face-classifier
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Face model to classify gender and race. Trained on LFWA+ Dataset.
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May 25, 2021 - Jupyter Notebook
It is a Easy, powerful and Simple face verification system.
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Aug 26, 2019 - Python
This project contains an implemented version of Face Detection using OpenCV and Mediapipe. This is a code snippet and can be used in projects.
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Oct 2, 2021 - Python
Image Style Transfer onto Real-time Smile Detected captured images
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Nov 23, 2020 - Jupyter Notebook
Solve classification of an image into face and non-face using 5 different techniques
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Sep 24, 2018 - Python
The aim of this project is to classify the faces. Olivetti Faces dataset has been used. In this dataset there are ten different images of each of 40 distinct subjects. For some subjects, the images were taken at different times, varying the lighting, facial expressions (open / closed eyes, smiling / not smiling) and facial details (glasses / no …
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Nov 26, 2019 - Jupyter Notebook
This is a self mini project that I undertook for my learning process. I have taken an episode from my favourite TV series called The Office (US) S06E01. Using this episode I have extracted images & using those images I have classified 17 characters using CV2 and Facenet Model.
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Feb 9, 2022 - Jupyter Notebook
A comparative study between 5 different binary classification techniques.
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Jul 7, 2018 - Python
AI Driven Face Recognizer Model powered by Transfer Learning
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Aug 29, 2020 - Jupyter Notebook
Face Detection and Recognition on some famous personalities
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Aug 1, 2020 - Jupyter Notebook
Face detection and recognition into 6 classes of some famous personalities.
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Aug 1, 2020 - Jupyter Notebook
Classifying by age and gender using a dataset of Northeast Asian face photos
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Mar 28, 2023 - Python
Final Project of Data Science & Algorithm Course
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May 27, 2019 - Jupyter Notebook
This repository contains a resnet-18 based face classifier. It can be used to train/test RAFD dataset.
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Aug 15, 2020 - Python
The aim of this project is to classify the faces. Olivetti Faces dataset has been used. In this dataset there are ten different images of each of 40 distinct subjects. For some subjects, the images were taken at different times, varying the lighting, facial expressions (open / closed eyes, smiling / not smiling) and facial details (glasses / no …
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Nov 26, 2019 - Jupyter Notebook
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