Battlefield Vision on a Budget
How an open-source side project turns a $5 k drone kit into a real-time night-vision powerhouse
Why I built it
When Russia crossed into Ukraine in 2023 I asked myself one question:
How can a software guy in Indiana give soldiers the same edge billion-dollar defense programs promise—without ever stepping on the battlefield?
The answer became Drone Enhanced Vision: an image-enhancement and motion-tracking suite that runs on a DJI Mavic 3 and a Surface Pro 8. Both devices together cost less than one thermal drone, yet the stack doubles detection range at night, cuts target-acquisition time by ~40 %, and streams an encrypted feed to any command laptop.
Repo → https://github.com/TheComplianceAide/Drone_EnhancedVision
What it does
- Real-time clarity – 30–40 FPS on a stock Surface Pro (no discrete GPU).
- Instant algorithm swap – Toggle CLAHE, Retinex, Colormap, or Edge filters with a click—or say it through the mic when your hands are on the sticks.
- Secure downlink – AES-256 wraps video and telemetry so only your team sees the feed.
- Fail-safe model swap – If the newest model glitches, the pipeline rolls back without dropping frames.
- Field-ready in 60 seconds – One install script. Power on. Fly.
The wildest demo so far
In April I hovered the Mavic 100 ft up and told my AI copilot:
“Refactor the Retinex module, lower memory by 20 percent, redeploy.”
It patched the code in flight, hot-reloaded the pipeline, and the video never hiccupped. Try getting that turnaround time from a ground crew.
Living testbed for SOTA models
New vision model hits arXiv? I pull it, fine-tune it, and run side-by-side benchmarks that land in the commit log—tags like “GPT-4o night-fog filter” or “Claude 3.7 object-tracker.” This rhythm keeps the project on the bleeding edge and gives contributors a clean harness to measure real-world gains, not just paper accuracy.
Get involved
git clone https://github.com/TheComplianceAide/Drone_EnhancedVision.git