Python

import os

import requests

import pandas as pd

import time

# Google Maps API Key

GOOGLE_MAPS_API_KEY = “AIzaSyCard2PScx5ziEsMJ8MwysTeEUHh8f19iY”

# Create a directory to store images

IMAGE_DIR = “roof_images”

os.makedirs(IMAGE_DIR, exist_ok=True)

print(“The script is starting…”)  # Debugging print

# Function to format the address using Google Maps API

def format_address(address):

    print(f”Formatting address: {address}”)  # Debugging print

    time.sleep(1)  # Add a delay to avoid blocking

    url = f”https://maps.googleapis.com/maps/api/geocode/json?address={address}&key={GOOGLE_MAPS_API_KEY}”

    response = requests.get(url)

    if response.status_code == 200:

        data = response.json()

        if data[“status”] == “OK”:

            formatted = data[“results”][0][“formatted_address”]

            print(f”Formatted address: {formatted}”)  # Debugging print

            return formatted

    print(f”Could not format address: {address}”)  # Debugging print

    return address  # Return original if formatting fails

# Function to get latitude and longitude using Google Maps API

def get_lat_lon(address):

    print(f”Getting coordinates for: {address}”)  # Debugging print

    time.sleep(1)  # Add a delay to avoid blocking

    url = f”https://maps.googleapis.com/maps/api/geocode/json?address={address}&key={GOOGLE_MAPS_API_KEY}”

    response = requests.get(url)

    if response.status_code == 200:

        data = response.json()

        if data[“status”] == “OK”:

            location = data[“results”][0][“geometry”][“location”]

            print(f”Coordinates for {address}: {location[‘lat’]}, {location[‘lng’]}”)  # Debugging print

            return location[“lat”], location[“lng”]

    print(f”Could not get coordinates for: {address}”)  # Debugging print

    return None, None

# Function to fetch satellite image

def fetch_satellite_image(lat, lon, address):

    url = f”https://maps.googleapis.com/maps/api/staticmap?center={lat},{lon}&zoom=20&size=600×600&maptype=satellite&key={GOOGLE_MAPS_API_KEY}”

    print(f”Fetching image for {address} at {url}”)

    response = requests.get(url)

    if response.status_code == 200:

        image_path = os.path.join(IMAGE_DIR, f”{address.replace(‘ ‘, ‘_’)}.png”)

        with open(image_path, “wb”) as file:

            file.write(response.content)

        print(f”Saved image to {image_path}”)

        return image_path

    else:

        print(f”Failed to fetch image for {address} with status code {response.status_code}”)

    return None

# Load CSV with separate address columns and process it

def process_csv(csv_file):

    print(f”Reading CSV file: {csv_file}”)  # Debugging print

    df = pd.read_csv(csv_file)

    print(“CSV read successfully!”)  # Debugging print

    df[“Full Address”] = df[“Street Address”] + “, ” + df[“City”] + “, ” + df[“State”] + ” ” + df[“Zip Code”].astype(str)

    print(“Formatting addresses…”)  # Debugging print

    df[“Formatted Address”] = df[“Full Address”].apply(format_address)

    print(“Processing addresses for images…”)  # Debugging print

    for index, row in df.iterrows():

        address = row[“Formatted Address”]

        print(f”Processing: {address}”)  # Debugging print

        lat, lon = get_lat_lon(address)

        if lat and lon:

            print(f”Fetching image for {address}”)  # Debugging print

            image_path = fetch_satellite_image(lat, lon, address)

            df.at[index, “Image Path”] = image_path

        else:

            print(f”Skipping {address}, no coordinates found.”)  # Debugging print

    output_csv = “output_with_images.csv”

    df.to_csv(output_csv, index=False)

    print(f”Processing complete. Output saved to {output_csv}”)  # Debugging print

print(“Starting CSV processing…”)

process_csv(“kansas.csv”)