Search Results for "real"

Posturr is a macOS application that uses computer vision and machine learning — specifically Apple’s Vision framework — to monitor a user’s posture in real time and encourage healthier habits by visually responding when poor posture is detected. Running locally on the Mac, the app accesses the built-in camera to detect when you slouch or sit incorrectly, and when it recognizes sustained slouching, it applies a progressive visual blur to the screen as a subtle but effective cue to straighten up. ...

RevenueCat is a powerful, reliable, and free-to-use in-app purchase server with cross-platform support. Our open-source framework provides a backend and a wrapper around StoreKit and Google Play Billing to make implementing in-app purchases and subscriptions easy. Send enriched purchase events to analytics and attribution tools with our easy integrations. Fetch products, make purchases, and check subscription status with our native SDKs. Host and configure products remotely from our...

The Swift Composable Architecture (TCA) is a reusable, testable architecture library for building Swift applications using unidirectional data flow, reducers, and dependency injection. It encourages modular code, easy state management, and full test coverage. Designed and authored by the Point-Free team with extensive real-world examples.

...If you're familiar with Image, you'll find it easy to use WebImage and AnimatedImage. Since SDWebImageSwiftUI is built on top of SDWebImage, it provide both the out-of-box features as well as advanced powerful features you may want in real world Apps.

GPUImage3 is a Swift framework for GPU-accelerated image and video processing on macOS and iOS. It is the third generation of the GPUImage project and replaces the earlier OpenGL-based approach with Apple’s Metal framework. The library aims to make real-time video processing and machine vision easier by hiding much of the GPU rendering boilerplate. It supports image and video sources, custom shader-based processing, and filter pipelines. Its API is intended to stay close to GPUImage2 so projects can migrate with less friction where possible. It is useful for Apple-platform developers building camera effects, visual filters, real-time image analysis, and Metal-based media processing tools.

A Machine Learning based location recording and activity detection framework for iOS. Combined, simplified Core Location and Core Motion recording. Filtered, smoothed, and simplified location and motion data. Near real-time stationary / moving state detection. Automatic energy use management, enabling all-day recording. Automatic stopping and restarting of recording, to avoid wasteful battery use. Machine Learning-based activity type detection. Improved detection of Core Motion activity types (stationary, walking, running, cycling, automotive). ...

...Now, keep in mind you'll probably want constants defined for many of these size/padding values, in order to keep the code cleaner and easier to maintain, but I decided to use real numbers for most of the values to make the code less obscure when new people are reading through the demonstration.