---
license: other
license_name: mixed-source-see-below
task_categories:
  - text-to-image
  - image-to-image
tags:
  - controlnet
  - pose-estimation
  - diffusion
  - openpose
pretty_name: Pose-ControlNet Training Data (COCO + Danbooru)
---

# Pose-ControlNet Training Data (COCO + Danbooru subset)

Paired (image, 18-point OpenPose-style pose skeleton, caption) triples for training a
pose-conditioned ControlNet, built as channel-concatenated conditioning alongside the
noisy latent (same mechanism as depth-conditioned ControlNets).

This is the **public subset** of a larger dataset — it excludes a Human-Art-derived
portion (real_human / sculpture / painting) that is kept local-only per that dataset's
non-commercial, no-redistribution license.

## Contents

| Column | Description |
|---|---|
| `file_name` | The source RGB image (photograph or anime illustration) |
| `conditioning_image` | The paired pose skeleton map — same resolution/alignment as `file_name`, 18-point body-only OpenPose-style rendering, no hands or face |
| `text` | A caption describing appearance, clothing, setting, color, lighting, and camera technique. Captions **deliberately exclude all body-position/pose language** — pose information is carried entirely by `conditioning_image`, not the text |

## Sources and licensing

- **COCO-WholeBody** (photoreal subset): images from the COCO dataset (Flickr-sourced, subject to COCO's own terms), pose annotations sourced from COCO-WholeBody, whose annotations are licensed for **research and non-commercial use only** (SenseTime Research) — separate from the images' own licensing.
- **Danbooru** (anime subset): community-sourced illustrations pulled via the public Danbooru API. Rating-filtered to `general`+`sensitive` only (`questionable`/`explicit` excluded). An additional tag-based filter was applied to exclude any content coded as depicting minors, independent of the official content rating.

Given the mixed and partially non-commercial licensing of the source annotations, **this dataset is provided for research purposes**; check the original source licenses before any commercial use.

## Pose skeleton schema

18-point body-only OpenPose-style skeleton (COCO-17/MPII-16 remapped to a unified schema
where applicable; DWPose used for Danbooru). Hands and face are deliberately excluded —
hand-keypoint detection proved unreliable on stylized art, and standardizing to body-only
kept the schema consistent across all sources.

## Captioning methodology

Captions were generated via Gemini 3.5 Flash-Lite (Google), following a fixed prompt
enforcing:
- Medium-first opening (e.g. "A photograph of...", "An anime illustration depicts...")
- Verbatim transcription of any legible text/signage in the image
- Zero pose, posture, gesture, or body-position language of any kind
- No camera framing that implies body-crop extent (e.g. "close-up", "waist up")
- 1-3 trailing style/technique tags
- 60-124 word range

Manually reviewed at multiple sample checkpoints throughout generation; a small residual
rate of incidental pose-adjacent language (~1-1.5%) may remain despite the filter, tracked
via automated post-hoc checks.

## Content notes

- Danbooru content was rating-filtered and additionally tag-filtered for apparent-minor
  content before inclusion; any content flagged by the generation model as prohibited was
  excluded from the dataset rather than force-captioned.
- This is training data for a pose-conditioning model, not a curated art collection —
  quality and content vary by source.