You are totally right. There is no imposed constraint on execution time since you wait for the image to be acquired and processed before execution continue.
It is exactly as on an ordinary computer where you have to wait for example for the home page to load before you read it, up to a certain not well defined limit faster is however better. Nicklas Karlsson On Wed, 08 Oct 2014 09:01:20 -0500 sam sokolik <sa...@empirescreen.com> wrote: > I don't need realtime. The process in my mind would go like this. > > Move camera to target - wait for opencv to acquire target (maybe > averaging over a number acuisitions..) Calculate based on camera > location and target location where the target actually is. > > we have some glorified vinyl cutters at work that use target > acquisitions to align the sheet. They are defiantly not realtime. The > video processing is done on the windows xp computer - and then gets sent > to the machine over a serial connection. > > sam > > > On 10/8/2014 8:25 AM, Ralph Stirling wrote: > > Running OpenCV code in a real time thread would be an entirely different > > matter, I suspect. I do not know if the cv2 library would be compatible > > with real time requirements, or what level of processing could be > > accomplished > > in a reasonable fraction of a servo period. You would also need to think > > carefully about what camera you use. I used a USB2 microscope camera, and > > I suspect USB2 would be entirely incompatible with the realtime > > requirements. > > Perhaps some PCI bus board with internal frame buffer could work, if OpenCV > > could talk to it. I normally just get UVC compatible cameras, but those > > are all > > USB2. > > > > If you wanted to really get into it, you could work with the machinekit > > fork, > > and use the Parallella board as your platform. That has a 16 core (or 64 > > core) > > processor that has had OpenCV ported already. There is also a Xilinx fpga > > (which contains two Arm cores that run Linux) that could be used for CNC > > tasks. I have one sitting on my desk, but don't know when I'm going to have > > time to play with it. There would still be the matter of camera > > communications. > > > > -- Ralph > > ________________________________________ > > From: Javier Ros [j...@unavarra.es] > > Sent: Wednesday, October 08, 2014 1:00 AM > > To: Enhanced Machine Controller (EMC) > > Subject: Re: [Emc-users] opencv for shape recognition > > > > Very interesting Ralph. > > > > I always wandered if it would be possible to do head position tracking for > > robot calibration based on OpenCV. Do you think that this would be possible > > using a real time HAL module, written in C, using the a PREEMPT RT PATH > > real time based kernel?. If it is possible, I suppose that GPU power could > > theoretically be made available to OpenCV operations. > > > > What is you opinion?. > > > > Thanks, > > > > Javier > > > > > > On Tue, Oct 7, 2014 at 9:20 PM, Ralph Stirling < > > ralph.stirl...@wallawalla.edu> wrote: > > > >> This is what I used to do machine vision homing a couple of years ago: > >> FitElipse is a function that finds the best fit circle in the frame. I > >> can supply > >> that function too if you like. It is adapted from examples I found online. > >> > >> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ > >> # homecart.py > >> import sys > >> import urllib2 > >> import random > >> import cv2.cv as cv > >> import time > >> import hal > >> > >> if __name__ == '__main__': > >> > >> h = hal.component("homecart") > >> h.newpin("offset", hal.HAL_FLOAT, hal.HAL_OUT) > >> h.newpin("located", hal.HAL_BIT, hal.HAL_OUT) > >> h.ready() > >> > >> capture = cv.CaptureFromCAM(0) > >> > >> while True: > >> img = cv.QueryFrame(capture) > >> > >> gimg = cv.CreateImage((640,480), cv.IPL_DEPTH_8U, 1) > >> > >> cv.CvtColor(img, gimg, cv.CV_RGB2GRAY) > >> > >> fe = FitEllipse(gimg, 116) > >> h['offset'] = fe.offset > >> h['located'] = fe.located > >> > >> In the hal file, I have: > >> > >> loadusr ./homecart # Can't have .py on the end of the filename > >> > >> then I can use homecart.located and homecard.offset pins. I can't find > >> an example where I actually used it to do the homing though. I must have > >> gotten distracted by something else before I got that step completed. > >> > >> Hope this is useful. > >> > >> -- Ralph > >> > >> > >> > >> -- Ralph > >> ________________________________________ > >> From: sam sokolik [sa...@empirescreen.com] > >> Sent: Tuesday, October 07, 2014 11:59 AM > >> To: Enhanced Machine Controller (EMC) > >> Subject: Re: [Emc-users] opencv for shape recognition > >> > >> You make it sound /so/ easy... :) > >> > >> sam > >> On 10/7/2014 1:09 PM, andy pugh wrote: > >>> On 7 October 2014 19:06, sam sokolik <sa...@empirescreen.com> wrote: > >>>> this is my first real exposure to python. the next step is to see how I > >>>> can fidldle hal stuff with it.. > >>> import hal > >>> > >>> make hal pins, job done :-) > >>> > >>> > >> > >> ------------------------------------------------------------------------------ > >> Meet PCI DSS 3.0 Compliance Requirements with EventLog Analyzer > >> Achieve PCI DSS 3.0 Compliant Status with Out-of-the-box PCI DSS Reports > >> Are you Audit-Ready for PCI DSS 3.0 Compliance? 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