File Handlers

This page demonstrates loading and saving point clouds using the CSV-like and PLY handlers from pchandler.data_io.

CSV-like formats (CsvHandler)

Although this file handler is named CSV, it is more of a generic text delimited file format handler.

Supported extensions:

• .txt

• .csv

• .xyz

• .asc

• .ascii

• .pts

Load

import numpy as np
from pchandler.core import PointCloudData
from pchandler.data_io.csv import CsvHandler

# Example: load a CSV with header/comment lines and auto-delimited columns.
# The handler will sniff the file structure and locate XYZ plus any extra fields.
pcd = CsvHandler.load(
    "points.csv",
    scalar_fields=None, # Allows the selection of scalar fields or is needed when file has no header
    remove_prefix=True,  # In some cases, like cloud compare, a prefix is added to all scalar fields
    prefix="scalar_",
    column_names_row=-1, # refers to the row index in the header/comments which contains the column names
    comment="//",
    delimiter=None,  # Setting delimiter to None, the handler will attempt to "sniff" the file and determine it
    numerical_optimization_shift=None, # Other parameters for the PointCloudData keyword arguments can be passed
)

xyz = pcd.xyz
intensity = pcd.intensity

Save

from pchandler.data_io.csv import CsvHandler

# Save with a specific delimiter and prefixed scalar field names
CsvHandler.save(
    pcd,
    "points_out.csv",
    scalar_fields=None,  # Select which scalar fields to save (defaults to all fields)
    add_prefix=True,
    prefix="scalar_",
    revert_sf_types=False,   # Keep original dtypes for scalar fields where possible
    delimiter=",",
)

PLY format (PlyHandler)

Supported extension: .ply

Load

from pchandler.data_io.ply import PlyHandler

pcd = PlyHandler.load(
    "points.ply",
    scalar_fields=None,
    remove_prefix=True,
    prefix="scalar_",
    numerical_optimization_shift=None,
)

Save

from pchandler.data_io.ply import PlyHandler

PlyHandler.save(
    pcd,
    "points_out.ply",
    scalar_fields=None,
    add_prefix=False,
    prefix="scalar_",
    revert_sf_types=False,
    as_ascii=False,  # Write ASCII PLY (False -> binary, which is smaller/faster)
)

Roundtrip examples

CSV roundtrip

import numpy as np
from pchandler.core import PointCloudData
from pchandler.data_io.csv import CsvHandler

# Create a simple cloud with one scalar field
N = 5
pcd = PointCloudData(
    xyz=np.random.rand(N, 3),
    scalar_fields={"intensity": np.linspace(0, 1, N)},
    numerical_optimization_shift=None,
)

CsvHandler.save(pcd, "example.csv", add_prefix=True, prefix="scalar_")
pcd2 = CsvHandler.load("example.csv", remove_prefix=True, prefix="scalar_")

# Scalar fields and coordinates are preserved
assert len(pcd2) == N

PLY roundtrip

import numpy as np
from pchandler.core import PointCloudData
from pchandler.data_io.ply import PlyHandler

N = 5
pcd = PointCloudData(
    xyz=np.random.rand(N, 3),
    scalar_fields={"quality": np.random.rand(N)},
    numerical_optimization_shift=None,
)

PlyHandler.save(pcd, "example.ply", add_prefix=False)
pcd2 = PlyHandler.load("example.ply", remove_prefix=False)

assert len(pcd2) == N