{ "cells": [ { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "# Initialschätzung von Kurswechselpositionen eines Segelboots auf einer Karte anhang con Wind, Start und Zielpunkt\n", "\n", "## Motivation\n", "\n", "Ziel dieser Semester abschließenden schriftlichen Ausarbeitung im Fach \"Maschine Learning\" an der Fachhochschule Südwestfalen ist das Generieren einer Heatmap von Kurswechselpositionen eines Segelbootes zu einer Karte abhängig von Wind und der Zielpostion. Dies soll das Finden einer guten Route vereinfachen, indem die Qualität einer ersten Route, die danach über ein Quotientenabstiegsverfahren optimiert werden soll verbessern. Da ein solches Quotientenabstiegsverfahren sehr gerne in einem Lokalen minimum festhängt, müssen mehrere routen gefunden und optimiert werden. Hier soll untersucht werden, ob dies durch eine Ersteinschätzung der Lage durch KI verbessert werden kann.\n", "\n", "Eingesetzt werden soll die so erstellte KI in dem Segelroboter des [Sailing Team Darmstadt e.V.](https://www.st-darmstadt.de/) Einer Hochschulgruppe an der TU-Darmstadt welche den [\"roBOOTer\"](https://www.st-darmstadt.de/ueber-uns/boote/prototyp-ii/) ein vollautonomes Segelboot welches eines Tages den Atlantik überqueren soll. [Eine technische Herausforderung welche zuerst von einem norwegischen Team erfolgreich abgeschlossen wurde](https://www.microtransat.org/)." ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "## Inhaltsverzeichnis\n", "\n", "1. Einleitung\n", "\n", " 1.1. Situation\n", " \n", " 1.2. Vorgehen zur unterstützenden KI\n", " 1.2.1. Eingaben und Ausgeben\n", "2. Vorbereitungen\n", "\n", " 2.1. Imports\n", " \n", " 2.2. Parameter und Settings\n", " \n", "3. Szenarien und Routen Generieren\n", "\n", " 3.1. Generieren von Karten\n", " 3.2.1 Paremter zum Generieren der Karte\n", " \n", " 3.2. Generieren des Zieles\n", " \n", " 3.3. Das Normieren eines Scenarios\n", " \n", " 3.4. Massengenerierung von Scenarios\n", " \n", " 3.5. Daten Zusammenfassen\n", "\n", "4. Sencarios Filtern\n", "\n", " 4.1. Die Route verlässt die Karte\n", " \n", " 4.2. Routen auf Fehler überprüfen\n", " \n", " 4.3. Filter der Routen nach Kosten\n", " \n", " 4.4. Filter der Routen nach Komplexität\n", " \n", "5. Das konvertieren in trainierbare Daten\n", "\n", "6. Das KI Model erstellen\n", " \n", " 6.1. Der Generator\n", " \n", " \n", "\n", "7. Training\n", "\n", "8. Analyse der KI\n", "\n", "9. Ausblick\n", " \n", "10. Literaturverzeichnis" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "## Einleitung\n", "\n", "### Situation\n", "\n", "Eine Routenplanung für ein Segelboot hat ein Problem, welches man sonst so eher nicht kennt. Eine relativ freie Fläche auf der Sich das Schiff bewegen kann. Dies verändert die Wegfindung wie man sie von der Straße kennt fundamental.\n", "\n", "Navigiert man auf Straßen, hat man zumindest nach einer ersten abstraction relativ wenige Freiheitsgrade für den Weg.\n", "Die Richtung kann nur an Kreuzungen gewechselt werden und dort nur in Richtungen in die es Straßen gibt. Beim Segeln auf dem freien Meer ist jeder Ort ein potenzieller Wendepunkt von dem aus Potenziell in jede Richtung gesegelt werden kann.\n", "\n", "Dennoch ist es oft auch ohne Hindernisse zwischen Boot und Ziel oft nicht möglich das Ziel direkt anzufahren das sich die Maximalgeschwindigkeiten relativ zur Windrichtung verändern.\n", "Das folgende Diagramm zeigt die Segelgeschwindigkeiten an einem Katamaran.