「scene」の検索結果

Control Philips Hue lights locally: list lights and rooms, set brightness/color, activate scenes, read sensors. Trigger phrases: philips hue, hue lights, my lights.

日本語の概要は準備中です。原文の説明を表示しています。

Read and control Aqara smart home devices: plugs, switches, lights, AC, locks, curtains, scenes. Trigger phrases: aqara, aqara hub, aqara lock, aqara curtain.

日本語の概要は準備中です。原文の説明を表示しています。

在 Remotion 项目中创建带动画的金融 K 线图（蜡烛图）。涵盖数据获取（Yahoo Finance）、 插件架构（config / timeline / Scene / plugin）、Canvas 逐帧绘制、深色交易终端风格、 以及 Remotion Studio 预览和渲染输出。触发词：K线图、蜡烛图、candlestick、OHLC、 股票动画、金融图表视频、Remotion 图表。

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Apply Disney's 12 principles as practical design and engineering rules for procedural animation. Use when creating, improving, reviewing, or debugging code-driven motion in web, SVG, canvas, React, Remotion, game, UI, character, camera, or 3D scenes; especially when motion feels stiff, weightless, mechanical, unclear, or physically correct but visually weak.

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Write and edit project docs (README/markdown) as a glossary of principles, not a mirror of the code. Use when creating or revising a README; when a doc enumerates exact scenes, scenarios, helpers, class ids, file lists, or command/flag matrices the code already holds; when trimming narrative or changelog out of a doc; or when deduplicating overlapping docs and wiring a root doc to its sub-docs.

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Turn a product release (the list of shipped items plus real screen recordings) into a motion recap video and one explained demo per feature, with sound effects tied to on-screen motion and a composed music bed. Deterministic HTML scenes rendered frame by frame, ElevenLabs for sound effects and music, ffmpeg for the mix. Use when asked for a release video, a changelog video, a feature recap reel, or demo clips for release notes and docs.

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Creates talking head videos from any source material (docs, changelogs, blog posts, notes, transcripts). Produces multi-scene videos with avatar narration over screenshots/images using HeyGen v2 API. Supports Quick Shot and Full Producer modes.

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Generates Instagram Reels where product image cuts are synced to audio beats. Accepts audio as a local file, URL, or search query. Uses librosa for beat detection, FFmpeg Ken Burns for scene animation, and Pillow for text overlays. No AI video generation — fully free, fast, and scalable.

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Final QC gate for a rendered 9:16 video ad, run before it is published. One script checks what a machine can decide — exact 1080x1920 size, a hook that moves and speaks in the first second, no frozen stretches, no dead air, no black frames, the brand's real logo on the end card (never a favicon, never a redrawn or wrong logo), end-card colours near the brand palette — and builds one contact sheet (frames with the TikTok/Reels UI safe zones shaded, beside the logo, product images and a font specimen) for the checks that need eyes — font, product likeness, product consistency across scenes, safe zones. A declared silent-text profile covers silent, text-led formats such as kinetic text (no audio track needed, short blank beats between text beats allowed within fixed bounds). Exit 0 PASS / 2 FAIL / 3 ERROR. Use on every finished video master before pinning it.

日本語の概要は準備中です。原文の説明を表示しています。

Generate a single photoreal or designed image with OpenAI gpt-image via fal.ai. Supports gpt-image-1 (default, fixed sizes — the FAL fallback for Higgsfield's `gpt_image_2`) and gpt-image-2 (`openai/gpt-image-2`, custom output sizes up to 3840px). Routes to text-to-image or the edit variant depending on whether a reference image is provided. Use for photoreal character anchors, scene keyframes, and designed sheets (e.g. storyboards) where precise layout and legible text matter.

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Assemble an absurdist animated-explainer video ad (~38s, 9:16) from per-scene i2v clips + their measured VO windows — retime each clip to its VO, re-encode every segment to identical 30fps/libx264/yuv420p so the concat demuxer never drops frames, concat, build a REAL-product PIL end card (never AI) held static, mix VO (loudnorm I=-14) under music (loudnorm I=-26, volume 0.62, amix normalize=0), and burn libass captions last. FREE deterministic assembly (bash-free, Python + ffmpeg + PIL); the recipe supplies the clips, VO, music, product photo, palette, and caption table and gates the paid keyframe/clip/VO/music calls to their own capabilities. Use for the absurdist-explainer format.

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Watch a brand's own product footage (screen recording, product film), pick the moment that proves each line with the user, and render those picks as a product layer — free, local. survey.py turns footage into timestamped contact sheets + scene cuts + motion so the agent can actually look at it; the agent writes a cut list (beat → source window + framing); preview.py draws it as a review sheet the user corrects round by round; cut.py renders the approved list into a silent 1080x1920 layer with the creator's area left as a plate. Also frames footage as a filmed screen (keystone, bezel, handheld drift) with dissolves between beats, and takes still screenshots as sources. Use for any format that shows real product footage beside, between or instead of a creator (split-screen, screen inserts, walkthroughs).

