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Agent Skill · 图像处理

image-to-video-joyfun（图像到视频）

用于辅助图像生成、图片编辑、视觉素材处理或图像模型工作流。它适合让 Agent 根据文本生成图片、处理背景、整理视觉提示词或调用相关图像工具。使用时需要确认输入图片、版权来源、输出格式和模型限制；涉及人物、品牌、商品或公开展示素材时，应额外核对授权、真实性和内容合规边界。

image-to-video-joyfun 是图像处理类 Agent Skill，可用宿主为 OpenClaw，通过ClawHub获取，权限为接触敏感数据；许可证为 MIT-0，第三方扫描有提醒项，按安装量在图像处理类的 1,562 个 Skill 里排第 997。

总安装 1,939周安装 80GitHub Stars 公开资料未说明下载 634核验 2026-05-01
图像处理接触敏感数据ClawHub未标认证来源可访问许可证明确审计提醒OpenClaw

安装说明

本站只整理中文说明，不托管安装包，也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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：image-to-video-joyfun（图像到视频）
来源仓库：https://github.com/peand-rover/image-to-video-joyfun
安装命令：
openclaw skills install image-to-video-joyfun
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 image-to-video-joyfun

这个 Skill 是做什么的

图像处理类 Skill 处理生成、裁剪、压缩和批量转换图片的任务。

无需复杂设置即可生成趣味动画视频，提升内容娱乐属性。适用于游戏解说、儿童内容或年轻化品牌传播策略。上传图片并语音指令如“做个卡通风格动画”，系统自动渲染。支持 JPG/PNG/WEBP/GIF，单个文件最大 200MB，注意存储路径安全。禁止生成不当或误导性内容，遵守当地网络信息服务管理规定。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw；先确认自己用的是其中之一，再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install image-to-video-joyfun；命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开，让新装的 Skill 被重新扫描到，否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据，先在测试目录或测试账号里跑，确认没问题再放到正式项目。

常见问题

6 条

image-to-video-joyfun 怎么安装？

在终端执行 openclaw skills install image-to-video-joyfun。装完完全退出宿主工具再打开，让它重新扫描本地 Skill。

image-to-video-joyfun 支持哪些 AI 工具？

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录，一般也能手动放进去，但要自己确认触发方式是否一致。

image-to-video-joyfun 需要什么权限？

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置，应进入高风险复核队列，默认不自动发布。

image-to-video-joyfun 是免费的吗？

来源标注的许可证是 MIT-0。本站不代收任何费用，也不托管安装包；能否商用、要不要署名，以许可证原文为准。

image-to-video-joyfun 用的人多吗？

公开数据是累计安装 1,939 次，近一周安装 80 次，下载 634 次。这些数字来自第三方目录统计，只能当作热度参考，不代表质量或安全性。

image-to-video-joyfun 安全吗？

第三方扫描有提醒项，说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主，触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0，商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据，装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项，需要人工逐条确认。
  • 第三方目录整理，版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw，想直接扩展它能力的人。
  • 需要处理图像处理类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证，不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

图像处理类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
ai-image-generation

AI 图像生成 · Codex、Claude

4,365,552382调用外部服务未明确有提醒
openai-image-gen

OpenAI 图像生成 · OpenClaw

1,906,88432需要联网MIT-0有提醒
image

图像 · OpenClaw

525,99926需要联网MIT-0通过
baoyu-cover-image

宝玉封面图 · Codex、Claude

474,24016,779只读MIT有提醒
baoyu-image-gen

宝玉图像生成器 · Codex、Claude

468,00716,778接触敏感数据MIT通过
image-to-video-joyfun

图像到视频 · 本页

1,939—接触敏感数据MIT-0有提醒

按安装量取同分类前几名；数字来自第三方目录统计，只作热度参考，不代表质量结论。

SKILL.md 原文

name
image-to-video-joyfun
version
1.0.0
displayName
Image to Video Joyfun — Convert Images Into Video Clips
description
>
metadata
{"openclaw": {"emoji": "🎞️", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN", "variant": "greeting_v2"}}

Getting Started

Got still images to work with? Send it over and tell me what you need — I'll take care of the AI video creation.

Try saying:

  • "convert a single product photo or illustration into a 1080p MP4"
  • "animate this image into a 5-second video clip with smooth motion"
  • "turning static images into short animated videos for social media creators"

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.

Image to Video Joyfun — Convert Images Into Video Clips

Send me your still images and describe the result you want. The AI video creation runs on remote GPU nodes — nothing to install on your machine.

A quick example: upload a single product photo or illustration, type "animate this image into a 5-second video clip with smooth motion", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

Worth noting: higher contrast images with clear subjects animate more smoothly.

