Update app.py
Browse files
app.py
CHANGED
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import gradio as gr
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from
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import
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import textwrap
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#
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def generate_image(text_description):
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#
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draw = ImageDraw.Draw(img)
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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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#
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try:
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font = ImageFont.truetype("arial.ttf",
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except:
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font = ImageFont.load_default()
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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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# 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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# 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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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
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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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# 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():
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