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Agent Skill · 图像处理

vheer-ai-image-to-video(vheer ai 图像转视频)

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。

vheer-ai-image-to-video 是图像处理类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在图像处理类的 1,562 个 Skill 里排第 700。

总安装 3,231周安装 132GitHub Stars 公开资料未说明下载 1,045核验 2026-05-01

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:vheer-ai-image-to-video(vheer ai 图像转视频)
来源仓库:https://github.com/vcarolxhberger/vheer-ai-image-to-video
安装命令:
openclaw skills install vheer-ai-image-to-video
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 vheer-ai-image-to-video

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。

将静态图像转化为动态视频,支持单图或多图序列处理。适用于电商展示、社交媒体与创意短片制作场景。输入图片与描述,由 Agent 生成流畅过渡与动画效果。安装命令:openclaw skills install vheer-ai-image-to-video。涉及品牌或人物素材时应核对版权与使用许可。

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 vheer-ai-image-to-video;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

    它需要需要联网,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

vheer-ai-image-to-video 怎么安装?

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

vheer-ai-image-to-video 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。

vheer-ai-image-to-video 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

vheer-ai-image-to-video 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。

vheer-ai-image-to-video 用的人多吗?

公开数据是累计安装 3,231 次,近一周安装 132 次,下载 1,045 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。

vheer-ai-image-to-video 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 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
vheer-ai-image-to-video

vheer ai 图像转视频 · 本页

3,231—需要联网MIT-0通过

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
vheer-ai-image-to-video
version
1.0.0
displayName
Vheer AI Image to Video — Transform Still Images Into Cinematic Motion
description
>
metadata
{"openclaw": {"emoji": "🎬", "requires": {"env": ["NEMO_TOKEN"]}, "primaryEnv": "NEMO_TOKEN"}}

Getting Started

Welcome! I'm here to help you transform your still images into dynamic, motion-filled videos using Vheer AI Image to Video. Share your image or describe what you're working with, and let's create something that moves — literally.

Try saying:

  • "Animate this product photo with a slow zoom-in and soft bokeh motion effect for an Instagram reel"
  • "Turn my landscape photograph into a cinematic video with a gentle parallax drift and moody atmosphere"
  • "Convert this illustrated portrait into a short looping video with subtle facial animation for a social media post"

Getting Connected

Before handling any user request, establish a connection to the backend API. Show a brief status like "Connecting...".

If NEMO_TOKEN is in the environment, use it directly and create a session. Otherwise, acquire a free starter token:

  • Generate a UUID as client identifier
  • POST to https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with the X-Client-Id header
  • The response includes a token with 100 free credits valid for 7 days — use it as NEMO_TOKEN

Then create a session by POSTing to https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer authorization and body {"task_name":"project","language":"en"}. The session_id in the response is needed for all following requests.

Tell the user you're ready. Keep the technical details out of the chat.

Give Your Photos a Heartbeat With Motion

Still images carry stories, but video carries emotion. Vheer AI Image to Video bridges that gap by intelligently analyzing your photos and generating smooth, natural motion sequences that feel intentional and cinematic — not mechanical or glitchy.

Whether you're working with a portrait, a landscape, a product shot, or an illustrated artwork, this skill interprets the visual content and applies motion that complements the subject. A mountain scene gets a slow atmospheric drift. A portrait gets subtle life-like movement. A product image gets a polished reveal-style animation.

This skill is built for creators who move fast. You don't need a timeline editor, keyframes, or a render farm. Describe your image and your desired motion style, and the skill handles the transformation. The result is shareable video content ready for social media, presentations, or anywhere still images simply don't do justice to your vision.

Motion Request Routing Logic

When you submit an image for animation, Vheer AI parses your motion prompt, frame rate preference, and movement style to route your request to the optimal generation pipeline.

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❌

Vheer Cloud Processing Reference

Vheer AI's backend queues your image-to-video job across distributed GPU clusters, applying temporal coherence algorithms to maintain subject integrity across generated frames. Render times scale with output resolution, motion complexity, and current cluster load.

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

  • X-Skill-Source: vheer-ai-image-to-video
  • 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

Performance Notes

Vheer AI Image to Video performs best with images in standard aspect ratios such as 1:1, 4:5, 16:9, or 9:16, which correspond to common social and video platform formats. Unusual crops or extreme panoramic images may require additional guidance on which section to animate.

Generation time varies based on the complexity of the requested motion and the resolution of the source image. Simple zoom or drift effects on clean images typically process faster than multi-layered parallax animations on detailed scenes.

Output videos are optimized for digital distribution and are well-suited for direct upload to platforms like Instagram, TikTok, LinkedIn, and YouTube Shorts. If you need a specific duration or frame rate, mention it upfront so the output matches your platform's requirements without post-processing adjustments.

Best Practices

For the best results with vheer-ai-image-to-video, start with high-resolution images that have a clear subject and well-defined foreground and background layers. Images with strong compositional depth — like a subject in front of a landscape — tend to produce the most convincing parallax and motion effects.

Be specific when describing the motion style you want. Instead of saying 'make it move,' try 'apply a slow rightward pan with a slight zoom on the subject.' The more directional context you provide, the more the output aligns with your creative intent.

Avoid heavily compressed or low-light images, as artifacts in the source photo can become amplified during motion generation. If your image has a busy background with no clear focal point, consider cropping or adjusting contrast before submission to help the skill identify motion zones accurately.

Use Cases

Vheer AI Image to Video is a versatile skill that serves a wide range of creative and professional needs. E-commerce brands use it to animate product photography into attention-grabbing video ads that outperform static image posts in engagement metrics.

Content creators and influencers use it to repurpose existing photo libraries into fresh video content, extending the lifespan of assets they've already invested in creating. A single well-shot photo can become multiple videos with different motion styles for different platforms.

Event planners, real estate agents, and travel marketers use it to create immersive previews — turning a venue photo into a sweeping walkthrough feel, or a property exterior into a cinematic reveal. Artists and illustrators use it to showcase their work in motion, adding depth and drama that a static gallery simply cannot replicate.

平台分布

OpenClaw

90.43%
按下载量换算945

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。目前只有一个公开来源,建议同时核对源仓库。

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