Create app.py

app.py

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+import gradio as gr
+import torch
+from diffusers import DiffusionPipeline
+from PIL import Image, ImageDraw, ImageFont
+
+# Load the model
+model = DiffusionPipeline.from_pretrained("ginipick/flux-lora-eric-cat", torch_dtype=torch.float16)
+model = model.to("cuda")  # Move the model to GPU if available
+
+def generate_image(caption):
+    # Generate the image from the caption
+    image = model(caption).images[0]
+    
+    # Convert to PIL Image for drawing
+    image = image.convert("RGBA")
+    
+    # Create a draw object
+    draw = ImageDraw.Draw(image)
+    
+    # Define font size and color
+    font_size = 40
+    font_color = "white"
+    
+    # Load a font
+    font = ImageFont.load_default()  # You can specify a TTF font file if needed
+    
+    # Calculate text size and position
+    text_width, text_height = draw.textsize(caption, font=font)
+    text_position = ((image.width - text_width) // 2, 10)  # Centered at the top
+    
+    # Draw the text on the image
+    draw.text(text_position, caption, font=font, fill=font_color)
+    
+    return image
+
+# Create the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Text to Image Generation with Meme Caption")
+    
+    with gr.Row():
+        caption_input = gr.Textbox(label="Enter your caption", placeholder="Type your caption here...")
+        generate_button = gr.Button("Generate Image")
+    
+    output_image = gr.Image(label="Generated Image")
+    
+    generate_button.click(fn=generate_image, inputs=caption_input, outputs=output_image)
+
+# Launch the app
+demo.launch()