aerial-imagery

A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images. 📷

Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds

yolov5 + csl_label.(Oriented Object Detection)（Rotation Detection）（Rotated BBox）基于yolov5的旋转目标检测

Affordable Digital HD Video Transmission made easy!

DroneBridge is a system based on the WifiBroadcast approach. A bidirectional digital radio link between two endpoints is established using standard WiFi hardware and a custom protocol. DroneBridge is optimized for use in UAV applications and is a complete system. It is intended be a real alternative to other similar systems, such as DJI Lightbridge or OcuSync.

This repo is the codebase for our team to participate in DOTA related competitions, including rotation and horizontal detection.

TeleSculptor: Aerial Photogrammetry Application powered by KWIVER

C++/Python-based 3D geospatial application for simulating and visualizing dynamic objects in planetary environments

Official code of the paper "ReDet: A Rotation-Equivariant Detector for Aerial Object Detection" (CVPR 2021)

[ICRA'24 Best UAV Paper Award Finalist] An Efficient Global Planner for Aerial Coverage

Detect objects in drone videos and plot them on a map

Tools for detecting wildlife in aerial images using active learning

A simple yet highly configurable Mastodon bot that posts geotagged aerial imagery of a random location in the world.

Trans DOTA OBB format(poly format) to YOLO format.

[ICRA'23] A Prediction-boosted Planner for Fast and High-quality Autonomous Aerial Reconstruction

[CVPR'W19-Oral] Official repository for "iSAID: A Large-scale Dataset for Instance Segmentation in Aerial Images"

Google Maps keeps old satellite imagery around for a while – this tool collects what's available for a user-specified region in the form of a GIF.

A collection of some awesome public object detection and recognition datasets.

This project focuses on development of an algorithm for Template Matching on aerial images by implementing classical Computer Vision based techniques and deep-learning based techniques.