Python wrapper of LibE57Format to read and write .e57 point cloud files
import numpy as np
import pye57
e57 = pye57.E57("e57_file.e57")
# read scan at index 0
data = e57.read_scan(0)
# 'data' is a dictionary with the point types as keys
assert isinstance(data["cartesianX"], np.ndarray)
assert isinstance(data["cartesianY"], np.ndarray)
assert isinstance(data["cartesianZ"], np.ndarray)
# other attributes can be read using:
data = e57.read_scan(0, intensity=True, colors=True, row_column=True)
assert isinstance(data["cartesianX"], np.ndarray)
assert isinstance(data["cartesianY"], np.ndarray)
assert isinstance(data["cartesianZ"], np.ndarray)
assert isinstance(data["intensity"], np.ndarray)
assert isinstance(data["colorRed"], np.ndarray)
assert isinstance(data["colorGreen"], np.ndarray)
assert isinstance(data["colorBlue"], np.ndarray)
assert isinstance(data["rowIndex"], np.ndarray)
assert isinstance(data["columnIndex"], np.ndarray)
# the 'read_scan' method filters points using the 'cartesianInvalidState' field
# if you want to get everything as raw, untransformed data, use:
data_raw = e57.read_scan_raw(0)
# writing is also possible, but only using raw data for now
e57_write = pye57.E57("e57_file_write.e57", mode='w')
e57_write.write_scan_raw(data_raw)
# you can specify a header to copy information from
e57_write.write_scan_raw(data_raw, scan_header=e57.get_header(0))
# the ScanHeader object wraps most of the scan information:
header = e57.get_header(0)
print(header.point_count)
print(header.rotation_matrix)
print(header.translation)
# all the header information can be printed using:
for line in header.pretty_print():
print(line)
# the scan position can be accessed with:
position_scan_0 = e57.scan_position(0)
# the binding is very close to the E57Foundation API
# you can modify the nodes easily from python
imf = e57.image_file
root = imf.root()
data3d = root["data3D"]
scan_0 = data3d[0]
translation_x = scan_0["pose"]["translation"]["x"]pip install pye57
If you're on Windows and using python 3.5 or 3.6, wheels are available.
Otherwise, see the building notes below.
Binaries of xerces-c can be obtained from conda using: conda install xerces-c
Install libxerces-c-dev before installing.