DeblurProxy: Real-Time Video Enhancement for the Footage That Matters
Most of the time, your camera is recording — but not really seeing.
That’s the reality behind countless blurry, motion-streaked videos from surveillance cameras, doorbells, drones, and inspection systems. When the moment matters most, the footage breaks down.
DeblurProxy is a real-time video enhancement engine designed to change that.
It doesn’t guess, analyze, or interpret. It doesn’t send anything to the cloud.
It simply applies a trained neural network to restore clarity to each frame as the footage is captured.
No delay. No post-processing. Just better video, instantly — inline.
What DeblurProxy Actually Does
DeblurProxy is a real-time processing layer that sits between a camera and its display or recorder. It takes input from a live video stream — RTSP, USB webcam, or HDMI — and runs each frame through a trained deep learning model that reverses motion blur and low-light streaks.
The system runs entirely offline and is optimized for edge devices like the Raspberry Pi. You don’t need new cameras. You don’t need a GPU. You just plug in the pipeline and get better visuals.
Why It Matters
Most deblurring and video cleanup happens after the fact — often too late to be useful. DeblurProxy processes footage during capture, giving operators, analysts, or even downstream AI systems a clearer view in real time.
It’s not a “smart camera.” It’s a clarity upgrade that works with the gear you already have.
Where It Can Be Used
DeblurProxy is modular and flexible — it’s not hardcoded for security cameras.
Any system with real-time video can benefit.
Common use cases include:
Surveillance systems: Retail, warehouses, lobbies, outdoor cams
Smart doorbells: Better footage of fast-moving people or vehicles
Robotics and drones: Enhanced video from unstable platforms
Industrial inspection: In-line cleanup of blurry machine vision streams
Medical/lab equipment: Sharper output from handheld or microscope video
For law enforcement:
DeblurProxy is not embedded into bodycams (which are closed devices),
but it can enhance footage from bodycams in two ways:
Docking Station Processing
When bodycam footage is uploaded, a local DeblurProxy system can generate an enhanced version for analysis or review — without altering the original.Live Viewing Add-on
If the camera supports HDMI or RTSP output, DeblurProxy can sit between the feed and the monitor, improving visibility for supervisors or dispatch.
This preserves chain-of-custody while offering better visibility where it matters most.
What It’s Built With
DeblurProxy is built for simplicity, speed, and portability.
ONNX-based deep learning model trained for motion deblurring
C++ inference engine using ONNX Runtime and OpenCV
Real-time frame processing with minimal latency
Stream input support (RTSP, webcam, HDMI capture)
Local-only operation — no cloud, no internet dependency
Deployable on edge devices, including Raspberry Pi
Dockerized build environment for easy portability
Optional frame overlays, toggles, and video output modes
It’s lightweight. It’s fast. It runs where you need it to — not just where it’s easy.
Why We Built It
Because security footage shouldn’t fail when it’s needed most.
Because drones and robots deserve vision that holds up in motion.
Because enhancement shouldn’t wait until playback.
DeblurProxy doesn’t interpret, detect, or decide. It restores. It’s a visual signal booster — nothing more, but also, nothing less.
Open Source & In Progress
DeblurProxy is under active development and open to contributors.
Everything is being built transparently, with production use in mind.
You can track progress, explore the code, or contribute here:
github.com/DurgaDeepakValluri/DeBlurProxy
If you work with real-time video and blur is your bottleneck, DeblurProxy gives your system a second chance to see clearly.
It doesn’t replace your camera. It makes it more useful.
Clarity isn’t a luxury. It should be built-in.
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