正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

Visualizing smart insole data on iOS with a SwiftUI app using our Swift package Get sensor data, and even upload Tflite files for on-device machine learning (eg custom gesture recognition) Even works in Xcode Previews using our nodejs server to relay Bluetooth data via UDP (core Bluetooth only works... show more

BrilliantSole

1,039 subscribers

18,777 次观看 • 1 年前 •via X (Twitter)

教育游戏科学技术

Anya Rossi• Live Now

Private livecam show

1 条评论

Jean-Philippe DIEL 🧬 e/acc 🇫🇷🇳🇿 琼-菲利普的头像

Jean-Philippe DIEL 🧬 e/acc 🇫🇷🇳🇿 琼-菲利普1 年前

Love it

相关视频

Connecting an Apple Watch to our Smart Insoles Using our Brilliant Sole Swift Package in a SwiftUI app Get sensor data, trigger haptics, and even send ML models to the insoles It also works in Xcode Previews (Core Bluetooth doesn’t work on non-MacOS schemes, but you can use our nodejs server to relay sensor data over UDP, which surprisingly works in the WatchOS simulator but not on the watch itself)

Connecting an Apple Watch to our Smart Insoles Using our Brilliant Sole Swift Package in a SwiftUI app Get sensor data, trigger haptics, and even send ML models to the insoles It also works in Xcode Previews (Core Bluetooth doesn’t work on non-MacOS schemes, but you can use our nodejs server to relay sensor data over UDP, which surprisingly works in the WatchOS simulator but not on the watch itself)

Brilliant Wear

46,316 次观看 • 1 年前

Connecting our smart insoles to an Apple Vision Pro (simulator) using our Swift package + SwiftUI sample app The AVP simulator doesn’t have Bluetooth enabled, but fortunately our nodejs server can relay data via UDP Even works in Xcode previews - great for iterating (even if you do have an AVP system on hand)

Connecting our smart insoles to an Apple Vision Pro (simulator) using our Swift package + SwiftUI sample app The AVP simulator doesn’t have Bluetooth enabled, but fortunately our nodejs server can relay data via UDP Even works in Xcode previews - great for iterating (even if you do have an AVP system on hand)

BrilliantSole

29,372 次观看 • 1 年前

Created a Swift Package for our Smart Insoles, along with a sample SwiftUI app It even works directly in Xcode Previews Works on iOS, macOS, watchOS, visionOS, and tvOS

Created a Swift Package for our Smart Insoles, along with a sample SwiftUI app It even works directly in Xcode Previews Works on iOS, macOS, watchOS, visionOS, and tvOS

BrilliantSole

50,947 次观看 • 1 年前

Positional tracking on smart glasses and webcams Experimenting with Niantic Spatial 🌎’s 8th Wall engine to get position using camera and motion data Works with compatible smartglasses, in this case a modified Omi AI’s Omi Glass (based on the Seeed Studio ESP32-S3 Sense) running custom firmware Also works on webcams using our motion modules for supplying imu data

Positional tracking on smart glasses and webcams Experimenting with Niantic Spatial 🌎’s 8th Wall engine to get position using camera and motion data Works with compatible smartglasses, in this case a modified Omi AI’s Omi Glass (based on the Seeed Studio ESP32-S3 Sense) running custom firmware Also works on webcams using our motion modules for supplying imu data

Brilliant Wear

14,800 次观看 • 3 个月前

Made a Unity SDK for our smart insoles Scan for, connect to, and receive sensor data from our insoles via Bluetooth

Made a Unity SDK for our smart insoles Scan for, connect to, and receive sensor data from our insoles via Bluetooth

Brilliant Wear

492,629 次观看 • 1 年前

3D hand tracking on smart glasses Not only can we stream camera data with our Wearables SDK, but we can run MediaPipe for hand tracking, applying it in WebXR environments like Three.js and A-Frame Works with compatible smart glasses, in this case the Omi AI Omi Glass, based on the Seeed Studio XIAO ESP32-S3 Sense (running our custom Firmware)

3D hand tracking on smart glasses Not only can we stream camera data with our Wearables SDK, but we can run MediaPipe for hand tracking, applying it in WebXR environments like Three.js and A-Frame Works with compatible smart glasses, in this case the Omi AI Omi Glass, based on the Seeed Studio XIAO ESP32-S3 Sense (running our custom Firmware)

Brilliant Wear

79,410 次观看 • 5 个月前

Ported our firmware to the Seeed Studio XIAO ESP32-S3 Sense, allowing us to use our Wearables SDK with devices like the Omi Glass from Omi AI Stream camera and microphone data via Bluetooth or WiFi (WebSockets), and even motion data if you attach a compatible imu

Ported our firmware to the Seeed Studio XIAO ESP32-S3 Sense, allowing us to use our Wearables SDK with devices like the Omi Glass from Omi AI Stream camera and microphone data via Bluetooth or WiFi (WebSockets), and even motion data if you attach a compatible imu

Brilliant Wear

64,936 次观看 • 6 个月前

In #Flutter we say that everything is a widget, even the app itself! We took this concept to another level for a tutorial feature and we controlled our app with fake data within our app 🤪! I'm pretty happy with the result!

