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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