README.md

---
title: Face Recognition
emoji: 🖼
colorFrom: purple
colorTo: red
sdk: gradio
sdk_version: 5.0.1
app_file: app.py
pinned: false
license: mit
short_description: Trained model to recognize faces
startup_duration_timeout: 2h
---

---
license: mit
---

# Face Recognition Model
"CSSE416-final-project/face-recognition" is the Hugging Face (HF) repository for the Face Recognition Application. It runs the HF faceRecogModel


## Files
- app.py
  - App code to take-in an image, process it, feed it into the model, and format its outputs.
- face_detection.py
  - Crops group photos into various individual person photos to feed into the model
- celeb_indicies.py
  - List of all the celebrities our model can identify (used to match output index of model to celebrity name)
- dlib-19.24.99-cp310-cp310-linux_x86_64.whl
  - Pre-compiled dlib library needed to use the face-recognition library, which identifies and extracts the faces in the images we upload.
- DS_Store
- Arial Bold.ttf
- requirements.txt
  - Standard file used by the HF Space to determine which libraries it needs.

## Datasource
  - Upload your image via camera, clipboard (copy and pasting), or dragging and dropping a picture file into the UI
  - For large scale testing, check out the model itself

## Neccessary Package
  - Since the model all runs on Hugging Face, you don't need to install any packages.
  - However, if you do want to run the model locally, you will need to install these following packages:
      - pillow
      - gradio
      - numpy
      - diffusers
      - torchvision
      - torch
      - huggingface_hub
      - typing
      - accelerate
      - invisible_watermark
      - transformers
      - xformers
      - face-recognition

## Running
  - The app runs the model out of the box by simple visiting the URL for the HF Space.
  - Alternatively, if you want to test the model locally, you can download the repo and run "app.py"