src/ui/tabs/leaf_tab.py

"""
Leaf Disease Detection Tab
===========================
UI component for analyzing individual leaves.
"""

import gradio as gr
from src.utils.leaf_classifier import predict as classify_image


def analyze_leaf(image):
    """
    Analyze a leaf image to detect diseases.
    
    Args:
        image: PIL.Image from gr.Image component
    
    Returns:
        str: Result formatted as Markdown
    """
    if image is None:
        return "⚠️ Please upload an image of a leaf."
    
    # Call classifier
    result = classify_image(image)
    
    # Handle error
    if not result["success"]:
        return f"❌ Error: {result['error']}"
    
    # Format result as Markdown
    emoji = "✅" if result["is_healthy"] else "⚠️"
    status = "🌿 Healthy Plant" if result["is_healthy"] else "🦠 Disease Detected"
    
    output = f"""    
            ## 🔬 Analysis Result

            ### Main Diagnosis
            - **Prediction:** {emoji} {result["prediction"]}
            - **Confidence:** {result["confidence"]}%
            - **Status:** {status}

            ### Details
            - **Plant:** {result["plant"]}
            - **Condition:** {result["disease"]}

            ### Other Possibilities
            """
    
    # Add top-k alternatives (skip first one, it's the main prediction)
    for i, alt in enumerate(result["top_k"][1:], start=2):
        output += f"{i}. {alt['plant']} - {alt['disease']} ({alt['confidence']}%)\n"
    
    return output


def create_leaf_tab():
    """Create the leaf disease detection tab."""
    
    with gr.Tab("🍃 Leaves Disease Detection"):
        gr.Markdown("Analyze an individual leaf to detect diseases.")
        
        with gr.Row():
            with gr.Column():
                leaf_image = gr.Image(
                    label="📷 Upload a photo of the leaf",
                    type="pil",
                    height=300
                )
                leaf_btn = gr.Button("🔍 Analyze", variant="primary")
            
            with gr.Column():
                leaf_output = gr.Markdown(label="Result")
        
        # Example images
        gr.Markdown("### 📸 Try with example images:")
        gr.Examples(
            examples=[
                ["src/ui/pictures/leaves/185161-004-EAF28842.jpg"],
                ["src/ui/pictures/leaves/healthy.jpg"]
            ],
            inputs=[leaf_image],
            label="Example Leaves"
        )
        
        # Connect button
        leaf_btn.click(
            fn=analyze_leaf,
            inputs=[leaf_image],
            outputs=[leaf_output]
        )