updated maps and code

Author: coder12git

About.py

@@ -11,7 +11,7 @@ def load_lottieurl(url):
 
 
 st.set_page_config(
-    page_title="Skin Cancer",
+    page_title="Diagnose",
     page_icon="♋",
     layout="wide",
     initial_sidebar_state="expanded",
@@ -70,7 +70,7 @@ def load_lottieurl(url):
         Our application utilizes machine learning to predict what skin disease you may have, from just your skin images!
         We then recommend you specialized doctors based on your type of disease, if our model predicts you're healthy we'll suggest you a general doctor.
         ##
-        [Learn More >](https://youtu.be/sFIXmJn3vGk)
+        [Learn More >]()
         """
     with cols[1]:
         st_lottie(lottie_healthy, height=300, key="healthy")

pages/2_Demo.py

@@ -5,7 +5,7 @@
 import tensorflow as tf
 
 st.set_page_config(
-    page_title="Skin Cancer Detection",
+    page_title="Diagnose Demo",
     page_icon="♋",
     layout="centered",
     initial_sidebar_state="expanded",

pages/3_Contact.py

@@ -1,70 +1,70 @@
 # Contact Feature
 
 import streamlit as st
-from geopy.geocoders import Nominatim
+import pandas as pd
+import pydeck as pdk
 import requests
 
 st.set_page_config(
-    page_title="Skin Cancer",
+    page_title="Diagnose",
     page_icon="♋",
     layout="centered",
     initial_sidebar_state="expanded",
 )
 
-# Replace YOUR_API_KEY with your actual API key
-api_key = st.secrets["api_key"]
-
 
 st.title("Find a dermatologist")
-# Set the location and radius for the search
+
+# Create a function to search for nearby doctors based on city name
+def search_doctors(city):
+    # Google Maps API key
+    api_key = st.secrets["API_KEY"]
+    url = f"https://maps.googleapis.com/maps/api/place/textsearch/json?query=dermatologists+in+{city}&key={api_key}"
+    results = requests.get(url).json()
+    return results["results"]
+
+
+# Input city name
 city = st.text_input(
     label="Enter your city",
     placeholder="City (e.g. New Delhi)",
     help="Enter the name of the city where you want to find a dermatologist",
 ).strip()
 
-if city != "":
-    # Create a geolocator object
-    geolocator = Nominatim(user_agent="skin_cancer")
-
-    # Use the geolocator to get the latitude and longitude of the city
-    location = geolocator.geocode(city)
-    latitude = location.latitude
-    longitude = location.longitude
-
-    location = f"{latitude},{longitude}"
-    radius = 10000  # 10 km
-    keyword = "dermatologist"
-
-    # Make the request to the Places API
-    url = f"https://maps.googleapis.com/maps/api/place/nearbysearch/json?location={location}&radius={radius}&keyword={keyword}&key={api_key}"
-    response = requests.get(url)
-    results = response.json()["results"]
-
-    # Extract the place IDs of the results
-    place_ids = [result["place_id"] for result in results]
+if city:
+    # Search for nearby doctors
+    doctors = search_doctors(city)
 
-    # Use the place IDs to get the details of the places
-    dermatologists = []
-    for place_id in place_ids:
-        url = f"https://maps.googleapis.com/maps/api/place/details/json?place_id={place_id}&key={api_key}"
-        response = requests.get(url)
-        place_details = response.json()["result"]
-        dermatologists.append(
-            {
-                "name": place_details["name"],
-                "address": place_details["formatted_address"],
-            }
+    # Display the results to the user
+    st.write("Results for Dermatologist doctors in: ", city)
+    lat_long = [
+        (doc["geometry"]["location"]["lat"], doc["geometry"]["location"]["lng"])
+        for doc in doctors
+    ]
+    df = pd.DataFrame(lat_long, columns=["latitude", "longitude"])
+    st.pydeck_chart(
+        pdk.Deck(
+            map_style="mapbox://styles/mapbox/streets-v12",
+            initial_view_state=pdk.ViewState(
+                latitude=df["latitude"].mean(),
+                longitude=df["longitude"].mean(),
+                zoom=11,
+                pitch=50,
+            ),
+            layers=[
+                pdk.Layer(
+                    "ScatterplotLayer",
+                    data=df,
+                    get_position=["longitude", "latitude"],
+                    get_radius=100,
+                    get_color=[200, 30, 0],
+                    pickable=True,
+                    auto_highlight=True,
+                )
+            ],
         )
+    )
 
-    # Display the results in Streamlit
-    st.header("Results")
-    for i, dermatologist in enumerate(dermatologists, start=1):
-        # st.markdown(f"**{dermatologist['name']}**")
-        # st.markdown(dermatologist["address"])
-        st.markdown(
-            f"""
-            {i}. **{dermatologist['name']}**
-            > **Address:** {dermatologist['address']}
-            """
-        )
+    for i, doctor in enumerate(doctors):
+        st.write(f"{i+1}. **Name**: ", doctor["name"])
+        st.write("> **Address**: ", doctor["formatted_address"])

pages/4_Articles.py

@@ -6,7 +6,7 @@
 from streamlit_lottie import st_lottie
 
 st.set_page_config(
-    page_title="Skin Cancer",
+    page_title="Diagnose",
     page_icon="♋",
     layout="wide",
     initial_sidebar_state="expanded",