Reference for ultralytics/solutions/security_alarm.py

def authenticate(self, from_email: str, password: str, to_email: str) -> None:
    """Authenticate the email server for sending alert notifications.

    This method initializes a secure connection with the SMTP server and logs in using the provided credentials.

    Args:
        from_email (str): Sender's email address.
        password (str): Password for the sender's email account.
        to_email (str): Recipient's email address.

    Examples:
        >>> alarm = SecurityAlarm()
        >>> alarm.authenticate("sender@example.com", "password123", "recipient@example.com")
    """
    import smtplib

    self.server = smtplib.SMTP("smtp.gmail.com: 587")
    self.server.starttls()
    self.server.login(from_email, password)
    self.to_email = to_email
    self.from_email = from_email

def process(self, im0) -> SolutionResults:
    """Monitor the frame, process object detections, and trigger alerts if thresholds are exceeded.

    This method processes the input frame, extracts detections, annotates the frame with bounding boxes, and sends
    an email notification if the number of detected objects surpasses the specified threshold and an alert has not
    already been sent.

    Args:
        im0 (np.ndarray): The input image or frame to be processed and annotated.

    Returns:
        (SolutionResults): Contains processed image `plot_im`, 'total_tracks' (total number of tracked objects) and
            'email_sent' (whether an email alert was triggered).

    Examples:
        >>> alarm = SecurityAlarm()
        >>> frame = cv2.imread("path/to/image.jpg")
        >>> results = alarm.process(frame)
    """
    self.extract_tracks(im0)  # Extract tracks
    annotator = SolutionAnnotator(im0, line_width=self.line_width)  # Initialize annotator

    # Iterate over bounding boxes and classes index
    for box, cls in zip(self.boxes, self.clss):
        # Draw bounding box
        annotator.box_label(box, label=self.names[cls], color=colors(cls, True))

    total_det = len(self.clss)
    if total_det >= self.records and not self.email_sent:  # Only send email if not sent before
        self.send_email(im0, total_det)
        self.email_sent = True

    plot_im = annotator.result()
    self.display_output(plot_im)  # Display output with base class function

    # Return a SolutionResults
    return SolutionResults(plot_im=plot_im, total_tracks=len(self.track_ids), email_sent=self.email_sent)

def send_email(self, im0, records: int = 5) -> None:
    """Send an email notification with an image attachment indicating the number of objects detected.

    This method encodes the input image, composes the email message with details about the detection, and sends it
    to the specified recipient.

    Args:
        im0 (np.ndarray): The input image or frame to be attached to the email.
        records (int, optional): The number of detected objects to be included in the email message.

    Examples:
        >>> alarm = SecurityAlarm()
        >>> frame = cv2.imread("path/to/image.jpg")
        >>> alarm.send_email(frame, records=10)
    """
    from email.mime.image import MIMEImage
    from email.mime.multipart import MIMEMultipart
    from email.mime.text import MIMEText

    import cv2

    img_bytes = cv2.imencode(".jpg", im0)[1].tobytes()  # Encode the image as JPEG

    # Create the email
    message = MIMEMultipart()
    message["From"] = self.from_email
    message["To"] = self.to_email
    message["Subject"] = "Security Alert"

    # Add the text message body
    message_body = f"Ultralytics ALERT!!! {records} objects have been detected!!"
    message.attach(MIMEText(message_body))

    # Attach the image
    image_attachment = MIMEImage(img_bytes, name="ultralytics.jpg")
    message.attach(image_attachment)

    # Send the email
    try:
        self.server.send_message(message)
        LOGGER.info("Email sent successfully!")
    except Exception as e:
        LOGGER.error(f"Failed to send email: {e}")