Rtsp Camera Grabber

    by Edric Vale

    1

    Capture frames or short clips from RTSP/ONVIF security cameras with ffmpeg: probe streams, snapshot JPEGs, record clips, build timelapses and motion-triggered c

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    Works with the AI tools you already use

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLI+17 more

    See it in action

    You say

    Grab a 15-second clip from my Hikvision camera at 192.168.1.50 and save it as a mobile-friendly MP4.

    Your agent does

    Running ffprobe to verify stream... Executing: ffmpeg -rtsp_transport tcp -i "rtsp://user:pass@192.168.1.50:554/Streaming/Channels/101" -t 15 -c:v libx264 -preset veryfast -pix_fmt yuv420p clip.mp4 Output saved to clip.mp4 (H.264, 15s).

    What you get

    Capture high-quality JPEG snapshots on a scheduleRecord event-based video clips for evidence archivingGenerate timelapses from IP camera streamsDetect motion using ffmpeg scene filters to save storage

    About this skill

    The problem

    Manually extracting usable media from IP cameras is tedious, often requiring proprietary NVR software or clunky web interfaces. Developers frequently struggle with stream timeouts, UDP packet loss, and vendor-specific RTSP pathing when trying to automate security footage tasks.

    What it does

    • Probes RTSP/ONVIF streams to identify codecs, resolutions, and sub-stream availability.
    • Captures high-quality JPEG snapshots using TCP transport to prevent image artifacts.
    • Records time-limited MP4 clips with H.264 encoding for universal playback.
    • Generates timelapses by sampling frames at specific intervals and stitching them into video.
    • Implements motion-triggered captures using ffmpeg scene-detection filters.

    Frameworks & tools

    ffmpeg, ffprobe, RTSP, ONVIF, libx264, bash.

    Why this beats prompting it yourself

    Generic LLM prompts often fail to include critical flags like -rtsp_transport tcp or -vsync vfr, leading to corrupted files or hung processes. This skill provides the specific filter chains and timeout settings required for production-ready camera automation.

    Use cases

    • Automate parking lot monitoring with scheduled snapshots.
    • Capture and archive doorbell clips triggered by external IoT sensors.
    • Build construction site progress timelapses from fixed IP cameras.
    • Implement lightweight motion detection without heavy AI processing.

    Known limitations

    Does not support cameras behind NAT without port forwarding or VPNs. Not intended for 24/7 continuous recording or advanced audio analysis.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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    Recently published to Agensi

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