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This repository contains the implementation of a real-time human gender detection application using an optimized Darknet Library. For accurate detection of faces closer or farther from the camera, YOLOv3 architecture is used. It was trained on a modified FDDB dataset

C++ 36.90% Cuda 6.64% C 55.57% Perl 0.35% Python 0.54%
face-detection gender-classification convolutional-neural-networks darknet yolov3 fddb gpu cuda cudnn opencv visual-studio deep-learning

real-time-human-gender-detection's Introduction

Real-Time-Human-Gender-Detection

This repository contains the implementation of a real-time face detector and gender classifier using an optimized Darknet Library. This optimized version of the darknet library was created for inference only. For accurate detection of faces closer or farther from the camera, the model was created by applying transfer learning using YOLOv3, and training on a modified FDDB dataset.

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