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A Python package for delineating nested surface depressions from digital elevation data.
The main features of giswqs/lidar are: Terrain and 3D Reconstruction, Point Cloud Processing, Terrain and Elevation, Python Geospatial Libraries.
Projects with overlapping indexed features include: mrharicot/monodepth — Tensorflow implementation of unsupervised single image depth prediction using a convolutional neural network. jzbontar/mc-cnn — Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches. miss3d/s2p — Warning: this repository is not maintained, please use https://github.com/centreborelli/s2p instead. cmla/s2p — S2P is a Python library and command line tool that implements a stereo pipeline which produces elevation models from… intelrealsense/librealsense. cgal/cgal — CGAL is a software library that provides a comprehensive collection of computational geometry algorithms and data…
Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches
S2P is a Python library and command line tool that implements a stereo pipeline which produces elevation models from images taken by high resolution optical satellites such as Pléiades, WorldView, QuickBird, Spot or Ikonos. It generates 3D point clouds and digital surface models from stereo…
Warning: this repository is not maintained, please use https://github.com/centreborelli/s2p instead.