This might be overkill, but would using gdal to create an overview be suitable for you?
You could call gdaladdo or use the API (BuildOverviews) http://www.gdal.org/classGDALDataset.html#a2aa6f88b3bbc840a5696236af11dde15 Etienne On Wed, Apr 11, 2012 at 11:31 AM, K.-Michael Aye <[email protected]> wrote: > Dear all, > > is there a Python API for downsampling a huge dataset? > What I would like to do: > > * get my dataset > * read out RasterXSize and RasterYSize > * calculate how many lines and rows I need to skip to get a quick overview > image, e.g. 10 lines to skip. > * Have a ReadAsArray interface where I can say something like this: > ** data = ds.ReadAsArray(xoffset, yoffset, 10000, 10000, skipping=10) > > which in numpy terms would give me every 10nth line like this: array[:,:,10] > > I really don't need quality at all, just speed, for a rough overview for > further zooming in with lassos, as the images I deal with sometimes have > more than 200 MPixels. > > Is this possible in Python? > I was thinking now, maybe one could use numpy's memmap somehow for this, > don't know much about it, though… > > Thanks for any hints! > > Best regards, > Michael > > > _______________________________________________ > gdal-dev mailing list > [email protected] > http://lists.osgeo.org/mailman/listinfo/gdal-dev _______________________________________________ gdal-dev mailing list [email protected] http://lists.osgeo.org/mailman/listinfo/gdal-dev
