openvino_movenet_multipose – Real‑time Multi‑Pose Tracking with OpenVINO
From the repo · “MoveNet MultiPose Tracking on OpenVINO”
OpenVINO MoveNet MultiPose is a tool that enables precise multi-pose tracking for analytics, allowing startup founders to analyze human movement in videos or images.
- •When you need to track multiple people's movements in a video for sports analytics
- •When analyzing customer behavior in a retail setting through video footage
- •When developing fitness or dance applications that require accurate pose tracking
python demo.py --input video.mp4 --output tracked_video.mp4 --model movenet_multipose
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/openvino-movenet-multipose && curl -fsSL https://workflowstacks.com/api/skills/openvino-movenet-multipose/claude-skill -o ~/.claude/skills/openvino-movenet-multipose/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
Openvino_movenet_multipose – Real‑time Multi‑Pose Tracking with OpenVINO is a small Python project (~650 lines across 3 code files). Setup is light: installs like a normal app. Reading the code is optional. Last commit 51 months ago, MIT license, no tests found.
- 1README.mdStart here — what it does and how to install it
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/openvino-movenet-multipose && curl -fsSL https://workflowstacks.com/api/skills/openvino-movenet-multipose/claude-skill -o ~/.claude/skills/openvino-movenet-multipose/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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Includes the tested workflow and a written setup playbook. Needs: No extra API — just watches the pages you list.
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