1243 Open source projects that are alternatives of or similar to bob

3D Passive Face Liveness Detection (Anti-Spoofing) & Deepfake detection. A single image is needed to compute liveness score. 99,67% accuracy on our dataset and perfect scores on multiple public datasets (NUAA, CASIA FASD, MSU...).

This repo contains my attempt to create a Speaker Recognition and Verification system using SideKit-1.3.1

Novoic's audio feature extraction library

🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥

Official Dynamic Graph Representation PyTorch implement for iris/face recognition

Trained speaker embedding deep learning models and evaluation pipelines in pytorch and tesorflow for speaker recognition.

Face analysis mainly based on Caffe. At this time, face analysis tasks like detection, alignment and recognition have been done.

Simple Node.js package for robust face detection and face recognition. JavaScript and TypeScript API.

MaskedFace-Net is a dataset of human faces with a correctly and incorrectly worn mask based on the dataset Flickr-Faces-HQ (FFHQ).

Face detection using deep learning.

Face-recognition using Siamese network

C# 超简单的人脸识别库。

适用于复杂场景的人脸识别身份认证系统

The world's simplest facial recognition api for Python and the command line

Implementation for <SphereFace: Deep Hypersphere Embedding for Face Recognition> in CVPR'17.

This is an implematation project of face detection and recognition. The face detection using MTCNN algorithm, and recognition using LightenenCNN algorithm.

The World's Leading Cross Platform AI Engine for Edge Devices

Look Away to Pause Youtube - Experimental Chrome Extension

HMS ML Demo provides an example of integrating Huawei ML Kit service into applications. This example demonstrates how to integrate services provided by ML Kit, such as face detection, text recognition, image segmentation, asr, and tts.

Face recognition using Tensorflow

Ordinal Regression tutorial for the International Summer School on Deep Learning 2019

This repo provides projects on deep-learning mainly using Tensorflow 2.0

Recognize 2000+ faces on your Raspberry Pi 4 with database auto-fill and anti-spoofing

📖 This guide is to help you understand the basics of the computerized image and develop computer vision projects with OpenCV. Includes Python, Java, JavaScript, C# and C++ examples.

Fingerprint recognition engine for .NET that takes a pair of human fingerprint images and returns their similarity score. Supports efficient 1:N search.

PHP-ML - Machine Learning library for PHP

Face Recognition with Transfer Learning

Compare with various detectors - s3fd, dlib, ocv, ocv-dnn, mtcnn-pytorch, face_recognition

Face model to classify gender and race. Trained on LFWA+ Dataset.

A Java application for Face Recognition under expressions, occlusions and pose variations.

Perform deep neural network based face detection and recognition in the cloud (via AWS lambda) with zero model configuration or tuning.

Insightface face detection and recognition model that just works out of the box.

AI and machine leaning-based computer vision for a robot

One-shot Learning and deep face recognition notebooks and workshop materials

python api for SeetaFaceEngine(https://github.com/seetaface/SeetaFaceEngine.git)

JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js

Pretrained Pytorch face detection (MTCNN) and facial recognition (InceptionResnet) models

Human: 3D Face Detection, Body Pose, Hand & Finger Tracking, Iris Tracking and Age & Gender Prediction

VideoView that plays video only when 👀 are open and 👦 is detected with various other features

Learn OpenCV in 4 Hours - Code used in my Python and OpenCV course on freeCodeCamp.

Instagram AI bot with face detection. It works without instagram api, need only login and password.

Marvel - Face Recognition With Android & OpenCV

Vision framework example for my article. https://medium.com/compileswift/swift-world-whats-new-in-ios-11-vision-456ba4156bad

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;

A collection of face related papers

AntroPy: entropy and complexity of (EEG) time-series in Python

Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].

Pytorch implementation of subband decomposition

Nextcloud app that implement a basic facial recognition system.

Feature extraction of speech signal is the initial stage of any speech recognition system.

python speech signal processing library

A tutorial for Speech Enhancement researchers and practitioners. The purpose of this repo is to organize the world’s resources for speech enhancement and make them universally accessible and useful.

SincNet is a neural architecture for efficiently processing raw audio samples.

Pitch shifter using WSOLA and resampling implemented by Python3

This repo summarizes the tutorials, datasets, papers, codes and tools for speech separation and speaker extraction task. You are kindly invited to pull requests.

Some of the ML and DL related reading materials, research papers that I've read

State-of-the-art 2D and 3D Face Analysis Project

Self hosted alternative to Google Photos

🔉 spafe: Simplified Python Audio Features Extraction