clementapa/CelebFaces_Attributes_Classification
This repository is related to a project of the Introduction to Numerical Imaging (i.e, Introduction à l'Imagerie Numérique in French), given by the MVA Masters program at ENS-Paris Saclay. It was entirely build from scratch and contains code in PyTorch Lightning to train and then use a neural network for image classification. We used it to create a classifier allowing semantic attributes classification of faces with the dataset CelebA-HQ.
This project helps researchers and developers working with facial image analysis to automatically categorize faces based on various semantic attributes like 'smiling' or 'bald'. You input a collection of face images, and it outputs predictions for 40 different binary facial attributes for each image. This is ideal for those building or experimenting with facial recognition and attribute classification systems.
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Use this if you need a pre-built system to classify a wide range of semantic attributes on celebrity faces or want a flexible framework to train your own multi-label image classifier.
Not ideal if you are looking for a ready-to-use, production-grade facial attribute classification API without any coding or model training.
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MIT
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Last pushed
Aug 16, 2023
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