Developer Laboratory vs ScanKit

iOS Technical Sharing (APP icon creation, imitation of WeChat Moments, imitation of WeChat image viewer, preventing @mentions on Sina Weibo, imitation of Alipay password prompt, imitation of Post Circle, tags, JS interaction + WK, loading web pages, adaptive cell height, embedding video player in TableView to prevent lag, custom beautiful popups, address selection, time selection, color selection, custom navigation control, carousel, QR code scanning, facial tracking, custom camera, ID card photo capture, iOS media player, AVPlayer encapsulation, dropdown selection popup, Snake game, marquee, adaptive height for TableView, native image download caching, folder operations, database operations, third-party login, sharing, payment, Apple installation agreement, data transfer between apps, acknowledgments for support) https://github.com/HansenCCC/YPLaboratory YPLaboratory is the source code for this project. If you want to see how it's implemented, you can click to view the source code. https://github.com/HansenCCC/YPUIKit-ObjC YPUIKit-ObjC is the framework for this project, providing many out-of-the-box functionalities. It includes in-app purchases, subscriptions, prompt dialogs, app info, user agent retrieval, device info, unique identifiers (persistent even after deletion), badges, useful buttons, common categories, MD5, hooks, regular expressions, hashed colors, image matrices, black-and-white images, base64 images, navigation settings, handy input fields, file management, floating draggable buttons, single-line input, multi-line input, loading dialogs, custom dialogs, local logs, marquee, waterfall flow, carousel, image preview, and more.

IDEA ScanKit facilitates the extraction of extensive spatiotemporal data from Apple devices with LiDAR Scanners in order to enable researchers to perform external processing with data that would otherwise be only accessible through custom apps. DATA According to the users' selection, raw data is collected in form of RGB videos of a specified quality, ARKit depth data, and ARKit confidence data. QRCodes can be detected and ARWorldMap information from ARKit can also be directly saved to disk in a JSON format. Point clouds are generated automatically on the fly and are saved in the .las file format.