sai kethamakka's profile - activity

I am sure you could do that with Qt, zooming to pixel level shows you RGB values of those pixels

Check this article out, https://pdfs.semanticscholar.org/174e...

You could try using background subtraction and motion segmentation. Here's an article that might be useful http://www.pyimagesearch.com/2015/05/...

cv::Mat tmp(qImage.height(), qImage.width(), CV_8UC4, (void*) qImage.bits(), qImage.bytesPerLine());
cv::cvtColor(tmp, cvImage, CV_RGBA2RGB);

This code worked for me to convert QImage to 8UC4 cv::Mat, hope it helps. And reversing from Mat to QImage,

QImage tmp((unsigned char*) cvImage.data, cvImage.size().width, cvImage.size().height, cvImage.step, QImage::Format_RGB888);
qImage = tmp.rgbSwapped().convertToFormat(QImage::Format_ARGB32_Premultiplied);

Edited: Conversion from 8UC4 to QImage

As the spots are well defined and assuming camera is fixed, you could use opencv background subtraction with sufficient amount of history to detect if there is an object in a particular parking spot. Look at this opencv tutorial for more information. http://docs.opencv.org/master/d1/dc5/...

You can do it using opencv built with Qt. imshow() has a ton of features with Qt. You can zoom in to a pixel level.

Here are a couple of interesting links that can be useful http://stackoverflow.com/questions/26... http://flothesof.github.io/smile-reco...

Hi, here are a few methods that are related

opencv: cv::adaptiveThreshold, cv::threshold with OTSU method

opensource implementations: https://github.com/zp-j/binarizewolfj..., https://github.com/rmtheis/bradley-ad...

other links to similar discussions: http://stackoverflow.com/questions/13..., http://stackoverflow.com/questions/13..., http://stackoverflow.com/questions/20...

Hope this helps