日本語の概要は準備中です。原文の説明を表示しています。

Use when bridging UIKit and SwiftUI, modernizing UIKit apps (scene lifecycle, resizability), debugging Auto Layout, Combine, TextKit, PencilKit, or UIKit animations.

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Use when the user mentions window resizing support, resizable-window readiness, iPhone Mirroring compatibility, iPhone Duo readiness, scene-lifecycle migration checking, or preparing an app for the 27-cycle resizing model.

日本語の概要は準備中です。原文の説明を表示しています。

Build iOS augmented reality and 3D experiences with RealityKit and ARKit. Use when adding RealityView content, loading entities or USDZ models, anchoring objects to planes or world positions, distinguishing entity hit tests from ARKit real-world raycasts, handling AR camera availability, world tracking, scene updates, or RealityKit entity gestures and interactions.

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Build CarPlay-enabled apps using the CarPlay framework. Use when creating navigation, audio, communication, EV charging, parking, or food ordering apps for the car display, working with CPTemplateApplicationScene, CPInterfaceController template hierarchies, CPListTemplate, CPMapTemplate, CPNowPlayingTemplate, configuring CarPlay entitlements, or integrating with CarPlay Simulator for testing.

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Implements keyboard, directional, and scene-level focus behavior across SwiftUI and UIKit. Use when managing @FocusState, defaultFocus, focused values, focusable interactions, focus sections, tvOS geometric focus and Siri Remote navigation, watchOS Digital Crown input, visionOS connected-device focus versus gaze hover/input targets, macOS key view loop and Full Keyboard Access, focus restoration after presentation changes, custom focus routing with UIFocusGuide, or debugging focus with UIFocusDebugger.

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Expert guidance for simulating RoadRunner scenarios via the MATLAB programmatic API and Simulink co-simulation. Use when the user wants to run a simulation, step through a simulation, control actors during co-simulation, add observers, attach sensors, retrieve simulation logs, or read/write scenario variables. Covers simulateScenario, createSimulation, ScenarioSimulation set/get, ActorSimulation getAttribute/setAttribute, addObserver, SensorSimulation, Simulink co-sim blocks, and publishActorBehavior. NOT for project setup, scene building, scenario authoring, or trajectory export.

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Import recorded driving sensor data (GPS, camera, lidar, actor tracks, lanes) into scenariobuilder.* objects (GPSData, CameraData, LidarData, ActorTrackData, Trajectory, laneData) and run preprocessing — synchronize, offset correction, crop, normalizeTimestamps, convertTimestamps. Also: compute actor tracks from lidar when no annotations exist, attach camera/lidar mounting + intrinsics, export to MAT/workspace/timetable/script. Use for raw driving dataset files (KITTI, nuScenes, Waymo, Pandaset, ROS/ROS2 bags, .mat, .csv, .mp4) or driving/vehicle/sensor logs that need wrapping. drivingLogAnalyzer (DLA) is OPT-IN ONLY — invoke only on explicit user request ('DLA', 'open in DLA', 'inspect/explore/analyze the recording') or reported sensor problem (sync drift, timestamp mismatch, overlay misalignment). NEVER auto-launch DLA after wrapping (Rule 0). For 'build scenario / export to RoadRunner / drivingScenario / OpenSCENARIO / Unreal / simulate', hand off to matlab-use-scenario-builder.

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Build RoadRunner HD Map entities in MATLAB — lanes, boundaries, markings, junctions, signs, signals, barriers, parking. Use when creating driving scenes from scratch, authoring road networks for simulation and testing automated driving systems, or assembling RRHD maps from Lanelet2 or other HD map sources.

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Build declarative 3D scenes with React Three Fiber (R3F) - a React renderer for Three.js. Use when building interactive 3D experiences in React applications with component-based architecture, state management, and reusable abstractions. Ideal for product configurators, portfolios, games, data visualization, and immersive web experiences.

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Comprehensive skill for Babylon.js 3D web rendering engine. Use this skill when building real-time 3D experiences, browser-based games, interactive visualizations, or immersive web applications. Triggers on tasks involving Babylon.js, 3D scenes, WebGL/WebGPU rendering, entity-component systems, physics simulations, PBR materials, shadow mapping, or 3D model loading. Alternative to Three.js with built-in editor integration and game engine features.

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Declarative web framework for building browser-based 3D, VR, and AR experiences using HTML and entity-component architecture. Use this skill when creating WebXR applications, VR experiences, AR experiences, 360-degree media viewers, or immersive web content with minimal JavaScript. Triggers on tasks involving A-Frame, WebXR, VR development, AR development, entity-component-system, declarative 3D, or HTML-based 3D scenes. Built on Three.js with accessible HTML-first approach.

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Fast, lightweight 2D rendering engine for creating interactive graphics, particle effects, and canvas-based applications using WebGL/WebGPU. Use this skill when building 2D games, particle systems, interactive canvases, sprite animations, or UI overlays on 3D scenes. Triggers on tasks involving PixiJS, 2D rendering, sprite sheets, particle effects, filters, or high-performance canvas graphics. Alternative to Canvas2D with WebGL acceleration for rendering thousands of sprites at 60 FPS.

日本語の概要は準備中です。原文の説明を表示しています。