In [1]: import pdal
...: import numpy as np
...: import matplotlib.pyplot as plt
In [13]: pipeline = {
...: "pipeline": [
...: {
...: "type": "readers.las",
...: "filename": "/Users/shilulu/Downloads/sample.laz"
...: },
...: {
...: "type": "writers.pcd",
...: "filename": "/Users/shilulu/Downloads/sample.pcd"
...: }
...: ]
...: }
In [14]: pipeline = pdal.Pipeline(json.dumps(pipeline))
...:
In [15]: pipeline.execute()
Out[15]: 150395
{
"pipeline":[
{
"type":"readers.las",
"filename":"input.las"
},
{
"type":"filters.reprojection",
"in_srs":"EPSG:4326",
"out_srs":"EPSG:3857"
},
{
"type":"writers.las",
"filename":"output.las"
}
]
}
{
"pipeline": [
{
"type": "readers.las",
"filename": "input.las"
},
{
"type": "filters.assign",
"assignment": "X=(X*5)"
},
{
"type": "writers.las",
"filename": "output.las"
}
]
}
import numpy as np
from pdal import pipeline
def multiply_x(arr: np.ndarray, factor: float) -> np.ndarray:
arr['X'] *= factor
return arr
json = """
{
"pipeline": [
{
"type": "readers.las",
"filename": "input.las"
},
{
"type": "filters.python",
"function": "multiply_x",
"module": "your_module",
"add_dimension": "X",
"pdalargs": {
"factor": 5
}
},
{
"type": "writers.las",
"filename": "output.las"
}
]
}
"""
pipeline = pdal.Pipeline(json)
pipeline.execute()
