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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…
A Python package for delineating nested surface depressions from digital elevation data.
Warning: this repository is not maintained, please use https://github.com/centreborelli/s2p instead.
The main features of intelrealsense/librealsense are: Terrain and 3D Reconstruction, Terrain and Elevation.
Open-source alternatives to intelrealsense/librealsense include: cmla/s2p — S2P is a Python library and command line tool that implements a stereo pipeline which produces elevation models from… giswqs/lidar — A Python package for delineating nested surface depressions from digital elevation data. 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. mrharicot/monodepth — Tensorflow implementation of unsupervised single image depth prediction using a convolutional neural network. opendronemap/opendronemap — A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images. 📷.