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import gradio as gr
import upscaler
import os
from PIL import Image
def upscale_image(prompt,negative_prompt, rows=3,seed=0, image=None,enable_custom_sliders=False,guidance=7,iterations=50,xformers_input=False,cpu_offload_input=False,attention_slicing_input=False):
cols = rows
output_image = upscaler.upscale_image(image, int(rows), int(cols),int(seed), prompt,negative_prompt,xformers_input,cpu_offload_input,attention_slicing_input,enable_custom_sliders,guidance,iterations)
output_image_path = "result.png"
output_image.save(output_image_path)
return output_image_path
image_input = gr.inputs.Image(label="Input Image")
prompt_input = gr.inputs.Textbox(default="8k, photography, cgi, unreal engine, octane render, best quality",label="Prompt")
negative_prompt_input = gr.inputs.Textbox(default="jpeg artifacts, lowres, bad quality",label="Negative prompt")
seed_input = gr.inputs.Number(default=-1, label="Seed")
row_input = gr.inputs.Number(default=1, label="Tile grid dimension amount (number of rows and columns) - v x v")
xformers_input = gr.inputs.Checkbox(default=True,label="Enable Xformers memory efficient attention")
enable_custom_sliders = gr.inputs.Checkbox(default=False,label="(NOT RECOMMENDED) Click to enable the sliders below; if unchecked, it will ignore them and use the default settings")
cpu_offload_input = gr.inputs.Checkbox(default=True,label="Enable sequential CPU offload")
attention_slicing_input = gr.inputs.Checkbox(default=True,label="Enable attention slicing")
output_image = gr.outputs.Image(label="Output Image",type='pil')
guidance = gr.Slider(2, 15, 7, step=1, label='Guidance Scale: How much the AI influences the Upscaling.')
iterations = gr.Slider(10, 75, 50, step=1, label='Number of Iterations')
#save_png_button, save_png_halfsize_button ; I don't know how to implement them
save_png_button = gr.Button(label="Save as a PNG image") # Added this button with the save_png function
save_png_halfsize_button = gr.Button(label="Save as a PNG image (half size)") # Added this button with the save_png_halfsize function
gr.Interface(fn=upscale_image,
inputs=[prompt_input,negative_prompt_input,row_input,
seed_input,
image_input,
enable_custom_sliders,
guidance,
iterations,
xformers_input,
cpu_offload_input,
attention_slicing_input],
outputs=[output_image],
title="Stable Diffusion x4 Upscaler - Web GUI",
allow_flagging=False).launch()
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