OpenFace聽vs聽TensorFlow

OpenFace
OpenFace

21
71
+ 1
2
TensorFlow
TensorFlow

1.9K
1.9K
+ 1
72
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OpenFace vs TensorFlow: What are the differences?

OpenFace: Free and open source face recognition with deep neural networks. OpenFace is a Python and Torch implementation of face recognition with deep neural networks and is based on the CVPR 2015 paper FaceNet: A Unified Embedding for Face Recognition and Clustering by Florian Schroff, Dmitry Kalenichenko, and James Philbin at Google; TensorFlow: Open Source Software Library for Machine Intelligence. TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

OpenFace can be classified as a tool in the "Facial Recognition" category, while TensorFlow is grouped under "Machine Learning Tools".

OpenFace is an open source tool with 12.2K GitHub stars and 2.99K GitHub forks. Here's a link to OpenFace's open source repository on GitHub.

Advice on OpenFace and TensorFlow
Adithya Shetty
Adithya Shetty
Student at PES UNIVERSITY | 5 upvotes 2K views
Needs advice
on
TensorFlowTensorFlowPyTorchPyTorch
and
KerasKeras

I have just started learning some basic machine learning concepts. So which of the following frameworks is better to use: Keras / TensorFlow/PyTorch. I have prior knowledge in python(and even pandas), java, js and C. It would be nice if something could point out the advantages of one over the other especially in terms of resources, documentation and flexibility. Also, could someone tell me where to find the right resources or tutorials for the above frameworks? Thanks in advance, hope you are doing well!!

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    What is OpenFace?

    OpenFace is a Python and Torch implementation of face recognition with deep neural networks and is based on the CVPR 2015 paper FaceNet: A Unified Embedding for Face Recognition and Clustering by Florian Schroff, Dmitry Kalenichenko, and James Philbin at Google.

    What is TensorFlow?

    TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
    What companies use OpenFace?
    What companies use TensorFlow?

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    What tools integrate with OpenFace?
    What tools integrate with TensorFlow?
      No integrations found

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      What are some alternatives to OpenFace and TensorFlow?
      OpenCV
      OpenCV was designed for computational efficiency and with a strong focus on real-time applications. Written in optimized C/C++, the library can take advantage of multi-core processing. Enabled with OpenCL, it can take advantage of the hardware acceleration of the underlying heterogeneous compute platform.
      Rekognition API
      ReKognition API offers services for detecting, recognizing, tagging and searching faces and concepts as well as categorizing scenes in any photo, through a RESTFUL API. We process and analyze photos from anywhere, so you can mix and match photo sources with user IDs, which can enable you to, say, recognize objects in Facebook and Flickr photos.
      Kairos API
      Commercial-grade emotion analysis, face detection and recognition engine provided as a public API. Kairos takes the complexity out of facial recognition and emotion analysis so you can focus on building a great product.
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