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Apple ARKit VS OpenCV

Compare Apple ARKit VS OpenCV and see what are their differences

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Apple ARKit logo Apple ARKit

A framework to create Augmented Reality experiences for iOS

OpenCV logo OpenCV

OpenCV is the world's biggest computer vision library
  • Apple ARKit Landing page
    Landing page //
    2022-06-30
  • OpenCV Landing page
    Landing page //
    2023-07-29

Apple ARKit features and specs

  • Ease of Integration
    Apple ARKit is seamlessly integrated into the iOS ecosystem, making it easier for developers to leverage existing Apple services and frameworks like SceneKit, SpriteKit, and Metal.
  • High-Quality Tracking
    ARKit provides robust tracking capabilities, including face tracking, ambient light estimation, and motion capture, which ensures a high-quality augmented reality experience.
  • Large User Base
    Targeting iOS devices means developers can reach millions of users who are likely to have hardware that supports AR experiences.
  • Consistent Hardware and Software
    iOS devices typically have consistent hardware and software environments, making it easier to predict performance and tailor AR experiences without the need for extensive optimization across varied devices.
  • Developer Support
    Apple provides extensive documentation, tutorials, and support for ARKit, making it easier for developers to get started and troubleshoot issues.

Possible disadvantages of Apple ARKit

  • Platform Limitation
    ARKit is exclusively available on iOS, which limits its use to Apple devices and excludes Android and other platforms.
  • Hardware Requirements
    Older iOS devices do not support ARKit, meaning developers must ensure their audience has relatively recent hardware capable of running AR applications.
  • Learning Curve
    While well-documented, ARKit still requires developers to learn new concepts and technologies, which can be challenging for those new to augmented reality development.
  • Resource Intensive
    ARKit applications can be resource-intensive, requiring significant processing power and battery life, which may affect the user experience on longer uses.
  • Competition
    The augmented reality space is highly competitive, with other platforms like Google's ARCore vying for developer attention, requiring developers to choose or maintain cross-platform solutions.

OpenCV features and specs

  • Comprehensive Library
    OpenCV offers a wide range of tools for various aspects of computer vision, including image processing, machine learning, and video analysis.
  • Cross-Platform Compatibility
    OpenCV is designed to run on multiple platforms, including Windows, Linux, macOS, Android, and iOS, which makes it versatile for development across different environments.
  • Open Source
    Being open-source, OpenCV is freely available for use and allows developers to inspect, modify, and enhance the code according to their needs.
  • Large Community Support
    A large community of developers and researchers actively contributes to OpenCV, providing extensive support, tutorials, forums, and continuously updated documentation.
  • Real-Time Performance
    OpenCV is highly optimized for real-time applications, making it suitable for performance-critical tasks in various industries such as robotics and interactive installations.
  • Extensive Integration
    OpenCV can easily be integrated with other libraries and frameworks such as TensorFlow, PyTorch, and OpenCL, enhancing its capabilities in deep learning and GPU acceleration.
  • Rich Collection of examples
    OpenCV provides a large number of example codes and sample applications, which can significantly reduce the learning curve for beginners.

Possible disadvantages of OpenCV

  • Steep Learning Curve
    Due to the vast array of functionalities and the complexity of some of its advanced features, beginners may find it challenging to learn and use effectively.
  • Documentation Gaps
    While the documentation is extensive, it can sometimes be incomplete or outdated, requiring users to rely on community forums or external sources for solutions.
  • Resource Intensive
    Some functions and algorithms in OpenCV can be quite resource-intensive, requiring significant processing power and memory, which can be a limitation for low-end devices.
  • Limited High-Level Abstractions
    OpenCV provides a wealth of low-level functions, but it may lack higher-level abstractions and frameworks, necessitating more hands-on coding and algorithm development.
  • Dependency Management
    Setting up and managing dependencies can be cumbersome, especially when integrating OpenCV with other libraries or on certain operating systems.
  • Backward Compatibility Issues
    With frequent updates and new versions, backward compatibility can sometimes be problematic, potentially breaking existing code when updating.

