Create app.py

app.py

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+import streamlit as st
+import requests
+import firebase_admin
+from firebase_admin import credentials, db, auth
+from PIL import Image
+import numpy as np
+from geopy.geocoders import Nominatim
+from tensorflow.keras.applications import MobileNetV2
+from tensorflow.keras.applications.mobilenet_v2 import decode_predictions, preprocess_input
+import json
+
+# Initialize Firebase
+if not firebase_admin._apps:
+    cred = credentials.Certificate("firebase_credentials.json")  
+    firebase_admin.initialize_app(cred, {
+        'databaseURL': 'https://binsight-beda0-default-rtdb.asia-southeast1.firebasedatabase.app/'
+    })
+
+# Load MobileNetV2 pre-trained model
+mobilenet_model = MobileNetV2(weights="imagenet")
+
+# Function to classify the uploaded image using MobileNetV2
+def classify_image_with_mobilenet(image):
+    try:
+        img = image.resize((224, 224))
+        img_array = np.array(img)
+        img_array = np.expand_dims(img_array, axis=0)
+        img_array = preprocess_input(img_array)
+        predictions = mobilenet_model.predict(img_array)
+        labels = decode_predictions(predictions, top=5)[0]
+        return {label[1]: float(label[2]) for label in labels}
+    except Exception as e:
+        st.error(f"Error during image classification: {e}")
+        return {}
+
+# Function to get user's location using geolocation API
+def get_user_location():
+    st.write("Fetching location, please allow location access in your browser.")
+    geolocator = Nominatim(user_agent="binsight")
+    try:
+        ip_info = requests.get("https://ipinfo.io/json").json()
+        loc = ip_info.get("loc", "").split(",")
+        latitude, longitude = loc[0], loc[1] if len(loc) == 2 else (None, None)
+        if latitude and longitude:
+            address = geolocator.reverse(f"{latitude}, {longitude}").address
+            return latitude, longitude, address
+    except Exception as e:
+        st.error(f"Error retrieving location: {e}")
+    return None, None, None
+
+# User Login
+st.sidebar.header("User Login")
+user_email = st.sidebar.text_input("Enter your email")
+login_button = st.sidebar.button("Login")
+
+if login_button:
+    if user_email:
+        st.session_state["user_email"] = user_email
+        st.sidebar.success(f"Logged in as {user_email}")
+
+if "user_email" not in st.session_state:
+    st.warning("Please log in first.")
+    st.stop()
+
+# Get user location and display details
+latitude, longitude, address = get_user_location()
+if latitude and longitude:
+    st.success(f"Location detected: {address}")
+else:
+    st.warning("Unable to fetch location, please ensure location access is enabled.")
+    st.stop()
+
+# Streamlit App
+st.title("BinSight: Upload Dustbin Image")
+
+uploaded_file = st.file_uploader("Upload an image of the dustbin", type=["jpg", "jpeg", "png"])
+submit_button = st.button("Analyze and Upload")
+
+if submit_button and uploaded_file:
+    image = Image.open(uploaded_file)
+    st.image(image, caption="Uploaded Image", use_container_width=True)
+
+    classification_results = classify_image_with_mobilenet(image)
+    
+    if classification_results:
+        db_ref = db.reference("dustbins")
+        dustbin_data = {
+            "user_email": st.session_state["user_email"],
+            "latitude": latitude,
+            "longitude": longitude,
+            "address": address,
+            "classification": classification_results,
+            "allocated_truck": None,
+            "status": "Pending"
+        }
+        db_ref.push(dustbin_data)
+        st.success("Dustbin data uploaded successfully!")
+        st.write(f"**Location:** {address}")
+        st.write(f"**Latitude:** {latitude}, **Longitude:** {longitude}")
+    else:
+        st.error("Missing classification details. Cannot upload.")
+
+
+