VPN by kean

 

Sample custom VPN client/server in Swift.

from https://github.com/kean/VPN

cartool

Export images from OS X / iOS .car CoreUI archives. Very rough code, probably tons wrong with it, but still useful.

from https://github.com/steventroughtonsmith/cartool

GPUImage

 

An open source iOS framework for GPU-based image and video processing.

http://www.sunsetlakesoftware.com/2012/02/12/introducing-gpuimage-framework

Brad Larson

http://www.sunsetlakesoftware.com

@bradlarson

contact@sunsetlakesoftware.com

Overview

The GPUImage framework is a BSD-licensed iOS library that lets you apply GPU-accelerated filters and other effects to images, live camera video, and movies. In comparison to Core Image (part of iOS 5.0), GPUImage allows you to write your own custom filters, supports deployment to iOS 4.0, and has a simpler interface. However, it currently lacks some of the more advanced features of Core Image, such as facial detection.

For massively parallel operations like processing images or live video frames, GPUs have some significant performance advantages over CPUs. On an iPhone 4, a simple image filter can be over 100 times faster to perform on the GPU than an equivalent CPU-based filter.

However, running custom filters on the GPU requires a lot of code to set up and maintain an OpenGL ES 2.0 rendering target for these filters. I created a sample project to do this:

http://www.sunsetlakesoftware.com/2010/10/22/gpu-accelerated-video-processing-mac-and-ios

and found that there was a lot of boilerplate code I had to write in its creation. Therefore, I put together this framework that encapsulates a lot of the common tasks you'll encounter when processing images and video and made it so that you don't need to care about the OpenGL ES 2.0 underpinnings.

This framework compares favorably to Core Image when handling video, taking only 2.5 ms on an iPhone 4 to upload a frame from the camera, apply a gamma filter, and display, versus 106 ms for the same operation using Core Image. CPU-based processing takes 460 ms, making GPUImage 40X faster than Core Image for this operation on this hardware, and 184X faster than CPU-bound processing. On an iPhone 4S, GPUImage is only 4X faster than Core Image for this case, and 102X faster than CPU-bound processing. However, for more complex operations like Gaussian blurs at larger radii, Core Image currently outpaces GPUImage.

License

BSD-style, with the full license available with the framework in License.txt.

Technical requirements

• OpenGL ES 2.0: Applications using this will not run on the original iPhone, iPhone 3G, and 1st and 2nd generation iPod touches
• iOS 4.1 as a deployment target (4.0 didn't have some extensions needed for movie reading). iOS 4.3 is needed as a deployment target if you wish to show live video previews when taking a still photo.
• iOS 5.0 SDK to build
• Devices must have a camera to use camera-related functionality (obviously)
• The framework uses automatic reference counting (ARC), but should support projects using both ARC and manual reference counting if added as a subproject as explained below. For manual reference counting applications targeting iOS 4.x, you'll need add -fobjc-arc to the Other Linker Flags for your application project.

General architecture

GPUImage uses OpenGL ES 2.0 shaders to perform image and video manipulation much faster than could be done in CPU-bound routines. However, it hides the complexity of interacting with the OpenGL ES API in a simplified Objective-C interface. This interface lets you define input sources for images and video, attach filters in a chain, and send the resulting processed image or video to the screen, to a UIImage, or to a movie on disk.

Images or frames of video are uploaded from source objects, which are subclasses of GPUImageOutput. These include GPUImageVideoCamera (for live video from an iOS camera), GPUImageStillCamera (for taking photos with the camera), GPUImagePicture (for still images), and GPUImageMovie (for movies). Source objects upload still image frames to OpenGL ES as textures, then hand those textures off to the next objects in the processing chain.

Filters and other subsequent elements in the chain conform to the GPUImageInput protocol, which lets them take in the supplied or processed texture from the previous link in the chain and do something with it. Objects one step further down the chain are considered targets, and processing can be branched by adding multiple targets to a single output or filter.

