app.py

from contextlib import nullcontext
import gradio as gr
from torch import autocast
from removebg import RemoveBg
import os
import torch

import PIL
from PIL import Image

from diffusers import StableDiffusionPipeline
from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer

def image_grid(imgs, rows, cols):
    assert len(imgs) == rows*cols

    w, h = imgs[0].size
    grid = Image.new('RGB', size=(cols*w, rows*h))
    grid_w, grid_h = grid.size
    
    for i, img in enumerate(imgs):
        grid.paste(img, box=(i%cols*w, i//cols*h))
    return grid

pretrained_model_name_or_path = "vmanot/valiant-effort-one" #@param {type:"string"}

tokenizer = CLIPTokenizer.from_pretrained(
    pretrained_model_name_or_path,
    subfolder="tokenizer",
)
text_encoder = CLIPTextModel.from_pretrained(
    pretrained_model_name_or_path, subfolder="text_encoder", torch_dtype=torch.float16
)

device = "cuda" if torch.cuda.is_available() else "cpu"
context = autocast if device == "cuda" else nullcontext
dtype = torch.float16 if device == "cuda" else torch.float32

pipe = StableDiffusionPipeline.from_pretrained(
    pretrained_model_name_or_path,
    revision="main",
    torch_dtype=torch.float16,
    text_encoder=text_encoder,
    tokenizer=tokenizer,
).to("cuda")

disable_safety = True

if disable_safety:
  def null_safety(images, **kwargs):
      return images, False
  pipe.safety_checker = null_safety

  
num_samples = 2 #@param {type:"number"}
num_rows = 2 #@param {type:"number"}

def infer(prompt, n_samples, steps, scale):
    i = 0
    with context("cuda"):
        images = pipe(n_samples*[prompt], guidance_scale=scale, num_inference_steps=steps).images
    return images

css = """
        a {
            color: inherit;
            text-decoration: underline;
        }
        .gradio-container {
            font-family: 'IBM Plex Sans', sans-serif;
        }
        .gr-button {
            color: white;
            border-color: #9d66e5;
            background: #9d66e5;
        }
        input[type='range'] {
            accent-color: green;
        }
        .dark input[type='range'] {
            accent-color: green;
        }
        .container {
            max-width: 500px;
            margin-left: 200px;
            padding-top: 1.5rem;
        }
        #gallery {
            min-height: 22rem;
            margin-bottom: 15px;
            margin-left: auto;
            margin-right: auto;
            border-bottom-right-radius: .5rem !important;
            border-bottom-left-radius: .5rem !important;
        }
        #gallery>div>.h-full {
            min-height: 20rem;
        }
        .details:hover {
            text-decoration: underline;
        }
        .gr-button {
            white-space: nowrap;
        }
        .gr-button:focus {
            border-color: rgb(147 197 253 / var(--tw-border-opacity));
            outline: none;
            box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
            --tw-border-opacity: 1;
            --tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);
            --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);
            --tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));
            --tw-ring-opacity: .5;
        }
        #advanced-options {
            margin-bottom: 20px;
        }
        .dark { filter: invert(1); }
        .dark  {
            border-color: #303030;
        }
        .dark  {
            background: #0b0f19;
        }
        .acknowledgments h4{
            margin: 1.25em 0 .25em 0;
            font-weight: bold;
            font-size: 115%;
        }
"""

block = gr.Blocks(css=css)

examples = [
    [
        'Yoda',
        2,
        7.5,
    ],
    [
        'Abraham Lincoln',
        2,
        7.5,
    ],
    [
        'George Washington',
        2,
        7,
    ],
]

with block:
    gr.HTML(
        """
            <div style="text-align: center; max-width: 650px; margin: 0 auto;">
            </div>
        """
    )
    with gr.Group():
        with gr.Box():
            with gr.Row().style(mobile_collapse=False, equal_height=True):
                text = gr.Textbox(
                    label="Enter your prompt",
                    show_label=False,
                    max_lines=1,
                    placeholder="Enter your prompt",
                ).style(
                    border=(True, False, True, True),
                    rounded=(True, False, False, True),
                    container=False,
                )
                btn = gr.Button("Generate image").style(
                    margin=False,
                    rounded=(False, True, True, False),
                )

        gallery = gr.Gallery(
            label="Generated images", show_label=False, elem_id="gallery"
        ).style(grid=[2], height="auto")


        with gr.Row(elem_id="advanced-options"):
            samples = gr.Slider(label="Images", minimum=1, maximum=4, value=2, step=1)
            steps = gr.Slider(label="Steps", minimum=5, maximum=50, value=25, step=5)
            scale = gr.Slider(
                label="Guidance Scale", minimum=0, maximum=50, value=7.5, step=0.1
            )


        ex = gr.Examples(examples=examples, fn=infer, inputs=[text, samples, scale], outputs=gallery, cache_examples=False)
        ex.dataset.headers = [""]


        text.submit(infer, inputs=[text, samples, steps, scale], outputs=gallery)
        btn.click(infer, inputs=[text, samples, steps, scale], outputs=gallery)

block.launch(debug=True)