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Messages - k8jb

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General / Re: Rev on WIndows 10 crash dumps
« on: 2020 January 27 11:19:06 »
AMEN!  That's why my primary machine is Linux!  Tnx again!

General / Re: Rev on WIndows 10 crash dumps
« on: 2020 January 27 10:45:44 »
Tnx, I'll try your suggestions. 

HALLELUJAH - we have a solution!  The --opengl=desktop stopped the crashes!  I haven't done any further  regression testing but so far, so good!

What does this tell you???


General / Re: Rev on WIndows 10 crash dumps
« on: 2020 January 27 09:25:50 »
If I'm reading the BIOS info correctly, the integrated graphics is already disabled as it should be. 

Only thing I can think of is both machines have 32GB of RAM - more than I ever used before. 

Both machines also use SSDs.

General / Re: Rev on WIndows 10 crash dumps
« on: 2020 January 27 09:13:16 »
I'm using a GTX1050 graphics card with the latest drivers.  The only thing I did recently was add 16GB of memory (for a total of 32GB) - both machines have 32GB. The other Win10 machine has an RTX 2080 card in it also with the latest drivers.

Here's a PI benchmark so that should have all the info you asked for:
Benchmark version ...... 1.00.08
Input checksum ......... 2cd72b67e12fff2812ef5b5da054ab2a70a25e23
Serial number .......... E7117P7423M52465U24C1IER87CUUXJ2

CPU Identification
CPU vendor ............. GenuineIntel
CPU model .............. Intel(R) Core(TM) i7-7700K CPU @ 4.20GHz

System Information
Platform ............... Windows
Operating system ....... Microsoft Windows 10 Pro
Core version ........... PixInsight Core 1.8.8-4 (x64)
Logical processors ..... 8
Total memory size ...... 31.962 GiB

Execution Times
Total time ............. 01:09.55
CPU time ............... 00:46.22
Swap time .............. 00:23.31
Swap transfer rate ..... 711.162 MiB/s

Performance Indices
Total performance ...... 6763
CPU performance ........ 8189
Swap performance ....... 3939

I'll have to look at the BIOS to disable the Intel HD graphics - assuming its there, can't see it from Windows - unless its hidden somewhere!  I usually use my Linux machine anyway but it's disconcerting to see the crash dumps that I can't stop!



General / Re: Rev on WIndows 10 crash dumps
« on: 2020 January 27 07:55:31 »
More info:  Checked another Win10 machine (new, first PI install) and I get exactly the same crash dumps.

General / Rev on WIndows 10 crash dumps
« on: 2020 January 26 10:30:09 »
For some reason, I get a crash dump with PixInsight on Windows 10 every time I load the program.  Haven't done anything at all except load the program and I get a ~26MB dump.  Everything seems to work OK, just the incessant dumps for no obvious reason!  Can't find anything similar on Linux Mint 19.3.

The Win10 Event Viewer shows:
Faulting application name: PixInsight.exe, version:, time stamp: 0x5e1db5eb
Faulting module name: Qt5WebEngineCore.dll, version:, time stamp: 0x5dc1834c
Exception code: 0xc0000005
Fault offset: 0x0000000001c3d1c3
Faulting process id: 0xd00
Faulting application start time: 0x01d5d47522694db8
Faulting application path: C:\Program Files\PixInsight\bin\PixInsight.exe
Faulting module path: C:\Program Files\PixInsight\bin\Qt5WebEngineCore.dll
Report Id: 908fff17-257e-4528-a6fa-ef1319ea588c
Faulting package full name:
Faulting package-relative application ID:

Anybody know anything about this?  I suppose I could uninstall/re-install but until I know what the problem is, I'd rather see what others might have found.


General / Re: Missing scripts
« on: 2020 January 09 13:32:44 »
Tnx, just found the same thing and they appear to have been added!  Wonder why they didn't get added the first time around...

