AIML-Human-Attributes-Detection-with-Facial-Feature-ExtractionThis is a Human Attributes Detection program with facial features extraction. It detects facial coordinates using FaceNet model and uses MXNet facial attribute extraction model for extracting 40 types of facial attributes. This solution also detects Emotion, Age and Gender along with facial attributes.
Stars: ✭ 48 (+108.7%)
11K-HandsTwo-stream CNN for gender classification and biometric identification using a dataset of 11K hand images.
Stars: ✭ 44 (+91.3%)
age-and-genderPredict Age and Gender of people from images | Determination of gender and age
Stars: ✭ 68 (+195.65%)
WreckFaceAppAndroid application for gender, age and face recognition using OpenCV and JavaCV libraries
Stars: ✭ 21 (-8.7%)
pytorch-DEXPytorch implementation of DEX: Deep EXpectation of apparent age from a single image
Stars: ✭ 61 (+165.22%)
javacv-cnn-exampleA example to demonstrate the usage of JavaCV and CNN for gender and age recognition
Stars: ✭ 24 (+4.35%)
voice gender detection♂️♀️ Detect a person's gender from a voice file (90.7% +/- 1.3% accuracy).
Stars: ✭ 51 (+121.74%)
face age genderCan we predict the age and gender of someone given a picture of their face ?
Stars: ✭ 40 (+73.91%)
name2genderExtrapolate gender from first names using Naïve-Bayes and PyTorch Char-RNN
Stars: ✭ 24 (+4.35%)
UHV-OTS-SpeechA data annotation pipeline to generate high-quality, large-scale speech datasets with machine pre-labeling and fully manual auditing.
Stars: ✭ 94 (+308.7%)
Face Api.jsJavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js
Stars: ✭ 13,258 (+57543.48%)
FreeSRA Free Library for Speaker Recognition (Verification),implemented by ncnn.
Stars: ✭ 21 (-8.7%)
genderizePython client for the Genderize.io web service.
Stars: ✭ 59 (+156.52%)
namsor-python-sdk2NamSor API v2 Python SDK - classify personal names accurately by gender, country of origin, or ethnicity.
Stars: ✭ 23 (+0%)
multi-task-learningMulti-task learning smile detection, age and gender classification on GENKI4k, IMDB-Wiki dataset.
Stars: ✭ 154 (+569.57%)