# Image Embdding with DOLG
*author: David Wang*
< br / >
## Description
This operator extracts features for image with [DOLG ](https://arxiv.org/abs/2108.02927 ) which has special design for image retrieval task. It integrates local and global information inside images into compact image representations. This operator is an adaptation from [dongkyuk/DOLG-pytorch ](https://github.com/dongkyuk/DOLG-pytorch ).
< br / >
## Code Example
Load an image from path './towhee.jpg' to generate an image embedding.
*Write the pipeline in simplified style* :
```python
import towhee
towhee.glob('./towhee.jpg') \
.image_decode.cv2() \
.image_embedding.dolg(img_size=512, input_dim=3, hidden_dim=1024, output_dim=2048) \
.show()
```
< img src = "https://towhee.io/image-embedding/dolg/raw/branch/main/result1.png" alt = "result1" style = "height:20px;" / >
*Write a same pipeline with explicit inputs/outputs name specifications:*
```python
import towhee
towhee.glob['path']('./towhee.jpg') \
.image_decode.cv2['path', 'img']() \
.image_embedding.dolg['img', 'vec'](img_size=512, input_dim=3, hidden_dim=1024, output_dim=2048) \
.select['img', 'vec']() \
.show()
```
< img src = "https://towhee.io/image-embedding/dolg/raw/branch/main/result2.png" alt = "result2" style = "height:60px;" / >
< br / >
## Factory Constructor
Create the operator via the following factory method
***image_embedding.dolg(img_size=512, input_dim=3, hidden_dim=1024, output_dim=2048)***
**Parameters:**
** *img_size:*** *int*
Scaled input image size to extract embedding. The higher resolution would generate the more discriminateive feature but cost more time to calculate.
** *input_dim:*** *int*
The input dimension of DOLG module (equals pretrained cnn output dimension).
** *hidden_dim:*** *int*
The hidden dimension size, local feature branch output dimension.
** *output_dim:*** *int*
The output dimsion size, same as embedding size.
< br / >
## Interface
An image embedding operator takes a [towhee image ](link/to/towhee/image/api/doc ) as input.
It uses the pre-trained model specified by model name to generate an image embedding in ndarray.
**Parameters:**
** *img:*** *towhee.types.Image (a sub-class of numpy.ndarray)*
The decoded image data in towhee.types.Image (numpy.ndarray).
**Returns:** *numpy.ndarray*
The image embedding extracted by model.
