Search Results for "image steganography code"
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Showing 11 open source projects for "image steganography code"
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1
FengNiao
A command line tool for cleaning unused resources in Xcode
The FengNiao project is a lightweight command-line utility designed to help iOS/macOS developers clean up their Xcode projects by detecting and removing unused image resource files. As projects evolve, image assets often accumulate — many of which may no longer be referenced in code, storyboards, or asset catalogs; FengNiao scans the project directory (and subfolders) to identify those orphaned resources and optionally delete them, helping to reduce project bloat and potential app size. The tool is written in Swift, distributed under MIT license, and supports installation via Swift Package Manager or compilation from source. ... -
2
Nuke
Image loading system
...Nuke has an automated test suite 2x the size of the codebase itself, ensuring excellent reliability. Every feature is carefully designed and optimized for performance. Fast LRU memory cache, native HTTP disk cache, and custom aggressive LRU disk cache. Customize image pipeline using built-in Alamofire, Gifu, FLAnimatedImage, WebP plugins or create your own. Enable progressive decoding with a single line of code. Nuke supports progressive JPEG out of the box, and WebP via a plugin built by the community. Automatically prefetch images ahead of time using either Preheat or native table and collection view prefetching APIs. -
3
EFQRCode
A better way to operate QR Code in Swift, support iOS, macOS, etc.
EFQRCode is a lightweight, pure-Swift library for generating stylized QRCode images with watermark or icon, and for recognizing QRCode from images, inspired by qrcode. Based on CoreGraphics, CoreImage, and ImageIO, EFQRCode provides you with a better way to handle QRCode in your app, no matter if it is on iOS, macOS, watchOS, and/or tvOS. You can integrate EFQRCode through CocoaPods, Carthage, and/or Swift Package Manager. -
4
R.swift
Autocompleted resources like images, fonts & segues in Swift projects
Get strong typed, autocompleted resources like images, fonts and segues in Swift projects. It makes your code that uses resources to be fully typed, less casting and guessing what a method will return. Compile time checked, no more incorrect strings that make your app crash at runtime. Autocompleted, never have to guess that image name again. For autocompleted images, and compiletime checked images. After installing R.swift into your project you can use the R-struct to access resources. ... -
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5
Posturr
A macOS app that blurs your screen when you slouch
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... -
6
Airtest
UI Automation Framework for Games and Apps
¿Airtest provides cross-platform APIs, including app installation, simulated input, assertion and so forth. Airtest uses image recognition technology to locate UI elements so that you can automate games and apps without injecting any code. Airtest cases can be easily run on large device farms, using the command line or python API. HTML reports with detailed info and screen recording allow you to quickly locate failure points. NetEase builds Airlab on top of the Airtest Project. ... -
7
PinLayout
Fast Swift Views layouting without auto layout
Extremely Fast views layouting without auto layout. No magic, pure code, full control and blazing fast. Concise syntax, intuitive, readable & chainable. PinLayout can layouts UIView, NSView, and CALayer. UIImageView's size is 100x100 and the layout is below the UINavigationBar with a margin of 10 pixels all around. UISegmentedControl is at the right of the logo image, use the remaining horizontal space with a left and right margin of 20 pixels. -
8
APNGKit
High performance and delightful way to play with APNG format in iOS
The APNGKit project is a high-performance framework for loading, displaying, and animating images in the UIKit / AppKit ecosystem (iOS, macOS, tvOS), specifically targeting the APNG (Animated PNG) image format. Unlike traditional static PNG images, APNG supports frame-by-frame animation with full-color images and transparency — yielding better visual fidelity than GIFs while remaining efficient. APNGKit offers a friendly API (e.g. APNGImage, APNGImageView) that behaves similarly to the... -
9
SwipeCellKit
Swipeable UITableViewCell/UICollectionViewCell
Introducing SwipeCellKit. A swipeable UITableViewCell based on the stock Mail.app, implemented in Swift. All source code for SwipeCellKit is available on GitHub. It includes a Demo app that copies the Mail.app Inbox interface. Left and right swipe actions. Action buttons with: text only, text + image, image only. Haptic Feedback. Customizable transitions: Border, Drag, and Reveal. Customizable action button behavior during swipe. Animated expansion when dragging past threshold. ... -
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10
Iconic
Auto-generated icon font library for iOS, watchOS and tvOS
Iconic helps make icon fonts integration effortless on iOS, tvOS and watchOS. Its main component is in charge of auto-generating strongly typed Swift code with SwiftGen, compatible with Objective-C. You will interact with an auto-generated class under the name of {FontName}Icon.swift, which is a light abstraction of the IconDrawable.swift protocol. Some open-sourced icon fonts don't include the names of each of their glyphs. This could result in a non-descriptive enum, which can make things... -
11
GPUImage 2
Framework for GPU-accelerated video and image processing
GPUImage 2 is the second generation of the GPUImage framework, an open source project for performing GPU-accelerated image and video processing on Mac, iOS, and now Linux. The original GPUImage framework was written in Objective-C and targeted Mac and iOS, but this latest version is written entirely in Swift and can also target Linux and future platforms that support Swift code. The objective of the framework is to make it as easy as possible to set up and perform realtime video processing or machine vision against image or video sources. ...
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