Integrate DockKit for subject tracking with motorized iPhone docks.
npx skills add https://github.com/Roy-wonji/claude-config --skill dockkit-roy-wonji
Please help me install this Agent Skill. Skill: dockkit Source: https://github.com/Roy-wonji/claude-config/tree/main/skills/swift-ios-skills/skills/dockkit Command: npx skills add https://github.com/Roy-wonji/claude-config --skill dockkit-roy-wonji
This Skill helps you integrate DockKit so your iOS camera app can automatically track people or objects and control a motorized camera dock for smooth pan and tilt.
Use the dockkit skill to build an iPhone camera app that detects faces or bodies, enables system tracking when a DockKit accessory is docked, and restores the tracking mode after any manual control or animations.
High-intent search queries and answers about installing and using this skill.
Implement subject tracking by integrating DockKit to enable intelligent face, body, or object tracking with motorized iPhone docks using AVFoundation camera frames for automatic pan and tilt movement.
DockKit accessory discovery and camera control requires iOS 17 or later, using DockAccessoryManager and DockAccessory APIs to react to docked state changes and obtain accessory identity details.
Yes, you can provide custom ML or Vision observations for faces, bodies, or objects at a correct frame rate of 10 to 30 fps, choosing framing modes and setting a region of interest for custom tracking.
Select a specific subject by tapping on the AVFoundation camera frames or selecting subject UUIDs, which locks DockKit's built-in face or body tracking to that individual target.
Custom tracking observations must be delivered at 10 to 30 fps with correct normalized coordinates and DockKit-compatible camera information to ensure smooth motorized pan and tilt control.
Yes, your app can restore the active tracking mode after manual control or animations by properly enabling or disabling system tracking through the DockKit APIs.
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