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SPECIFICTION
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DroneDeploy Aerial vs OpenMVG

DroneDeploy Aerial

dronedeploy.com

OpenMVG

github.com

Side by side

FigureDroneDeploy AerialOpenMVG
Price from$159/moFree
Free plan—Yes
Free trialYes—
Open source—Yes
WebYes—
Windows—Yes
macOS—Yes
Linux—Yes
iOSYesYes
AndroidYesYes
APIYesYes
Self-hosted—Yes
Plans published41
Spec score · Photogrammetry Software8.3 (#11)8.6 (#4)
PurposeDroneDeploy Aerial lets teams fly drones, capture site data and turn it into automated insights.OpenMVG is a multiple view geometry library for 3D computer vision and structure from motion.
SupportThe Flight & Analysis plan includes email and live chat support; Ag Lite lists email-based support.The repository lists a project contact email and directs users to its wiki for tutorials and usage resources.

Plans

DroneDeploy Aerial

  • Ag Lite Plan$1,908 a year
  • Flight & Analysis Plan$4,188 a year
  • Advanced Flight & Analysis PlanPriced on request
  • DroneDeploy AerialPriced on request

DroneDeploy Aerial pricing →

OpenMVG

  • OpenMVGFree

OpenMVG pricing →

In their own words

DroneDeploy Aerial

DroneDeploy Aerial has no write-up on Specifiction yet; its figures are above.

Visit dronedeploy.com

OpenMVG

OpenMVG is an open-source C++ library for multiple-view geometry, 3D computer vision, and structure from motion. It provides libraries, binaries, and pipelines for reconstructing 3D scenes from images. Library areas include image manipulation, feature description and matching, feature tracking, camera models, multiple-view geometry, robust estimation, and structure-from-motion algorithms. Its binaries can initialize scenes, detect and match features, perform reconstruction, and export scenes to other multiple-view-stereo frameworks. Those frameworks can compute dense point clouds or textured meshes from exported scenes. OpenMVG is released under the Mozilla Public License 2.0 and is listed as free. The project says it aims to support reproducible research through readable implementations of classic and state-of-the-art algorithms. It is designed for reading, learning, modification, and use, with test-driven development and samples. Tutorials cover data structures, library use, and processing an image dataset. Platforms listed are Windows, macOS, Linux, iOS, Android, and self-hosted, with desktop deployment, API access, point-cloud export, and ground control point support.

Visit github.com