NeuronWriter
Google ARCore
Vuforia SDK
Apple ARKit
ARToolKit
Wikitude SDK
ZapWorks
Vuforia
MAXST
TensorFlow
PyTorch
Scikit-learn
Keras
IBM Watson Studio
OpenCV
Amazon SageMaker
Pega Platform
Google ARCore TensorFlowNo Google ARCore videos yet. You could help us improve this page by suggesting one.
Google ARCore might be a bit more popular than TensorFlow. We know about 8 links to it since March 2021 and only 7 links to TensorFlow. 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
Converting the images to a tensor: Deep learning models work with tensors, so the images should be converted to tensors. This can be done using the to_tensor function from the PyTorch library or convert_to_tensor from the Tensorflow library. - Source: dev.to / about 1 year ago
So I went to tensorflow.org to find some function that can generate a CSR representation of a matrix, and I found this function https://www.tensorflow.org/api_docs/python/tf/raw_ops/DenseToCSRSparseMatrix. Source: almost 2 years ago
Can anyone offer up an explanation for why there is a performance difference, and if possible, what could be done to fix it. I'm using the installation guidelines found on tensorflow.org and installing tf2.7 through pip using an anaconda3 env. Source: almost 2 years ago
I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org. Source: about 2 years ago
I have looked at this TensorFlow website and TensorFlow.org and some of the examples are written by others, and it seems that I am stuck in RNNs. What is the best way to install TensorFlow, to follow the documentation and learn the methods in RNNs in Python? Is there a good tutorial/resource? Source: about 2 years ago
Vuforia SDK - Vuforia is a vision-based augmented reality software platform.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Apple ARKit - A framework to create Augmented Reality experiences for iOS
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
ARToolKit - The world's most widely used tracking library for augmented reality.
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.