OpenCV – Water's Home

Test QR Code with OpenCV

Posted on June 11, 2021 by admin

Use SURF Detector to Match Login View in DeXing APP

Posted on November 27, 2020 by admin

First, Get the KeyPoint

Second, Capture the screen with your camera

Finally, Get the result with SURF Detector

Opencv Tutorial

Posted on April 28, 2020August 26, 2020 by admin

Matplotlib RGB & OpenCV BGR

Posted on January 9, 2019 by admin

Matplotlib RGB & OpenCV BGR

```
import matplotlib.pyplot as plt
```
```
import numpy as np
```
```
import cv2
```
```
 
```
```
img = np.array([
```

    [[255, 0, 0], [0, 255, 0], [0, 0, 255]],

    [[255, 255, 0], [255, 0, 255], [0, 255, 255]],

    [[255, 255, 255], [128, 128, 128], [0, 0, 0]],

```
], dtype=np.uint8)
```
```
 
```
```
plt.imsave('img_pyplot.png', img)
```
```
cv2.imwrite('img_cv2.jpg', img)
```

QT + OpenCV Example

Posted on December 30, 2018 by admin

Source

```
#include <QCoreApplication>
```
```
 
```
```
#include <opencv2/opencv.hpp>
```
```
 
```
```
int main(int argc, char *argv[])
```
```
{
```
```
    //QCoreApplication a(argc, argv);
```
```
 
```
```
    using namespace cv;
```

    Mat image = imread("/Users/water/Downloads/Share.jpg");

```
    imshow("Output", image);
```
```
 
```
```
    waitKey(1000);
```
```
 
```
```
    return 0;
```
```
 
```
```
    //return a.exec();
```
```
}
```

pro

```
QT -= gui
```
```
 
```
```
CONFIG += c++11 console
```
```
CONFIG -= app_bundle
```
```
 
```

# The following define makes your compiler emit warnings if you use

# any Qt feature that has been marked deprecated (the exact warnings

# depend on your compiler). Please consult the documentation of the

# deprecated API in order to know how to port your code away from it.

```
DEFINES += QT_DEPRECATED_WARNINGS
```
```
 
```

# You can also make your code fail to compile if it uses deprecated APIs.

# In order to do so, uncomment the following line.

# You can also select to disable deprecated APIs only up to a certain version of Qt.

#DEFINES += QT_DISABLE_DEPRECATED_BEFORE=0x060000    # disables all the APIs deprecated before Qt 6.0.0

```
 
```
```
SOURCES += \
```
```
        main.cpp
```
```
 
```
```
# Default rules for deployment.
```
```
qnx: target.path = /tmp/$${TARGET}/bin
```

else: unix:!android: target.path = /opt/$${TARGET}/bin

!isEmpty(target.path): INSTALLS += target

```
 
```
```
INCLUDEPATH += /usr/local/include
```

INCLUDEPATH += /usr/local/include/opencv

INCLUDEPATH += /usr/local/include/opencv2

```
LIBS += -L/usr/local/lib \
```
```
 -lopencv_core \
```
```
 -lopencv_highgui \
```
```
 -lopencv_imgproc \
```
```
  -lopencv_imgcodecs \
```

OpenCV3 On ARM

Posted on May 3, 2018 by admin

Source Code Dir

CMake-GUI Configure

Configure/Generate

Unix Makefiles
Specify options for cross-compiling

Choose ARM – LINUX

Operating System : arm-linux
C Compilers :
C++ Compilers :
Target Root : The Cross Compiler BIN Directory

CMAKE_INSTALL_PREFIX

make & make install

```
make
```
```
make install
```

Maybe Need It !

