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import torch
from diffusers import StableDiffusionPipeline
from controlnet_aux import CannyDetector, OpenposeDetector, MidasDetector
import gradio as gr
pipe = StableDiffusionPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
torch_dtype=torch.float16)
if torch.backends.mps.is_available():
device = "mps"
elif torch.cuda.is_available():
device = "cuda"
else:
device = "cpu"
pipe.to(device)
canny_detector = CannyDetector()
pose_detector = OpenposeDetector.from_pretrained("lllyasviel/ControlNet")
midas_detector = MidasDetector.from_pretrained("lllyasviel/ControlNet")
def generate_pics(prompt):
image = pipe(prompt).images[0]
canny_image = canny_detector(image)
pose_image = pose_detector(image)
depth_image = midas_detector(image)
return image, canny_image, pose_image, depth_image
gr.Interface(
fn=generate_pics,
inputs=gr.Textbox(lines=2, label="Enter your prompt"),
outputs=[
gr.Image(label="Generated Image"),
gr.Image(label="Canny"),
gr.Image(label="OpenPose"),
gr.Image(label="Depth"),
],
title="Image Generation using Stable Diffusion",
description="Enter the prompt to generate an image using Stable Diffusion"
).launch()
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