app.py

import streamlit as st
from PIL import Image
from gtts import gTTS
import os

# Mock object detection function
def detect_objects(image):
    st.write("Detecting objects in the image...")
    # Simulated output
    return ["table", "chair", "lamp"]

# Mock context-aware filter function
def filter_relevant_objects(detected_objects, setting):
    st.write(f"Filtering relevant objects for setting: {setting}")
    # Simulated filtering based on setting
    if setting == "indoor":
        return [obj for obj in detected_objects if obj in ["table", "lamp"]]
    return detected_objects

# Mock summarization function
def generate_summary(relevant_objects):
    st.write("Generating summary for relevant objects...")
    # Simulated summary
    summary = f"This is an {len(relevant_objects)}-item scene including: {', '.join(relevant_objects)}."
    return summary

# Mock text-to-speech function
def text_to_speech(text):
    st.write("Converting summary to speech...")
    tts = gTTS(text)
    tts.save("summary.mp3")
    st.audio("summary.mp3")

# Mock GPS navigation function
def get_distance_to_object(address):
    st.write(f"Calculating distance to address: {address}")
    # Simulated output
    return "5 km", "15 mins"

# Streamlit app main function
def main():
    st.title("Context-Aware Object Detection App")
    
    # Step 1: Capture Image from Camera
    captured_image = st.camera_input("Take a picture")

    if captured_image is not None:
        # Open the captured image
        image = Image.open(captured_image)
        st.image(image, caption="Captured Image", use_column_width=True)

        # Step 2: Detect Objects
        detected_objects = detect_objects(image)
        st.write(f"Detected Objects: {detected_objects}")

        # Step 3: Filter Relevant Objects
        setting = st.selectbox("Select Setting", ["indoor", "outdoor"], index=0)
        relevant_objects = filter_relevant_objects(detected_objects, setting)
        st.write(f"Relevant Objects: {relevant_objects}")

        # Step 4: Generate Summary
        summary = generate_summary(relevant_objects)
        st.write(f"Summary: {summary}")

        # Step 5: Convert Summary to Speech
        text_to_speech(summary)

        # Step 6: GPS Navigation (simulated)
        address = st.text_input("Enter Object's Address", "1600 Amphitheatre Parkway, Mountain View, CA")
        if st.button("Get Distance to Object"):
            distance, duration = get_distance_to_object(address)
            st.write(f"Distance to Object: {distance}, Duration: {duration}")

if __name__ == "__main__":
    main()