Paul, You could call gdal_calc.py and pass it the numpy formulas on the command line…Otherwise it might be best to bring the raster in to OpenCV.
--Eric From: gdal-dev [mailto:gdal-dev-boun...@lists.osgeo.org] On Behalf Of Paul Meems Sent: Thursday, August 03, 2017 2:51 PM To: Chris Waigl Cc: gdal-dev@lists.osgeo.org Subject: Re: [gdal-dev] Raster statistics Thanks Chris for your reply. I forgot to mention I'm not using GDAL with Python. I use it with C++ and/or C#. Paul [http://www.bontepaarden.nl/bontepaarden/images/newButton.png]Paul Meems Release manager, configuration manager and forum moderator of MapWindow GIS. www.mapwindow.org<http://www.mapwindow.org/> Owner of MapWindow.nl - Support for Dutch speaking users. www.mapwindow.nl<http://www.mapwindow.nl/> The MapWindow GIS project has moved to GitHub<https://github.com/MapWindow>! Download the latest MapWinGIS mapping engine.<https://github.com/MapWindow/MapWinGIS/releases> Download the latest MapWindow 5 open source desktop application.<https://github.com/MapWindow/MapWindow5/releases> 2017-08-03 20:05 GMT+02:00 Chris Waigl <cwa...@alaska.edu<mailto:cwa...@alaska.edu>>: I would not use gdal for this particular task. I presume you have the band data in a 2D numpy array. Then I’d get the 80th percentile for example with np.percentile() and use a boolean expression to generate a mask for the array (droneraster > perc80value ). Chris -- Christine (Chris) Waigl - cwa...@alaska.edu<mailto:cwa...@alaska.edu> - +1-907-474-5483<tel:(907)%20474-5483> - Skype: cwaigl_work Geophysical Institute, UAF, 903 Koyukuk Drive, Fairbanks, AK 99775-7320, USA On Aug 3, 2017, at 5:43 AM, Paul Meems <bontepaar...@gmail.com<mailto:bontepaar...@gmail.com>> wrote: I have a drone raster file which I want to use for some calculation. Before the calculation, I need to loose some extreme values. I want to do something like a percentile calculation where you get all values, order them and loose the top 10%. For this, I need to get all values first which can be slow when using a large file. I looked at the statistics (band.GetStatistics) but that doesn't work well. I thought I could use 2 times the standard deviation added to the mean to get roughly 97%. But with these statistics: STATISTICS_MAXIMUM=33.186080932617 STATISTICS_MEAN=24.840205979603 STATISTICS_MINIMUM=1.5951598882675 STATISTICS_STDDEV=4.7285348016053 Mean + 2*std is larger than the max. So I moved to the histogram. It is also very fast, but I'm not sure how to use it. I have this: 256 buckets from 1.53322 to 33.248: 410 77 66 66 65 58 56 45 42 87 57 72 61 65 68 70 73 82 93 ... Does this mean, bucket 1 = 410 that I have 410 pixels of value 1.53322 and the second bucket means I have 77 pixels between 1.53322 and 1.657? 1.657 = 1.53322 + ((33.248 - 1.53322)/256) Is this a good approach? Or can/should I use a different one. Thanks, Paul _______________________________________________ gdal-dev mailing list gdal-dev@lists.osgeo.org<mailto:gdal-dev@lists.osgeo.org> https://lists.osgeo.org/mailman/listinfo/gdal-dev
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