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Based on our record, PyTorch seems to be a lot more popular than Google ARCore. While we know about 106 links to PyTorch, we've tracked only 8 mentions of Google ARCore. 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.
I don't know houw you would do it on ios but you should be able to do it on android if the phone supports it with.this library from google: https://developers.google.com/ar. Source: 11 months ago
If you have any control on the choice of the source/webcam, I'd recommend using a camera that can sense depth from the start (lidar cameras, like Intel RealSense if you are building something like a commercial robot; or a consumer device with lidar capabilities like iPad Pros since 2020, because they come with SDKs to do what you want from the start. E.g. https://developer.apple.com/augmented-reality/arkit/ or... Source: about 2 years ago
You guys are right that Unity doesn't support building for arm64 Linux. It looks like the op could potentially install Android on the Raspberry Pi, which may allow them to run Android APKs built with Unity. However, AR Core is needed in order for Unity's AR functionality to work, and I suspect it would take additional work to get AR Core working on the Pi with an external camera and gyroscope. Source: about 2 years ago
If the phone doesn't support ARCore, then you would have to implement all of the world / surface detection yourself inside your application code, which is very difficult problem to solve. Source: over 2 years ago
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 2 years ago
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more... - Source: dev.to / 12 days ago
*My post explains Dot, Matrix and Element-wise multiplication in PyTorch. - Source: dev.to / about 2 months ago
Import torch # we use PyTorch: https://pytorch.org Data = torch.tensor(encode(text), dtype=torch.long) Print(data.shape, data.dtype) Print(data[:1000]) # the 1000 characters we looked at earlier will to the GPT look like this. - Source: dev.to / 2 months ago
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries. - Source: dev.to / about 2 months ago
Which label applies to a tool sometimes depends on what you do with it. For example, PyTorch or TensorFlow can be called a library, a toolkit, or a machine-learning framework. - Source: dev.to / about 2 months ago
Vuforia SDK - Vuforia is a vision-based augmented reality software platform.
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Apple ARKit - A framework to create Augmented Reality experiences for iOS
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
ARToolKit - The world's most widely used tracking library for augmented reality.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.