facenet
arXiv2021-RIFE
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facenet | arXiv2021-RIFE | |
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5 | 21 | |
13,479 | 2,558 | |
- | - | |
0.0 | 7.9 | |
9 months ago | almost 2 years ago | |
Python | Python | |
MIT License | MIT License |
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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As for me, openface is already outdated - the latest release was in 2016.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
arXiv2021-RIFE
- I'm trying to get Flowframes for Mac, if there is such a thing?
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Cooling issue: i7 8700
RIFE Link - https://github.com/hzwer/arXiv2020-RIFE
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Official Question Thread! Ask /r/photography anything you want to know about photography or cameras! Don't be shy! Newbies welcome!
Now I see that a new model called RIFE is available: https://github.com/hzwer/arXiv2020-RIFE but I'm not sure of there are any open source frontends for it.
- These are the raw frames I got from Gaugan2, but I'll be posting modified versions in the comment section.
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Problem with points
You might be able to clean up your video frames with something like RIFE and/or Real-ESRGAN.
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I Animated half of the frames, the rest was done with a frame interpolation app. Cool right?
You mean RIFE. Dang swipe/voice dictation!
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Just a mild amount of exaggeration
That is already quickly becoming a thing. There is an AI called RIFE, which is publicly accessible for free (github repo), if you know how to use the terminal/command line, and some python you can get it working fairly easily, and it interpolates video with really good quality and efficiency.
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Raiden with Sucrose wings
The video was interpolated to 60 fps using RIFE (which explains any artifacts or distortions)
- Canon created a dual fisheye lens for a new VR video system
- VQGAN + Giger + Lovecraft + Meshuggah
What are some alternatives?
insightface - State-of-the-art 2D and 3D Face Analysis Project
DAIN - Depth-Aware Video Frame Interpolation (CVPR 2019)
deepface - A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
vapoursynth-mvtools - Motion compensation and stuff
Face Recognition - The world's simplest facial recognition api for Python and the command line
jina - ☁️ Build multimodal AI applications with cloud-native stack
CompreFace - Leading free and open-source face recognition system
ECCV2022-RIFE - ECCV2022 - Real-Time Intermediate Flow Estimation for Video Frame Interpolation
DeepStack - The World's Leading Cross Platform AI Engine for Edge Devices
Real-ESRGAN - Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
anime-face-detector - Anime Face Detector using mmdet and mmpose
DeOldify - A Deep Learning based project for colorizing and restoring old images (and video!)