Quote:
Originally Posted by Munchskull
Would you be able to post the computer version of the code?
And if you can, would you be able to give directions on how to run it? (Ex. What environment I would need? Required libraries? Required camera? Ect.)
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I'll take a quick shot at this, from memory. Give it a try and ask questions if you run into problems. This will eventually morph into a readme in our code, but feedback will help us debug it.
The code in our git repo (
https://github.com/FRC900/2015VisionCode) will build and run on Linux or Windows. The training code will require either Linux or cygwin for some of the scripts. The C++ code will build on everything we've tried, which includes X86 windows, X86 Linux, ARM Linux (for the Jetson) and so on.
You'll need OpenCV 2.4.x installed. On Linux this is typically an apt-get thing or the equivalent. For windows, the OpenCV page is good -
http://docs.opencv.org/doc/tutorials...s_install.html.
For cygwin, we've had luck with the tarball at
http://hvrl.ics.keio.ac.jp/kimura/op...cv-2.4.11.html. I think we had to move the files extracted into /lib, /share, and so on for the compiler to find them.
The code works with any camera we've thrown at it. It will also run on still images or on video files. For example, for testing we ran the code against video we've downloaded from youtube. We have special code in place for Logitech C920s under Linux since that's what we used, but it wasn't as critical as we thought to use that particular camera.
The detection code itself is in the subdir bindetection. Steps to build :
1. cd bindetection/galib247
2. make
3. cd ..
4. cmake .
5. make
We've hit a weird bug where occasionally you get a weird link error the first time through. If so, repeat the "cmake ." and make.
This will produce the creatively named binary "test", which is the recycle bin detector.
Most of the options to those code can be controlled from the command line. One thing to edit is line 25 of classifierio.cpp. Change the initial /home/ubuntu to the directory the code has been downloaded to. This will require a recompile to take effect.
To run using a camera, run test. This will open the default camera and start detecting. Adding a number to the command line to pick another camera.
To run against a video, add the video name to the command line (e.g. "test video.avi").
I'm sure I'm missing something but that's a start.