How to Write Video File in Opencv 2.4.3

How to write video file in OpenCV 2.4.3

The problem might be the codec you are using.

A simple test to make sure your stuff is working properly is to simply retrieve frames from a webcam and write them on a video file:

// Load input video
cv::VideoCapture input_cap(argv[1]);
if (!input_cap.isOpened())
{
        std::cout << "!!! Input video could not be opened" << std::endl;
        return;
}

// Setup output video
cv::VideoWriter output_cap(argv[2], 
               input_cap.get(CV_CAP_PROP_FOURCC),
               input_cap.get(CV_CAP_PROP_FPS),
               cv::Size(input_cap.get(CV_CAP_PROP_FRAME_WIDTH),
               input_cap.get(CV_CAP_PROP_FRAME_HEIGHT)));

if (!output_cap.isOpened())
{
        std::cout << "!!! Output video could not be opened" << std::endl;
        return;
}

// Loop to read from input and write to output
cv::Mat frame;

while (true)
{       
    if (!input_cap.read(frame))             
        break;

    output_cap.write(frame);
}

input_cap.release();
output_cap.release();

Python opencv video writer

So I did some research and figured it out....
https://docs.opencv.org/3.1.0/dd/d43/tutorial_py_video_display.html

import numpy as np
import cv2

haar_face_cascade = cv2.CascadeClassifier('haarcascades/haarcascade_frontalface_alt.xml')
video = cv2.VideoCapture(0)  
a = 0

fourcc = cv2.VideoWriter_fourcc(*'XVID')
out = cv2.VideoWriter('output.avi',fourcc, 20.0, (640,480))

while True:

    a = a + 1    
    check, frame = video.read()

    print(frame)

    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = haar_face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5);
    for (x, y, w, h) in faces:
        cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 0, 255), 2)

    out.write(frame)
    cv2.imshow("Face Detector", frame)

    key = cv2.waitKey(1)    
    if key == ord('q'):
        break

print(a)

video.release()
out.release()
cv2.destroyAllWindows()

Installing OpenCV 2.4.3 in Visual C++ 2010 Express

1. Installing OpenCV 2.4.3

First, get OpenCV 2.4.3 from sourceforge.net. Its a self-extracting so just double click to start the installation. Install it in a directory, say C:\.

Wait until all files get extracted. It will create a new directory C:\opencv which
contains OpenCV header files, libraries, code samples, etc.

Now you need to add the directory C:\opencv\build\x86\vc10\bin to your system PATH. This directory contains OpenCV DLLs required for running your code.

Open Control Panel → System → Advanced system settings → Advanced Tab → Environment variables...

On the System Variables section, select Path (1), Edit (2), and type C:\opencv\build\x86\vc10\bin; (3), then click Ok.

On some computers, you may need to restart your computer for the system to recognize the environment path variables.

This will completes the OpenCV 2.4.3 installation on your computer.

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2. Create a new project and set up Visual C++

Open Visual C++ and select File → New → Project... → Visual C++ → Empty Project. Give a name for your project (e.g: cvtest) and set the project location (e.g: c:\projects).

Click Ok. Visual C++ will create an empty project.

Make sure that "Debug" is selected in the solution configuration combobox. Right-click cvtest and select Properties → VC++ Directories.

Select Include Directories to add a new entry and type C:\opencv\build\include.

Click Ok to close the dialog.

Back to the Property dialog, select Library Directories to add a new entry and type C:\opencv\build\x86\vc10\lib.

Click Ok to close the dialog.

Back to the property dialog, select Linker → Input → Additional Dependencies to add new entries. On the popup dialog, type the files below:

opencv_calib3d243d.lib
opencv_contrib243d.lib
opencv_core243d.lib
opencv_features2d243d.lib
opencv_flann243d.lib
opencv_gpu243d.lib
opencv_haartraining_engined.lib
opencv_highgui243d.lib
opencv_imgproc243d.lib
opencv_legacy243d.lib
opencv_ml243d.lib
opencv_nonfree243d.lib
opencv_objdetect243d.lib
opencv_photo243d.lib
opencv_stitching243d.lib
opencv_ts243d.lib
opencv_video243d.lib
opencv_videostab243d.lib

Note that the filenames end with "d" (for "debug"). Also note that if you have installed another version of OpenCV (say 2.4.9) these filenames will end with 249d instead of 243d (opencv_core249d.lib..etc).

Click Ok to close the dialog. Click Ok on the project properties dialog to save all settings.

NOTE:

These steps will configure Visual C++ for the "Debug" solution. For "Release" solution (optional), you need to
repeat adding the OpenCV directories and in Additional
Dependencies section, use:

opencv_core243.lib
opencv_imgproc243.lib
...

instead of:

opencv_core243d.lib
opencv_imgproc243d.lib
...

You've done setting up Visual C++, now is the time to write the real code. Right click your project and select Add → New Item... → Visual C++ → C++ File.

Name your file (e.g: loadimg.cpp) and click Ok. Type the code below in the editor:

#include <opencv2/highgui/highgui.hpp>
#include <iostream>

using namespace cv;
using namespace std;

int main()
{
    Mat im = imread("c:/full/path/to/lena.jpg");
    if (im.empty()) 
    {
        cout << "Cannot load image!" << endl;
        return -1;
    }
    imshow("Image", im);
    waitKey(0);
}

The code above will load c:\full\path\to\lena.jpg and display the image. You can
use any image you like, just make sure the path to the image is correct.

Type F5 to compile the code, and it will display the image in a nice window.

And that is your first OpenCV program!

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3. Where to go from here?

Now that your OpenCV environment is ready, what's next?

1. Go to the samples dir → c:\opencv\samples\cpp.
2. Read and compile some code.
3. Write your own code.

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