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Facenet Alternatives
Similar projects and alternatives to facenet
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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deepface
A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
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facenet-pytorch
Pretrained Pytorch face detection (MTCNN) and facial recognition (InceptionResnet) models
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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face-api
FaceAPI: AI-powered Face Detection & Rotation Tracking, Face Description & Recognition, Age & Gender & Emotion Prediction for Browser and NodeJS using TensorFlow/JS
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DeepCamera
Open-Source AI Camera. Empower any camera/CCTV with state-of-the-art AI, including facial recognition, person recognition(RE-ID) car detection, fall detection and more
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better facenet alternative or higher similarity.
facenet reviews and mentions
Posts with mentions or reviews of facenet.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-05-07.
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CompreFace - Free and open-source self-hosted face recognition system from Exadel
As for me, openface is already outdated - the latest release was in 2016. If you look for a library, the easiest to use is ageitgey/face_recognition. The more accurate libraries are davidsandberg/facenet and deepinsight/insightface.
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Facial recognition using cluster
ML training is practically impossible on micro-controllers. Inferencing on the other hand is quite doable, especially if aided by a [TPU coprocessor](https://coral.ai/products/accelerator/). Supposedly with the TPU you can do some quantization-aware training, but I haven't tried this. I am working on a security system that does facial recognition to recognize me and some friends and considers anyone else as an intruder. How I am doing this is by retraining [Facenet](https://github.com/davidsandberg/facenet) with my facial embeddings. Use something like Haar Cascade in OpenCV to get the bounding box for a face and put it through the model to extract face embeddings. You can then save these embeddings as a sort of databases for the faces you want it to recognize during the inferencing phase. After that you can impose something like a SVM classifier to say who in your face database it is. One thing I will note is that the problem is even easier if you are only concerned with one face - in which case it is technically face identification - not recognition. If that is the case, you only need to do a difference calculation between the embeddings you saved during training and the result output from inferencing. If you do end up using the TPU, you can connect to it over USB from inside a container (I only know how to do this in Docker though) too. Hope this was helpful. I am actually looking to use a k8s cluster eventually too as a sort of smart hub for my security system and other devices so I can handle much more traffic (not sure if this is overkill or not on the pi 4s).
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Man with foot up on desk in Pelosi's office at Capitol arrested
He might just be a solid techie because the scripts are freely available on github. https://github.com/davidsandberg/facenet
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A note from our sponsor - InfluxDB
www.influxdata.com | 19 Apr 2024
Stats
Basic facenet repo stats
5
13,479
0.0
9 months ago
davidsandberg/facenet is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of facenet is Python.
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