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import gradio as gr
from diffusers import StableDiffusionPipeline
import torch
from PIL import Image
# Load the model
model_path = "gremlin97/RemoteDiff224"
pipe = StableDiffusionPipeline.from_pretrained(model_path)
# Fixed negative prompt
fixed_negative_prompt = "weird colors, low quality, jpeg artifacts, lowres, grainy, deformed structures, blurry, opaque, low contrast, distorted details, details are low"
# Function to generate images based on input text
def generate_image(prompt):
prompt += " , 8k, best quality, high-resolution"
image = pipe(prompt=prompt, negative_prompt=fixed_negative_prompt, num_inference_steps=50, guidance_scale=7.5).images[0]
return image
# Create a Gradio interface with a submit button
iface = gr.Interface(
fn=generate_image,
inputs="text",
outputs=gr.Image(), # Initial placeholder for the image,
title="RemoteDiff224 Image Generator",
description="Stable Diffusion for Remote Sensing!",
)
# Launch the Gradio interface
iface.launch(share=True)
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