dschandra commited on
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192fee3
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Update app.py

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  1. app.py +19 -39
app.py CHANGED
@@ -1,54 +1,34 @@
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  import gradio as gr
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- from PIL import Image, ImageDraw, ImageFont
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- import random
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- import textwrap
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- # Enhanced function for image generation with better visual representation
 
 
 
 
 
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  def generate_image(text_description):
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- # Create a blank image with a gradient background to simulate a sunset
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- img = Image.new('RGB', (512, 512), color=(0, 0, 0)) # Start with black
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- draw = ImageDraw.Draw(img)
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-
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- # Create a simple gradient for sunset (orange to purple)
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- for y in range(512):
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- r = int(255 * (1 - y / 512) * 0.8) # Fade red/orange
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- g = int(100 * (1 - y / 512)) # Minimal green
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- b = int(150 + 105 * (y / 512)) # Increase blue/purple
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- draw.line([(0, y), (512, y)], fill=(r, g, b))
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- # Load a default font (fallback to system font if arial.ttf is unavailable)
 
 
 
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  try:
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- font = ImageFont.truetype("arial.ttf", 25)
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  except:
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  font = ImageFont.load_default()
 
 
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- # Wrap text to fit within the image
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- wrapper = textwrap.TextWrapper(width=20) # Adjust width for better wrapping
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- wrapped_text = wrapper.fill(text=text_description)
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- lines = wrapped_text.split('\n')
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-
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- # Draw each line of text at the bottom
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- y_text = 400
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- for line in lines:
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- bbox = draw.textbbox((0, 0), line, font=font)
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- line_width = bbox[2] - bbox[0]
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- line_height = bbox[3] - bbox[1]
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- draw.text((20, y_text), line, font=font, fill=(255, 255, 255))
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- y_text += line_height + 5
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-
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- # Add graphical elements based on description
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- if "lake" in text_description.lower():
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- draw.rectangle([150, 300, 350, 400], fill=(0, 191, 255)) # Blue lake
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- if "mountains" in text_description.lower():
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- draw.polygon([(200, 250), (250, 200), (300, 250)], fill=(255, 255, 255)) # White mountain
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- draw.polygon([(250, 200), (300, 150), (350, 200)], fill=(255, 255, 255)) # Second mountain
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-
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- return img
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  # Gradio interface
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  with gr.Blocks(title="Text-to-Image Generator") as demo:
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  gr.Markdown("# Text-to-Image Generator")
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- gr.Markdown("Enter a description below and generate an image!")
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  with gr.Row():
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  with gr.Column():
 
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  import gradio as gr
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+ from diffusers import StableDiffusionPipeline
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+ import torch
 
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+ # Load the Stable Diffusion model (use a lightweight version for Spaces)
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+ model_id = "runwayml/stable-diffusion-v1-5"
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+ pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
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+ pipe = pipe.to("cuda") # Use GPU if available
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+
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+ # Function to generate image from description
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  def generate_image(text_description):
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+ # Generate image using Stable Diffusion
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+ image = pipe(text_description, num_inference_steps=50, guidance_scale=7.5).images[0]
 
 
 
 
 
 
 
 
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+ # Optional: Add text to the image
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+ from PIL import Image, ImageDraw, ImageFont
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+ img_with_text = image.copy()
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+ draw = ImageDraw.Draw(img_with_text)
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  try:
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+ font = ImageFont.truetype("arial.ttf", 20)
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  except:
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  font = ImageFont.load_default()
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+ text = f"Generated: {text_description}"
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+ draw.text((10, image.height - 100), text, font=font, fill=(255, 255, 255))
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+ return img_with_text
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  # Gradio interface
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  with gr.Blocks(title="Text-to-Image Generator") as demo:
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  gr.Markdown("# Text-to-Image Generator")
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+ gr.Markdown("Enter a description below and generate a detailed image!")
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  with gr.Row():
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  with gr.Column():