At the moment it's offline so I'm processing the images on a mac.
However there are smaller embedded systems that will have the capability to process data (at a slower rate). My thinking is possibly:
C2 Odroid 64bit (2GB) performing the control, focus etc but then cross mount the images to stream over to a second system vs wifi which then takes the feed and processes the images. The difference is it's running on a dedicated embedded system (12V).
There's a couple of deep learning ideas I want to try - including noise removal and processing. The idea is that you can see both the raw images but also the processed ones.
I've done a lot of OpenCL too so I may be tempted to make a GPU library for the pipeline but as always GPU works best with it's own memory and you need a couple of GB to keep the images in memory or do FFT etc.
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I've started playing with Octave
I run a 64 bit version of INDI (compiled myself) and use the 32bit version of the drivers.
It's possible
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So one issue with the 64bit version and the latest "numpty" is that the issue with the astrometry script and the rule changes in numpty about dynamic casting:
TypeError: Cannot cast ufunc add output from dtype('int32') to dtype('uint16') with casting rule 'same_kind'
OpenPHD2 can store guider frames (the raw FITS) for the entire run.
Not many people use this perhaps, however I use it to create the point spread function for each long exposure frame.
I've had a look but couldn't see how todo this on Ekos.. can you?
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Just got a new iPhone for my birthday (old one was 2009 3GS!).. VNC client app and hey presto!
djibb wrote: