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import gradio as gr
from PIL import Image
from food_identification import identify_food
from nutritional_analysis import get_nutritional_info
from portion_size_analysis import estimate_portion_size
def analyze_food(image):
"""
Analyze the uploaded image for food items and provide dynamic nutritional and portion size information.
"""
# Step 1: Identify food items
food_items = identify_food(image)
# Step 2: Fetch nutritional data dynamically
nutrition_data = get_nutritional_info(food_items)
# Step 3: Estimate portion size
portion_size = estimate_portion_size(image)
# Format output
description = f"Detected food items: {', '.join(food_items)}.\n\n"
description += f"Portion size: {portion_size}.\n\n"
description += "Nutritional Information:\n"
for food, nutrients in nutrition_data.items():
if "Error" in nutrients:
description += f"- {food}: {nutrients['Error']}\n"
else:
description += (
f"- {food}:\n"
f" - Energy: {nutrients['Energy (kcal)']} kcal\n"
f" - Protein: {nutrients['Protein (g)']} g\n"
f" - Carbs: {nutrients['Carbs (g)']} g\n"
f" - Fiber: {nutrients['Fiber (g)']} g\n"
f" - Fat: {nutrients['Fat (g)']} g\n"
f" - Sugar: {nutrients['Sugar (g)']} g\n"
)
return description
# Gradio Interface
iface = gr.Interface(
fn=analyze_food,
inputs=gr.Image(type="pil"),
outputs="text",
title="Diet Nutrition Analyzer",
description="Upload an image of your food plate to analyze nutrition and portion size dynamically."
)
if __name__ == "__main__":
iface.launch()
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