This is a demonstration of a face search system

Work flows:

• Detect faces from the images
• Crop the face to 224x224 pixels
• Align the face
• Feed face images through a feature extractor (I use vgg face feature extractor)
• Save the vector representations into database along with images names and url
• Queries run very fast thanks to Postgres's CUBE extension

This demo works on Ubuntu 16.04 LTS with Python 2.7, my laptop details:

• CPU: Intel core i5-4210U @1.7GHz
• RAM: 8GB DDR3
• GPU: NVIDIA GTX 840M

Details instruction: https://gist.github.com/trungkak/a934e92b3829a025f98a0b3419fad2da

Details instruction: https://gist.github.com/trungkak/3d9d0c1b9dda91623488a5e4a3373053

Details instruction: https://www.digitalocean.com/community/tutorials/how-to-install-and-use-postgresql-on-ubuntu-16-04

Get into src directory

cd /src

Open .env file then enter your config (DBName, USER, PASSWORD)

vi .env

To do things from scratch, download a face dataset like LFW (http://vis-www.cs.umass.edu/lfw/)

cd ../images
wget http://vis-www.cs.umass.edu/lfw/lfw-funneled.tgz
tar zxvf lfw-funneled.tgz

To index your images data, use:

python app.py -path <path-to-your-images-directory>

To identify a person, use:

python app.py -image <path-to-your-image>

To get help, use:

python app.py -h

• Deep Face Recognition: Link
• Face search at scale, 80 million gallery: Link

• Trung Le Hoang (trungkak@gmail.com)