Create app.py

app.py

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+import torch
+import gradio as gr
+from diffusers import StableDiffusionPipeline
+from PIL import Image, ImageDraw, ImageFont
+import os
+
+# Function to Generate Image
+def generate_image(prompt, height=1024, width=1024):
+    """
+    Generate an image using Stable Diffusion from Hugging Face.
+
+    Args:
+        prompt (str): The text prompt to guide image generation.
+        height (int): Height of the generated image.
+        width (int): Width of the generated image.
+
+    Returns:
+        PIL Image: Generated image.
+    """
+    # Load Hugging Face access token from environment variables
+    HUGGINGFACE_API_KEY = os.getenv("HUGGINGFACE_API_KEY")
+    if not HUGGINGFACE_API_KEY:
+        raise ValueError("Hugging Face API key is not set. Export it as HUGGINGFACE_API_KEY.")
+    
+    # Load the Stable Diffusion model
+    print("Loading Stable Diffusion model...")
+    model_id = "CompVis/stable-diffusion-v1-4"  # You can change to v2 models if needed
+    pipeline = StableDiffusionPipeline.from_pretrained(
+        model_id, 
+        use_auth_token=HUGGINGFACE_API_KEY,
+        torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32
+    )
+    
+    # Move to GPU if available
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    pipeline = pipeline.to(device)
+    
+    # Generate the image
+    print(f"Generating image for prompt: '{prompt}'...")
+    image = pipeline(prompt, height=height, width=width).images[0]
+    
+    return image
+
+# Function to Add Emphasized Text to the Image (Product Name, Tagline, CTA)
+def add_text_to_image(image, product_name, tagline, cta_text, font_size=50):
+    """
+    Add clean and sharp text (product name, tagline, and CTA) to the generated image with emphasis.
+    
+    Args:
+        image (PIL Image): Generated image to add text to.
+        product_name (str): Product name to be emphasized.
+        tagline (str): Tagline to be emphasized.
+        cta_text (str): Call to action text to be emphasized.
+        font_size (int): The font size.
+    
+    Returns:
+        PIL Image: Image with added text.
+    """
+    draw = ImageDraw.Draw(image)
+    
+    # Load font for product name, tagline, and CTA
+    product_font = ImageFont.truetype("arial.ttf", font_size + 20)  # Larger for product name
+    tagline_font = ImageFont.truetype("arial.ttf", font_size)       # Slightly smaller for tagline
+    cta_font = ImageFont.truetype("arial.ttf", font_size - 10)      # Smaller for CTA
+
+    # Define positions for text
+    product_name_position = (50, 50)
+    tagline_position = (50, 150)
+    cta_position = (50, 250)
+
+    # Add product name in large font
+    draw.text(product_name_position, product_name, font=product_font, fill="white")
+    
+    # Add tagline below the product name
+    draw.text(tagline_position, tagline, font=tagline_font, fill="white")
+    
+    # Add CTA below tagline
+    draw.text(cta_position, cta_text, font=cta_font, fill="gold")  # CTA in gold to stand out
+    
+    return image
+
+# Gradio Interface Function
+def generate_ad(brand_title, tagline, cta, brand_logo, product_image, custom_prompt):
+    """
+    Generate an advertisement image with the provided details.
+    
+    Args:
+        brand_title (str): Brand title for the advertisement.
+        tagline (str): Tagline for the advertisement.
+        cta (str): Call to action text.
+        brand_logo (file): Brand logo image (optional).
+        product_image (file): Product image (optional).
+        custom_prompt (str): Custom prompt for image generation.
+
+    Returns:
+        PIL Image: Final advertisement image.
+    """
+    # Prepare the final prompt
+    prompt = custom_prompt if custom_prompt else (
+        f"An elegant advertisement for {brand_title}, featuring gold and white tones, "
+        f"with a radiant and premium look. Product focus and beautiful typography for '{tagline}'."
+    )
+
+    # Generate the image
+    generated_image = generate_image(prompt)
+
+    # Add product and CTA text to the image
+    final_image = add_text_to_image(generated_image, brand_title, tagline, cta)
+
+    # Optionally, add brand logo and product image if provided
+    if brand_logo:
+        logo = Image.open(brand_logo).resize((150, 150))
+        final_image.paste(logo, (50, 350), logo.convert('RGBA'))
+
+    if product_image:
+        product = Image.open(product_image).resize((300, 300))
+        final_image.paste(product, (250, 350), product.convert('RGBA'))
+    
+    return final_image
+
+# Create Gradio Interface
+iface = gr.Interface(
+    fn=generate_ad,
+    inputs=[
+        gr.Textbox(label="Brand Title", placeholder="Enter brand title"),
+        gr.Textbox(label="Tagline", placeholder="Enter tagline"),
+        gr.Textbox(label="CTA", placeholder="Enter Call to Action"),
+        gr.Image(type="file", label="Brand Logo (optional)", optional=True),
+        gr.Image(type="file", label="Product Image (optional)", optional=True),
+        gr.Textbox(label="Custom Prompt (optional)", placeholder="Enter a custom prompt (or leave empty)"),
+    ],
+    outputs=gr.Image(label="Generated Advertisement"),
+)
+
+# Launch Gradio Interface
+iface.launch()