A Python base cli tool for caption images with WD series, Joy-caption-pre-alpha,meta Llama 3.2 Vision Instruct and Qwen2 VL Instruct models.
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Updated
Oct 30, 2025 - Python
A Python base cli tool for caption images with WD series, Joy-caption-pre-alpha,meta Llama 3.2 Vision Instruct and Qwen2 VL Instruct models.
Published: 2026-10-18
Labeling extension for A1111/Forge/Forge-Neo/Classic - Gradio3/4
A training set management tool based on SQLite, designed for each individual image to correspond to multiple annotations for different types of models.
⚡ An all-in-one workflow for Anima LoRA training: from data labeling and cleaning to automated training. Fully containerized with Docker Compose for one-click deployment.
本地动漫图库管理器 NEXT 版:打标用 PixAI Tagger v1.0(词表 30,877),语义搜索用中文 CLIP,角色识别用 CCIP(外置模型);另有局域网/手机网页只读浏览。基于上游 ai-image-manager v2.2.3(MIT)修改。
WD14 booru tagging + Florence-2 natural-language captioning, one-click in the img2img toprow. For Stable Diffusion WebUI Forge (Classic Neo).
Searchable tag library, saved prompts, history and local AI (TIPO, Qwen-VL, WD14) for Stable Diffusion WebUI Forge.
本地动漫图库管理器(本地版 · 已冻结:除非严重 bug 不再更新)。WD14 打标 + 全中文标签树 + 以图搜图 + 回收站;中文 CLIP 语义搜索;角色识别(CCIP 外置模型)可选。全部本地运行、不上传图片。
本地动漫图库管理器 WD 版(原 LAN 版,2026-10-18 改名)。局域网访问/手机网页 + WD14 打标(模型在包内)+ 中文 CLIP 语义搜索 + 角色识别(CCIP 外置模型可选)。全部本地运行、不上传图片。
该项目基于gradio、wd1.4、chatglm杂交组合,变相实现图像分析的功能,仅为自己练习Gradio,没有额外价值。
Minimal UI to train LoRAs with kohya_ss — 6 GB card presets, SD 1.5 & SDXL/Pony, WD14/BLIP auto captions, time estimates, auto copy to Forge. (FR UI, EN summary)
kohya 风格训练集的数据集标注器:编辑 caption、tag 过滤、WD14 批量打标、生成 dataset.toml · Dataset tagger for kohya-style training sets: edit captions, filter tags, batch WD14 tagging, dataset.toml · kohya 形式の学習セット向けデータセットタガー:キャプション編集、タグ絞り込み、WD14 一括タグ付け、dataset.toml 生成
Personal pipeline for archiving saved artwork: metadata + AI character tagging (anime-focused via WD14), human-in-the-loop review, files into your own sorted archive layout. Ingests from Reddit saves; built source-agnostic.
本地图像理解:让没有视觉能力的语言模型也能「看见」图片 — 零第三方依赖,自带基线 JPEG 解码与提示词反推,可脱离 Styx 独立使用
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