Apple ARKit videos

+ Add

Apple ARkit review | AR kit

More videos:

  • Review - IKEA PLACE: Genuine Augmented Reality furniture app using Apple ARKit

OpenCV videos

+ Add

AI Courses by OpenCV.org

More videos:

  • Review - Practical Python and OpenCV

Category Popularity

0-100% (relative to Apple ARKit and OpenCV)

Apple ARKit

OpenCV

Augmented Reality
100 100%
Augmented Reality
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
iPhone
100 100%
iPhone
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Apple ARKit and OpenCV

Apple ARKit Reviews

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OpenCV Reviews

7 Best Computer Vision Development Libraries in 2024
From the widespread adoption of OpenCV with its extensive algorithmic support to TensorFlow's role in machine learning-driven applications, these libraries play a vital role in real-world applications such as object detection, facial recognition, and image segmentation.
Source: www.labellerr.com
10 Python Libraries for Computer Vision
OpenCV is the go-to library for computer vision tasks. It boasts a vast collection of algorithms and functions that facilitate tasks such as image and video processing, feature extraction, object detection, and more. Its simple interface, extensive documentation, and compatibility with various platforms make it a preferred choice for both beginners and experts in the field.
Source: clouddevs.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
OpenCV is an open-source computer vision and machine learning software library that was first released in 2000. It was initially developed by Intel, and now it is maintained by the OpenCV Foundation. OpenCV provides a set of tools and software development kits (SDKs) that help developers create computer vision applications. It is written in C++, but it supports several...
Source: www.uubyte.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
These are some of the most basic operations that can be performed with the OpenCV on an image. Apart from this, OpenCV can perform operations such as Image Segmentation, Face Detection, Object Detection, 3-D reconstruction, feature extraction as well.
Source: neptune.ai
5 Ultimate Python Libraries for Image Processing
Pillow is an image processing library for Python derived from the PIL or the Python Imaging Library. Although it is not as powerful and fast as openCV it can be used for simple image manipulation works like cropping, resizing, rotating and greyscaling the image. Another benefit is that it can be used without NumPy and Matplotlib.
Source: towardsdatascience.com

Social recommendations and mentions

Based on our record, OpenCV should be more popular than Apple ARKit. It has been mentiond 59 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Apple ARKit mentions (6)

  • AR Software development
    Apple has quite nice page with docs at the bottom: https://developer.apple.com/augmented-reality/. Source: almost 2 years ago
  • AR news slowed down in the last days — is it the quiet before storm?
    Feels like you're grasping at straws to dismiss them. If you think lower weight, not-grainy MR, six years of a public AR SDK, far better computing units, and an existing high-quality software ecosystem are "not noticeable", I'm left wondering what you think is noticeable. Source: about 2 years ago
  • Your Augmented Reality Apps Need 3D Avatars, Here's Why
    If you're looking to build a more advanced application, there are plenty of useful resources for all major technologies. For mobile apps, the best places to get started are docs for Google ARCore and Apple ARKit. Both platforms work with popular gaming engines like Unity and Unreal Engine. - Source: dev.to / over 3 years ago
  • Matrix effect with LIDAR, Unity, and ARKit - Awesome
    ARKit is Apple's (A)ugmented (R)eality development (K)it. It takes the output from Unity and displays it in the goggles/headset the guy is wearing to see all this. Well, what a camera pointed at the display sees. Source: over 3 years ago
  • 10 Top UI/UX Design Trends For 2021
    Google and Apple have already released their augmented reality development platforms, ARCore or ARKit, enabling the seamless integration of the digital and physical worlds. - Source: dev.to / over 3 years ago
View more

OpenCV mentions (59)

  • Top Programming Languages for AI Development in 2025
    Ideal For: Computer vision, NLP, deep learning, and machine learning. - Source: dev.to / 13 days ago
  • Why 2024 Was the Best Year for Visual AI (So Far)
    Almost everyone has heard of libraries like OpenCV, Pytorch, and Torchvision. But there have been incredible leaps and bounds in other libraries to help support new tasks that have helped push research even further. It would be impossible to thank each and every project and the thousands of contributors who have helped make the entire community better. MedSAM2 has been helping bring the awesomeness of SAM2 to the... - Source: dev.to / 5 months ago
  • 20 Open Source Tools I Recommend to Build, Share, and Run AI Projects
    OpenCV is an open-source computer vision and machine learning software library that allows users to perform various ML tasks, from processing images and videos to identifying objects, faces, or handwriting. Besides object detection, this platform can also be used for complex computer vision tasks like Geometry-based monocular or stereo computer vision. - Source: dev.to / 6 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library is used for image and video processing, offering functions for tasks like object detection, filtering, and transformations in computer vision. - Source: dev.to / 7 months ago
  • Built in Days, Acquired for $20K: The NuloApp Story
    First of all, OpenCV, an open-source computer vision library, was used as the main editing tool. This is how NuloApp is able to get the correct aspect ratio for smartphone content, and do other cool things like centering the video on the speaker so that they aren't out of frame when the aspect ratio is changed. - Source: dev.to / 8 months ago
View more

What are some alternatives?

When comparing Apple ARKit and OpenCV, you can also consider the following products

Google ARCore - Google Augmented Reality SDK

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Made With ARKit - Hand-picked curation of the coolest stuff made with ARKit

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Facebook AR Studio - Facebook's developer platform for Augmented Reality

NumPy - NumPy is the fundamental package for scientific computing with Python

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