svyas23/GAMa

GAMa: Cross-view Video Geo-localization

26
/ 100
Experimental

This project helps pinpoint the exact geographical location of a video captured from the ground by matching it against a large aerial map. You input a ground-level video and a corresponding aerial image of the general area, and it outputs the video's precise trajectory overlaid on the aerial map. This is useful for urban planners, security analysts, or drone operators needing to track movement in large areas.

No commits in the last 6 months.

Use this if you need to accurately map a ground-level video's path onto an aerial or satellite image, especially for security, surveillance, or urban monitoring applications.

Not ideal if you only have ground-level video without any corresponding aerial imagery of the same region, or if you need to identify specific objects within the video rather than its geographical path.

geospatial-intelligence video-surveillance urban-mapping aerial-reconnaissance location-tracking
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 8 / 25
Community 10 / 25

How are scores calculated?

Stars

44

Forks

4

Language

Python

License

Last pushed

Nov 11, 2022

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/svyas23/GAMa"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.