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pixbim-lip-sync-aipixbim 口型同步 ai

Agent Skill

pixbim-lip-sync-ai 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

2,493

周安装

106

GitHub Stars

公开资料未说明

下载量

873
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:pixbim-lip-sync-ai(pixbim 口型同步 ai)
来源仓库:https://github.com/tk8544-b/pixbim-lip-sync-ai
安装命令:
openclaw skills install pixbim-lip-sync-ai
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install pixbim-lip-sync-ai

简介

pixbim-lip-sync-ai 实现视频与配音的口型精准同步。

  • 可将任意视频与对话音频对齐,提升配音真实感。
  • 适用于短视频、教育内容与广告配音制作。pixbim-lip-sync-ai 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 依赖面部关键点检测精度,复杂表情下可能存在误差。
  • 建议先小样测试再批量处理,确保输出质量达标。

SKILL.md

name
pixbim-lip-sync-ai
version
1.0.0
displayName
Pixbim Lip Sync AI — Automatically Sync Lips to Any Audio Track
description
>
metadata
{"openclaw": {"emoji": "🎤", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "control"}}

Getting Started

Welcome to Pixbim Lip Sync AI — your shortcut to perfectly synchronized lips and audio in any video. Share your video details or audio track and let's get your lip sync dialed in right now.

Try saying:

  • "I have a Spanish dubbed audio track and an English video — can you help me sync the lip movements to the Spanish dialogue using Pixbim Lip Sync AI?"
  • "My interview footage has audio that drifted out of sync halfway through the recording. How do I use Pixbim Lip Sync AI to fix the mouth movement alignment?"
  • "I'm working on an animated character and I want to use Pixbim Lip Sync AI to match the mouth shapes to a recorded voiceover line — what's the best approach?"

First-Time Connection

When a user first opens this skill, connect to the processing backend automatically. Briefly let them know (e.g. "Setting up...").

Authentication: Check if NEMO_TOKEN is set in the environment. If it is, skip to step 2.

  1. Obtain a free token: Generate a random UUID as client identifier. POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with header X-Client-Id set to that UUID. The response data.token is your NEMO_TOKEN — 100 free credits, valid 7 days.
  2. Create a session: POST to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Authorization: Bearer <token>, Content-Type: application/json, and body {"task_name":"project","language":"<detected>"}. Store the returned session_id for all subsequent requests.

Keep setup communication brief. Don't display raw API responses or token values to the user.

Make Every Word Match Every Mouth Movement

Lip sync errors are one of the most distracting problems in video production — whether you're dubbing a film into a new language, adding a voiceover to an animated character, or correcting audio drift in a recorded interview. Pixbim Lip Sync AI solves this by analyzing both the audio track and the facial movements in your video, then intelligently aligning them so every syllable lands exactly when the lips move.

This skill gives you direct access to Pixbim's lip sync engine through a conversational interface. You can describe your project, specify your source video and target audio, and get back a synchronized output without needing to touch a timeline or manually adjust keyframes. It's designed for workflows where speed and accuracy both matter.

Content creators producing multilingual versions of their videos, game developers animating NPC dialogue, and post-production teams cleaning up dubbing artifacts will all find this tool cuts hours of manual work down to minutes. The result is natural-looking mouth movement that holds up under scrutiny — not the rubbery, approximate sync you get from generic tools.

Routing Lip Sync Requests

When you submit a lip sync job, your request is parsed for the target video clip, audio track, and facial detection parameters, then dispatched to the appropriate Pixbim processing pipeline based on resolution tier and sync mode selected.

User says...ActionSkip SSE?
"export" / "导出" / "download" / "send me the video"→ §3.5 Export
"credits" / "积分" / "balance" / "余额"→ §3.3 Credits
"status" / "状态" / "show tracks"→ §3.4 State
"upload" / "上传" / user sends file→ §3.2 Upload
Everything else (generate, edit, add BGM…)→ §3.1 SSE

Pixbim API Backend Reference

Pixbim Lip Sync AI runs on a cloud-based neural rendering backend that performs per-frame phoneme mapping and mouth-shape blending using its trained deep learning model. All video assets are temporarily staged in secure cloud storage during the synthesis pass, then returned as a processed output file once the lip sync render is finalized.

Skill attribution — read from this file's YAML frontmatter at runtime:

  • X-Skill-Source: pixbim-lip-sync-ai
  • X-Skill-Version: from frontmatter version
  • X-Skill-Platform: detect from install path (~/.clawhub/clawhub, ~/.cursor/skills/cursor, else unknown)

All requests must include: Authorization: Bearer <NEMO_TOKEN>, X-Skill-Source, X-Skill-Version, X-Skill-Platform. Missing attribution headers will cause export to fail with 402.

