[pdal] [Filters] Decimation built into a reader

[Andrew Bell]

The problem with this is that there are lots of ways to decimate and it
would complicate the logic of the readers in order to fulfill this desire.

One simple thing you can do is to create a decimated file using streaming
mode and then use that as input to your more complex pipeline:

{
  "pipeline": [
    "input.las",
    {
      "type" : "filters.decimation",
      "step" : 10
    }"
    "output.las"
  ]
}

Then run this with 'pdal pipeline --stream decimator.json'

If your processing pipeline supports streaming mode directly, you can use
that as well and dispense with the creation of the intermediate file.

Hope that helps,


On Thu, Jun 15, 2017 at 10:18 AM, GUIMMARA, Sébastien (External) <
sebastien.guimmara.external at airbus.com> wrote:

> Hello everyone,
>
>
>
> I’m trying to import a massive point cloud as a collection of LAS files
> (6GB, 27 files), and I realized that my desktop computer simply couldn’t
> handle the memory footprint of such a massive dataset.
>
>
>
> So I’m putting a decimation filter to reduce the size, but I’m having a
> doubt: is the filter useful here or is the dataset entirely loaded into
> memory before even applying the filter ? In other words, does the
> downstream filters controls how the upstream reader loads data into memory ?
>
>
>
> If not, would it be a nice feature to include to some (all ?) readers ?
> Like a builtin decimation/sampling filter.
>
>
>
> Sébastien
>
>
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-- 
Andrew Bell
andrew.bell.ia at gmail.com
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