pratikrath126

pratikrath126 / ai-image-detector

Public

Advanced Hybrid Intelligence for detecting AI-generated images. Combines commercial-grade APIs, cutting-edge open-source models, and privacy-first local analysis.

aiimagedetector-ten.vercel.app
17
2
100% credibility
Found Feb 21, 2026 at 16 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A web app that analyzes uploaded images using multiple AI detection engines to determine if they are AI-generated or authentic.

How It Works

1
🔍 Discover the detector

You hear about a cool tool that instantly tells if pictures are made by AI or real people.

2
🌐 Visit the site

Open the eye-catching cyberpunk-style website with neon glows and smooth animations.

3
📁 Pick your image

Grab any photo from your computer – a meme, artwork, or snapshot you're wondering about.

4
🚀 Drop and analyze

Drag the image into the glowing upload zone and tap 'Analyze' to unleash the multi-engine magic.

5
⚡ Watch it work

In seconds, three smart checkers team up: one scans patterns, one reads clues, one checks details.

✅ Get your verdict

Celebrate clear results with confidence scores, breakdowns, and proof – now you know if it's real!

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Star Growth

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AI-Generated Review

What is ai-image-detector?

This Next.js web app lets you drag-and-drop any image to detect if it's AI-generated from tools like DALL-E, Midjourney, or Stable Diffusion. It runs three detection engines in parallel—a commercial API, a Hugging Face Vision Transformer model, and local metadata/entropy analysis—then aggregates results into a confidence-scored verdict with per-engine breakdowns. Privacy-focused: images process in-browser or via APIs without storage, and it deploys instantly to Vercel.

Why is it gaining traction?

The weighted ensemble voting crushes single-model detectors by slashing false positives through cross-validation, delivering reliable results under 5 seconds. Its cyberpunk neon UI with glassmorphism and smooth animations feels premium, while free Sightengine keys and optional Hugging Face token make it dead simple to spin up. Developers dig the advanced hybrid approach for ai generated image detection github projects, blending APIs, open models, and heuristics without heavy setup.

Who should use this?

Journalists fact-checking social media images, content moderators scanning uploads, or indie devs prototyping AI verification tools. Perfect for frontend teams needing quick detection in apps, or security researchers testing advanced github security against deepfakes.

Verdict

Grab it for a polished starting point on advanced hybrid ai image detection—demo works out of the box. But with just 17 stars and 1.0% credibility score, it's an early prototype lacking tests and broad validation; fork and harden it before production. (198 words)

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