Face Recognition
Dlib
Face++
Amazon Rekognition
Hiface
Smart Face Detector
Face It
Kairos
Scikit Image
OpenCV
Microsoft Computer Vision API
Amazon Rekognition
Microsoft Video API
Clarifai
SimpleCV
Cloudinary
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Based on our record, Face Recognition should be more popular than Scikit Image. It has been mentiond 14 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.
Did you look at egoblur? Its a lot more effective at face detection than https://github.com/ageitgey/face_recognition granted, you'd have to do your own face matching to do exception. - Source: Hacker News / about 1 year ago
Syncthing, python face_recognition [1], a static gallery (sigal [2]), and a few lines of bash and its fully automatic. I can even share links with family. [1] https://github.com/ageitgey/face_recognition. - Source: Hacker News / over 1 year ago
Camera connected to a PI? Something like this could run locally: https://github.com/ageitgey/face_recognition. Source: over 2 years ago
One of the most common challenges is the black-box problem, when the pipeline becomes too complex to understand it would happen. This can make it difficult to identify issues with the system or to understand why it isn't working as we expected or make accurate predictions that saiwa company find out the solution for Face Recognition. Another challenge is the time required for organizations to deploy a machine... Source: about 3 years ago
Second link is an easy to implement python library is you want to build it yourself Https://github.com/ageitgey/face_recognition. Source: about 3 years ago
We will use the Hugging Face transformers and diffusers libraries for inference, FiftyOne for data management and visualization, and scikit-image for evaluation metrics. - Source: dev.to / over 2 years ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / over 2 years ago
This is a good cv deep learning book with python examples https://www.manning.com/books/deep-learning-for-vision-systems. If you're pretty comfortable with the concepts of traditional image processing this is a good companion to cv2 (so you don't have to reinvent the wheel) https://scikit-image.org/. Source: over 3 years ago
Also, don't know if you're familiar with Python, but if you need ideas for to implement for future directions : https://scikit-image.org/. Source: almost 4 years ago
There's probably something in scikit-image to do what you want, or close enough to build on. Source: over 4 years ago
Dlib - Dlib is a modern C++ toolkit containing machine learning algorithms & tools for creating complex software in C++ to solve real world problem
OpenCV - OpenCV is the world's biggest computer vision library
Face++ - API for face detection โ also detects gender, age, pose
Microsoft Computer Vision API - Extract rich information from images and analyze content with Computer Vision, an Azure Cognitive Service.
Amazon Rekognition - Add Amazon's advanced image analysis to your applications.
Hiface - Hiface is a facial simulation app that lets you decide what makeup or style suits you.