CompreFace
facenet
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CompreFace | facenet | |
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28 | 5 | |
3,855 | 13,479 | |
5.1% | - | |
8.3 | 0.0 | |
26 days ago | 9 months ago | |
Java | Python | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
CompreFace
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Double-Take not getting enough events/images from Frigate?
# https://github.com/exadel-inc/CompreFace/blob/master/docs/Face-services-and-plugins.md)
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DeepStack (dead?) vs CompreFace (slow?)
I looked at Double Take (UI that lets you do the training of your face recondition easily) and found CompreFace as one of models they support. It looks like what I need but there is a catch... no OpenVino (intel CPUs AI accelerator) support. I really like my low power NVR setup and would like keep it that way. Running AI on CPU without acceleration is both power inefficient and much slower. I have a spare low end GPU but if dump it in the system the current AI acceleration brakes... (I know I can prob fix it but that is a rabbit hole I would prefer to avoid).
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self Hosted face recognition software
This has good UI and also good recognition: https://github.com/exadel-inc/CompreFace
- Do we have good, gpu accelerated, text-to-speech, speech-to-text, image/video-to-text face/object recognition that is open source and self-hosted ?
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need help installing a software in Ubuntus terminal
wget -q -O tmp.zip 'https://github.com/exadel-inc/CompreFace/releases/download/v1.1.0/CompreFace_1.1.0.zip' && unzip tmp.zip && rm tmp.zip
- Face comparison in Stable Diffusion
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security camera advice
https://github.com/exadel-inc/CompreFace/ Is already a good locally-run API for face detection and facial recognition. Thankyou for your suggestion.
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hey guys which is the best tool for making facial recognition using single image in deep learning
If you are looking for open source stuff and are able to self-host it, maybe have a look at CompreFace.
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The CompreFace 1.1. Release: What’s New?
As almost always, on GitHub https://github.com/exadel-inc/CompreFace
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Working with facial recognition
Looking into this I found Compreface (https://exadel.com/solutions/compreface/) an open source face recognition software. There are alread some controb scripts, like contrib/photils.lua, who take some images, run them through a tool, then tag them with data coming from the tool. Converting this to use Compreface looks likea promising avenue.
facenet
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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
What are some alternatives?
double-take - Unified UI and API for processing and training images for facial recognition.
insightface - State-of-the-art 2D and 3D Face Analysis Project
frigate - NVR with realtime local object detection for IP cameras
deepface - A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
Home Assistant - :house_with_garden: Open source home automation that puts local control and privacy first.
Face Recognition - The world's simplest facial recognition api for Python and the command line
DeepStack - The World's Leading Cross Platform AI Engine for Edge Devices
anime-face-detector - Anime Face Detector using mmdet and mmpose
librephotos - A self-hosted open source photo management service. This is the repository of the backend.
facenet-pytorch - Pretrained Pytorch face detection (MTCNN) and facial recognition (InceptionResnet) models