Build a Deep Facial Recognition App // Part 6 - Making Facial Recognition Predictions // #Python

Ever wanted to implement facial recognition or verification into your application? In this series you’ll learn how to build a deep facial recognition application to authenticate into an application. You’ll start off by building a model using Deep Learning with Tensorflow which replicates what is shown in the paper titled Siamese Neural Networks for One-shot Image Recognition. Once that’s all trained you’ll be able to integrate it into a Kivy app and actually authenticate! In Part 5 you’ll go through how to: 1. Making Predictions with a Siamese Neural network 2. Calculating Precision and Recall 3. Saving and reloading the model from a h5 file Get the code: Links Paper: ~rsalakhu/papers/ Labelled Faces in the Wild: Chapters: 0:00 - Start 0:28 - Explainer 1:00 - Tutorial Kickoff 2:02 - Import Metrics 4:04 - Get Data Batches 7:18 - Make Predictions 12:31 - Calculate Precision and Recall 16:3
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