# Retinaface Face Detection (Pytorch)

Authors: wxywb

## Overview

This opertator detects faces in the images by using RetinaFace Detector[1]. It will returns the locations, five keypoints and the cropped face images from origin images. This repo is a adopataion from [2].

## Interface

```python
__call__(self, image: 'towhee.types.Image')
```

**Args:**

- image:
  - the image to detect faces.
  - supported types: towhee.types.Image

**Returns:**

The Operator returns a tupe Tuple[('boxes', numpy.ndarray), ('keypoints', numpy.ndarray), ('cropped_imgs', numpy.ndarray)])] containing following fields:

- boxes: 
  - boxes of human faces.
  - data type: `numpy.ndarray`
  - shape: (num_faces, 4)
- keypoints:
  - keypoints of human faces.
  - data type: `numpy.ndarray`
  - shape: (10)
- cropped_imgs:
  - cropped face images.
  - data type: `numpy.ndarray`
  - shape: (h, w, 3)

## Requirements

You can get the required python package by [requirements.txt](./requirements.txt).

## How it works
The `towhee/retinaface-face-detection` Operators implents the function of face detection. The example pipeline can be found in [face-embedding-retinaface-inceptionresnetv1](https://towhee.io/towhee/face-embedding-retinaface-inceptionresnetv1)

## Reference

[1]. https://arxiv.org/abs/1905.00641  
[2]. https://github.com/biubug6/Pytorch_Retinaface