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import streamlit
from diffusers import StableDiffusionPipeline
import torch
model_id = "dream-textures/texture-diffusion"
if torch.cuda.is_available():
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")
pipe.enable_xformers_memory_efficient_attention()
else:
pipe = StableDiffusionPipeline.from_pretrained(model_id)
examplePrompt = "pbr brick wall"
streamlit.title("Texel Space Interpolation")
with streamlit.form(key="Interpolation"):
prompt = streamlit.text_input(label="Prompt", value=examplePrompt)
numSteps = streamlit.slider(label="Number of Inference steps", value=50, min_value=1, max_value=1000)
numImages = streamlit.slider(label="Number of Generated Images", value=1, min_value=1, max_value=10)
guidanceScale = streamlit.slider(label="Guidance Scale", value=7.5, min_value=0.0, max_value=100.0)
images = pipe(prompt=prompt, num_inference_steps=numSteps, num_images_per_prompt=numImages, guidance_scale=guidanceScale).images
streamlit.form_submit_button("Interpolate")
synthesizedImage = streamlit.image(images) |