skr_robo's profile - activity

Using Harris Corner Detector on video I am trying to use Harris Corner Detector on video based on the example given here

@whdt No. sorry.

API/ Library for re-orienting 360 degree camera frame efficiently I am trying to correct the orientation of a 360 degree

@Igor I had already solved it earlier and now I don't have a way of checking the solution. Sorry.

OpenCV - Streaming H264 over RTSP using FFMPEG in version 3.4 I am trying to capture an RTSP stream from a VIRB 360 came

OpenCV - Streaming H264 over RTSP using FFMPEG in version 3.4 I am trying to capture an RTSP stream from a VIRB 360 came

I tried cv::CAP_GSTREAMER option as well. It doesn't display anything.

OpenCV - Streaming H264 over RTSP using FFMPEG in version 3.4 I am trying to capture an RTSP stream from a VIRB 360 came

@manfeyn Do you mean Opencv 3.4 can capture h264 videos over rtsp streams?

I have to wait a day to add the answer, according to OpenCV forum rules. Anyways, thank you for the help.

I did see that file and I thought it was only necessary if I was trying to add the library using find_package().

How to check whether it is in compilation or linking? Anyways, I have figured what is wrong and I am adding it as an a

That did not fix the issue. This time cmake . gave a warning that it was dropping the third argument of target_link_libr

I added it here because I felt someone might have tried accessing Basler camera via OpenCV and may have figured out how

I added it here because I felt someone might have tried accessing Basler camera via OpenCV and may have figured out how

How to include and link Pylon library with OpenCV project I am trying to access images from a Basler camera interfaced w

How to include and link Pylon library with OpenCV project I am trying to access images from a Basler camera interfaced w

How to include and link Pylon library with OpenCV project I am trying to access images from a Basler camera interfaced w

How to include and link Pylon library with OpenCV project I am trying to access images from a Basler camera interfaced w

How to include and link Pylon library with OpenCV project I am trying to access images from a Basler camera interfaced w

How to include and link Pylon library with OpenCV project I am trying to access images from a Basler camera interfaced w

I tried the same code on my laptop and the webcam. The output of std::cout << cap.get(CV_CAP_PROP_FORMAT); was same: 16. But the images were fine.

I don't have documentation for this camera and the model is unknown, which is the stem of all problems. I printed format using std::cout << cap.get(CV_CAP_PROP_FORMAT);. It returned 16. I am trying to figure out what that means.

I tried YUV2BGR as well. No change in the results.

I am using the following code to access video feed from a camera (lsusb command in Jetson TX1 terminal lists the camera as Pixart Imaging, Inc.).

Code:

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>

int main()
{
        cv::VideoCapture cap(1);
        if(!cap.isOpened())
        {       
                std::cout << "Input error\n";
                return -1;
        }

        cv::namedWindow("Video Feed", cv::WINDOW_AUTOSIZE);

        for(;;)
        {
                cv::Mat frame;
                cap >> frame;
                std::cout << "Type: " << frame.type() << "\n";
                //cv::cvtColor(frame, frame, CV_YUV2RGB);
                //cv::resize(frame, frame, cv::Size2i(256, 144));
                cv::imshow("Video Feed", frame);        
                if (cv::waitKey(10) == 27)
                {
                        break;
                }
        }       
        cv::destroyAllWindows();
        return 0;
}

The screeenshots of the video feed can be seen below:

I am trying to identify the color format of the camera and convert it to RGB. I have tried different color formats, but I focused mainly on YUV to RGB conversion as shown below (this line is commented out in the above code): cv::cvtColor(frame, frame, CV_YUV2RGB);

I have also tried different variants of YUV as listed here. However, I haven't received any result close to a normal RGB image.

I am also getting the following message on the terminal:

Corrupt JPEG data: 1 extraneous bytes before marker 0xd9

1) Is this just a defective camera?

2) Are there any tests/ approaches to identify and rectify the problem?

Edit based on comments:

I have tried YUV2BGR as well, but the results are same. Is there a way to figure out output format of the camera if the model is unknown?

I saw an example for the usage of namedWindow as shown below:

namedWindow("edges", 1)

I believe that the number 1 is related to a flag such as WINDOW_AUTOSIZE. However, I am not able to find any clear documentation which says what number relates to what flag. In the case of imread, the documentation states:

>0 Return a 3-channel color image.

=0 Return a grayscale image.

<0 Return the loaded image as is (with alpha channel)

For namedWindow, I found that this link has a section called Enumerations which had the following content:

enum    cv::WindowFlags { 
  cv::WINDOW_NORMAL = 0x00000000, 
  cv::WINDOW_AUTOSIZE = 0x00000001, 
  cv::WINDOW_OPENGL = 0x00001000, 
  cv::WINDOW_FULLSCREEN = 1, 
  cv::WINDOW_FREERATIO = 0x00000100, 
  cv::WINDOW_KEEPRATIO = 0x00000000, 
  cv::WINDOW_GUI_EXPANDED =0x00000000, 
  cv::WINDOW_GUI_NORMAL = 0x00000010 
}
    Flags for cv::namedWindow.

However, I am not sure if this is what I am looking for because some of the values on RHS are not unique. So, how do we differentiate between them (for example cv::WINDOW_NORMAL and cv::WINDOW_KEEPRATIO)? Is there any other place where I can this information for namedWindow and other functions?

I used the solution available here and it works fine.

I have a hough transform object detection code which detects the target objects. But a few lines are detected from the green background (trees). I wish to eliminate all the green background. I tried a code based on this and it worked fine. But the problem is that the resulting image is black and white. I want the green part to go black, but I want the rest to remain as the original image.

I also tried the second solution from this, with the image given there. The problem was whenever I accessed the result image and displayed it with imshow, it would display like the original.

So, are there any better solutions? Is there a way that I can see all pixels that fall in an hsv range, using inRange and then, instead of turning the whole image black and white, just turn those pixels in the range to black?

What is the difference between the definitions:

1) vector<Vec4i> lines and

2) Vec4i l

I found both these in the same code here. I am wondering if there is any difference between the both? If not why use the first format which is longer?