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<font face="Times New Roman, Times, serif">No, this is unaaceptable,
but I cannot reproduce it. The only problem I had was with control
points that were too close together. Are yours evenly distributed?
Can you do tests with subsets of control points?<br>
<br>
</font>
<div class="moz-cite-prefix">On 12/12/2012 01:27 PM, Knut-Frode
Dagestad wrote:<br>
</div>
<blockquote cite="mid:ka9t7u$lpq$1@ger.gmane.org" type="cite">Hi
Jan,
<br>
<br>
That sounds interesting and promising.
<br>
<br>
For the mentioned file it takes about 2 minutes with "-et 5" (low
accuracy), and 12 minutes without this switch. Without -tps it
takes less than 0.5 seconds.
<br>
The machine is quite decent with 16 GB memory and SSD disk.
<br>
<br>
Best regards from Knut-Frode
<br>
<br>
<br>
<br>
On 12. des. 2012 13:24, Jan Hartmann wrote:
<br>
<blockquote type="cite">Hi Knut,
<br>
<br>
What do you mean by "very slow"? I regularly use gdalwarp -tps
on much
<br>
larger rasters with a few thousand gcp-s, and never noticed
unacceptable
<br>
delays. Do you have very little physical memory, or many
parallel
<br>
processes running?
<br>
<br>
Jan
<br>
<br>
On 12/12/2012 01:12 PM, Knut-Frode Dagestad wrote:
<br>
<blockquote type="cite">Hi list,
<br>
<br>
When warping images with many GCPs, the -tps switch (Thin
Plate
<br>
Spline) is found to be necessary to get decent accuracy. This
makes
<br>
however warping very slow. The only method I found to increase
speed
<br>
is the -et switch, but at cost of spatial accuracy.
<br>
<br>
<br>
Below some comments about the other tries which did not help:
<br>
<br>
- compiling GDAL with armadillo support had no effect on
speed.
<br>
Btw, to compile with armadillo I had to manually insert
-llapack in
<br>
the following line in configure:
<br>
if test -z "`${CXX} testarmadillo.cpp -o testarmadillo
-larmadillo
<br>
2>&1`" ; then .....
<br>
Perhaps ${LIBS} should be added permanently to this line in
trunk?
<br>
<br>
- compiling GDAL with OpenCL had also no effect. At first
surprising,
<br>
but looking at the opencl warp kernel it seems that it only
makes a
<br>
difference for other resampling algorithms than nearest
neighbour?
<br>
<br>
- Increasing memory with -wm had no effect
<br>
<br>
- Using several threads (-multi -wo NUM_THREADS=ALL_CPUS)
actually
<br>
increased computing time significantly (my proj version is
4.7.1).
<br>
<br>
From the debug output, a lot of the time is apparently spent
on:
<br>
"WARP: Copying metadata from first source to destination
dataset"
<br>
Is this an indication that much time is simply spent on
reading and
<br>
writing the GCPs to/from file? If so, we could perhaps expect
improved
<br>
performance if Geolocation Arrays could be used instead (not
possible
<br>
due to <a class="moz-txt-link-freetext" href="http://trac.osgeo.org/gdal/ticket/4907">http://trac.osgeo.org/gdal/ticket/4907</a>).
<br>
<br>
<br>
The tests are made with the following file and command on
Ubuntu:
<br>
<a class="moz-txt-link-freetext" href="http://dl.dropbox.com/u/15885758/testgcp.tif">http://dl.dropbox.com/u/15885758/testgcp.tif</a> (3212 GCPs and
2048x2511
<br>
pixels covering Southern Europe)
<br>
<br>
time gdalwarp --debug on -et 5 -tps -t_srs '+proj=merc'
testgcp.tif
<br>
out.tif (+ other swithces mentioned above)
<br>
<br>
<br>
Best regards from Knut-Frode
<br>
<br>
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</blockquote>
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