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import gradio as gr
import spaces
from gradio_imageslider import ImageSlider
from image_gen_aux import UpscaleWithModel
from image_gen_aux.utils import load_image
# This uses https://github.com/asomoza/image_gen_aux/blob/main/src/image_gen_aux/upscalers/README.md
# Also this space has been duplicated from their official huggingface space, https://huggingface.co/spaces/OzzyGT/basic_upscaler
# They did great work, and I was happy to see them to also use my models :) I thought Id duplicate it and extend it.
# It basically made me get a pro account so I can make a Zero GPU space. And I will also upload more of my models as a model card now to use here.
# Start out with my own models. If others like kim, sirosky, and other model trainers would like their models added here, then thats great.
# I simply want them to message me first so I know that everythings okay with having their model as a selection here since they are the author of that model. If they want their model on here or not basically.
# I load models from huggingface model cards though, so the model should be hosted on huggingface.
MODELS = {
"4xNomosWebPhoto_RealPLKSR": "OzzyGT/4xNomosWebPhoto_RealPLKSR",
"4xRealWebPhoto_v4_dat2": "Phips/4xRealWebPhoto_v4_dat2",
"4xNomos2_hq_drct-l": "Phips/4xNomos2_hq_drct-l",
}
@spaces.GPU
def upscale_image(image, model_selection):
original = load_image(image)
upscaler = UpscaleWithModel.from_pretrained(MODELS[model_selection]).to("cuda")
image = upscaler(original, tiling=True, tile_width=1024, tile_height=1024)
return original, image
def clear_result():
return gr.update(value=None)
title = """<h1 align="center">Image Upscaler</h1>
<div align="center">Use this Space to upscale your images, makes use of the
<a href="https://github.com/asomoza/image_gen_aux">Image Generation Auxiliary Tools</a> library. <br> For now makes use of my self trained models, but can be extended to more models from other authors if they message me.</div>
"""
with gr.Blocks() as demo:
gr.HTML(title)
with gr.Row():
with gr.Column():
input_image = gr.Image(type="pil", label="Input Image")
model_selection = gr.Dropdown(
choices=list(MODELS.keys()),
value="4xNomos2_hq_drct-l",
label="Model",
)
run_button = gr.Button("Upscale")
with gr.Column():
result = ImageSlider(
interactive=False,
label="Generated Image",
)
run_button.click(
fn=clear_result,
inputs=None,
outputs=result,
).then(
fn=upscale_image,
inputs=[input_image, model_selection],
outputs=result,
)
demo.launch(share=False)
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