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2017-02-21 10:00:45 -0600	asked a question	What is a recommended way to find the corresponding points of the top-down image when calculating the Perspective Transform? Is it done just visually? Like here http://www.pyimagesearch.com/2014/08/... So if it was a more complicated image like that of a road, and I wanted a top-down view of part of a lane of the road. The only way for me to select corresponding points for the best possible top-down view would be by visual inspection?
2016-11-01 12:25:35 -0600	commented answer	Why does the HoughLinesP output a 3D array, instead of a 2D array? Awesome. Thanks a lot for your help!
2016-11-01 11:59:49 -0600	commented answer	Why does the HoughLinesP output a 3D array, instead of a 2D array? Thanks. Is there a link/github code to these "python wrappers" for me to look at?
2016-11-01 11:46:40 -0600	received badge	● Scholar (source)
2016-11-01 11:46:39 -0600	received badge	● Supporter (source)
2016-11-01 11:46:33 -0600	commented answer	Why does the HoughLinesP output a 3D array, instead of a 2D array? Both the links in your answer link to the same line of code. Was that intentional? But regardless, my skills aren't enough to understand how this all gets converted, and what it means that Vec41 is a descendant of Matx. It's not necessary, but if you could point me in a general direction to understand the "process" of it all better, I would highly appreciate it. But thank you!
2016-11-01 11:13:08 -0600	commented question	Why does the HoughLinesP output a 3D array, instead of a 2D array? @berak OpenCV version : 3.1.0
2016-11-01 11:02:49 -0600	asked a question	Why does the HoughLinesP output a 3D array, instead of a 2D array? This is the sample output I have - `[[[539 340 897 538]] [[533 340 877 538]] [[280 460 346 410]] [[292 462 353 411]] [[540 343 798 492]]]` Its dimensions are (5,1,4) I am trying to understand what scenario will the function output something like (n,2,4) or (n,3,4). But I can't think of any and all the images I have worked with right now result in a 3D array of dimensions (n,1,4). Wouldn't just a 2D array be sufficient and perhaps more efficient?