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.
OpenFace is a tool in the Facial Recognition category of a tech stack.
OpenFace is an open source tool with 13K GitHub stars and 3.3K GitHub forks. Here’s a link to OpenFace's open source repository on GitHub
Who uses OpenFace?
16 developers on StackShare have stated that they use OpenFace.
Why developers like OpenFace?
Here’s a list of reasons why companies and developers use OpenFace
- Detect faces with pre-trained models
- Transform faces for the neural network
- Use deep neural networks to reprsent or embed the face on a hypersphere
- Apply favorite clustering or classification techniques to the features to complete recognition task
OpenFace Alternatives & Comparisons
What are some alternatives to OpenFace?
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 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.
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.