For example, an application that takes in live video from the camera, converts that video to a sepia tone, then displays the video onscreen would set up a chain looking something like the following:

GPUImageVideoCamera -> GPUImageSepiaFilter -> GPUImageView

Adding the static library to your iOS project

Note: if you want to use this in a Swift project, you need to use the steps in the "Adding this as a framework" section instead of the following. Swift needs modules for third-party code.

Once you have the latest source code for the framework, it's fairly straightforward to add it to your application. Start by dragging the GPUImage.xcodeproj file into your application's Xcode project to embed the framework in your project. Next, go to your application's target and add GPUImage as a Target Dependency. Finally, you'll want to drag the libGPUImage.a library from the GPUImage framework's Products folder to the Link Binary With Libraries build phase in your application's target.

GPUImage needs a few other frameworks to be linked into your application, so you'll need to add the following as linked libraries in your application target:

• CoreMedia
• CoreVideo
• OpenGLES
• AVFoundation
• QuartzCore

You'll also need to find the framework headers, so within your project's build settings set the Header Search Paths to the relative path from your application to the framework/ subdirectory within the GPUImage source directory. Make this header search path recursive.

To use the GPUImage classes within your application, simply include the core framework header using the following:

#import "GPUImage.h"

As a note: if you run into the error "Unknown class GPUImageView in Interface Builder" or the like when trying to build an interface with Interface Builder, you may need to add -ObjC to your Other Linker Flags in your project's build settings.

Also, if you need to deploy this to iOS 4.x, it appears that the current version of Xcode (4.3) requires that you weak-link the Core Video framework in your final application or you see crashes with the message "Symbol not found: _CVOpenGLESTextureCacheCreate" when you create an archive for upload to the App Store or for ad hoc distribution. To do this, go to your project's Build Phases tab, expand the Link Binary With Libraries group, and find CoreVideo.framework in the list. Change the setting for it in the far right of the list from Required to Optional.

Additionally, this is an ARC-enabled framework, so if you want to use this within a manual reference counted application targeting iOS 4.x, you'll need to add -fobjc-arc to your Other Linker Flags as well.

Building a static library at the command line

If you don't want to include the project as a dependency in your application's Xcode project, you can build a universal static library for the iOS Simulator or device. To do this, run build.sh at the command line. The resulting library and header files will be located at build/Release-iphone. You may also change the version of the iOS SDK by changing the IOSSDK_VER variable in build.sh (all available versions can be found using xcodebuild -showsdks).

Adding this as a framework (module) to your Mac or iOS project

Xcode 6 and iOS 8 support the use of full frameworks, as does the Mac, which simplifies the process of adding this to your application. To add this to your application, I recommend dragging the .xcodeproj project file into your application's project (as you would in the static library target).

For your application, go to its target build settings and choose the Build Phases tab. Under the Target Dependencies grouping, add GPUImageFramework on iOS (not GPUImage, which builds the static library) or GPUImage on the Mac. Under the Link Binary With Libraries section, add GPUImage.framework.

This should cause GPUImage to build as a framework. Under Xcode 6, this will also build as a module, which will allow you to use this in Swift projects. When set up as above, you should just need to use

import GPUImage

to pull it in.

You then need to add a new Copy Files build phase, set the Destination to Frameworks, and add the GPUImage.framework build product to that. This will allow the framework to be bundled with your application (otherwise, you'll see cryptic "dyld: Library not loaded: @rpath/GPUImage.framework/GPUImage" errors on execution).

Documentation

Documentation is generated from header comments using appledoc. To build the documentation, switch to the "Documentation" scheme in Xcode. You should ensure that "APPLEDOC_PATH" (a User-Defined build setting) points to an appledoc binary, available on Github or through Homebrew. It will also build and install a .docset file, which you can view with your favorite documentation tool.

from https://github.com/BradLarson/GPUImage

Coding网站的iOS客户端项目

 CODING iOS 客户端源代码.

