Update app.py

app.py

@@ -1,43 +1,13 @@
 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
+# Function to get the user's live location based on IP
 def get_user_location():
     st.write("Fetching location, please allow location access in your browser.")
     geolocator = Nominatim(user_agent="binsight")
     try:
+        # Get the IP-based location
         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)
@@ -48,62 +18,14 @@ def get_user_location():
         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}")
+    st.write(f"**Latitude:** {latitude}, **Longitude:** {longitude}")
 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.")
-
-
-
-
-
 
 
 # best with firebase but below code is not giving correct location of user.