Skip to content
#

face-detection

Here are 3,390 public repositories matching this topic...

Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.

  • Updated Jun 1, 2022
  • Python

papers about Face Detection; Face Alignment; Face Recognition && Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution && Face Deblurring; Face Generation && Face Synthesis; Face Transfer; Face Anti-Spoofing; Face Retrieval;

  • Updated May 30, 2022

TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.

  • Updated Jun 1, 2022
  • C++

Javascript/WebGL lightweight face tracking library designed for augmented reality webcam filters. Features : multiple faces detection, rotation, mouth opening. Various integration examples are provided (Three.js, Babylon.js, FaceSwap, Canvas2D, CSS3D...).

  • Updated May 2, 2022
  • JavaScript
kamathhrishi
kamathhrishi commented Jun 27, 2019

The current examples are in the form of scripts. To make easier and more interactive for users of the library it would help to have notebooks demonstrating these examples. For now the notebooks would go under examples folder under branch 2.0 where porting to Python 3+ is happening.

good first issue
DefTruth
DefTruth commented Feb 13, 2022

这个issue主要讲一下,如何把你自己的模型添加到lite.ai.toolkit。lite.ai.toolkit集成了一些比较新的基础模型,比如人脸检测、人脸识别、抠图、人脸属性分析、图像分类、人脸关键点识别、图像着色、目标检测等等,可以直接用到具体的场景中。但是,毕竟lite.ai.toolkit的模型还是有限的,具体的场景下,可能有你经过优化的模型,比如你自己训了一个目标检测器,可能效果更好。那么,如何把你的模型加入到lite.ai.toolkit中呢?这样既能用到lite.ai.toolkit一些已有的算法能力,也能兼容您的具体场景。这个issue主要是讲这个问题。大家有疑惑的可以提在这个issue,我会尽可能回答~

good first issue

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.

  • Updated Jun 14, 2021
  • Jupyter Notebook

Improve this page

Add a description, image, and links to the face-detection topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the face-detection topic, visit your repo's landing page and select "manage topics."

Learn more