The END

```
tar jcvf opencv-arm.tar.bz2 opencv-arm/
```

Lucas-Kanade & Farneback

Posted on May 3, 2018 by admin

LucasKanade Tracker

        // Check if there are points to track

```
        if(!trackingPoints[0].empty())
```
```
        {
```

            // Status vector to indicate whether the flow for the corresponding features has been found

```
            vector<uchar> statusVector;
```
```
 
```

            // Error vector to indicate the error for the corresponding feature

```
            vector<float> errorVector;
```
```
 
```

            // Check if previous image is empty

```
            if(prevGrayImage.empty())
```
```
            {
```

                curGrayImage.copyTo(prevGrayImage);

```
            }
```
```
 
```

            // Calculate the optical flow using Lucas-Kanade algorithm

            calcOpticalFlowPyrLK(prevGrayImage, curGrayImage, trackingPoints[0], trackingPoints[1], statusVector, errorVector, windowSize, 3, terminationCriteria, 0, 0.001);

```
 
```
```
            int count = 0;
```
```
 
```

            // Minimum distance between any two tracking points

```
            int minDist = 7;
```
```
 
```

            for(int i=0; i < trackingPoints[1].size(); i++)

```
            {
```
```
                if(pointTrackingFlag)
```
```
                {
```

                    // If the new point is within 'minDist' distance from an existing point, it will not be tracked

                    if(norm(currentPoint - trackingPoints[1][i]) <= minDist)

```
                    {
```

                        pointTrackingFlag = false;

```
                        continue;
```
```
                    }
```
```
                }
```
```
 
```

                // Check if the status vector is good

```
                if(!statusVector[i])
```
```
                    continue;
```
```
 
```

                trackingPoints[1][count++] = trackingPoints[1][i];

```
 
```

                // Draw a filled circle for each of the tracking points

```
                int radius = 8;
```
```
                int thickness = 2;
```
```
                int lineType = 8;
```

                circle(image, trackingPoints[1][i], radius, Scalar(0,255,0), thickness, lineType);

```
            }
```
```
 
```

            trackingPoints[1].resize(count);

```
        }
```
```
 
```

        // Refining the location of the feature points

        if(pointTrackingFlag && trackingPoints[1].size() < maxNumPoints)

```
        {
```
```
            vector<Point2f> tempPoints;
```

            tempPoints.push_back(currentPoint);

```
 
```

            // Function to refine the location of the corners to subpixel accuracy.

            // Here, 'pixel' refers to the image patch of size 'windowSize' and not the actual image pixel

            cornerSubPix(curGrayImage, tempPoints, windowSize, cvSize(-1,-1), terminationCriteria);

```
 
```

            trackingPoints[1].push_back(tempPoints[0]);

```
            pointTrackingFlag = false;
```
```
        }
```

Farneback Tracker

```
        // Check if the image is valid
```
```
        if(prevGray.data)
```
```
        {
```

            // Initialize parameters for the optical flow algorithm

```
            float pyrScale = 0.5;
```
```
            int numLevels = 3;
```
```
            int windowSize = 15;
```
```
            int numIterations = 3;
```
```
            int neighborhoodSize = 5;
```
```
            float stdDeviation = 1.2;
```
```
 
```

            // Calculate optical flow map using Farneback algorithm

            calcOpticalFlowFarneback(prevGray, curGray, flowImage, pyrScale, numLevels, windowSize, numIterations, neighborhoodSize, stdDeviation, OPTFLOW_USE_INITIAL_FLOW);

```
 
```
```
            // Convert to 3-channel RGB
```

            cvtColor(prevGray, flowImageGray, COLOR_GRAY2BGR);

```
 
```

            // Draw the optical flow map

            drawOpticalFlow(flowImage, flowImageGray);

```
 
```
```
            // Display the output image
```

            imshow(windowName, flowImageGray);

```
        }
```

Other Morphological Operators

Posted on May 3, 2018 by admin

Opening

Mat performOpening(Mat inputImage, int morphologyElement, int morphologySize)

```
{
```
```
    Mat outputImage, tempImage;
```
```
    int morphologyType;
```
```
 
```
```
    if(morphologyElement == 0)
```
```
        morphologyType = MORPH_RECT;
```
```
 
```
```
    else if(morphologyElement == 1)
```
```
        morphologyType = MORPH_CROSS;
```
```
 
```
```
    else if(morphologyElement == 2)
```
```
        morphologyType = MORPH_ELLIPSE;
```
```
 