编译环境：Xcode-Version 8.0 (8A218a)

让项目跑起来先

项目里用到了 CocoaPods 和 Carthage，如果没有安装的话，需要先自行安装。

Clone 代码后，初次执行前，需要双击运行根目录下的bootstrap脚本。这个过程涉及到下载依赖，可能会有点久，需耐心等待。

Tip：由于用到了 submodule，所以必需要把 git 仓库 clone 到本地，而不是只点击‘下载’按钮下载 zip 文件！！！

精彩项目	任务管理	项目文档	代码托管	趣味冒泡

下面介绍一下文件的大概目录先：

    .
    ├── Coding_iOS
    │   ├── Models：数据类
    │   ├── Views：视图类
    │   │   ├── CCell：所有的 CollectionViewCell 都在这里
    │   │   ├── Cell：所有的 TableViewCell 都在这里
    │   │   └── XXX：ListView（项目、动态、任务、讨论、文档、代码）和 InputView（用于聊天和评论的输入框）
    │   ├── Controllers：控制器，对应app中的各个页面
    │   │   ├── Login：登录页面
    │   │   ├── RootControllers：登录后的根页面
    │   │   ├── MeSetting：设置信息页面
    │   │   └── XXX：其它页面
    │   ├── Images：app 中用到的所有的图片都在这里
    │   ├── Resources：资源文件
    │   ├── Util：一些常用控件和 Category、Manager 之类
    │   │   ├── Common
    │   │   ├── Manager
    │   │   ├── OC_Category
    │   │   └── ObjcRuntime
    │   └── Vendor：用到的一些第三方类库，一般都有改动
    │       ├── AFNetworking
    │       ├── AGEmojiKeyboard
    │       ├── ASProgressPopUpView
    │       ├── ActionSheetPicker
    │       ├── FontAwesome+iOS
    │       ├── MJPhotoBrowser
    │       ├── MLEmojiLabel
    │       ├── NSDate+Helper
    │       ├── NSStringEmojize
    │       ├── PPiAwesomeButton
    │       ├── QBImagePickerController
    │       ├── RDVTabBarController
    │       ├── SMPageControl
    │       ├── SVPullToRefresh
    │       ├── SWTableViewCell
    │       ├── UMENG
    │       ├── UMessage_Sdk_1.1.0
    │       ├── XGPush
    │       ├── XTSegmentControl
    │       └── iCarousel
    └── Pods：项目使用了 [CocoaPods](http://code4app.com/article/cocoapods-install-usage) 这个类库管理工具

再说下项目的启动流程：

在 AppDelegate 的启动方法中，先设置了一下 Appearance 的样式，然后根据用户的登录状态选择是去加载登录页面 LoginViewController，还是登录后的 RootTabViewController 页面。

RootTabViewController 继承自第三方库 RDVTabBarController。在 RootTabViewController 里面依次加载了 Project_RootViewController、MyTask_RootViewController、Tweet_RootViewController、Message_RootViewController、Me_RootViewController 五个 RootViewController，后续的页面跳转都是基于这几个 RootViewController 引过去的。

项目里面还有些需要注意的点

• Coding_NetAPIManager：基本上 app 的所有请求接口都放在了这里。网络请求使用的是 AFNetworking 库，与服务器之间的数据交互格式用的都是 json（与 Coding 使用的 api 一致）。

• 关于推送：刚开始是用的 友盟推送，后来又改用了 腾讯信鸽，因为要兼顾旧版本 app 的推送，所以服务器是同时保留了两套推送。但是为了确保新版本的 app 不同时收到双份相同的推送消息，所以当前代码里还存留了友盟的 sdk，用于解除推送 token 与友盟 Alias 的绑定。

• 关于 ProjectViewController：这个就是进入到某个项目之后的页面，这里包含了项目的动态、任务、讨论、文档、代码、成员各类信息，而且每类信息里面还可能会有新的分类（如‘任务’里面还分有各个成员的任务）；这个页面相当的臃肿，我对它们做了拆分，都放在视图类 Views 目录下面。 首先是把数据列表独立成了对应的 XXXListView（如 ProjectTaskListView）；然后如果需要标签切换的话，会再新建一个 XXXsView（如：ProjectTasksView），在这个视图中，上面会放一个切换栏 XTSegmentControl 显示各个标签，下面放一个 iCarousel 可以滑动显示各个标签的内容；最后这些视图都会存储在 ProjectViewController 的 projectContentDict 变量里面，根据顶部导航栏选择的类别，去显示或隐藏对应的视图。

