yolov8-face
anylabeling
| yolov8-face | anylabeling | |
|---|---|---|
| 2 | 6 | |
| 386 | 1,861 | |
| - | - | |
| 4.7 | 6.0 | |
| about 1 month ago | 1 day ago | |
| Python | Python | |
| GNU General Public License v3.0 only | GNU General Public License v3.0 only |
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yolov8-face
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[D] Face encoding and face clustering
Hello. Q1: I have a large collection of files from which i have to encode faces. Until now, the fastest way i've found is to use a yolov8 finetune model (https://github.com/derronqi/yolov8-face) for face detection and the face_recognition library for encoding in a 128. I've tried using deepface but it's much slower.
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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
anylabeling
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AnyLabeling Auto-labeling with MobileSAM - the newest and fastest variant of Segment Anything
Check out AnyLabeling v0.3.2 today: https://github.com/vietanhdev/anylabeling/releases/tag/v0.3.2.
- AnyLabeling - Image Labeling tool with Auto Labeling from Segment Anything + YOLOs
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labelme VS anylabeling - a user suggested alternative
2 projects | 15 Apr 2023
AnyLabeling is a desktop app for image data labeling. It is a fork of LabelMe with upgraded UI and AI-assisted labeling with Segment Anything and YOLO models.
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labelImg VS anylabeling - a user suggested alternative
2 projects | 15 Apr 2023
AnyLabeling is a desktop app for image data labeling. It is a fork of LabelMe with upgraded UI and AI-assisted labeling with Segment Anything and YOLO models.
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AnyLabeling v0.2.2 now supported all Segment Anything models (ViT-B, ViT-L, ViT-H) + YOLOv5 + YOLOv8 for auto labeling
We also fixed some bugs from the last release and improved model performance. Check out at: https://github.com/vietanhdev/anylabeling We will love to hear your feedback to improve this program. Discussion at: https://github.com/vietanhdev/anylabeling/discussions/30
- Segment Anything Demo by Meta AI
What are some alternatives?
retinaface - RetinaFace: Deep Face Detection Library for Python
autodistill - Images to inference with no labeling (use foundation models to train supervised models).
deepface - A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python
labelme - Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
yolov5-face - YOLO5Face: Why Reinventing a Face Detector (https://arxiv.org/abs/2105.12931) ECCV Workshops 2022)
segment-anything - The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Adaptive-Face-Recognition
labelImg - LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source data labeling tool for images, text, hypertext, audio, video and time-series data.
facenet-pytorch - Pretrained Pytorch face detection (MTCNN) and facial recognition (InceptionResnet) models
MobileSAM - This is the official code for MobileSAM project that makes SAM lightweight for mobile applications and beyond!
inference - A fast, easy-to-use, production-ready inference server for computer vision supporting deployment of many popular model architectures and fine-tuned models.
DIS - This is the repo for our new project Highly Accurate Dichotomous Image Segmentation