```

    // Create the structuring element for erosion

    Mat element = getStructuringElement(morphologyType, Size(2*morphologySize + 1, 2*morphologySize + 1), Point(morphologySize, morphologySize));

```
 
```

    // Apply morphological opening to the image using the structuring element

    erode(inputImage, tempImage, element);

    dilate(tempImage, outputImage, element);

```
 
```
```
    // Return the output image
```
```
    return outputImage;
```
```
}
```

Closing

Mat performClosing(Mat inputImage, int morphologyElement, int morphologySize)

```
{
```
```
    Mat outputImage, tempImage;
```
```
    int morphologyType;
```
```
 
```
```
    if(morphologyElement == 0)
```
```
        morphologyType = MORPH_RECT;
```
```
 
```
```
    else if(morphologyElement == 1)
```
```
        morphologyType = MORPH_CROSS;
```
```
 
```
```
    else if(morphologyElement == 2)
```
```
        morphologyType = MORPH_ELLIPSE;
```
```
 
```

    // Create the structuring element for erosion

    Mat element = getStructuringElement(morphologyType, Size(2*morphologySize + 1, 2*morphologySize + 1), Point(morphologySize, morphologySize));

```
 
```

    // Apply morphological opening to the image using the structuring element

    dilate(inputImage, tempImage, element);

    erode(tempImage, outputImage, element);

```
 
```
```
    // Return the output image
```
```
    return outputImage;
```
```
}
```

Morphological Gradient

Mat performMorphologicalGradient(Mat inputImage, int morphologyElement, int morphologySize)

```
{
```

    Mat outputImage, tempImage1, tempImage2;

```
    int morphologyType;
```
```
 
```
```
    if(morphologyElement == 0)
```
```
        morphologyType = MORPH_RECT;
```
```
 
```
```
    else if(morphologyElement == 1)
```
```
        morphologyType = MORPH_CROSS;
```
```
 
```
```
    else if(morphologyElement == 2)
```
```
        morphologyType = MORPH_ELLIPSE;
```
```
 
```

    // Create the structuring element for erosion

    Mat element = getStructuringElement(morphologyType, Size(2*morphologySize + 1, 2*morphologySize + 1), Point(morphologySize, morphologySize));

```
 
```

    // Apply morphological gradient to the image using the structuring element

    dilate(inputImage, tempImage1, element);

    erode(inputImage, tempImage2, element);

```
 
```
```
    // Return the output image
```
```
    return tempImage1 - tempImage2;
```
```
}
```

TopHat

Mat performTopHat(Mat inputImage, int morphologyElement, int morphologySize)

```
{
```
```
    Mat outputImage;
```
```
    int morphologyType;
```
```
 
```
```
    if(morphologyElement == 0)
```
```
        morphologyType = MORPH_RECT;
```
```
 
```
```
    else if(morphologyElement == 1)
```
```
        morphologyType = MORPH_CROSS;
```
```
 
```
```
    else if(morphologyElement == 2)
```
```
        morphologyType = MORPH_ELLIPSE;
```
```
 
```

    // Create the structuring element for erosion

    Mat element = getStructuringElement(morphologyType, Size(2*morphologySize + 1, 2*morphologySize + 1), Point(morphologySize, morphologySize));

```
 
```

    // Apply top hat operation to the image using the structuring element

    outputImage = inputImage - performOpening(inputImage, morphologyElement, morphologySize);

```
 
```
```
    // Return the output image
```
```
    return outputImage;
```
```
}
```

BlackHat

Mat performBlackHat(Mat inputImage, int morphologyElement, int morphologySize)

```
{
```
```
    Mat outputImage;
```
```
    int morphologyType;
```
```
 
```
```
    if(morphologyElement == 0)
```
```
        morphologyType = MORPH_RECT;
```
```
 
```
```
    else if(morphologyElement == 1)
```
```
        morphologyType = MORPH_CROSS;
```
```
 
```
```
    else if(morphologyElement == 2)
```
```
        morphologyType = MORPH_ELLIPSE;
```
```
 
```

    // Create the structuring element for erosion

    Mat element = getStructuringElement(morphologyType, Size(2*morphologySize + 1, 2*morphologySize + 1), Point(morphologySize, morphologySize));

```
 
