diff --git a/scripts/UserImageDownload.py b/scripts/UserImageDownload.py
new file mode 100644
index 0000000..1474a35
--- /dev/null
+++ b/scripts/UserImageDownload.py
@@ -0,0 +1,129 @@
+import os
+import firebase_admin
+from firebase_admin import credentials, firestore
+import pandas as pd
+from urllib.request import urlopen
+import datetime
+import tkinter as tk
+from tkinter import filedialog
+
+# Initialize Firebase Admin SDK
+cred = credentials.Certificate(r'C:\Users\smila\PycharmProjects\pythonProject\hpos-prod-firebase-adminsdk-bionp-5486f7becd.json')  # Replace with your own service account key path
+firebase_admin.initialize_app(cred)
+
+# Get a reference to the Firestore database
+db = firestore.client()
+
+# Specify the collections
+patient_collection = db.collection("patientData")
+test_collection = db.collection("testData")
+
+# Create a tkinter root window (hidden)
+root = tk.Tk()
+root.withdraw()
+
+# Ask the user to select the base folder where images and data will be saved
+base_output_folder = filedialog.askdirectory(title="Select Base Output Folder")
+
+# Get user-defined date ranges
+start_date = "2023-08-01"
+end_date = "2023-08-10"
+
+# Parse the date range to get a list of days
+start_datetime = datetime.datetime.strptime(start_date, "%Y-%m-%d")
+end_datetime = datetime.datetime.strptime(end_date, "%Y-%m-%d")
+date_range = [start_datetime + datetime.timedelta(days=x) for x in range((end_datetime - start_datetime).days + 1)]
+
+# Iterate through each day
+for date in date_range:
+    current_date = date.strftime("%Y-%m-%d")
+    output_folder = os.path.join(base_output_folder, current_date)
+    os.makedirs(output_folder, exist_ok=True)
+
+    print(f"Processing data for {current_date}...")
+
+    # Query Firestore for patient data
+    query = patient_collection.where("createdAt", ">=", current_date).where("createdAt", "<", (date + datetime.timedelta(days=1)).strftime("%Y-%m-%d"))
+    patient_docs = query.stream()
+
+    # Initialize a list to hold the combined data
+    data = []
+
+    # Iterate through patient documents
+    for patient_doc in patient_docs:
+        patient_data = patient_doc.to_dict()
+        patient_id = patient_data["_id"]
+
+        # Query the document from testData collection based on the common _id
+        test_docs = test_collection.where("_id", "==", patient_id).stream()
+
+        # Iterate through test documents
+        for test_doc in test_docs:
+            test_data = test_doc.to_dict()
+
+            # Combine the data from both collections into a single dictionary
+            combined_data = {**patient_data, **test_data}
+
+            # Access specific attributes from the combined data
+            csv_path = combined_data.get("csvPath", "")
+            if csv_path and not csv_path.startswith("http"):
+                # Perform the desired action
+                print("CSV path does not start with 'http'.")
+
+            # Append the combined_data dictionary to the list
+            data.append(combined_data)
+
+            # Download images separately and store them in the specified folder
+            user_image_url = combined_data.get("userImageURL", "")
+            if user_image_url and user_image_url.startswith("http"):
+                image_data = urlopen(user_image_url).read()
+                image_filename = f"{patient_id}.jpg"  # Use only patient ID as the filename
+                image_path = os.path.join(output_folder, image_filename)
+                with open(image_path, "wb") as image_file:
+                    image_file.write(image_data)
+
+    # Convert the data to a DataFrame
+    df = pd.DataFrame(data)
+
+    # Rename columns
+    df.rename(columns={
+        "name": "Name",
+        "abhaId": "ABHA ID",
+        "birthYear": "Age",
+        "gender": "Gender",
+        "category": "Category",
+        "maritalStatus": "Marital Status",
+        "careOf": "Care-of",
+        "city": "Address",
+        "district": "District",
+        "state": "State",
+        "pinCode": "Pincode",
+        "phoneNumber": "Mobile Number",
+        "bloodGroup": "Blood group",
+        "result": "Test Result"
+    }, inplace=True)
+
+    # Select specific columns
+    selected_columns = [
+        "Name", "ABHA ID", "Age", "Gender", "Category", "Marital Status",
+        "Care-of", "Address", "District", "State", "Pincode", "Mobile Number",
+        "Blood group", "Test Result"
+    ]
+
+    # Check if selected columns are present in the DataFrame
+    missing_columns = [col for col in selected_columns if col not in df.columns]
+    if missing_columns:
+        print(f"Missing columns: {missing_columns}")
+    else:
+        # Create a new DataFrame with selected columns
+        df = df[selected_columns]
+
+        # Save the DataFrame to a CSV file
+        output_filename = f"data_{current_date}.csv"
+        output_path = os.path.join(output_folder, output_filename)
+        df.to_csv(output_path, index=False)
+
+        print(f"Data and images for {current_date} saved to '{output_folder}'")
+
+# Close the Firebase Admin SDK
+firebase_admin.delete_app(firebase_admin.get_app())