An open-source iOS camera library that simplifies camera integration with high performance and built-in features.
CameraKit is an iOS library that helps developers add reliable camera functionality to their apps quickly. It provides a consistent camera platform with scalable service and extensive customization possibilities, making complex camera operations straightforward.
iOS developers building apps that require camera features, such as photo/video capture, face detection, or custom camera sessions, particularly those working in Swift or Objective-C.
Developers choose CameraKit because it abstracts the complexities of the iOS Camera API, offering automatic handling of permissions, preview scaling, and orientation, along with built-in tools like face detection and tap to focus, saving development time.
Library for iOS Camera API. Massively increase performance and ease of use within your next iOS Project.
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CameraKit automatically manages system permissions, preview scaling, and output orientation, reducing boilerplate code for developers as highlighted in the README.
Includes face detection, overlay grid, tap to focus, pinch to zoom, flash toggle, and camera position toggle, providing out-of-the-box functionality for common camera needs.
Fully compatible with Objective-C projects, allowing seamless integration without requiring Swift, as confirmed in the README's import instructions.
Allows extending and creating custom camera sessions for tailored functionality, such as setting custom resolutions and frame rates, enabling advanced use cases.
Supports image and video capture within the same preview session, simplifying development for multi-media apps as demonstrated in the code samples.
Camera functionality cannot be fully tested on iOS simulators, requiring a physical device for development and debugging, which slows down the testing process.
Installation requires Cocoapods or Carthage, adding complexity for projects not using these dependency managers or those preferring Swift Package Manager.
Primarily designed for UIKit with no mention of SwiftUI support, limiting its use in modern SwiftUI-based apps without additional wrapping code.
While it covers basics, it lacks built-in support for real-time filters, AR integration, or custom video processing pipelines, requiring extensions for such needs.