Checkpoint-agnostic
Compatible with all checkpoints and training flavors. No lock-in—just clean data that slots into your pipeline.
Drop in your photos and get a clean, trainer-ready dataset: JoyCaption analysis on every image, popular-trainer filename patterns, and rich text descriptions tailored to your LoRA goals.
.txt
per image with a rich, goal-aligned descriptionPurpose-built for LoRA creators. Opinionated defaults, trainer-ready outputs.
Compatible with all checkpoints and training flavors. No lock-in—just clean data that slots into your pipeline.
Per-photo scanning extracts tags, entities, and attributes to guide captions and filename tokens precisely.
Auto-renames with patterns recognized by popular training apps (Kohya / AI Toolkit / Civitai Trainer and more).
Creates a .txt
next to each image with a detailed, goal-aligned description optimized for your LoRA concept.
Frequent improvements keep up with training best practices and new trainer conventions.
Outputs tidy, de-duplicated folders that are ready to caption, preview, or train immediately.
Each image is analyzed for subject, style, attributes, and context—forming the backbone of accurate captions and filename tokens.
Auto-naming uses patterns recognized by leading trainers so buckets, class tokens, and repeats are interpreted correctly.
.txt
descriptionsGenerates a companion text file per image that’s tailored to your LoRA goals—clean, descriptive, and trainer-friendly.
Yes. It’s checkpoint-agnostic and works across all popular LoRA training setups.
Each photo is scanned with JoyCaption to extract accurate tags and attributes, then written into a rich .txt
tailored to your LoRA goals.
The tool names files for all popular training applications, including Kohya, AI Toolkit, and Civitai Trainer—so buckets and repeats are read correctly.