daitomanabe

daitomanabe / gaze-effect

Public

macOS camera eye-contact effect concept and core

11
1
100% credibility
Found May 05, 2026 at 11 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Swift
AI Summary

A macOS tool that uses facial details to subtly adjust eye positions in videos, creating the illusion of direct eye contact.

How It Works

1
🎥 Record your video

You create a talking-head video, but your eyes wander off-camera, making it hard to connect with viewers.

2
🔍 Discover Gaze Effect

You learn about Gaze Effect, a helpful tool that makes eyes look straight at the camera for more engaging videos.

3
✨ Turn on eye contact mode

With one simple switch in your video app, the magic starts working to adjust your gaze naturally.

4
👁️ Eyes get analyzed

It quietly spots your face, eyes, and pupils to understand where you're looking.

5
➡️ Gaze shifts smoothly

Your pupils gently move toward the center, with soft blending so it feels real and not robotic.

6
😴 Blinks handled perfectly

When you blink, it pauses the adjustment to keep everything looking natural.

😍 Eye contact achieved!

Now your video draws viewers in with confident, direct eye contact every time.

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AI-Generated Review

What is gaze-effect?

Gaze-effect is a Swift library for macOS apps that applies a gaze correction effect to camera feeds, shifting detected pupil positions toward the eye center to simulate direct eye contact during video calls. It processes face landmarks from your macOS camera preview, handling real-time adjustments for better gaze cueing effect and gaze following effect, even amid blinks or low confidence detections. Developers drop it into custom macOS camera apps or effects pipelines via Swift Package Manager for instant eye-contact simulation without building from scratch.

Why is it gaining traction?

It stands out with configurable params for smoothing, shift limits, and blink thresholds, delivering smooth gaze effector centre corrections that feel natural in macOS camera reactions and gestures. Unlike generic Vision wrappers, it skips output on blinks or poor face confidence, avoiding jittery gaze cascade effects. The hook: quick integration for polished macOS camera background effects or test tools, with a built CLI checker for verifying gaze effect meaning in your setup.

Who should use this?

macOS developers building video apps, like custom Zoom clients or streaming tools, needing gaze effect limbus-style corrections. Suited for indie devs prototyping macOS camera settings tweaks or reaction gestures in preview windows. Avoid if you're not feeding it Vision landmarks already.

Verdict

At 11 stars and 1.0% credibility, it's an early concept with solid unit tests via CLI but thin docs—prototype-worthy for macOS camera effects hackers, but wait for more polish before production. Pair with a full face detection pipeline for real use.

(178 words)

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