ntw-au

ntw-au's Stars

• pybind/pybind11

  Seamless operability between C++11 and Python

  Language:C++15.2k2.1k

• mamba-org/mamba

  The Fast Cross-Platform Package Manager

  Language:C++6.6k345

• truebelief/artemis_treeiso

  TLS tree isolation/segmentation code

  Language:C++298

• jianboqi/CSF

  LiDAR point cloud ground filtering / segmentation (bare earth extraction) method based on cloth simulation

  Language:C++468131

• opengeos/segment-geospatial

  A Python package for segmenting geospatial data with the Segment Anything Model (SAM)

  Language:Python2.8k274

• Yarroudh/segment-lidar

  Python package for segmenting LiDAR data using Segment-Anything Model (SAM) from Meta AI.

  Language:Python31435

• tommyod/KDEpy

  Kernel Density Estimation in Python

  Language:Jupyter Notebook56588

• microsoft/torchgeo

  TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data

  Language:Python2.4k300

• csiro-robotics/raycloudtools

  Language:C++5916

• lutraconsulting/MDAL

  Mesh Data Abstraction Library

  Language:Roff15648

• microsoft/onnxruntime

  ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

  Language:C++13.6k2.8k

• TNO/lightkde

  Lightning fast, lightweight, and reliable kernel density estimation for 1d and 2d samples

  Language:Python4

• Esri/lerc

  Limited Error Raster Compression

  Language:C++19157

• hsutter/cppfront

  A personal experimental C++ Syntax 2 -> Syntax 1 compiler

  Language:C++5.3k225

• Jaybro/pico_tree

  A C++ header only library for fast nearest neighbor and range searches using a KdTree. It supports interfacing with Eigen, OpenCV, and custom data types and provides optional Python bindings.

  Language:C++368

• carbon-language/carbon-lang

  Carbon Language's main repository: documents, design, implementation, and related tools. (NOTE: Carbon Language is experimental; see README)

  Language:C++32.3k1.5k

• googlefonts/atkinson-hyperlegible

  Language:HTML2097

• aws/deep-learning-containers

  AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.

  Language:Python963445

• NUAAXQ/awesome-point-cloud-analysis-2023

  A list of papers and datasets about point cloud analysis (processing) since 2017. Update every day!

  1.5k191

• PDAL/PDAL

  PDAL is Point Data Abstraction Library. GDAL for point cloud data.

  Language:C++1.1k438

• ASPRSorg/LAS

  LAS Specification

  Language:Python14016

• koordinates/kart

  Distributed version-control for geospatial and tabular data

  Language:Python51539

• isl-org/Open3D

  Open3D: A Modern Library for 3D Data Processing

  Language:C++10.9k2.2k

• azavea/raster-vision

  An open source library and framework for deep learning on satellite and aerial imagery.

  Language:Python2k380

• google/or-tools

  Google's Operations Research tools:

  Language:C++10.8k2.1k

• rapidsai/cuml

  cuML - RAPIDS Machine Learning Library

  Language:C++4.1k525

• sacridini/Awesome-Geospatial

  Long list of geospatial tools and resources

  4k612

• opengeos/python-geospatial

  A collection of Python packages for geospatial analysis with binder-ready notebook examples

  Language:Shell691120

• davideberly/GeometricTools

  A collection of source code for computing in the fields of mathematics, geometry, graphics, image analysis and physics.

  Language:C++1.1k202

• kthohr/gcem

  A C++ compile-time math library using generalized constant expressions

  Language:C++65761