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app.py

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+import gradio as gr
+import numpy as np
+import cv2
+from PIL import Image
+
+def process_image(input_image, size_option):
+    """
+    This is a placeholder function that demonstrates image processing.
+    In a real application, you would implement proper image editing here.
+    """
+    # Convert to numpy array
+    img = np.array(input_image)
+    
+    # Convert to grayscale for demonstration
+    processed_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    
+    # Add a watermark to show this is just a demo
+    cv2.putText(processed_img, "DEMO ONLY", (50, 50), 
+                cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 0), 2)
+    
+    # Add text based on size option
+    size_text = f"Size: {size_option}"
+    cv2.putText(processed_img, size_text, (50, 100), 
+                cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 0), 2)
+    
+    return Image.fromarray(processed_img)
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Image Processing Demo")
+    gr.Markdown("Built with [anycoder](https://huggingface.co/spaces/akhaliq/anycoder)")
+    
+    with gr.Row():
+        with gr.Column():
+            input_image = gr.Image(label="Upload Image", type="pil")
+            size_option = gr.Radio(["Small", "Medium", "Large"], 
+                                 label="Processing Option", 
+                                 value="Medium")
+            submit_btn = gr.Button("Process Image")
+        
+        with gr.Column():
+            output_image = gr.Image(label="Processed Result")
+    
+    submit_btn.click(
+        fn=process_image,
+        inputs=[input_image, size_option],
+        outputs=output_image
+    )
+
+demo.launch(
+    theme=gr.themes.Soft(primary_hue="blue"),
+    footer_links=[{"label": "Built with anycoder", "url": "https://huggingface.co/spaces/akhaliq/anycoder"}]
+)

requirements.txt

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+Pillow
+cv2
+gradio
+numpy