General / Missing scripts
« on: 2020 January 09 10:43:53 »
I have the latest PI installed on a Linux platform and Windows 10.  Both show the Linear Defect detection and Pattern Subtraction scripts as having been downloaded and installed but they don't show up in any of the script categories. As I recall, I had a similar problem a long time ago but I can't remember how I fixed it.  The Batch Channel Extraction script was installed at the same time and it shows up!



Announcements / Re: New Image, PuWe 1, and related contents
« on: 2020 January 06 13:01:26 »
Ok, what am I doing wrong - still don't see the scripts!


Announcements / Re: New Image, PuWe 1, and related contents
« on: 2019 December 30 13:23:42 »
Where did you find the scripts to download?  Nothing shows up when I check for updates.


Announcements / Re: PixInsight 1.8.7 Released
« on: 2019 October 01 15:38:17 »
Downloaded 1.8.7 for Linux twice and got two different files: one had the installer and PixInsight folder, the second had a tar file with the same installer and folder.  Neither seemed to install properly -  the installer reports no errors but 1.8.7 refuses to run.  I tried installing on VirtualBox but that has its own set of problems.

I re-installed 1.8.6 and it runs fine.  For the record, I'm using Linux Mint 18.3 Cinnamon on an i7-3770 platform with 16GB of memory.  I installed the Windows version on a Windows 10 system and so far so good and 1.8.7 also seemed to be OK on VMWare/Windows 7 installation.

Any ideas why my PI 1.8.7 installation fails while 1.8.6 is fine?


General / Re: NB processing problem
« on: 2018 August 06 06:57:55 »

I get  an error message:

Error 403 - Forbidden
You don't have permission to access the requested resource. Please contact the web site owner for further assistance.

Docs access is OK.


General / NB processing problem
« on: 2018 August 05 18:45:26 »
Just started doing NB recently and ran into a problem I haven't been able to work around.  M27: I have my RGB image (and an LRGB version that turned out decent) but I want to combine some OIII and Ha.  Tried using the NB script but the result completely washes out the interesting interior of the nebula while adding to the faint nebulosity outside the main body.  The OIII and Ha images are very bright and somewhat featureless compared to the RGB image.

I've investigated a couple of NBRGB combination techniques and none seem to work for me on M27, other large nebulae, no problem, but M27 is giving me fits!  Someone point me in the right direction.



ES127mm-FCD100, 0.7xFF, QSI-683

One thing I might add:  the problem seems to arise ONLY on cosmetically corrected subs, but in this case, it only seems to affect my green subs. 

I did a full integration sequence (including LocalNormalization) using the non-CC'd subs and the green channel integration was about the same background level as the blue.  Now I wonder what the CosmeticCorrection process is doing that would cause this...


(1) I'm having a hard time understanding what's happening here. 

RGB data sets, all 3 uncalibrated images roughly the same minimum sky background levels (R about half B or G, B and G about the same).  After calibration, about the same ratios, nothing looks odd.  I integrate using LocalNormalization (AdditiveWithScaling has the same effect) and my integrated Green image is now 10% of the R and B (i.e., G background is .004 while R and B are closer to .030.  Stats shows about the same standard deviation in all integrated images but the average G is again 10% of the B and R images. 

If I disable normalization, the integrated G image is now similar to the B and R.  I've read the description of the processes but why I'm seeing such a huge scaling eludes me.  FWIW, my dataset was only some test images (15x60s of M81/82), not nearly enough and transparency wasn't all that good either but I'm at a loss to understand the results I'm getting.  Any help appreciated!

2nd question: I thought I had a handle on flats until I went from a long focus RC to a short focus refractor and a new camera.  Looks like my previous technique needs some adjustment but my question is this:  I've always abided by the conventional wisdom 1/3-1/2 the sensor's linear range but I'm wondering should a flat be in some way matched to the average image level, or average background, etc?  Something like that rather than some arbitrary level?  I've made flats using a flat panel at 3 different exposure levels for each filter and when I use the results to calibrate an existing dataset, I can get very different results.  I'd appreciate some advice...

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