app.py

import gradio as gr
import util
import process_image
from run_cmd import run_cmd

is_colab = util.is_google_colab()

css = '''
    .file-preview {
        overflow: hidden !important;
        margin: 5px 0 !important;
        padding: 0 10px !important;
    }

    .file-preview div div:nth-child(2) {
        flex-grow: 1 !important;
    }

    .file-preview div div:nth-child(3) {
        text-align: right !important;
    }

    #preview_img {
        user-select: none !important;
        touch-action: none !important;
        pointer-events: none !important;
    }
'''

title = "ESRGAN Upscaling With Custom Models"

with gr.Blocks(title=title, css=css) as demo:
    gr.Markdown(
    f"""
    # {title}
    This space uses old ESRGAN architecture to upscale images, using models made by the community.

    Once the photo upscaled, click or tap the **download button** under the image to download it. **The preview image is not the upscaled one**

    I'll add more models after optimizing to size of the output image, right now it could be quite big.
    
    **Colab coming soon™**
    """)

    with gr.Box():
        with gr.Row():
            with gr.Column():
                input_image = gr.Image(type="pil", label="Input")
                upscale_size = gr.Radio(["x4", "x2"], label="Upscale by:", value="x4")
                upscale_type = gr.Radio(["Manga", "Anime", "General"], label="Select the type of picture you want to upscale:", value="Manga")

                with gr.Row():
                    upscale_btn = gr.Button(value="Upscale", variant="primary")

            with gr.Column():
                output_image = gr.Image(type="filepath", interactive=False, label="Upscaled image", elem_id="preview_img")
                
                with gr.Row():
                    out_file = gr.File(interactive=False, show_label=False, visible=False)

    gr.HTML(value="<p><a href='https://upscale.wiki/wiki/Model_Database'>Model Database</a></p>")
        
    upscale_btn.click(process_image.inference, inputs=[input_image, upscale_size, upscale_type], outputs=[output_image, out_file])

demo.queue()
demo.launch(debug=is_colab, share=is_colab, inline=is_colab)