QML parking detection

gistfile1.txt

import pennylane as qml
import sqlite3
import time
import openai
import json
from google.cloud import vision_v1
from google.cloud.vision_v1 import types
from pennylane import numpy as np
import cv2


# Quantum Language Model
class QuantumLanguageModel:
    def __init__(self, num_qubits):
        self.num_qubits = num_qubits
        self.dev = qml.device('default.qubit', wires=self.num_qubits)

    def quantum_layer(self, params):
        for i in range(self.num_qubits):
            qml.RY(params[i], wires=i)
        for i in range(self.num_qubits - 1):
            qml.CNOT(wires=[i, i+1])

    def quantum_model(self, params):
        for _ in range(len(params)):
            self.quantum_layer(params)

# Database Manager
class DatabaseManager:
    def __init__(self, db_name):
        self.conn = sqlite3.connect(db_name)
        self.cursor = self.conn.cursor()

    def create_tables(self):
        self.cursor.execute("""
        CREATE TABLE IF NOT EXISTS illegal_parking_signs (
            location TEXT,
            sign_details TEXT
        )
        """)
        self.cursor.execute("""
        CREATE TABLE IF NOT EXISTS illegal_parking_log (
            license_plate TEXT,
            location TEXT,
            timestamp TEXT,
            tag_status TEXT
        )
        """)
        self.conn.commit()

    def insert_illegal_parking(self, license_plate, location, timestamp, tag_status):
        self.cursor.execute("INSERT INTO illegal_parking_log (license_plate, location, timestamp, tag_status) VALUES (?, ?, ?, ?)", (license_plate, location, timestamp, tag_status))
        self.conn.commit()

    def get_last_illegal_parkings(self, count=5):
        self.cursor.execute("SELECT license_plate, location, timestamp FROM illegal_parking_log ORDER BY ROWID DESC LIMIT ?", (count,))
        return self.cursor.fetchall()

    def close(self):
        self.conn.close()

# Illegal Parking Detector
class IllegalParkingDetector:
    def __init__(self, db_name="parking.db"):
        self.qml_model = QuantumLanguageModel(2)
        self.db_manager = DatabaseManager(db_name)
        self.db_manager.create_tables()
        self.client = vision_v1.ImageAnnotatorClient()

    def extract_license_plate(self, image_path):
        with open(image_path, 'rb') as image_file:
            content = image_file.read()
        image = types.Image(content=content)
        response = self.client.text_detection(image=image)
        texts = response.text_annotations
        license_plate = texts[0].description if texts else None
        return license_plate

    def map_license_plate_to_qml_parameters(self, license_plate):
        prompt = f"Map the license plate '{license_plate}' to Quantum Language Model parameters."
        system_message = {'role': 'system', 'content': 'Map the license plate to QML parameters.'}
        response = openai.ChatCompletion.create(
            model='gpt-3.5-turbo',
            messages=[system_message, {'role': 'user', 'content': prompt}],
        )
        user_reply = response['choices'][0]['message']['content']
        params = json.loads(user_reply).get("parameters", [])
        return [float(val) for val in params]

    def encode_parking_info_into_qml(self, parking_params):
        np.random.seed(42)
        @qml.qnode(self.qml_model.dev)
        def circuit(params):
            self.qml_model.quantum_model(params)
            return [qml.expval(qml.PauliZ(wires=i)) for i in range(self.qml_model.num_qubits)]
        return circuit(parking_params)

    def check_active_tag_stickers(self, license_plate):
        prompt = f"Check if the license plate '{license_plate}' has active tag stickers."
        system_message = {'role': 'system', 'content': 'Check for active tag stickers.'}
        response = openai.ChatCompletion.create(
            model='gpt-3.5-turbo',
            messages=[system_message, {'role': 'user', 'content': prompt}],
        )
        user_reply = response['choices'][0]['message']['content']
        return user_reply


    def detect_illegal_parking(self, input_image):
        location = self.get_current_location()
        location_str = f"{location[0]}, {location[1]}"
        timestamp = time.strftime("%Y-%m-%d %H:%M:%S")
        license_plate = self.extract_license_plate(input_image)
        if license_plate:
            parking_params = self.map_license_plate_to_qml_parameters(license_plate)
            qml_results = self.encode_parking_info_into_qml(parking_params)
            legal_score, illegal_score = qml_results
            tag_status = self.check_active_tag_stickers(license_plate)
            if illegal_score > legal_score:
                self.db_manager.insert_illegal_parking(license_plate, location_str, timestamp, tag_status)
                return "Illegal Parking Detected"
            else:
                return "Legal Parking"
        else:
            return "License Plate Not Found"

# TUI Interface
class ParkingTUI:
    def __init__(self, detector):
        self.detector = detector
        self.camera = cv2.VideoCapture(0)

    def main_menu(self):
        while True:
            print("\nIllegal Parking Detector")
            print("1. Detect Illegal Parking")
            print("2. View Last 5 Illegally Parked Vehicles")
            print("3. Exit")
            choice = input("Please choose an option (1-3): ")
            if choice == '1':
                self.detect_parking()
            elif choice == '2':
                self.view_last_parkings()
            elif choice == '3':
                print("Exiting...")
                break
            else:
                print("Invalid choice. Please try again.")

    def detect_parking(self):
        print("Detecting illegal parking...")
        ret, frame = self.camera.read()
        if ret:
            image_path = "temp_image.jpg"
            cv2.imwrite(image_path, frame)
            result = self.detector.detect_illegal_parking(image_path)
            print("Result:", result)
        else:
            print("Error: Unable to capture image from camera.")

    def view_last_parkings(self):
        print("\nLast 5 Illegally Parked Vehicles:")
        last_parkings = self.detector.db_manager.get_last_illegal_parkings()
        for parking in last_parkings:
            print(f"License Plate: {parking[0]}, Location: {parking[1]}, Time: {parking[2]}")

# Main function
def main():
    detector = IllegalParkingDetector()
    tui = ParkingTUI(detector)
    tui.main_menu()

if __name__ == "__main__":
    main()