# Image Captioning with ExpansionNet v2

*author: David Wang*


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## Description

This operator generates the caption with [ExpansionNet v2](https://arxiv.org/abs/2208.06551) which describes the content of the given image. ExpansionNet v2 introduces the Block Static Expansion which distributes and processes the input over a heterogeneous and arbitrarily big collection of sequences characterized by a different length compared to the input one. This is an adaptation from [jchenghu/ExpansionNet_v2](https://github.com/jchenghu/expansionnet_v2).


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## Code Example

Load an image from path './image.jpg' to generate the caption. 

*Write a pipeline with explicit inputs/outputs name specifications:*
```python
from towhee import pipe, ops, DataCollection


p = (
    pipe.input('url')
    .map('url', 'img', ops.image_decode.cv2_rgb())
    .map('img', 'text', ops.image_captioning.expansionnet_v2(model_name='expansionnet_rf'))
    .output('img', 'text')
)

DataCollection(p('./image.jpg')).show()
```
<img src="./tabular.png" alt="result2" style="height:60px;"/>


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## Factory Constructor

Create the operator via the following factory method

***expansionnet_v2(model_name)***

**Parameters:**

​   ***model_name:*** *str*

​   The model name of ExpansionNet v2. Supported model names: 
- expansionnet_rf    

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## Interface

An image captioning operator takes a [towhee image](link/to/towhee/image/api/doc) as input and generate the correspoing caption.


**Parameters:**

​	***data:*** *towhee.types.Image (a sub-class of numpy.ndarray)* 

​  The image to generate caption.

**Returns:** *str*

​   The caption generated by model.