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import gradio as gr
from ppdiffusers import StableDiffusionPipeline
def generate_image(model, prompt, width, height, num_inference_steps, guidance_scale):
if model == "shanshui_gen_style":
pipe = StableDiffusionPipeline.from_pretrained("megemini/shanshui_gen_style", from_hf_hub=True)
elif model == "shanshui_style":
pipe = StableDiffusionPipeline.from_pretrained("megemini/shanshui_style", from_hf_hub=True)
else:
raise
image = pipe(
prompt,
num_inference_steps=100,
guidance_scale=7.5,
height=height,
width=width,).images[0]
return image
demo = gr.Blocks()
with demo:
gr.Markdown(
r"### 【Hackathon】基于PaddleNLP PPDiffusers 训练 AIGC 趣味模型"
)
gr.Markdown(
r"""
[【Hackathon】基于PaddleNLP PPDiffusers 训练 AIGC 趣味模型](https://github.com/PaddlePaddle/community/blob/master/hackthon_4th/%E3%80%90PaddlePaddle%20Hackathon%204%E3%80%91%20%E6%A8%A1%E5%9E%8B%E5%A5%97%E4%BB%B6%E5%BC%80%E6%BA%90%E8%B4%A1%E7%8C%AE%E4%BB%BB%E5%8A%A1%E5%90%88%E9%9B%86.md#no105%E5%9F%BA%E4%BA%8Epaddlenlp-ppdiffusers-%E8%AE%AD%E7%BB%83-aigc-%E8%B6%A3%E5%91%B3%E6%A8%A1%E5%9E%8B-)
模型 ``shanshui_style`` 可以生成水墨山水画。
模型 ``shanshui_gen_style`` 可以生成水墨山水画的具像图片。
"""
)
with gr.Row():
with gr.Column():
with gr.Row():
model = gr.Dropdown(["shanshui_gen_style", "shanshui_style"], label="Model")
with gr.Row():
prompt = gr.Textbox(label='Prompt')
with gr.Row():
width = gr.Slider(128, 768, value=512, step=8, label="Width")
height = gr.Slider(128, 768, value=512, step=8, label="Height")
with gr.Row():
num_inference_steps = gr.Textbox(label='num inference steps')
guidance_scale = gr.Textbox(label='guidance scale')
with gr.Row():
btn = gr.Button(value="Run")
with gr.Column():
with gr.Row():
output = gr.Image()
gr.Examples(
[
[
"shanshui_gen_style",
"A fantasy landscape in <shanshui-gen-style>",
512,
288,
100,
7.5,
],
[
"shanshui_style",
"A fantasy landscape in <shanshui-style>",
512,
288,
100,
7.5,
],
],
[model, prompt, width, height, num_inference_steps, guidance_scale]
)
btn.click(
generate_image,
[model, prompt, width, height, num_inference_steps, guidance_scale],
output)
if __name__ == "__main__":
demo.launch(debug=True)
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