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Summary
The recognition is completely based on deep learning neural network and implanted using Tensorflow framework
Overview
In UiPath Attended Robot Framework you can find a TensorFlow implementation of the face recognizer described in the paper FaceNet: A Unified Embedding for Face Recognition and Clustering. The project also uses ideas from the paper Deep Face Recognition from the Visual Geometry Group at Oxford.
The framework allows you to add an extra layer of security in attended scenarios. In order to do that the robot will ask your name and to take few photos.
The model needs to be trained once, for each user that is allowed to kick start the digital assistent for sensitive processes.
Face Recognition Framework is splited in two major segments:
- Training: When the robot gets train with new photos for an existing user or a new one.
- Execution of a business process by having in front of the computer a known user.
Benefits
Published: 2020-02-26T07:07:00+00:00 | Updated: 2020-12-11T05:11:08+00:00
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License
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Tags
tensorflow
deep learning
python
attended
robot
Compatibility
Any Windows machine with Python 3.6, pip 10.0.1. and the packages from Prerequisites/requirements.txt
Dependencies
Must have: Python 3.6 with pip 10.0.1 Tensorflow (1.4.0) Scipy (0.17.0) Scikit-learn (0.19.1) Opencv (2.4.9.1)
Documentation
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