Matching Input to Actions

User prompts referencing image to video joyfun, aspect ratio, text overlays, or audio tracks get routed to the corresponding action via keyword and intent classification.

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❌

Cloud Render Pipeline Details

Each export job queues on a cloud GPU node that composites video layers, applies platform-spec compression (H.264, up to 1080x1920), and returns a download URL within 30-90 seconds. The session token carries render job IDs, so closing the tab before completion orphans the job.

All calls go to https://mega-api-prod.nemovideo.ai. The main endpoints:

  1. Session — POST /api/tasks/me/with-session/nemo_agent with {"task_name":"project","language":"<lang>"}. Gives you a session_id.
  2. Chat (SSE) — POST /run_sse with session_id and your message in new_message.parts[0].text. Set Accept: text/event-stream. Up to 15 min.
  3. Upload — POST /api/upload-video/nemo_agent/me/<sid> — multipart file or JSON with URLs.
  4. Credits — GET /api/credits/balance/simple — returns available, frozen, total.
  5. State — GET /api/state/nemo_agent/me/<sid>/latest — current draft and media info.
  6. Export — POST /api/render/proxy/lambda with render ID and draft JSON. Poll GET /api/render/proxy/lambda/<id> every 30s for completed status and download URL.

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

Three attribution headers are required on every request and must match this file's frontmatter:

HeaderValue
X-Skill-Sourceimage-to-video-joyfun
X-Skill-Versionfrontmatter version
X-Skill-Platformauto-detect: clawhub / cursor / unknown from install path

Include Authorization: Bearer <NEMO_TOKEN> and all attribution headers on every request — omitting them triggers a 402 on export.

Draft JSON uses short keys: t for tracks, tt for track type (0=video, 1=audio, 7=text), sg for segments, d for duration in ms, m for metadata.

Example timeline summary:

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

Translating GUI Instructions

The backend responds as if there's a visual interface. Map its instructions to API calls:

  • "click" or "点击" → execute the action via the relevant endpoint
  • "open" or "打开" → query session state to get the data
  • "drag/drop" or "拖拽" → send the edit command through SSE
  • "preview in timeline" → show a text summary of current tracks
  • "Export" or "导出" → run the export workflow

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.

Error Codes

  • 0 — success, continue normally
  • 1001 — token expired or invalid; re-acquire via /api/auth/anonymous-token
  • 1002 — session not found; create a new one
  • 2001 — out of credits; anonymous users get a registration link with ?bind=<id>, registered users top up
  • 4001 — unsupported file type; show accepted formats
  • 4002 — file too large; suggest compressing or trimming
  • 400 — missing X-Client-Id; generate one and retry
  • 402 — free plan export blocked; not a credit issue, subscription tier
  • 429 — rate limited; wait 30s and retry once

Tips and Tricks

The backend processes faster when you're specific. Instead of "make it look better", try "animate this image into a 5-second video clip with smooth motion" — concrete instructions get better results.

Max file size is 200MB. Stick to JPG, PNG, WEBP, GIF for the smoothest experience.

Use PNG images for cleaner edges and better animation output quality.

Common Workflows

Quick edit: Upload → "animate this image into a 5-second video clip with smooth motion" → Download MP4. Takes 30-60 seconds for a 30-second clip.

Batch style: Upload multiple files in one session. Process them one by one with different instructions. Each gets its own render.

Iterative: Start with a rough cut, preview the result, then refine. The session keeps your timeline state so you can keep tweaking.

平台分布

OpenClaw

84.98%
按下载量换算539

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置，应进入高风险复核队列，默认不自动发布。

安装前确认

本站仅展示第三方公开信息，不托管安装包，不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项，安装前请自行复核。目前只有一个公开来源，建议同时核对源仓库。

继续浏览同类 Skills

更多图像处理 Skills（1,562）返回 Skills 目录

上一个 Skill

image-to-video-jiggle（图像到视频抖动）

tk8544-b/image-to-video-jiggle

用于辅助图像生成、图片编辑、视觉素材处理或图像模型工作流。它适合让 Agent 根据文本生成图片、处理背景、整理视觉提示词或调用相关图像工具。使用时需要确认输入图片、版权来源、输出格式和模型限制；涉及人物、品牌、商品或公开展示素材时，应额外核对授权、真实性和内容合规边界。

下一个 Skill

image-to-video-json-prompt（图像 TO video JSON prompt）

francemichaell-15/image-to-video-json-prompt

用于辅助图像生成、图片编辑、视觉素材处理或图像模型工作流。它适合让 Agent 根据文本生成图片、处理背景、整理视觉提示词或调用相关图像工具。使用时需要确认输入图片、版权来源、输出格式和模型限制；涉及人物、品牌、商品或公开展示素材时，应额外核对授权、真实性和内容合规边界。