# Inception-ResNet v1 Face Embedding Operator
*author: David Wang*
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## Description
This operator extracts embedding vector from facial image using [Inception-ResNet ](https://arxiv.org/pdf/1602.07261.pdf ). The implementation is an adaptation from [timesler/facenet-pytorch ](https://github.com/timesler/facenet-pytorch ).
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## Code Example
Extract face image embedding from './img.png'.
*Write the pipeline in simplified style* :
```python
import towhee
towhee.glob('./img.png') \
.image_decode.cv2() \
.face_embedding.inceptionresnetv1() \
.to_list()
```
*Write a same pipeline with explicit inputs/outputs name specifications:*
```python
import towhee
towhee.glob['path']('./img.png') \
.image_decode.cv2['path', 'img']() \
.face_embedding.inceptionresnetv1['img', 'vec']() \
.select['img','vec']() \
.show()
```
< img src = "https://towhee.io/face-embedding/inceptionresnetv1/raw/branch/main/result.png" alt = "result" style = "height:60px;" / >
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## Factory Constructor
Create the operator via the following factory method:
***face_embedding.inceptionresnetv1(image_size = 160)***
**Parameters:**
***image_size:*** *int*
Scaled input image size to extract embedding. The higher resolution would generate the more discriminative feature but cost more time to calculate.
supported types: `int` , default is 160.
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## Interface
A face embedding operator takes a face image as input. It extracts the embedding in ndarray.
**Parameters:**
** *img:*** *towhee.types.Image (a sub-class of numpy.ndarray)*
The input image.
**Returns:** *numpy.ndarray*
The extracted image embedding.