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Facial Attributes Detection, Cellebrite

Abstract

Detect facial attributes & accessories on images and label them accordingly.

Challenges (at least two)

Dealing with large datasets and files
Accuracy on small attributes
Trade-off between frame per second and Accuracy/Loss (choice between DL or ML models)

Achievements (according to KPIs)

Code library with classes such as loadmodel (for pretrained models), summarize (for metrics), preprocessing ( for data augmentation and preprocess), Train…
Application using Flask with inference on images

Future project development

Training on more attributes
Generating images with unique attribute
Improving small attribute detection
Working on Neural networks to reduce the running time VS Improving performance with Machine Learning
Improving face detection models for not frontal images