DEDUPED Hot AI repos, turned into use cases Get the Monday 5

How to use Edit Drift: what you can do with it

What is Edit Drift? Edit Drift is a chained-edit benchmark and scorer that measures how much image models alter the untouched parts of a photo across 40 consecutive edits, with a CLI and a Claude Code plugin.

How do I use it? Install with pip install git+https://github.com/MegaTroll222/edit-drift; then List the edits with editdrift steps benchmarks/milk; generate each edit with your model, applying it to the previous result. Full steps below.

Trended earlier

View repo on GitHub

Third-party repos we don't own. AI-written use cases can be wrong. Disclaimer

3 use cases

Quick start with Edit Drift

  1. Check you have what it needs: Python with pip; Outputs from the image models you want to compare.
  2. Open MegaTroll222/edit-drift on GitHub and read the README and license.
  3. Install with pip install git+https://github.com/MegaTroll222/edit-drift
  4. List the edits with editdrift steps benchmarks/milk
  5. Generate each edit with your model, applying it to the previous result
  6. Score with editdrift score benchmarks/milk results/milk/my-model

These steps come from our top use case, Score how much an image model changes what it shouldn't, which also has a copy-paste agent prompt.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for MegaTroll222/edit-drift

Add Deduped to Claude Code once

claude mcp add --transport http deduped https://dedupedai.com/mcp

Cursor, ChatGPT, others

Edit Drift alternatives · Best AI repos for Data and analytics

About this repo

  • Who it is forML engineers and teams choosing an image editing model who care about fidelity in untouched regions.
  • Why it is hot14 stars, launched 19 days ago, picked up by one AI source we track
  • LanguagePython
  • Sourcegithub.com/MegaTroll222/edit-drift · Back to Hot repos

Requirements

  • Python with pip
  • Outputs from the image models you want to compare

Add this badge to your README

Maintain Edit Drift? Show readers where to find these use cases. Use cases on Deduped

Markdown

[![Use cases on Deduped](https://dedupedai.com/badge/MegaTroll222/edit-drift.svg)](https://dedupedai.com/use-cases/megatroll222-edit-drift/?utm_source=github&utm_medium=badge&utm_campaign=MegaTroll222-edit-drift)

HTML

<a href="https://dedupedai.com/use-cases/megatroll222-edit-drift/?utm_source=github&amp;utm_medium=badge&amp;utm_campaign=MegaTroll222-edit-drift"><img src="https://dedupedai.com/badge/MegaTroll222/edit-drift.svg" alt="Use cases on Deduped" height="20"></a>

A static image, no tracking script. About the badge

Questions about Edit Drift

What is Edit Drift?

Edit Drift is a chained-edit benchmark and scorer that measures how much image models alter the untouched parts of a photo across 40 consecutive edits, with a CLI and a Claude Code plugin. It is an open-source project on GitHub: https://github.com/MegaTroll222/edit-drift.

How do I use Edit Drift?

Install with pip install git+https://github.com/MegaTroll222/edit-drift; then List the edits with editdrift steps benchmarks/milk; generate each edit with your model, applying it to the previous result. The use cases on this page give the full steps and a copy-paste agent prompt for each job.

Who is Edit Drift for?

ML engineers and teams choosing an image editing model who care about fidelity in untouched regions.

What can I do with Edit Drift?

3 use cases so far, for example: Score how much an image model changes what it shouldn't; Compare image models with a leaderboard and video; Run the benchmark from Claude Code. Each has steps and a copy-paste agent prompt.

What do I need to run Edit Drift?

Python with pip; Outputs from the image models you want to compare.

What are alternatives to Edit Drift?

Other hot AI repos in Data and analytics: LangExtract, Crawl4AI, Firecrawl, OpenBB, DSH Usage.

Is Edit Drift safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.