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...") 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}") 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...") 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}") return "5 km", "15 mins" # Streamlit app main function def main(): st.title("Context-Aware Object Detection App") captured_image = st.camera_input("Take a picture") if captured_image is not None: image = Image.open(captured_image) st.image(image, caption="Captured Image", use_column_width=True) detected_objects = detect_objects(image) st.write(f"Detected Objects: {detected_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}") summary = generate_summary(relevant_objects) st.write(f"Summary: {summary}") text_to_speech(summary) 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()