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Update app.py
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app.py
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@@ -1,9 +1,9 @@
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import gradio as gr
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import numpy as np
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import random
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import spaces
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from diffusers import DiffusionPipeline
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import torch
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device = "cuda" if torch.cuda.is_available() else "cpu"
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model_repo_id = "stabilityai/stable-diffusion-3.5-large-turbo"
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STYLE_NAMES = [style["name"] for style in style_list]
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DEFAULT_STYLE_NAME = STYLE_NAMES[0]
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def infer(
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prompt,
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negative_prompt="",
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guidance_scale=0.0,
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num_inference_steps=4,
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style="Style Zero",
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progress=gr.Progress(track_tqdm=True),
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):
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# Apply selected style
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generator = torch.Generator().manual_seed(seed)
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return
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examples = [
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"Chocolate dripping from a donut against a yellow background, in the style of brocore, hyper-realistic oil --ar 2:3 --q 2 --s 750 --v 5 --ar 2:3 --q 2 --s 750 --v 5",
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"3d image, cute girl, in the style of Pixar --ar 1:2 --stylize 750, 4K resolution highlights, Sharp focus, octane render, ray tracing, Ultra-High-Definition, 8k, UHD, HDR, (Masterpiece:1.5), (best quality:1.5)",
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"Cold coffee in a cup bokeh --ar 85:128 --v 6.0 --style raw5, 4K, Photo-Realistic",
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"Food photography of a milk shake with flying strawberrys against a pink background, professionally studio shot with cinematic lighting. The image is in the style of a professional studio shot --ar 85:128 --v 6.0 --style raw"
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]
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css = '''
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with gr.Blocks(css=css, theme="prithivMLmods/Minecraft-Theme") as demo:
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with gr.Column(elem_id="col-container"):
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gr.Markdown("## SD3.5 TURBO")
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with gr.Row():
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prompt = gr.Text(
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label="Prompt",
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run_button = gr.Button("Run", scale=0, variant="primary")
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result = gr.Image(label="Result", show_label=False)
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with gr.Row(visible=True):
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style_selection = gr.Radio(
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show_label=True,
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label="Quality Style",
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)
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with gr.Accordion("Advanced Settings", open=False, visible=False):
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negative_prompt = gr.Text(
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label="Negative prompt",
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outputs=[result, seed],
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fn=infer,
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cache_examples=True)
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gr.on(
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triggers=[run_button.click, prompt.submit],
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fn=infer,
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guidance_scale,
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num_inference_steps,
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style_selection,
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],
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outputs=[result, seed],
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)
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if __name__ == "__main__":
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demo.launch()
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import gradio as gr
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import numpy as np
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import random
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from diffusers import DiffusionPipeline
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import torch
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from PIL import Image
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device = "cuda" if torch.cuda.is_available() else "cpu"
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model_repo_id = "stabilityai/stable-diffusion-3.5-large-turbo"
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STYLE_NAMES = [style["name"] for style in style_list]
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DEFAULT_STYLE_NAME = STYLE_NAMES[0]
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grid_sizes = {
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"2x1": (2, 1),
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"1x2": (1, 2),
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"2x2": (2, 2),
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"2x3": (2, 3),
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"3x2": (3, 2),
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"1x1": (1, 1)
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}
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@gr.GPU(duration=60)
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def infer(
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prompt,
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negative_prompt="",
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guidance_scale=0.0,
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num_inference_steps=4,
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style="Style Zero",
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grid_size="1x1",
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progress=gr.Progress(track_tqdm=True),
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):
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# Apply selected style
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generator = torch.Generator().manual_seed(seed)
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# Get grid size
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grid_size_x, grid_size_y = grid_sizes.get(grid_size, (1, 1))
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num_images = grid_size_x * grid_size_y
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# Generate multiple images
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options = {
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"prompt": styled_prompt,
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"negative_prompt": styled_negative_prompt,
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"guidance_scale": guidance_scale,
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"num_inference_steps": num_inference_steps,
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"width": width,
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"height": height,
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"generator": generator,
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}
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torch.cuda.empty_cache() # Clear GPU memory
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images = pipe(**options).images
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# Create grid image
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grid_img = Image.new('RGB', (width * grid_size_x, height * grid_size_y))
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for i, img in enumerate(images[:num_images]):
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grid_img.paste(img, (i % grid_size_x * width, i // grid_size_x * height))
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return grid_img, seed
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examples = [
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"Chocolate dripping from a donut against a yellow background, in the style of brocore, hyper-realistic oil --ar 2:3 --q 2 --s 750 --v 5 --ar 2:3 --q 2 --s 750 --v 5",
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"3d image, cute girl, in the style of Pixar --ar 1:2 --stylize 750, 4K resolution highlights, Sharp focus, octane render, ray tracing, Ultra-High-Definition, 8k, UHD, HDR, (Masterpiece:1.5), (best quality:1.5)",
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"Cold coffee in a cup bokeh --ar 85:128 --v 6.0 --style raw5, 4K, Photo-Realistic",
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"Food photography of a milk shake with flying strawberrys against a pink background, professionally studio shot with cinematic lighting. The image is in the style of a professional studio shot --ar 85:128 --v 6.0 --style raw"
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]
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css = '''
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with gr.Blocks(css=css, theme="prithivMLmods/Minecraft-Theme") as demo:
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with gr.Column(elem_id="col-container"):
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gr.Markdown("## SD3.5 TURBO")
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with gr.Row():
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prompt = gr.Text(
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label="Prompt",
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run_button = gr.Button("Run", scale=0, variant="primary")
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result = gr.Image(label="Result", show_label=False)
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with gr.Row(visible=True):
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style_selection = gr.Radio(
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show_label=True,
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label="Quality Style",
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)
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with gr.Row(visible=True):
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grid_size_selection = gr.Dropdown(
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choices=["2x1", "1x2", "2x2", "2x3", "3x2", "1x1"],
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value="1x1",
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label="Grid Size"
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)
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with gr.Accordion("Advanced Settings", open=False, visible=False):
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negative_prompt = gr.Text(
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label="Negative prompt",
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outputs=[result, seed],
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fn=infer,
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cache_examples=True)
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gr.on(
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triggers=[run_button.click, prompt.submit],
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fn=infer,
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guidance_scale,
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num_inference_steps,
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style_selection,
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grid_size_selection,
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],
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outputs=[result, seed],
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)
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if __name__ == "__main__":
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demo.launch()
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