Swiss Territorial Data Lab
- 38 followers
- Switzerland
- https://stdl.ch/
Popular repositories
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object-detector
object-detector PublicA suite of Python scripts allowing the end-user to use Deep Learning to detect objects in georeferenced raster images.
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proj-qalidar
proj-qalidar PublicChange detection between two LiDAR point clouds using voxelization. Highlight discrepancies in geometry and classification.
Python 3
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swiss-territorial-data-lab.github.io
swiss-territorial-data-lab.github.io PublicSwiss Territorial Data Lab Public Technical Website
HTML 2
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csv-wkt-to-uv3
csv-wkt-to-uv3 PublicTool for shapefile geometries conversion to UV3 format
MATLAB 1
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auto-rasterize
auto-rasterize PublicForked from hurielreichel/auto-rasterize
This tool allows one to rasterize a shapefile, automatically turning it into a binary GeoTiff file
Python 1
Repositories
- object-detector Public
A suite of Python scripts allowing the end-user to use Deep Learning to detect objects in georeferenced raster images.
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- proj-rooftops Public
Three workflows based on aerial imagery or LiDAR point clouds to evaluate the surface available on rooftops by detecting objects.
- proj-roadsurf Public
The goal of this project is to classify the roads of Switzerland based on the type of their surface, artificial or natural.
- proj-qalidar Public
Change detection between two LiDAR point clouds using voxelization. Highlight discrepancies in geometry and classification.
- mmsegmentation Public Forked from open-mmlab/mmsegmentation
OpenMMLab Semantic Segmentation Toolbox and Benchmark. Modified version that can support 5-channel images.
- scale-mae Public Forked from bair-climate-initiative/scale-mae
Modified ScaleMAE for 5 channel RGB-NIR-nDSM dataset
- segment-geospatial Public Forked from opengeos/segment-geospatial
A Python package for segmenting geospatial data with the Segment Anything Model (SAM)
- proj-hetres Public
This project provides a suite of Python, R and Octave/Matlab scripts allowing the end-user to use machine learning to assess the health state of trees based on orthophotos and a LiDAR point cloud.