In #Flutter we say that everything is a widget, even the app itself! We took this concept to another level for a tutorial feature and we controlled our app with fake data within our app 🤪! I'm pretty happy with the result!

Romain Rastel 💙

10,253 次观看 • 2 年前

Meet Bitrig Remote: a professional app development environment for iPad. Connect to Bitrig running on your Mac and build with: - The full Xcode toolchain - Streaming Xcode Simulator previews - Real Xcode projects - GitHub integration - Claude Code and Codex

Meet Bitrig Remote: a professional app development environment for iPad. Connect to Bitrig running on your Mac and build with: - The full Xcode toolchain - Streaming Xcode Simulator previews - Real Xcode projects - GitHub integration - Claude Code and Codex

Bitrig

40,212 次观看 • 1 个月前

The FDA is removing restrictions on using real-world data in drug and device applications. If a product works in the real world, we ought to know.

The FDA is removing restrictions on using real-world data in drug and device applications. If a product works in the real world, we ought to know.

Dr. Marty Makary

64,495 次观看 • 6 个月前

DataTransfer iOS app wip. Ver 1.0.0 Perfect for Anyone that wants to quickly, easily, and reliably pull out all media data from device and can use to restore on another iOS device. Made for iOS only. Mainly started this project because there’s no app I can reliably use without it crashing or too much $ for a simple data backup, plus I need something like this for iOS data recovery situations when customers come in with iOS device for data transfer but FMI on and they cannot remember the login. So this way I can backup data FAST and have multiple ways to transfer the backup files, (Air drop wired or wireless, iCloud, etc) Also, main focus for this app will be elegant UI and high reliability and speed for backups.

DataTransfer iOS app wip. Ver 1.0.0 Perfect for Anyone that wants to quickly, easily, and reliably pull out all media data from device and can use to restore on another iOS device. Made for iOS only. Mainly started this project because there’s no app I can reliably use without it crashing or too much $ for a simple data backup, plus I need something like this for iOS data recovery situations when customers come in with iOS device for data transfer but FMI on and they cannot remember the login. So this way I can backup data FAST and have multiple ways to transfer the backup files, (Air drop wired or wireless, iCloud, etc) Also, main focus for this app will be elegant UI and high reliability and speed for backups.

Mr. Creator

20,658 次观看 • 1 年前

Using our smart insoles as foot trackers in VRChat With our OSC server we can stream motion and pressure data into #VRChat *Our insoles are 3DoF (just orientation, no position) We fixed the feet to the ground for demonstration, but they’re best used alongside other trackers Special thanks to Duinrahaic for helping out with debugging

Using our smart insoles as foot trackers in VRChat With our OSC server we can stream motion and pressure data into #VRChat *Our insoles are 3DoF (just orientation, no position) We fixed the feet to the ground for demonstration, but they’re best used alongside other trackers Special thanks to Duinrahaic for helping out with debugging

Brilliant Wear

111,764 次观看 • 1 年前

Experimenting with wrist controls on smart glasses Using our Wearables SDK, we can display a 3D wireframe A-Frame scene on compatible smartglasses (in this case the Brilliant Labs Frame running our custom firmware) We’re also using our SDK to control a virtual cursor with our Ukaton motion module strapped to our wrist, running an Edge Impulse model to detect pinches There’s a lot of third party hand control accessories we could use (TapWithUs, Doublepoint, and Mudra Band), but using our own hardware/software is great for creating custom gestures

Experimenting with wrist controls on smart glasses Using our Wearables SDK, we can display a 3D wireframe A-Frame scene on compatible smartglasses (in this case the Brilliant Labs Frame running our custom firmware) We’re also using our SDK to control a virtual cursor with our Ukaton motion module strapped to our wrist, running an Edge Impulse model to detect pinches There’s a lot of third party hand control accessories we could use (TapWithUs, Doublepoint, and Mudra Band), but using our own hardware/software is great for creating custom gestures

Brilliant Wear

29,397 次观看 • 8 个月前

Realtime Maps on Smart Glasses Using our Wearables SDK and OpenStreetMap to display a simple map overlay, allowing us to see what places are around us (and if they’re open or not) Works with compatible smart glasses (in this case the Brilliant Labs Frame running custom firmware)

Realtime Maps on Smart Glasses Using our Wearables SDK and OpenStreetMap to display a simple map overlay, allowing us to see what places are around us (and if they’re open or not) Works with compatible smart glasses (in this case the Brilliant Labs Frame running custom firmware)

