This repo detect objects automatically for LiDAR data
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Updated
May 7, 2019 - Python
This repo detect objects automatically for LiDAR data
Plugin to generate a three light exposure hillshade (shaded relief by combining three light exposures)
An improved AHN3 gridded DTM/DSM done as university project for the MSc Geomatics @ TU Delft
Python CLI tool which helps you to download AHN point cloud data easily
`ptcfextract` computes **per-point local geometry features** from point clouds stored in **LAS/LAZ**, useful for feature extraction research pipelines:
Quality-assurance CLI for LAS/LAZ LiDAR point clouds: CRS, classification, density, header and return integrity.
Code-first Python guides for LiDAR & point cloud processing — PDAL pipelines, ground filtering, DTM/DSM generation, and batch/cloud automation.
Aerial LiDAR quality assessment over IIT Kanpur campus - 6.45M points, 8 USGS/ASPRS parameters, Python
Binary LiDAR ground classification pipeline (ground vs non-ground) with SMRF/CSF reclassification, HAG feature extraction, and ML train/evaluate/predict workflows.
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