# Face-Recognition

**Repository Path**: weiran23/Face-Recognition

## Basic Information

- **Project Name**: Face-Recognition
- **Description**: Face Recognition project in PyTorch using CNNs
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 1
- **Created**: 2020-12-10
- **Last Updated**: 2024-01-26

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Face Recognition

Face Recognition using a CNN architecture.

## Dataset

Project uses Yale dataset as a demo, but is extensible to any face recognition dataset. Download Yale Face Database from [here](http://vision.ucsd.edu/content/yale-face-database).

## Running

- Do `pip install -r requirements.txt` to install all deps.
- Get the database as mentioned above. Run `python utils.py <yale_dataset_folder> <data_folder>` to create train and val data from `yale_dataset_folder` into `data_folder`.
- Run `giftopng.sh <folder>` to convert all the images inside the subfolders of `<folder>` into pngs.
- Run using `python main.py --data <data_folder>` where `data_folder` contains folders `train` and `val` containing training and validation data respectively.
- Inside `train` and `val` folders, program expects folder for each of the labels and these folder contains samples for these labels.

## TODO

Add picture for the architecture and tune it.

## License
MIT