Face Recognition using Siamese Network

Dataset - http://vis-www.cs.umass.edu/lfw/

Paper - https://www.cs.cmu.edu/~rsalakhu/papers/oneshot1.pdf

Youtube Video Reffered for help Video By Nicolas

How to Use and Remarks

• I have used used Docker for the hassle free setup of the tensorflow gpu with jupyter notebook
• All the training, preprocessing and inferences are done with this.

First Create the Following folder structure

data/
├── anchor/
├── positive/
└── negative/

and

application_data/
├── input_image/
└── verification_images/

Fire up your docker container

docker compose up

1. You can run the notebook in that environment but to add the positive and anchor images you have to use imageCollector,py file on your local machine due to the fact that docker doesn't connect to hardware directly. If you are a linux user you can add "/dev/video0:/dev/video0" in the devices in docker compose file. Otherwise its much of a hassle to set it up.

2. Download the data,unzip it and move the images to desired folders using the notebook.

3. Go through the notebook for all other steps

and for verification it goes the same

Run verification.py I have configured it to run on CPU, you can change to GPU as well.