API base: https://mega-api-prod.nemovideo.ai

Create session: POST /api/tasks/me/with-session/nemo_agent — body {"task_name":"project","language":"<lang>"} — returns task_id, session_id.

Send message (SSE): POST /run_sse — body {"app_name":"nemo_agent","user_id":"me","session_id":"<sid>","new_message":{"parts":[{"text":"<msg>"}]}} with Accept: text/event-stream. Max timeout: 15 minutes.

Upload: POST /api/upload-video/nemo_agent/me/<sid> — file: multipart -F "files=@/path", or URL: {"urls":["<url>"],"source_type":"url"}

Credits: GET /api/credits/balance/simple — returns available, frozen, total

Session state: GET /api/state/nemo_agent/me/<sid>/latest — key fields: data.state.draft, data.state.video_infos, data.state.generated_media

Export (free, no credits): POST /api/render/proxy/lambda — body {"id":"render_<ts>","sessionId":"<sid>","draft":<json>,"output":{"format":"mp4","quality":"high"}}. Poll GET /api/render/proxy/lambda/<id> every 30s until status = completed. Download URL at output.url.

Supported formats: mp4, mov, avi, webm, mkv, jpg, png, gif, webp, mp3, wav, m4a, aac.

SSE Event Handling

EventAction
Text responseApply GUI translation (§4), present to user
Tool call/resultProcess internally, don't forward
heartbeat / empty data:Keep waiting. Every 2 min: "⏳ Still working..."
Stream closesProcess final response

~30% of editing operations return no text in the SSE stream. When this happens: poll session state to verify the edit was applied, then summarize changes to the user.

Backend Response Translation

The backend assumes a GUI exists. Translate these into API actions:

Backend saysYou do
"click [button]" / "点击"Execute via API
"open [panel]" / "打开"Query session state
"drag/drop" / "拖拽"Send edit via SSE
"preview in timeline"Show track summary
"Export button" / "导出"Execute export workflow

Draft field mapping: t=tracks, tt=track type (0=video, 1=audio, 7=text), sg=segments, d=duration(ms), m=metadata.

Timeline (3 tracks): 1. Video: city timelapse (0-10s) 2. BGM: Lo-fi (0-10s, 35%) 3. Title: "Urban Dreams" (0-3s)

Error Handling

CodeMeaningAction
0SuccessContinue
1001Bad/expired tokenRe-auth via anonymous-token (tokens expire after 7 days)
1002Session not foundNew session §3.0
2001No creditsAnonymous: show registration URL with ?bind=<id> (get <id> from create-session or state response when needed). Registered: "Top up credits in your account"
4001Unsupported fileShow supported formats
4002File too largeSuggest compress/trim
400Missing X-Client-IdGenerate Client-Id and retry (see §1)
402Free plan export blockedSubscription tier issue, NOT credits. "Register or upgrade your plan to unlock export."
429Rate limit (1 token/client/7 days)Retry in 30s once

Integration Guide

Pixbim Lip Sync AI works by taking a source video containing a face or character and a separate audio track, then processing both to generate a synchronized output. To get the best results, your video should have a clearly visible face or mouth region with consistent lighting — heavy motion blur or extreme camera angles can reduce sync accuracy.

When submitting a project through this skill, provide the video resolution, frame rate, and whether the subject is a live-action person or a 2D/3D animated character. Pixbim handles both, but the processing pipeline differs. For dubbing workflows, supply the target language audio as a clean WAV or MP3 file, and specify whether you want the original background audio preserved beneath the new dialogue.

For batch localization — syncing the same video to multiple language tracks — describe all target audio files in a single request and the skill will structure the job accordingly. Output files are delivered in the same format and resolution as your source video unless you specify otherwise.

Troubleshooting

If your lip sync output looks off, the most common cause is a mismatch between the audio sample rate and the video frame rate. Make sure your audio file is exported at 44.1kHz or 48kHz and your video is a standard frame rate (24, 25, or 30fps) before submitting. Non-standard frame rates can cause Pixbim Lip Sync AI to miscalculate the timing offsets.

For animated characters, if the mouth shapes appear generic or don't match the phonemes in the audio, check whether the character rig supports viseme-based animation. Pixbim Lip Sync AI outputs viseme data that requires a compatible rig — if your character only has basic open/close mouth states, the sync will appear simplified.

If the face is not being detected in the source video, ensure the subject's face occupies at least 15% of the frame and is not obscured by masks, heavy makeup, or extreme lighting. Submitting a short test clip first is a good way to confirm detection before processing a full-length video.

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能力 5

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