])
## [expand]
## [complex_and_real]
planes = [np.float32(padded), np.zeros(padded.shape, np.float32)]
complexI = cv2.merge(planes) # Add to the expanded another plane with zeros
## [complex_and_real]
## [dft]
cv2.dft(complexI, complexI) # this way the result may fit in the source matrix
## [dft]
# compute the magnitude and switch to logarithmic scale
# = > log(1 + sqrt(Re(DFT(I)) ^ 2 + Im(DFT(I)) ^ 2))
## [magnitude]
cv2.split(complexI, planes) # planes[0] = Re(DFT(I), planes[1] = Im(DFT(I))
cv2.magnitude(planes[0], planes[1], planes[0])# planes[0] = magnitude
magI = planes[0]
## [magnitude]
## [log]
matOfOnes = np.ones(magI.shape, dtype=magI.dtype)
cv2.add(matOfOnes, magI, magI) # switch to logarithmic scale
cv2.log(magI, magI)
## [log]
## [crop_rearrange]
magI_rows, magI_cols = magI.shape
# crop the spectrum, if it has an odd number of rows or columns
magI = magI[0:(magI_rows & -2), 0:(magI_cols & -2)]
cx = int(magI_rows/2)
cy = int(magI_cols/2)
q0 = magI[0:cx, 0:cy] # Top-Left - Create a ROI per quadrant
q1 = magI[cx:cx+cx, 0:cy] # Top-Right
q2 = magI[0:cx, cy:cy+cy] # Bottom-Left
q3 = magI[cx:cx+cx, cy:cy+cy] # Bottom-Right
tmp = np.copy(q0) # swap quadrants (Top-Left with Bottom-Right)
magI[0:cx, 0:cy] = q3
magI[cx:cx + cx, cy:cy + cy] = tmp
tmp = np.copy(q1) # swap quadrant (Top-Right with Bottom-Left)
magI[cx:cx + cx, 0:cy] = q2
magI[0:cx, cy:cy + cy] = tmp
## [crop_rearrange]
## [normalize]
cv2.normalize(magI, magI, 0, 1, cv2.NORM_MINMAX) # Transform the matrix with float values into a
## viewable image form(float between values 0 and 1).
## [normalize]
cv2.imshow("Input Image" , I ) # Show the result
cv2.imshow("spectrum magnitude", magI)
cv2.waitKey()
if __name__ == "__main__":
main(sys.argv[1:])
samples/python/tutorial_code/core/mat_mask_operations/mat_mask_operations.py
+13 -13
View File
@@ -1,9 +1,10 @@
from __future__ import print_function
import sys
import time
import numpy as np
import cv2
## [basic_method]
def is_grayscale(my_image):
return len(my_image.shape) < 3
@@ -26,7 +27,6 @@ def sharpen(my_image):
height, width, n_channels = my_image.shape
result = np.zeros(my_image.shape, my_image.dtype)
## [basic_method_loop]
for j in range(1, height - 1):
for i in range(1, width - 1):
@@ -36,17 +36,16 @@ def sharpen(my_image):
result[j, i] = saturated(sum_value)
else:
for k in range(0, n_channels):
sum_value = 5 * my_image[j, i, k] - my_image[j + 1, i, k] - my_image[j - 1, i, k] \
- my_image[j, i + 1, k] - my_image[j, i - 1, k]
sum_value = 5 * my_image[j, i, k] - my_image[j + 1, i, k] \
- my_image[j - 1, i, k] - my_image[j, i + 1, k]\
- my_image[j, i - 1, k]
result[j, i, k] = saturated(sum_value)
## [basic_method_loop]
return result
## [basic_method]
def main(argv):
filename = "../data/lena.jpg"
filename = "../../../../data/lena.jpg"
img_codec = cv2.IMREAD_COLOR
if argv:
@@ -57,8 +56,9 @@ def main(argv):
src = cv2.imread(filename, img_codec)
if src is None:
print "Can't open image [" + filename + "]"
print "Usage:\nmat_mask_operations.py [image_path -- default ../data/lena.jpg] [G -- grayscale]"
print("Can't open image [" + filename + "]")
print("Usage:")
print("mat_mask_operations.py [image_path -- default ../../../../data/lena.jpg] [G -- grayscale]")
return -1
cv2.namedWindow("Input", cv2.WINDOW_AUTOSIZE)
@@ -70,7 +70,7 @@ def main(argv):
dst0 = sharpen(src)
t = (time.time() - t) / 1000
print "Hand written function time passed in seconds: %s" % t
print("Hand written function time passed in seconds: %s" % t)
cv2.imshow("Output", dst0)
cv2.waitKey()
@@ -81,13 +81,13 @@ def main(argv):
[-1, 5, -1],
[0, -1, 0]], np.float32) # kernel should be floating point type
## [kern]
## [filter2D]
dst1 = cv2.filter2D(src, -1, kernel) # ddepth = -1, means destination image has depth same as input image
dst1 = cv2.filter2D(src, -1, kernel)
# ddepth = -1, means destination image has depth same as input image
## [filter2D]
t = (time.time() - t) / 1000
print "Built-in filter2D time passed in seconds: %s" % t
print("Built-in filter2D time passed in seconds: %s" % t)
cv2.imshow("Output", dst1)