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<p>Hey Connor,</p>
<p>thanks for the reply. I have looked at the subset option and I
think it would work well for the case where I have already
computed all the models. For example if I have a folder with:</p>
<p>1.las<br>
2.las<br>
...</p>
<p>Then I could spin four machines and do:</p>
<p>1] entwine build -i 1.las 2.las --subset 1 4 -o out1<br>
2] entwine build -i 1.las 2.las --subset 2 4 -o out2<br>
3] entwine build -i 1.las 2.las --subset 3 4 -o out3<br>
4] entwine build -i 1.las 2.las --subset 4 4 -o out4<br>
<br>
Then merge the results. I've noticed two things with this. It
seemed that as the number of input files increased, the memory and
time required to create each subset seemed increased also (that's
why I opted to use scan + build --run 1). The second is that I
need to wait for all point clouds to be available (both 1.las and
2.las need to be available before I can start processing them).</p>
<p>I wanted to rule out whether it was possible to do something like
(on two separate machines):</p>
<p>1] entwine build -i 1.las -o out1<br>
2] entwine build -i 2.las -o out2<br>
</p>
<p>And then merge the resulting EPT indexes into a "global" one:</p>
<p>entwine merge -i out1 out2 -o merged</p>
<p>But I don't think it's possible, correct?</p>
<p>-Piero<br>
</p>
<br>
<br>
<div class="moz-cite-prefix">On 6/13/19 10:43 AM, Connor Manning
wrote:<br>
</div>
<blockquote type="cite"
cite="mid:CAO=FyjLPi99vi4T02gaCUexSiWhc6UadmD0HZqeNAhadwQeCSQ@mail.gmail.com"
id="mid_CAO_FyjLPi99vi4T02gaCUexSiWhc6UadmD0HZqeNAhadwQeCSQ_mail_gmail_com"
class=" cite">
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<div dir="ltr">The `subset` option lets each iteration of the
build run a spatially distinct region, which can be trivially
merged afterward, which sounds like what you're after. Another
option could be to simply use multiple indexes - potree can
accept multiple input EPT sources, and a PDAL pipeline may have
multiple EPT readers.</div>
<br>
<div class="gmail_quote">
<div dir="ltr" class="gmail_attr">On Thu, Jun 13, 2019 at 6:46
AM Piero Toffanin <<a href="mailto:pt@masseranolabs.com"
moz-do-not-send="true">pt@masseranolabs.com</a>> wrote:<br>
</div>
<blockquote class="gmail_quote cite" style="margin:0px 0px 0px
0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"
id="Cite_7070813">
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<p>Hi there,</p>
<p>I have a question regarding the usage of Entwine and was
hoping somebody could help me? The use case is merging
point clouds that have been generated on different
machines. Each of these point clouds is part to the same
final dataset. Entwine works great with the current
workflow:</p>
<p>entwine scan -i a.las b.las ... -o output/</p>
<p>for i in {a, b, ... }<br>
</p>
<p> entwine build -i output/scan.json -o output/ --run 1</p>
<p>The "--run 1" is done to lower the memory usage. On small
datasets runtime is excellent, but with more models the
runtime starts to increase quite a bit. I'm looking
specifically to see if there are ways to speed the
generation of the EPT index. In particular, since I
generate the various LAS files on different machines, I
was wondering if there was a way to let each machine
contribute its part of the index from the individual LAS
files (such index mapped to a network location) or if a
workflow is supported in which each machine can build its
own EPT index and then merge all EPT indexes into one? I
don't think this is possible, but wanted to check.</p>
<p>Thank you for any help,</p>
<p>-Piero<br>
</p>
<p><br>
</p>
</div>
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<div class="moz-signature">-- <br>
<p><font face="Helvetica, Arial, sans-serif"><b>Piero Toffanin</b><br>
Drone Solutions Engineer<br>
</font></p>
<p><font face="Helvetica, Arial, sans-serif"> <font
color="#5599ff"><a href="https://www.masseranolabs.com">masseranolabs.com</a></font><br>
</font> <a href="https://www.piero.dev">piero.dev</a><br>
</p>
<p><br>
</p>
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