app.py

import gradio as gr
from PIL import Image  
import torch

from diffusers import StableDiffusionPipeline
from free_lunch_utils import register_free_upblock2d, register_free_crossattn_upblock2d


torch.manual_seed(42)
model_id = "CompVis/stable-diffusion-v1-4"
        
# pip_sd = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
# pip_sd = pip_sd.to("cuda")

# pip_freeu = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
# pip_freeu = pip_freeu.to("cuda")
# # -------- freeu block registration
# register_free_upblock2d(pip_freeu, b1=1.2, b2=1.4, s1=0.9, s2=0.2)
# register_free_crossattn_upblock2d(pip_freeu, b1=1.2, b2=1.4, s1=0.9, s2=0.2)
# # -------- freeu block registration

pip = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pip = pip.to("cuda")

def infer(prompt, model, seed, b1, b2, s1, s2):

    # pip = StableDiffusionPipeline.from_pretrained(model, torch_dtype=torch.float16)
    # pip = pip.to("cuda")

   
    # register_free_upblock2d(pip, b1=1.0, b2=1.0, s1=1.0, s2=1.0)
    # register_free_crossattn_upblock2d(pip, b1=1.0, b2=1.0, s1=1.0, s2=1.0)
   
    torch.manual_seed(seed)
    print("Generating SD:")
    sd_image = pip(prompt).images[0]  

    # register_free_upblock2d(pip, b1=b1, b2=b2, s1=s1, s2=s1)
    # register_free_crossattn_upblock2d(pip, b1=b1, b2=b2, s1=s1, s2=s1)

    torch.manual_seed(seed)
    print("Generating FreeU:")
    freeu_image = pip(prompt).images[0]  

    # First SD, then freeu
    images = [sd_image, freeu_image]

    return images


examples = [
    [
        "A small cabin on top of a snowy mountain in the style of Disney, artstation",
    ],
    [
        "a monkey doing yoga on the beach",
    ],
    [
        "half human half cat, a human cat hybrid",
    ],
    [
        "a hedgehog using a calculator",
    ],
    [
        "kanye west | diffuse lighting | fantasy | intricate elegant highly detailed lifelike photorealistic digital painting | artstation",
    ],
    [
        "astronaut pig",
    ],
    [
        "two people shouting at each other",
    ],
    [
        "A linked in profile picture of Elon Musk",
    ],
    [
        "A man looking out of a rainy window",
    ],
    [
        "close up, iron man, eating breakfast in a cabin, symmetrical balance, hyper-realistic --ar 16:9 --style raw"
    ],
    [
        'A high tech solarpunk utopia in the Amazon rainforest',
    ],
    [
        'A pikachu fine dining with a view to the Eiffel Tower',
    ],
    [
        'A mecha robot in a favela in expressionist style',
    ],
    [
        'an insect robot preparing a delicious meal',
    ],
]
    
    
css = """
h1 {
  text-align: center;
}

#component-0 {
  max-width: 730px;
  margin: auto;
}
"""

block = gr.Blocks(css='style.css')

options = ['SD1.4', 'SD1.5', 'SD2.1']

with block:
    gr.Markdown("SD vs. FreeU.")
    with gr.Group():
        with gr.Row(): 
            sd_options = gr.Dropdown(['SD1.4', 'SD1.5', 'SD2.1'], value='SD1.4', label="SD options")

            if sd_options == 'SD1.5':
                model = "runwayml/stable-diffusion-v1-5"
            elif sd_options == 'SD2.1':
                model = "stabilityai/stable-diffusion-2-1"
            else:
                model = "CompVis/stable-diffusion-v1-4"
            
            # pip = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
            # pip = pip.to("cuda")
            
            with gr.Row():
                with gr.Column():
                    text = gr.Textbox(
                        label="Enter your prompt",
                        show_label=False,
                        max_lines=1,
                        placeholder="Enter your prompt",
                        container=False,
                    )
                    btn = gr.Button("Generate image", scale=0)
                
                seed = gr.Slider(label='seed',
                                        minimum=0,
                                        maximum=1000,
                                        step=1,
                                        value=42)

    
    with gr.Group():
        with gr.Row():
            with gr.Accordion('FreeU Parameters: b', open=True):
                b1 = gr.Slider(label='b1: backbone factor of the first stage block of decoder',
                                        minimum=1,
                                        maximum=1.6,
                                        step=0.1,
                                        value=1)
                b2 = gr.Slider(label='b2: backbone factor of the second stage block of decoder',
                                        minimum=1,
                                        maximum=1.6,
                                        step=0.1,
                                        value=1)
            with gr.Accordion('FreeU Parameters: s', open=True):
                s1 = gr.Slider(label='s1: skip factor of the first stage block of decoder',
                                        minimum=0,
                                        maximum=1,
                                        step=0.1,
                                        value=1)
                s2 = gr.Slider(label='s2: skip factor of the second stage block of decoder',
                                        minimum=0,
                                        maximum=1,
                                        step=0.1,
                                        value=1)    
                    
    with gr.Row():
        with gr.Group():
            # btn = gr.Button("Generate image", scale=0)
            with gr.Row():
                with gr.Column(min_width=256) as c1:
                    image_1 = gr.Image(interactive=False)
                    image_1_label = gr.Markdown("SD")
            
        with gr.Group():
            # btn = gr.Button("Generate image", scale=0)
            with gr.Row():
                with gr.Column(min_width=256) as c2:
                    image_2 = gr.Image(interactive=False)
                    image_2_label = gr.Markdown("FreeU")
        
        
    ex = gr.Examples(examples=examples, fn=infer, inputs=[text, model, seed, b1, b2, s1, s2], outputs=[image_1, image_2], cache_examples=False)
    ex.dataset.headers = [""]

    text.submit(infer, inputs=[text, model, seed, b1, b2, s1, s2], outputs=[image_1, image_2])
    btn.click(infer, inputs=[text, model, seed, b1, b2, s1, s2], outputs=[image_1, image_2])

block.launch()
# block.queue(default_enabled=False).launch(share=False)