README.md

---
title: Try
emoji: 🔥
colorFrom: pink
colorTo: gray
sdk: gradio
sdk_version: 4.14.0
app_file: app.py
pinned: false
license: artistic-2.0
---

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

---

---
title: Try
emoji: 🔥
colorFrom: pink
colorTo: gray
sdk: gradio
sdk_version: 4.14.0
app_file: app.py
pinned: false
license: artistic-2.0
---

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference


# Christmas

# Image Processor

## Overview

The `ImageProcessor` class is designed to overlay graphical gadgets on detected faces in an image. Using a facial detection model, it identifies faces and relevant keypoints (like the nose) and overlays pre-defined gadgets (like hats or other accessories) at appropriate positions on the face.
We are using a pretrain model for the face detection : https://github.com/google/mediapipe/blob/master/docs/solutions/face_detection.md

## Dependencies

- Python 3.x
- OpenCV (`cv2`)
- NumPy
- MediaPipe

To install these dependencies, run:

```bash
pip install numpy opencv-python mediapipe
```


## Setup

Ensure all dependencies are installed.
Place the ImageProcessor script in your project directory.
Download the gadgets folder. You can add your own. Please make sure you adapt the code if you are doing so. The code is not super robust yet.

```bash
from prototype import ImageProcessor

import cv2
import mediapipe

# Load your image
image = cv2.imread('/path/to/your/image.jpg')

# Specify the folder containing your gadgets
folder_path = 'gadgets/'

model = mediapipe.solutions.face_detection.FaceDetection(model_selection=1, min_detection_confidence=0.8)

# Create an instance of the ImageProcessor
processor = ImageProcessor(image, folder_path, model)
processor.detect_and_overlay(write = True, output = "my_edited_image")
```