Update app.py

app.py

@@ -1,23 +1,35 @@
 import gradio as gr
-from transformers import pipeline
-
-# Load the text-to-image pipeline from Hugging Face
-generator = pipeline('text-to-image', model="CompVis/stable-diffusion-v1-4")
+from PIL import Image, ImageDraw, ImageFont
 
+# Function to generate a simple image based on description
 def generate_image(description):
-    # Generate the image based on the description
-    image = generator(description)
-    return image[0]['image']
+    # Create a blank white canvas of 300x300 pixels
+    img = Image.new('RGB', (300, 300), color=(255, 255, 255))
+    
+    # Create an ImageDraw object to add shapes and text
+    draw = ImageDraw.Draw(img)
+
+    # Check for specific keywords in the description
+    if "circle" in description.lower():
+        # Draw a blue circle
+        draw.ellipse([(50, 50), (250, 250)], fill="blue", outline="black")
+    
+    # Add the description text on the image
+    font = ImageFont.load_default()
+    draw.text((60, 260), description, fill="black", font=font)
+    
+    # Return the generated image
+    return img
 
-# Create the Gradio interface
+# Create a Gradio interface
 interface = gr.Interface(
     fn=generate_image,
     inputs="text",
     outputs="image",
-    title="Image Generator from Description",
-    description="Enter a text description and generate an image based on it."
+    title="Simple Text-to-Image Generator",
+    description="Enter a description, and the app will generate an image based on it. For example, try 'circle'."
 )
 
-# Launch the Gradio interface
+# Launch the Gradio app
 if __name__ == "__main__":
     interface.launch()