ID: 5d8624e7850bb704a303272e

Facenet

by SHIVAM GARG

Face Recognition Using Facenet model


License: MIT license

Tags: Computer Vision Tensorflow Facerecognition FaceEmbeddings

Ā Model stats and performance
Dataset Used VGG face
Framework Tensorflow
OS Used Linux
Publication View
Inference time in seconds per sample.

Screenshots


FACENET FOR FACE RECOGNITION

WHAT IS IT?

Facenet is a system built by Florian Schroff, Dmitry Kalenichenko, James Philbin. They wrote a paper about it as well. It directly learns a mapping from face images into a compact Euclidean space where distances directly correspond to a measure of face similarity. Once these embeddings are created then procedures like face recognition and verification can be done utilising these embeddings as features. Facenet creates a 128-dimensional embedding from images and inserts them into a feature space, in such a way, that the squared distance between all faces, regardless of the imaging conditions, of the same identity, is small, whereas the squared distance between a pair of face images from distinct characters is large.

HOW TO USE?

To run the script python run.py br1.jpg br2.jpg For help - python run.py -h

usage: run.py [-h] [--image_size IMAGE_SIZE] [--margin MARGIN]  image_files [image_files ...]

positional arguments:

image_files           Images to compare

optional arguments:

-h, --help  show this help message and exit --image_size     IMAGE_SIZE            Image size (height, width) in pixels. --margin            MARGIN                   Margin for the crop around the bounding box (height,width) in pixels.

WHAT ARE THE REQUIREMENTS?

To get all the requirements and dependencies installed run the command For GPU pip install -r gpu_requirements.txt For CPU pip install -r cpu_requirements.txt

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SHIVAM GARG
New Delhi, India
Level 41 74240 XP

2928 Profile
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A philosophy student cleverly disguised as a Coax Deep Learning engineer spending whole day, practically every day, experimenting with TensorFlow,Pytorch, and Caffe; dabbling with Python and C++; and drinking a wide variety of Coffee everyday.

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