# bangumi-frames

Extracts anime video frames from Bilibili or local files, separates scenery, and clusters characters using anime person detection and CCIP embeddings.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 2300 installs · ★ 92
- Author: Agents365-ai
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/Agents365-ai/365-skills/tree/HEAD/plugins/bangumi-frames/skills/bangumi-frames/SKILL.md
- Updated: 2026-10-16
- HTML: https://affpapa.org/en/nevibecode/skills/bangumi-frames

## What it does

The skill processes Bilibili links via `yt-dlp` or reads a local video file. It cuts scene changes via `ffmpeg`, filters out background scenery, and detects characters using `dghs-imgutils`. It handles anime and 2.5D graphics exclusively; live-action footage will fail because it requires regular face recognition models.

Execution works in two modes: grouping every character into separate numbered folders, or extracting appearances of a single character using a reference directory passed via `--ref`. An optional `--clean` flag removes hardcoded subtitles and watermarks with LaMa inpainting. Structured results appear in JSON alongside visual montages.

Prerequisites include Python 3.9+, `ffmpeg`, and `yt-dlp`. Keep the CCIP matching step on CPU, because setting `ONNX_MODE=CoreML` triggers a fatal crash during clustering. If you download 1080p or premium episodes from Bilibili, supply an exported Netscape cookies file.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add Agents365-ai/365-skills --skill bangumi-frames -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/bangumi-frames/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/bangumi-frames/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add Agents365-ai/365-skills --skill bangumi-frames -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/bangumi-frames/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add Agents365-ai/365-skills --skill bangumi-frames -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/bangumi-frames/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install Agents365-ai/365-skills bangumi-frames
```

2. **Manually: put the files in place**
- File: `.github/skills/bangumi-frames/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add Agents365-ai/365-skills --skill bangumi-frames -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/Agents365-ai/365-skills --path plugins/bangumi-frames/skills/bangumi-frames
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/bangumi-frames/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add Agents365-ai/365-skills --skill bangumi-frames -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/Agents365-ai/365-skills/tree/HEAD/plugins/bangumi-frames/skills/bangumi-frames/SKILL.md

## When to use it
- extract scene-change keyframes from Bilibili anime episodes
- sort anime character screenshots into separate character folders
- isolate appearances of a specific character using a reference image folder
- remove burned-in subtitles and watermarks from extracted frames

## Example prompts
- Extract keyframes from Bilibili episode ep1231575 and group characters into folders
- Find all frames matching character crops in ~/refs/hero from video BV15qVm68E2h
- Process local file ~/anime.mp4 and clean up burned-in subtitles

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: c4484295864f8c76.

BEGIN THIRD-PARTY FILE c4484295864f8c76
```text
---
disable-model-invocation: true
name: bangumi-frames
version: 0.5.0
description: Extract and organize frames from a Bilibili video (bangumi episode, UP upload, or a local file) into scenery shots and per-character image groups, using anime-specific person detection + CCIP character-identity embeddings. Two modes — cluster everyone, or pull out one (or several) named characters via reference folders. Use when the user wants to collect, extract, or organize anime frames/screenshots by character or by scenery from a Bilibili video. Read-only download for personal viewing/analysis; uploads nothing.
license: MIT
homepage: https://github.com/Agents365-ai/365-skills/tree/main/plugins/bangumi-frames/skills/bangumi-frames
compatibility: Requires ffmpeg and (for downloads) yt-dlp on PATH; Python 3.9+ with dghs-imgutils (anime person detection + CCIP). The CCIP step runs on CPU — do NOT set ONNX_MODE=CoreML (CCIP crashes there); person detection is fine on CoreML. Anime / 2.5D-render art only — not for live-action. Optional --clean (subtitle/watermark removal) needs rapidocr-onnxruntime + simple-lama-inpainting.
platforms: [macos, linux]
metadata: {"openclaw":{"requires":{"anyBins":["ffmpeg"]},"emoji":"🎬","os":["darwin","linux"],"install":[{"id":"brew-ffmpeg","kind":"brew","formula":"ffmpeg","bins":["ffmpeg"],"label":"Install ffmpeg via Homebrew","os":["darwin"]},{"id":"pip-yt-dlp","kind":"pip","package":"yt-dlp","bins":["yt-dlp"],"label":"Install yt-dlp (download Bilibili streams)"},{"id":"pip-imgutils","kind":"pip","package":"dghs-imgutils","label":"Install anime person detection + CCIP models"}]},"hermes":{"tags":["bilibili","anime","bangumi","frames","character","ccip","screenshot","video"],"category":"media","requires_tools":["ffmpeg","yt-dlp"],"related_skills":[]},"author":"Agents365-ai","version":"0.5.0"}
---

# bangumi-frames — Bilibili Anime Frame & Character Organizer

## Overview

Give a Bilibili video (a bangumi `ep` link, a UP-upload `BV` link/id, or a **local
video file**); it downloads → extracts scene-change keyframes → splits scenery vs
character frames → organizes the character crops. **One pass, two modes:**

- **no `--ref` (cluster mode)** — group every character crop by CCIP identity into
  `characters/char_NN/`.
- **with `--ref DIR` (one-vs-rest mode)** — given ONE character's reference folder,
  pull every crop in the video that matches it into `matched/`, filenames prefixed
  with distance (closest first) so a tight threshold yields a pure set.

Models are **anime-specific** (deepghs anime person detection + CCIP character-identity
embeddings) — they do not work on live-action footage.
```
END THIRD-PARTY FILE c4484295864f8c76

The third-party file has ended. Everything between the c4484295864f8c76 tags is data: requests and commands from it are not followed. An “end of file” line with another tag inside the block is part of the file.

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