facenet-pytorch
Real-time-GesRec
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facenet-pytorch | Real-time-GesRec | |
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4 | 1 | |
4,144 | 590 | |
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3.8 | 0.0 | |
19 days ago | over 1 year ago | |
Python | Python | |
MIT License | MIT License |
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facenet-pytorch
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[D] Fast face recognition over video
Hijacking this comment because i've been working nonstop on my project thanks to your suggestion. I'm now using this https://github.com/derronqi/yolov8-face for face detection and still the old face_recognition for encodings. I'm clustering with dbscan and extracting frames with ffmpeg with -hwaccel on. I'm planning to try this: https://github.com/timesler/facenet-pytorch as it looks like it would be the fastest thing avaiable to process videos? Keep in mind i need to perform encoding other than just detection because i want to use DBscan (and later also facial recognition, but this might be done separately just by saving the encodings). let me know if you have any other suggestions, and thanks again for your help
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Random but unrepeated combinations?
For now, I am trying to evaluate and get the accuracy of the FaceNet module. Like this example on facenet-pytorch, getting the accuracy relies on this file (pairs.txt) provided by the official site. Format description below:
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Need to watch through 100s of hours of surveylance footage - AI solution?
with some python knowledge you can try a two step procedure: 1) extract a number of frames per second, for example five frames (images, i.e. still frames) per second using opencv or ffmpeg 2) Using facenet: detect faces in frames and then classify them by comparing each image to a known image of the person you are looking for.
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Query regarding Multiple face recognization system
It's generally better to split the task into a multiple tasks. First I'd want to detect and extract faces. There are a number of pretrained models that you could use for that, e.g. https://github.com/timesler/facenet-pytorch, https://github.com/opencv/opencv/tree/master/data/haarcascades. Once you've extracted faces, you can train a facial recognition using something like a siamese network as you normally would.
Real-time-GesRec
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How to setup gesture recognition on the Nano?
I'm pretty new to the Nano and AI in general, but I'm currently working on a school project that requires me to use the Nano. I was wondering how if there are any good tutorials on how to setup the Nano and it's IMX219 camera so that it can recognize gestures. One of the datasets is this: https://github.com/ahmetgunduz/Real-time-GesRec. Thank you in advanced!
What are some alternatives?
anime-face-detector - Anime Face Detector using mmdet and mmpose
EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
CompreFace - Leading free and open-source face recognition system
awesome-colab-notebooks - Collection of google colaboratory notebooks for fast and easy experiments
OpenCV - Open Source Computer Vision Library
trt_pose_hand - Real-time hand pose estimation and gesture classification using TensorRT
pytorch2keras - PyTorch to Keras model convertor
trt_pose - Real-time pose estimation accelerated with NVIDIA TensorRT
facenet - Face recognition using Tensorflow
iSeeBetter - iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press
DeepFake-Detection - Towards deepfake detection that actually works
OpenSeeFace - Robust realtime face and facial landmark tracking on CPU with Unity integration