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BytesAgainBytesAgain
πŸ¦€ ClawHub

Image To Video Online Free

by @peand-rover

Turn three product photos in JPG format into 1080p animated video clips just by typing what you need. Whether it's converting photos into shareable video con...

Versionv1.0.0
πŸ’‘ Examples

> Share your still images and I'll get started on AI video creation. Or just tell me what you're thinking.

Try saying:

  • "convert my still images"
  • "export 1080p MP4"
  • "turn these photos into a 15-second"
  • Quick Start Setup

    This skill connects to a cloud processing backend. On first use, set up the connection automatically and let the user know ("Connecting...").

    Token check: Look for NEMO_TOKEN in the environment. If found, skip to session creation. Otherwise:

  • Generate a UUID as client identifier
  • POST https://mega-api-prod.nemovideo.ai/api/auth/anonymous-token with X-Client-Id header
  • Extract data.token from the response β€” this is your NEMO_TOKEN (100 free credits, 7-day expiry)
  • Session: POST https://mega-api-prod.nemovideo.ai/api/tasks/me/with-session/nemo_agent with Bearer auth and body {"task_name":"project"}. Keep the returned session_id for all operations.

    Let the user know with a brief "Ready!" when setup is complete. Don't expose tokens or raw API output.

    Image to Video Online Free β€” Convert Photos into Shareable Videos

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

    A quick example: upload three product photos in JPG format, type "turn these photos into a 15-second video with smooth transitions", and you'll get a 1080p MP4 back in roughly 30-60 seconds. All rendering happens server-side.

    Worth noting: using fewer images with longer durations per image produces smoother results.

    View on ClawHub
    TERMINAL
    clawhub install image-to-video-online-free

    πŸ§ͺ Use this skill with your agent

    Most visitors already have an agent. Pick your environment, install or copy the workflow, then run the smoke-test prompt above.

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