Create app.py
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app.py
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# @title 📸 Image Generation (multimodel + Gradio Web Interface)
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# Install Dependencies
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!pip install transformers torch diffusers accelerate invisible_watermark safetensors huggingface-hub gradio --quiet
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from diffusers import DiffusionPipeline, StableDiffusionPipeline
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import torch
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from gradio.components import Gallery
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from PIL import Image
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from IPython.display import display
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import os
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from datetime import datetime
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import gradio as gr
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# Function to generate and display images
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def generate_and_display_images(model_selection, scenery, style, height, width, num_images=2, n_steps=50, high_noise_frac=0.5, guidance_scale=2.6, negative_prompt="", seed=None):
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if seed is None or seed == '':
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seed = torch.randint(low=0, high=2**32, size=(1,)).item()
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else:
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try:
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seed = int(seed)
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except ValueError:
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return "Invalid seed value. Seed must be an integer."
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torch.manual_seed(seed)
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prompt = f"Scenery: {scenery}; Style: {style}"
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generated_images = []
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if model_selection == "dreamlike-art/dreamlike-photoreal-2.0":
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model = StableDiffusionPipeline.from_pretrained(model_selection, torch_dtype=torch.float16).to("cuda")
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for _ in range(num_images):
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image = model(prompt=prompt, num_inference_steps=n_steps, guidance_scale=guidance_scale, negative_prompt=negative_prompt, height=height, width=width).images[0]
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generated_images.append(image)
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else:
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base = DiffusionPipeline.from_pretrained(model_selection, torch_dtype=torch.float16, use_auth_token=True).to("cuda")
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for _ in range(num_images):
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if "refiner" in model_selection:
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image_latent = base(prompt=prompt, num_inference_steps=n_steps, denoising_end=high_noise_frac, output_type="latent").images
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image = image_latent[0] # Placeholder for actual refiner step
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else:
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image = base(prompt=prompt, num_inference_steps=n_steps, guidance_scale=guidance_scale, negative_prompt=negative_prompt, height=height, width=width).images[0]
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generated_images.append(image)
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# Save images and return file paths for Gradio display
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file_paths = []
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for i, image in enumerate(generated_images):
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timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
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filename = f"{seed}_{timestamp}_{i}.jpg"
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image.save(filename)
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file_paths.append(filename)
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return file_paths
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# Define Gradio interface
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iface = gr.Interface(
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fn=generate_and_display_images,
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inputs=[
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gr.components.Dropdown(choices=["stabilityai/sdxl-turbo", "stabilityai/stable-diffusion-xl-base-1.0", "runwayml/stable-diffusion-v1-5", "dreamlike-art/dreamlike-photoreal-2.0", "Kardbord/stable-diffusion-v1-5-unsafe"], label="Model Selection"),
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gr.components.Textbox(label="Scenery", placeholder="Describe the scenery you want in the image"),
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gr.components.Textbox(label="Style", placeholder="Describe the style of the image (e.g., photorealistic, liminal, dark)"),
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gr.components.Slider(minimum=1, maximum=2048, step=1, value=1024, label="Height"),
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gr.components.Slider(minimum=1, maximum=2048, step=1, value=576, label="Width"),
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gr.components.Number(value=10, label="Number of Images"),
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gr.components.Slider(minimum=0, maximum=60, step=1, value=30, label="Number of Inference Steps"),
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gr.components.Slider(minimum=0.0, maximum=1.0, step=0.01, value=0.16, label="High Noise Fraction"),
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gr.components.Slider(minimum=0.0, maximum=10.0, step=0.1, value=8, label="Guidance Scale"),
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gr.components.Textbox(value="", label="Negative Prompt"),
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gr.components.Textbox(value=None, label="Seed (Optional)")
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],
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outputs=Gallery(label="Generated Images"),
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examples=[["dreamlike-art/dreamlike-photoreal-2.0", "scenery : melting flesh", "style : (((photorealistic))), liminal, cryptic, cinematic, highly detailed, sharp focus, dark, creepy, weirdcore", 1024, 576, 10, 30, 0.16, 8, "2D || naked || Low Quality || text logos || watermarks || signatures || out of frame || jpeg artifacts || ugly || poorly drawn || extra limbs || extra hands || extra feet || backwards limbs || extra fingers || extra toes || unrealistic, incorrect, bad anatomy || cut off body pieces || strange body positions || impossible body positioning || Mismatched eyes || cross eyed || crooked face || crooked lips || unclear || undefined || mutations || deformities || off center || poor_composition || duplicate faces, blurry, blurred, unclear, deformed anatomy, deformed face, crazy eyes, bad hands, deformed body", None]],
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title="Image Generation Tool",
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description="Generate images using various diffusion models."
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)
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# Launch the interface
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iface.launch(share=True, debug=True)
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