wjmcat's picture
create app.py
934409f
raw history blame
No virus
2.94 kB
import os
import requests
from uuid import uuid4
from PIL import Image
import gradio as gr
def gen_image(prompt: str):
"""generate the image from the chinese stable diffusion model of paddlenlp server
Args:
prompt (str): the source of the prompt
"""
if not prompt:
return
access_token = os.environ['token']
url = f"https://aip.baidubce.com/rpc/2.0/nlp-itec/poc/stable_diffusion?access_token={access_token}&text={prompt}"
content = requests.get(url).content
cache_dir = 'images'
os.makedirs(cache_dir, exist_ok=True)
tempfile = os.path.join(cache_dir, f'{str(uuid4())}.png')
with open(tempfile, 'wb') as f:
f.write(content)
image = Image.open(tempfile)
os.remove(tempfile)
return [image]
def read_content(file_path: str) -> str:
"""read the content of target file
"""
with open(file_path, 'r', encoding='utf-8') as f:
content = f.read()
return content
block = gr.Blocks(css=read_content('assets/style.css'))
examples = [
'贝尼·赖特森、丹·蒙福德、亚伦·霍尔基的黑白血腥维多利亚小镇夜景特写街景,恐怖,月亮升起,交叉阴影,高对比度,超精细,极简主义构图,4k',
'马头雕塑插图印刷,超精细,丹·蒙福德,亚伦·霍基,高对比度,低聚合风格',
'一只熊从篝火旁的冰箱里偷食物,黑白雕刻版画,交叉影线',
'厚涂层油画《悲伤男孩的特写肖像》,本·科迪,希卡里·希莫达'
]
with block:
gr.HTML(read_content("assets/header.html"))
gr.Markdown("[![Stargazers repo roster for @PaddlePaddle/PaddleNLP](https://reporoster.com/stars/PaddlePaddle/PaddleNLP)](https://github.com/PaddlePaddle/PaddleNLP)")
with gr.Group():
with gr.Box():
with gr.Row().style(mobile_collapse=False, equal_height=True):
text = gr.Textbox(
label="Prompt",
show_label=False,
max_lines=1,
placeholder="输入中文,生成图片",
).style(
border=(True, False, True, True),
rounded=(True, False, False, True),
container=False,
)
btn = gr.Button("Generate image").style(
margin=False,
rounded=(False, True, True, False),
)
gallery = gr.Gallery(
label="Generated images", show_label=False, elem_id="gallery"
).style(grid=[1, 1], height="auto")
gr.Examples(examples=examples, fn=gen_image, inputs=text, outputs=gallery)
text.submit(gen_image, inputs=text, outputs=gallery)
btn.click(gen_image, inputs=text, outputs=gallery)
gr.Image('./assets/paddlenlp-preview.jpeg')
gr.HTML(read_content("assets/footer.html"))
block.queue(concurrency_count=5).launch(debug=True)