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vheer-ai-image-to-videovheer ai 图像转视频

Agent Skill

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。

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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: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

简介

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。

SKILL.md

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.

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