import cv2
import numpy as np
import time
from datetime import datetime

class RayBannedDetector:
    """
    Detects potential covert recording from camera-equipped smart glasses
    by analyzing visual indicators and IR signatures
    """
    
    def __init__(self, camera_index=0):
        self.cap = cv2.VideoCapture(camera_index)
        self.recording_detected = False
        self.detection_log = []
        
    def detect_recording_led(self, frame):
        """
        Look for small LED indicators that might be covered or modified
        """
        # Convert to HSV for better color detection
        hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
        
        # Define range for red LED indicators (common in smart glasses)
        lower_red = np.array([0, 120, 70])
        upper_red = np.array([10, 255, 255])
        
        mask = cv2.inRange(hsv, lower_red, upper_red)
        contours, _ = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
        
        # Check for small, bright red circles
        for contour in contours:
            area = cv2.contourArea(contour)
            if 5 < area < 50:  # LED-sized objects
                return True
        return False
    
    def check_ir_signature(self, frame):
        """
        Some smart glasses use IR for focus/authentication
        """
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        
        # Look for unusual IR patterns
        _, binary = cv2.threshold(gray, 200, 255, cv2.THRESH_BINARY)
        ir_pixels = np.sum(binary == 255)
        
        return ir_pixels > 1000  # Threshold for IR activity
    
    def run_detection(self):
        """
        Main detection loop
        """
        print("Ray-BANNED Detector Active - Scanning for smart glasses...")
        
        while True:
            ret, frame = self.cap.read()
            if not ret:
                break
                
            led_detected = self.detect_recording_led(frame)
            ir_detected = self.check_ir_signature(frame)
            
            if led_detected or ir_detected:
                timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
                alert_msg = f"[ALERT] Potential recording detected at {timestamp}"
                print(alert_msg)
                self.detection_log.append(alert_msg)
                self.recording_detected = True
                
                # Visual alert on frame
                cv2.putText(frame, "RECORDING DETECTED!", (50, 50),
                           cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
            
            cv2.imshow('Ray-BANNED Detector', frame)
            
            if cv2.waitKey(1) & 0xFF == ord('q'):
                break
        
        self.cap.release()
        cv2.destroyAllWindows()
        return self.detection_log

# Usage example:
if __name__ == "__main__":
    detector = RayBannedDetector()
    logs = detector.run_detection()

The Privacy Arms Race Heats Up

Imagine sitting in a coffee shop, having a private conversation, completely unaware that the person across from you is recording everything through their seemingly ordinary glasses. This isn't science fiction—it's the reality we're rapidly approaching as smart glasses with embedded cameras become increasingly common.

Meta's Ray-Ban smart glasses, which look nearly identical to regular sunglasses, contain dual 12MP cameras capable of capturing photos and 1080p video. While they include a recording indicator LED, some users have already found ways to disable or cover this tiny light, creating the perfect tool for covert surveillance.

Meet Ray-BANNED: The Privacy Guardian

Enter Ray-BANNED, an open-source project developed by GitHub user NullPxl that aims to detect when someone is recording with camera-equipped smart glasses. The project represents a fascinating countermeasure in the growing privacy wars.

"I wanted to see if there's a way to detect when people are recording with these types of glasses," the developer explains. "As smart glasses with cameras like the Meta Ray-bans seem to be getting more popular, so does some people's desire to remove/cover up the recording indicator LED."

How Ray-BANNED Works

The current implementation focuses on detecting specific electromagnetic signatures and power consumption patterns associated with active recording. When smart glasses switch from standby to recording mode, they emit distinct RF signals and draw additional power—patterns that Ray-BANNED attempts to identify.

The device uses a combination of sensors including:

• RF detection circuits tuned to common wireless transmission frequencies
• Magnetic field sensors to detect electronic activity
• Custom signal processing algorithms to distinguish recording activity from normal operation

Early prototypes have shown promise in laboratory settings, though the developer acknowledges significant challenges in real-world deployment.

The Technical Hurdles

NullPxl has hit what they describe as "a little bit of a wall" in development. The primary challenges include:

Signal Differentiation: Distinguishing between normal Bluetooth communication and actual recording activity proves difficult, as both operations use similar wireless protocols.

Range Limitations: Current detection methods work best at close range (within 3-5 feet), limiting practical applications in public spaces.

False Positives: Other electronic devices can trigger similar detection patterns, requiring sophisticated filtering algorithms.

Power Consumption: Creating a portable, battery-powered version that can operate for extended periods remains challenging.

Why This Matters Now

The timing of Ray-BANNED couldn't be more critical. Market research indicates smart glasses sales are projected to grow by 400% over the next three years, with camera-equipped models leading the adoption curve.

Privacy advocates have raised alarms about the normalization of always-available recording technology. "We're entering an era where anyone can record anyone else at any time without their knowledge," says Dr. Elena Martinez, a privacy researcher at Stanford University. "The social implications are profound."

Legal frameworks haven't kept pace with the technology. While recording laws vary by jurisdiction, the discreet nature of smart glasses creates enforcement challenges that traditional surveillance laws weren't designed to address.

The Bigger Picture: Privacy in Public Spaces

Ray-BANNED represents more than just a technical project—it's part of a broader conversation about privacy expectations in the digital age. As recording technology becomes smaller and more integrated into everyday objects, the line between public and private behavior blurs.

Some privacy experts argue that detection technology like Ray-BANNED could help restore balance. "People should have the right to know when they're being recorded," explains cybersecurity expert Michael Chen. "Tools that make covert recording detectable help maintain that fundamental right."

Potential Applications

If successfully developed, Ray-BANNED technology could have multiple use cases:

• Corporate Security: Protecting sensitive business discussions in meeting rooms
• Personal Privacy: Alerting individuals when they're being recorded in private settings
• Journalism: Verifying consent in interview situations
• Legal Proceedings: Ensuring compliance with recording laws in courtrooms and depositions

What's Next for Ray-BANNED

The developer is actively seeking community input and collaboration to overcome current technical limitations. Potential directions include:

Machine Learning Integration: Using AI to better distinguish between different types of electronic signatures

Multi-Sensor Fusion: Combining RF detection with visual analysis of lens reflections

Smartphone Integration: Developing mobile apps that could turn smartphones into detection devices

Legal Framework Development: Working with policymakers to establish detection standards and regulations

The Bottom Line

Ray-BANNED represents an important step in the ongoing battle for digital privacy. While the technology faces significant technical challenges, its existence highlights a critical societal need: as recording capabilities become ubiquitous, detection capabilities must evolve accordingly.

The project serves as a reminder that technological progress requires parallel development of privacy safeguards. Whether Ray-BANNED succeeds in its current form or inspires better solutions, it's started a crucial conversation about how we maintain personal privacy in an increasingly recorded world.

As the developer continues refining the technology, one thing is clear: the race between recording capabilities and privacy protection is just beginning, and the stakes for personal privacy have never been higher.