←新闻详情

蚂蚁 inclusionAI:GitHub 新仓库更新于 10月14日 12:13

蚂蚁 inclusionAI 开源 ConceptEdit-12M 与 ConceptEdit-Bench

GitHub - inclusionAI/ConceptEdit: ConceptEdit-12M and ConceptEdit-Bench · GitHub

AI 导读

蚂蚁 inclusionAI 在 GitHub 发布 ConceptEdit-12M 与 ConceptEdit-Bench,用于大规模、基于分类体系的图像编辑数据集生成。该仓库提供三阶段流水线,并附带 ConceptBench 基准评测代码,涵盖推理、VLM 评判、指标聚合与可视化。项目采用 MIT 许可证,各步骤幂等且支持断点续跑。

正文

当前显示原文,中文全文译文尚未就绪。

inclusionAI; ConceptEdit

Repository navigation

NotificationsYou must be signed in to change notification settings; Fork0 (0); Star39 (39)You must be signed in to star a repository

ConceptEdit-12M and ConceptEdit-Bench

Repository files navigation

README; MIT license

Image-Editing Concept Pipeline

A 3-stage pipeline for generating large-scale, taxonomy-grounded image-editing datasets:

Two variants are shipped side-by-side:

Repo layout

Setup

config.py is gitignored — never commit it.

You will need:

an OpenAI-compatible VLM endpoint (e.g. vLLM or SGLang serving a vision-language model) for instruction generation and evaluation; a local FLUX checkpoint loadable by 🤗 diffusers; (optional) object-storage credentials if your source images live in object storage; local file input is fully supported as well

Running the pipeline

All commands are run from the repo root (so that config.py is on the Python path).

Single-concept

Output of each step lives next to its input:

Multi-concept

Identical commands with the multi_ prefix:

multi_instruct_gen.py can also consume a JSONL of object-storage image paths via --jsonl (one JSON object per line, with an images field). Use --help for the full list of flags.

Benchmark evaluation

The benchmark/ directory provides code for evaluating image-editing models on ConceptBench, including inference, VLM-judge evaluation, metric aggregation, and interactive visualization of evaluation reports. Please refer to benchmark/README.md for benchmark data placement, inference and evaluation commands, metric definitions, and report visualization.

Every step is idempotent and resume-safe:

instruct_gen skips images for which a JSON with the right prefix already exists; flux_edit skips JSONs whose _edit.png already exists; eval_metric skips JSONs whose _vqa_result.json already exists

Killing the process and re-running picks up exactly where it left off.

License

Released under the MIT License. See LICENSE.

ConceptEdit-12M and ConceptEdit-Bench

来源

蚂蚁 inclusionAI:GitHub 新仓库