app.py

#!/usr/bin/env python

from __future__ import annotations

import os

import gradio as gr
import torch

from model import Model

DESCRIPTION = "# [Multiresolution Textual Inversion](https://github.com/giannisdaras/multires_textual_inversion)"

DETAILS = """
- To run the Semi Resolution-Dependent sampler, use the format: `<jane(number)>`.
- To run the Fully Resolution-Dependent sampler, use the format: `<jane[number]>`.
- To run the Fixed Resolution sampler, use the format: `<jane|number|>`.

For this demo, only `<jane>`, `<gta5-artwork>` and `<cat-toy>` are available.
Also, `number` should be an integer in [0, 9].
"""

CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES") == "1"

model = Model()

with gr.Blocks(css="style.css") as demo:
    gr.Markdown(DESCRIPTION)

    with gr.Row():
        with gr.Group():
            with gr.Row():
                prompt = gr.Textbox(label="Prompt")
            with gr.Row():
                num_images = gr.Slider(
                    label="Number of images",
                    minimum=1,
                    maximum=9,
                    step=1,
                    value=1,
                )
            with gr.Row():
                num_steps = gr.Slider(label="Number of inference steps", minimum=1, maximum=50, step=1, value=10)
            with gr.Row():
                seed = gr.Slider(label="Seed", minimum=0, maximum=100000, step=1, value=100)
            with gr.Row():
                run_button = gr.Button("Run")

        with gr.Column():
            result = gr.Gallery(label="Result", object_fit="scale-down")

    with gr.Row():
        with gr.Group():
            fn = lambda x: model.run(x, 2, 10, 100)
            with gr.Row():
                gr.Examples(
                    label="Examples 1",
                    examples=[
                        ["an image of <gta5-artwork(0)>"],
                        ["an image of <jane(0)>"],
                        ["an image of <jane(3)>"],
                        ["an image of <cat-toy(0)>"],
                    ],
                    inputs=prompt,
                    outputs=result,
                    fn=fn,
                    cache_examples=CACHE_EXAMPLES,
                )
            with gr.Row():
                gr.Examples(
                    label="Examples 2",
                    examples=[
                        ["an image of a cat in the style of <gta5-artwork(0)>"],
                        ["a painting of a dog in the style of <jane(0)>"],
                        ["a painting of a dog in the style of <jane(5)>"],
                        ["a painting of a <cat-toy(0)> in the style of <jane(3)>"],
                    ],
                    inputs=prompt,
                    outputs=result,
                    fn=fn,
                    cache_examples=CACHE_EXAMPLES,
                )
            with gr.Row():
                gr.Examples(
                    label="Examples 3",
                    examples=[
                        ["an image of <jane[0]>"],
                        ["an image of <jane|0|>"],
                        ["an image of <jane|3|>"],
                    ],
                    inputs=prompt,
                    outputs=result,
                    fn=fn,
                    cache_examples=CACHE_EXAMPLES,
                )

        inputs = [
            prompt,
            num_images,
            num_steps,
            seed,
        ]
        prompt.submit(
            fn=model.run,
            inputs=inputs,
            outputs=result,
            api_name=False,
        )
        run_button.click(
            fn=model.run,
            inputs=inputs,
            outputs=result,
            api_name="run",
        )

    with gr.Accordion("About available prompts", open=False):
        gr.Markdown(DETAILS)

demo.queue(max_size=10).launch()