```

    // Apply black hat operation to the image using the structuring element

    outputImage = performClosing(inputImage, morphologyElement, morphologySize) - inputImage;

```
 
```
```
    // Return the output image
```
```
    return outputImage;
```
```
}
```

Slimming/Thickening The Shapes

Posted on May 3, 2018 by admin

Erosion

Mat performErosion(Mat inputImage, int erosionElement, int erosionSize)

```
{
```
```
    Mat outputImage;
```
```
    int erosionType;
```
```
 
```
```
    if(erosionElement == 0)
```
```
        erosionType = MORPH_RECT;
```
```
 
```
```
    else if(erosionElement == 1)
```
```
        erosionType = MORPH_CROSS;
```
```
 
```
```
    else if(erosionElement == 2)
```
```
        erosionType = MORPH_ELLIPSE;
```
```
 
```

    // Create the structuring element for erosion

    Mat element = getStructuringElement(erosionType, Size(2*erosionSize + 1, 2*erosionSize + 1), Point(erosionSize, erosionSize));

```
 
```

    // Erode the image using the structuring element

    erode(inputImage, outputImage, element);

```
 
```
```
    // Return the output image
```
```
    return outputImage;
```
```
}
```

Dilation

Mat performDilation(Mat inputImage, int dilationElement, int dilationSize)

```
{
```
```
    Mat outputImage;
```
```
    int dilationType;
```
```
 
```
```
    if(dilationElement == 0)
```
```
        dilationType = MORPH_RECT;
```
```
 
```
```
    else if(dilationElement == 1)
```
```
        dilationType = MORPH_CROSS;
```
```
 
```
```
    else if(dilationElement == 2)
```
```
        dilationType = MORPH_ELLIPSE;
```
```
 
```

    // Create the structuring element for dilation

    Mat element = getStructuringElement(dilationType, Size(2*dilationSize + 1, 2*dilationSize + 1), Point(dilationSize, dilationSize));

```
 
```

    // Dilate the image using the structuring element

    dilate(inputImage, outputImage, element);

```
 
```
```
    // Return the output image
```
```
    return outputImage;
```
```
}
```

Background Subtraction VS Frame Differencing

Posted on May 3, 2018 by admin

Background Subtraction

    // Create MOG Background Subtractor object

    pMOG= cv::bgsegm::createBackgroundSubtractorMOG();//new BackgroundSubtractorMOG();

```
 
```

    // Create MOG2 Background Subtractor object

    pMOG2 = createBackgroundSubtractorMOG2(20, 16, true);//new BackgroundSubtractorMOG2();

```
 
```
```
        // Capture the current frame
```
```
        cap >> frame;
```
```
 
```
```
        // Resize the frame
```

        resize(frame, frame, Size(), scalingFactor, scalingFactor, INTER_AREA);

```
 
```

        // Update the MOG background model based on the current frame

```
        pMOG->apply(frame, fgMaskMOG);
```
```
 
```

        // Update the MOG2 background model based on the current frame

        pMOG2->apply(frame, fgMaskMOG2);

```
 
```
```
        // Show the current frame
```
```
        //imshow("Frame", frame);
```
```
 
```
```
        // Show the MOG foreground mask
```

        //imshow("FG Mask MOG", fgMaskMOG);

```
 
```

        // Show the MOG2 foreground mask

        imshow("FG Mask MOG 2", fgMaskMOG2);

Frame Differencing

Mat frameDiff(Mat prevFrame, Mat curFrame, Mat nextFrame)

```
{
```

    Mat diffFrames1, diffFrames2, output;

```
 
```

    // Compute absolute difference between current frame and the next frame

    absdiff(nextFrame, curFrame, diffFrames1);

```
 
```

    // Compute absolute difference between current frame and the previous frame

    absdiff(curFrame, prevFrame, diffFrames2);

```
 
```

    // Bitwise "AND" operation between the above two diff images

    bitwise_and(diffFrames1, diffFrames2, output);

```
 
```
```
    return output;
```
```
}
```