# Image generation using Stable Diffusion

A text2image operator generates image given a text prompt.
This operator is implemented with [Huggingface Diffusers](https://github.com/huggingface/diffusers).


## Code example

```python
from towhee import pipe, ops

pipe = (
    pipe.input('prompt')
        .map('prompt', 'image', ops.text2image.stable_diffusion())
        .output('image')
)

image = pipe('an orange cat')
image.save('an_orange_cat.png')
```

<img src="./an_orange_cat.png" width="800px"/>

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## Factory Constructor

Create the operator via the following factory method:

***text2image.stable_diffusion(model_id='stabilityai/stable-diffusion-2-1', device=None)***

**Parameters:**

***model_id***: *str*

The model id in string, defaults to 'stabilityai/stable-diffusion-2-1'.

Supported model names: [pretrained diffuser models](https://huggingface.co/models?library=diffusers&sort=downloads)


***device***: *str*

The device to running model on, defaults to None.
If None, it will automatically use cuda if gpu is available.

<br />

## Interface

The operator takes a text prompt in string as input.
It loads pretrained diffuser model and generates an image.

***\_\_call\_\_(txt)***

**Parameters:**

***prompt***: *str*

​	The text in string.

**Returns**:

*PIL.Image*

​	The generated image.

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