app.py

```bash
pip install opencv-python face-recognition simple-salesforce
```

### Python Code

```python
import cv2
import face_recognition
import os
from simple_salesforce import Salesforce
from datetime import datetime

# Salesforce connection
sf = Salesforce(username='your_username', password='your_password', security_token='your_security_token')

# Function to query Salesforce for PAN and Aadhar match
def query_salesforce(pan, aadhaar):
    # Query staff
    staff_query = f"SELECT Id, Name FROM Staff__c WHERE PAN__c = '{pan}' OR Aadhar__c = '{aadhar}'"
    staff_result = sf.query(staff_query)
    
    if staff_result['totalSize'] > 0:
        return f"Match found in Staff: {staff_result['records'][0]['Name']}"
    
    # Query customer
    customer_query = f"SELECT Id, Name FROM Customer__c WHERE PAN__c = '{pan}' OR Aadhar__c = '{aadhar}'"
    customer_result = sf.query(customer_query)
    
    if customer_result['totalSize'] > 0:
        return f"Match found in Customer: {customer_result['records'][0]['Name']}"
    
    return None

# Function to send alert if no match found
def send_alert():
    print("ALERT: No match found in Salesforce for the captured face!")

# Load known faces (you should have a known_faces folder with images of staff and customers)
known_faces_dir = 'known_faces'
known_faces = []
known_names = []

# Iterate over each file in the known_faces folder
for filename in os.listdir(known_faces_dir):
    image_path = os.path.join(known_faces_dir, filename)
    image = face_recognition.load_image_file(image_path)
    encoding = face_recognition.face_encodings(image)[0]
    known_faces.append(encoding)
    known_names.append(filename.split('.')[0])  # Assuming file name format is staff or customer name

# Read images from folder
image_folder = 'images_to_check'
for filename in os.listdir(image_folder):
    image_path = os.path.join(image_folder, filename)
    unknown_image = face_recognition.load_image_file(image_path)
    
    # Detect faces
    face_locations = face_recognition.face_locations(unknown_image)
    face_encodings = face_recognition.face_encodings(unknown_image, face_locations)
    
    for face_encoding in face_encodings:
        # Compare the detected face with known faces
        matches = face_recognition.compare_faces(known_faces, face_encoding)
        face_distances = face_recognition.face_distance(known_faces, face_encoding)
        best_match_index = face_distances.argmin()

        # Capture timestamp
        timestamp = datetime.now().strftime('%Y-%m-%d %H:%M:%S')

        if matches[best_match_index]:
            name = known_names[best_match_index]
            print(f"Face matched with {name} at {timestamp}")
            # You can add logic to fetch PAN/Aadhar and call Salesforce for match verification
            # pan = ... (Fetch corresponding PAN from your dataset)
            # aadhaar = ... (Fetch corresponding Aadhar from your dataset)
            # result = query_salesforce(pan, aadhar)
            # if result:
            #     print(result)
            # else:
            #     send_alert()
        else:
            send_alert()

```