• 关于 UIMessageInputView：这个是私信聊天的输入框。因为这个输入框好多地方都有用到（冒泡、任务、讨论的评论还有私信），所以这个输入框就写成了一个相对独立的控件，并且直接显示在了 keyWindow 里面而不是某个视图里。这里的表情键盘用的是 AGEmojiKeyboard 改写了一下。

• 关于 Emoji：这个，Coding 站点的 emoji 都是用的图片，而且服务器是不接受大部分 emoji 字符的，所以刚开始的时候 app 一直不能处理 emoji 表情；又因为没有 emoji 图片名和 emoji code 码的对应关系表，所以拖了很久都没能做好转换。直到在 github 上面找到了 NSStringEmojize 这个项目；试了一下，虽然也不能全部解析，但是大部分表情都能正确显示了，不能更感谢。

• 关于如何正确显示冒泡的内容：api 返回的数据里面，冒泡内容都是 html 格式，需要做一下预处理；其实私信、讨论里面的内容也是 html。解析 html 的类名是 HtmlMediaItem，它是先用 hpple 对 html 进行了解析，然后把对应的 media 元素和对应的位置做一个存储，显示的时候便可以根据需要来显示了。

最后说下 CocoaPods 里面用到的第三方类库

• SDWebImage：图片加载
• TTTAttributedLabel：富文本的 label，可点击链接
• RegexKitLite：正则表达式
• hpple：html 解析
• MBProgressHUD：hud 提示框
• ODRefreshControl：下拉刷新
• TPKeyboardAvoiding：有文字输入时，能根据键盘是否弹出来调整自身显示内容的位置
• JDStatusBarNotification：状态栏提示框
• BlocksKit：block 工具包。将很多需要用 delegate 实现的方法整合成了 block 的形式
• ReactiveCocoa：基于响应式编程思想的 oc 实践（是个好东西呢）

from https://github.com/Coding/Coding-iOS

Potatso_swift5

Potatso compiled with swift5 xcode 10.2.1 mojave 10.14.5.

Important

Please read this first before you do anything with this project.
In short, you need to respect the license of the project. You cannot copy the source code and publish to App Store.

---

What is it?

Potatso is an iOS client that implements custom proxies with the leverage of Network Extension framework introduced by Apple since iOS 9.

Currently, Potatso is compatible with following proxies:

• Shadowsocks
• ShadowsocksR

Subscribe Telegram Channel to get updates of Potatso.
Join Telegram Group to chat with users.

Original Author: @icodesign

Project Info

Potatso has in total 26 dependencies as following

• 20 Cocoapod dependencies
• 4 submodules dependencies via local cocoapod

The project is tested with Xcode 10.2.1 on iOS 12.3.1 device with cocoapod version 1.4.0+.
If you experienced an expected issue, try to use those versions, if still experience the problem please file the issue.

The project will be further reduced for its dependencies.

How to Build Project

Perform the following steps to be able to build the project. Be warned that you should not call pod update as newer version of pod frameworks that Potatso depends on might break building process and there will be errors.

1. git clone this project path
2. cd Potatso_swift5
3. git submodule update --init to update git submodule
4. pod install to pull down dependencies into our project
5. Open Potatso_swift5.xcworkspace then Build and Run the project.
6. Change the targets-Potaso bundle identifier (use your's),do the same to targets-PacketTunnel,targets-TodayWidget bundle
7. Change the targets-Potaso-Capabilities App Groups,iCloud,keychain Sharing,do the same to PacketTunnel,TodayWidget
8. Now your can run it on your device.

from https://github.com/Git-KevinChuang/Potatso-swift5