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)
