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from diffusers import StableDiffusionPipeline, DDIMScheduler
import gradio as gr
import torch
stable_model_list = [
"runwayml/stable-diffusion-v1-5",
"stabilityai/stable-diffusion-2",
"stabilityai/stable-diffusion-2-base",
"stabilityai/stable-diffusion-2-1",
"stabilityai/stable-diffusion-2-1-base"
]
stable_inpiant_model_list = [
"stabilityai/stable-diffusion-2-inpainting",
"runwayml/stable-diffusion-inpainting"
]
stable_prompt_list = [
"a photo of a man.",
"a photo of a girl."
]
stable_negative_prompt_list = [
"bad, ugly",
"deformed"
]
def stable_diffusion_text2img(
model_path:str,
prompt:str,
negative_prompt:str,
guidance_scale:int,
num_inference_step:int,
height:int,
width:int,
):
pipe = StableDiffusionPipeline.from_pretrained(
model_path,
safety_checker=None,
torch_dtype=torch.float16
).to("cuda")
pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)
pipe.enable_xformers_memory_efficient_attention()
images = pipe(
prompt,
height=height,
width=width,
negative_prompt=negative_prompt,
num_inference_steps=num_inference_step,
guidance_scale=guidance_scale,
).images
return images[0]
def stable_diffusion_text2img_app():
with gr.Tab('Text2Image'):
text2image_model_path = gr.Dropdown(
choices=stable_model_list,
value=stable_model_list[0],
label='Text-Image Model Id'
)
text2image_prompt = gr.Textbox(
lines=1,
value=stable_prompt_list[0],
label='Prompt'
)
text2image_negative_prompt = gr.Textbox(
lines=1,
value=stable_negative_prompt_list[0],
label='Negative Prompt'
)
with gr.Accordion("Advanced Options", open=False):
text2image_guidance_scale = gr.Slider(
minimum=0.1,
maximum=15,
step=0.1,
value=7.5,
label='Guidance Scale'
)
text2image_num_inference_step = gr.Slider(
minimum=1,
maximum=100,
step=1,
value=50,
label='Num Inference Step'
)
text2image_height = gr.Slider(
minimum=128,
maximum=1280,
step=32,
value=512,
label='Image Height'
)
text2image_width = gr.Slider(
minimum=128,
maximum=1280,
step=32,
value=768,
label='Image Height'
)
text2image_predict = gr.Button(value='Generator')
variables = {
"model_path": text2image_model_path,
"prompt": text2image_prompt,
"negative_prompt": text2image_negative_prompt,
"guidance_scale": text2image_guidance_scale,
"num_inference_step": text2image_num_inference_step,
"height": text2image_height,
"width": text2image_width,
"predict": text2image_predict
}
return variables
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