Brilliant Wear

53,763 次观看 • 8 个月前

Helix is now learning directly from human video data We have already trained on data collected in the real world, including Brookfield residential units To our knowledge, this is the first instance of a humanoid robot learning navigation end-to-end using only human video

Helix is now learning directly from human video data We have already trained on data collected in the real world, including Brookfield residential units To our knowledge, this is the first instance of a humanoid robot learning navigation end-to-end using only human video

Figure

46,041 次观看 • 9 个月前

Vocabulary Learning App created using the #SwiftUI Framework :D I'd love to get your feedback, Let me know. #ios #iosdeveloper #dev #programming #tech #apple #coding #xcode #iosdevelopment

Vocabulary Learning App created using the #SwiftUI Framework :D I'd love to get your feedback, Let me know. #ios #iosdeveloper #dev #programming #tech #apple #coding #xcode #iosdevelopment

Shubham Singh

11,265 次观看 • 1 年前

Gradient Generator using On-Device Intelligence | FoundationModels | SwiftUI | Xcode 26 | WWDC 2025

Gradient Generator using On-Device Intelligence | FoundationModels | SwiftUI | Xcode 26 | WWDC 2025

Kavsoft

16,969 次观看 • 1 年前

Hgraph AI Data Agent ✨ Now Live! Instantly chat with @Hedera data in your browser for free using our new data agent. Meet the network explorer that explores for you. Send a prompt → Watch now fast it is...

Hgraph AI Data Agent ✨ Now Live! Instantly chat with @Hedera data in your browser for free using our new data agent. Meet the network explorer that explores for you. Send a prompt → Watch now fast it is...

Hgraph

25,175 次观看 • 6 个月前

Play to Xcode is here! Ship your projects in Play to the App Store. › Export your styles, components, pages, and entire app to Xcode › All your interactions and logic in Play carry over 1:1 to Xcode › Use real data by loading in JSON files or connect to your own APIs › Create AI features in Play by tapping into popular APIs like OpenAI › Export to SwiftUI or UIKit and easily mix with your existing codebase › Keep your app up to date by simply updating your Swift package Learn more and try it today!

Play to Xcode is here! Ship your projects in Play to the App Store. › Export your styles, components, pages, and entire app to Xcode › All your interactions and logic in Play carry over 1:1 to Xcode › Use real data by loading in JSON files or connect to your own APIs › Create AI features in Play by tapping into popular APIs like OpenAI › Export to SwiftUI or UIKit and easily mix with your existing codebase › Keep your app up to date by simply updating your Swift package Learn more and try it today!

Play

175,664 次观看 • 1 年前

Consistent Hashing Explained Simply Let's break down consistent hashing in a way that's easy to get. It's a handy technique for distributing data evenly across servers. And if you're more of a visual learner, don't miss the attached video which brings this concept to life. Here's how it works: We don't just hash our data keys; we also hash the server names using the same method. This puts everything on a scale, known as the hash space, which we think of as a big circular ring. So, imagine we've got a few servers. We hash them and place them on this ring. We do the same with our data, hashing it by key. To figure out where to store a piece of data, we travel clockwise on the ring from where the data lands until we bump into a server. Like, data key 0 might end up on server 0, and key 1 on server 1. Adding a new server? Only the data near the new server needs to shift. And if a server has to go? Only the data it was holding needs a new spot. But there's a little challenge: sometimes, data doesn't spread out evenly. The fix? Virtual nodes. They're like mini-replicas of a server placed around the ring. The more virtual nodes we have, the better the balance. But there's a catch: more virtual nodes mean more memory usage for tracking them, and it can make the whole system a bit more complex to manage. – Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages):

Consistent Hashing Explained Simply Let's break down consistent hashing in a way that's easy to get. It's a handy technique for distributing data evenly across servers. And if you're more of a visual learner, don't miss the attached video which brings this concept to life. Here's how it works: We don't just hash our data keys; we also hash the server names using the same method. This puts everything on a scale, known as the hash space, which we think of as a big circular ring. So, imagine we've got a few servers. We hash them and place them on this ring. We do the same with our data, hashing it by key. To figure out where to store a piece of data, we travel clockwise on the ring from where the data lands until we bump into a server. Like, data key 0 might end up on server 0, and key 1 on server 1. Adding a new server? Only the data near the new server needs to shift. And if a server has to go? Only the data it was holding needs a new spot. But there's a little challenge: sometimes, data doesn't spread out evenly. The fix? Virtual nodes. They're like mini-replicas of a server placed around the ring. The more virtual nodes we have, the better the balance. But there's a catch: more virtual nodes mean more memory usage for tracking them, and it can make the whole system a bit more complex to manage. – Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages):

Sahn Lam

36,787 次观看 • 2 年前