PDAL | PDAL is Point Data Abstraction Library GDAL for point cloud data | Image Editing library
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Trending Discussions on PDAL
QUESTION
How can you use filters to compute the height (Z) of the point in a point view that is higher than 90% of the other points using PDAL?
...ANSWER
Answered 2022-Mar-30 at 14:16Maybe you can use pdal's filters.python. In the filter use numpy.percentile to filter for the 90% percentile.
QUESTION
I'm using a .yml file to create an environment on an external drive.
My .yml file contains...
...ANSWER
Answered 2021-Jan-29 at 23:13I found the problem, after receiving a more coherent error message...
QUESTION
I'm working on a project that's using .las lidar files.
I googled and found that PDAL can be used to convert .las to .pcd files, so that I can use the PCL library.
I converted files from .las to .pcd using PDAL.
When I tried to read the pcd files using the following code:
...ANSWER
Answered 2020-Oct-29 at 14:57I would suggest that you take a close look at the PCD writer documentation for a number of helpful pointers for this particular conversion.
The issue here is that, while double precision floats are valid PCD, they are not supported by PCL's default point types. You could hand edit the PCD file you've already converted, changing the size of the x, y, and z dimensions from 8 to 4. Or you could just rerun pdal translate
being sure to set the datatype and precision while selecting the fields you want converted with the order
option. An example would look something like
QUESTION
For context, this problem relates to a docker image that will be run using azure batch.
Here is the Dockerfile
, in full:
ANSWER
Answered 2020-Mar-10 at 19:32The problem you are facing is because you added the conda activate
to the .bashrc
script which is only activated for login shells. When you run the container interactively, that is what you are getting. However, when you just try to invoke the python script directly, you do not get a login shell so your conda environment is not activated.
One think you could do is not use the conda activate and instead run the script with conda run
. To simplify the command-line, add this entrypoint to your Dockerfile:
ENTRYPOINT ["conda", "run", "-n", "$CONDA_DEFAULT_ENV", "python", "classify.py"]
Using this in the entrypoint also allows the caller to pass command-line arguments via docker run.
From the Dockerfile reference
Command line arguments to docker run will be appended after all elements in an exec form ENTRYPOINT
For a more detailed explanation, see Activating a Conda environment in your Dockerfile
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