Last week was spent trying different camera calibration methods. A few days\u00a0were spent on the checkerboard method, a few more on sticky notes and other color detection. Many problems cropped up with both these methods. I couldn’t get the program to truly recognize the checkerboard, and the way my program is set up it was very difficult to get the blob detection up and running.<\/p>\n
This week I tried the last resort clicking method which surely was the least problematic out of all the methods. Some annoying issues I ran into were:
\n1) finding reliable Python tutorials and documentation as most resources were only available for C++
\n2) once a python resource was found, it was version 2.7 rather than 3.6, so a lot of time was spent fixing up indentation and syntax issues<\/p>\n
Once all that was figured out, I wrote a tiny simple algorithm to take in the first two mouse clicks and stop after the first two, and then find the distance between the two. I have also finished up with the pixel -> mm conversion math, all that needs to be done now is testing with a reliable piece of paper \/ sticky note etc.\u00a0taped to the forehead. I will probably do that on Sunday and edit this post with results, along with adding the option for command line arguments for more generality.<\/p>\n
The only final issue is consistency, as hough circles distance in pixels detection seems to work on only 50% of the images, and I have yet to find out a solution for the short-scalar overflow. It shouldn’t be occurring based on the method I’m using, not sure what’s wrong.<\/p>\n","protected":false},"excerpt":{"rendered":"
Last week was spent trying different camera calibration methods. A few days\u00a0were spent on the checkerboard method, a few more on sticky notes and other color detection. Many problems cropped up with both these methods. I couldn’t get the program … Continue reading