pypcd-imp 0.1.5

Pure Python PCD reader/writer

pypcd-imp

What?

Pure Python module to read and write point clouds stored in the PCD file format, used by the Point Cloud Library. Slightly adapted and improved from klintan and dimatira. Can now handle Structured PointClouds (at least in binary compressed format)

Why?

You want to mess around with your point cloud data without writing C++ and waiting hours for the template-heavy PCL code to compile.

You tried to get some of the Python bindings for PCL to compile and just gave up.

How does it work?

It parses the PCD header and loads the data (whether in ascii, binary or binary_compressed format) as a Numpy structured array. It creates an instance of the PointCloud class, containing the point cloud data as pc_data, and some convenience functions for I/O and metadata access.

Example

from pypcd_imp import pypcd
# also can read from file handles.
pc = pypcd.PointCloud.from_path('foo.pcd')
# pc.pc_data has the data as a structured array
# pc.fields, pc.count, etc have the metadata

# center the x field
pc.pc_data['x'] -= pc.pc_data['x'].mean()

# save as binary compressed
pc.save_pcd('bar.pcd', compression='binary_compressed')

Is it beautiful, production-ready code?

No.

What else can it do?

There's a bunch of functionality accumulated over time, much of it hackish and untested. In no particular order,

• Supports ascii, binary and binary_compressed data. The latter requires the lzf module.
• Decode and encode RGB into a single float32 number. If you don't know what I'm talking about consider yourself lucky.
• Point clouds from pandas dataframes.
• Convert to and from ROS PointCloud2 messages. Requires the ROS sensor_msgs package with Python bindings installed. This functionality uses code developed by Jon Binney under the BSD license, included as numpy_pc2.py.

What can't it do?

There's no synchronization between the metadata fields in PointCloud and the data in pc_data. If you change the shape of pc_data without updating the metadata fields you'll run into trouble.

I've only used it for unorganized point cloud data (in PCD conventions, height=1), not organized data like what you get from RGBD.

While padding and fields with count larger than 1 seem to work, this is a somewhat ad-hoc aspect of the PCD format, so be careful. If you want to be safe, you're probably better off using neither -- just name each component of your field something like FIELD_00, FIELD_01, etc.

It's slow!

Try using binary or binary_compressed; using ASCII is slow and takes up a lot of space, not to mention possibly inaccurate if you're not careful with how you format your floats.

I found a bug / I added a feature / I made your code cleaner

Thanks! Please submit a pull request.

I want to congratulate you / insult you

Original Developers email is [e-mail].

Copyright (C) 2015 - 2018 Daniel Maturana

My email is [e-mail]. Copyright (C) 2023 Joel Oswald