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()