ImageStylization¶
- class agentlego.tools.ImageStylization(model='timbrooks/instruct-pix2pix', inference_steps=20, device='cuda', toolmeta=None)[源代码]
A tool to stylize an image.
- 参数:
model (str) – The model name used to inference. Which can be found in the
diffusersrepository. Defaults to ‘timbrooks/instruct-pix2pix’.inference_steps (int) – The number of inference steps. Defaults to 20.
device (str) – The device to load the model. Defaults to ‘cuda’.
toolmeta (None | dict | ToolMeta) – The additional info of the tool. Defaults to None.
默认工具信息¶
名称: ImageStylization
描述: This tool can modify the input image according to the input instruction. Here are some example instructions: “turn him into cyborg”, “add fireworks to the sky”, “make his jacket out of leather”.
输入:
image (ImageIO)
instruction (str)
输出:
ImageIO
Examples¶
Use the tool directly (without agent)
from agentlego.apis import load_tool
# load tool
tool = load_tool('ImageStylization', device='cuda')
# apply tool
image = tool('examples/demo.png', 'turn the cat into a cartoon cat')
print(image)
With Lagent
from lagent import ReAct, GPTAPI, ActionExecutor
from agentlego.apis import load_tool
# load tools and build agent
# please set `OPENAI_API_KEY` in your environment variable.
tool = load_tool('ImageStylization', device='cuda').to_lagent()
agent = ReAct(GPTAPI(temperature=0.), action_executor=ActionExecutor([tool]))
# agent running with the tool.
img_path = 'examples/demo.png'
ret = agent.chat(f'According to the image `{img_path}`, turn the cat into a cartoon cat.')
for step in ret.inner_steps[1:]:
print('------')
print(step['content'])
Set up¶
Before using this tool, please confirm you have installed the related dependencies by the below commands.
pip install -U diffusers
Reference¶
This tool uses a instruct-pix2pix model in default settings. See the following paper for details.
@article{brooks2022instructpix2pix,
title={InstructPix2Pix: Learning to Follow Image Editing Instructions},
author={Brooks, Tim and Holynski, Aleksander and Efros, Alexei A},
journal={arXiv preprint arXiv:2211.09800},
year={2022}
}