Tools tagged with "Machine Learning"

COLMAP is a sophisticated open-source photogrammetry software solution designed for 3D reconstruction from collections of images. It implements a robust and modular Structure-from-Motion (SfM) and Multi-View Stereo (MVS) pipeline. This tool is widely used for generating dense point clouds and 3D models from unordered image sets, making it valuable for various computer vision and geospatial applications.

jakteristics is an open-source Python library designed for extracting geometric features from point cloud data. It provides tools for analyzing the local neighborhood of points and deriving various descriptive attributes, which are crucial for tasks like classification and segmentation of 3D data.

This GitHub repository provides a comprehensive collection of resources focused on the intersection of mineral exploration and machine learning. It features useful code examples, libraries, and tools to assist practitioners and researchers in applying advanced analytical methods to geological data. The repository serves as a valuable hub for discovering practical applications and learning materials in this specialized field.

This repository offers a global dataset of building density and height, generated quarterly by applying machine learning models to PlanetScope basemaps. It provides a global public layer and detailed data for five high-growth locations, distributed as Cloud-Optimized GeoTIFFs (COGs). The resource supports both data exploration and model training for users interested in urban development analysis.

The TACO dataset addresses the critical need for annotated images to train deep learning models for trash detection. It aims to advance AI applications in environmental monitoring, such as drone-based trash surveying and robotic litter collection, by providing a comprehensive and continually updated collection of segmented trash images.

Orfeo ToolBox (OTB) is a powerful C++ library designed for processing satellite images and other high-resolution geospatial data. It offers a wide array of image processing algorithms, including classification, segmentation, filtering, and geometric corrections, making it a robust solution for remote sensing applications.

SegmentAnyTree is an open-source GitHub repository dedicated to tree segmentation. It provides code and resources for identifying and delineating individual trees, likely utilizing advanced machine learning techniques on various types of geospatial imagery. This project supports detailed forest analysis and environmental monitoring efforts.

The CNG Blog is the official blog of the Cloud-Native Geospatial Forum, a community dedicated to advancing cloud-native geospatial practices. It features articles on new technologies, community sprints, technical developments, and expert insights.

This GitHub repository serves as an "awesome list" for photogrammetry, collecting a wide range of projects, libraries, and tools related to the field. It provides a community-driven compilation for developers, researchers, and enthusiasts looking for relevant resources. The list aims to categorize and highlight significant contributions in photogrammetry.