\n", "\n", "\"Ship\n", "\n", "Da der roBOOTer anders als an Katamaran nicht auf Geschwindigkeit, sondern auf mechanische Belastbarkeit ausgelegt wurde hat der Fahrtwind einen geringeren einfluss auf das Fahrtverhalten des Segelboots dies und eine andere Maximalgeschwindigkeit sorgen für ein etwas anderes Fahrverhalten. Die ungefähre Form der Kurven trifft aber auch auf den roBOOTer zu. Man kann deutlich erkennen das auch, wenn man nicht direkt gegen den Wind fahren kann man schräg gegen den wind immer noch erstaunlich schnell ist.\n", "\n", "Das aktuelle Verfahren zum Finden einer Route läuft folgendermaßen ab:\n", "\n", "Eine direkte Route wird berechnet. Die Route wird an jedem Hindernisse geteilt und rechts und links um jedes hindernis herum gelegt. Bei folgenden hindernissen werden die Routen wieder geteilt somit erhält man $2^n$ Vorschläge für Routen, wobei $n$ die Anzahl der Hindernisse auf der Route ist. Jeder Abschnitt der Route wird noch einmal zerteilt, um der Route mehr Flexibilität zu geben.\n", "\n", "Die Routen werden dann simuliert, um die Kosten der Route zu berechnen. Die so simulierte Route wird danach über die Kosten in einem Gradientenabstiegsverfahren optimiert.\n", "\n", "Das ganze oben beschriebene Verfahren ist relativ schnell sehr rechenaufwendig und findet nicht immer ein Ergebnis. Wird kein Ergebnis gefunden wird eine mehr oder weniger zufällige Route optimiert.\n", "\n", "Diese Ausarbeitung soll wenigstens bei der alternativen Routenfindung helfen. Im idealfall kann es aber auch genutzt werden, um die auswahl der Routen um Hindernisse frühzeitig zu reduzieren und den Rechenaufwand unter $2^n$ zu senken wobei $n$ die Anzahl von Hindernissen auf der Route ist.\n", "\n", "### Vorgehen zur unterstützenden KI\n", "\n", "#### Eingaben und Ausgeben\n", "\n", "Die Algorithm zur Wegfindung vom Sailing Team Darmstadt e.V. arbeiten intern mit Polygonen als Hindernissen. Diese werden durch die Shapely Bibliothek implementiert. Da eine variable Anzahl an Polygonen mit einer variablen Form und Position eine Relative komplexer Input muss dieser in eine normierte Form gebracht werden. Ein binärfärbens Bild ist dafür die einfachste Form.\n", "\n", "Für den Computer spielen sowohl Zentrierung, Skalierung und Ausrichtung der Karte keine Rolle.\n", "Wir rotieren also die Karte immer so das der Wind von *Norden* kommt und das Boot / die Startposition in der *Mitte* der Karte liegt. Da distanz Liner ist, wird davon ausgegangen das Scenario einfach skaliert passend skaliert werden kann.\n", "\n", "Die nächste eingabe ist die Zielposition relativ zum Startpunkt. Diese kann entweder durch ein einzelnes Pixel in einem zweiten Farbkanal oder aber in abstrakterer Form an die KI übergeben werden.\n", "\n", "Als ausgabe wird eine Heatmap erwartet. Zwei alternative Heatmaps sind relative einfach denkbar.\n", "\n", "1. Eine Headmap der Kurswechselpositionen\n", "2. Eine Headmap des Kursverlaufes\n", "\n", "Headmaps sind in gewisser Weise Bilder. Das Problem wird daher wie ein Bild zu Bild KI Problem betrachtet. Diese werden normalerweise durch ANNs gelöst.\n", "\n", "Um eine ANN zu trenntieren gibt es immer die Wahl zwischen drei Primären prinzipien. Dem unüberwachten Lernen, dem reinforcement Learning und dem überwachten Lernen. Letzteres ist dabei meist am einfachsten wenn auch nicht immer möglich.\n", "\n", "Der Wegfindealgorithmus des Sailing Team Darmstadt e.V. ist zwar noch in der Entwicklung, funktioniert aber hinreichend gut, um auf einem normalen PC Scenarios mit Routen zu paaren oder auch diese zu *labeln*, um beim KI lingo zu bleiben. Um anpassungsfähig an andere Scenarios zu sein wird eine große Menge unterschiedlicher Scenarios und Routen benötigt.\n", "Da das Haupteinsatzgebiet das Meer ist gehen wir von einer Insellandschaft oder Küstenlandschaft aus.\n", "\n", "Zum Finden von Scenarios gibt es zwei Möglichkeiten.\n", "\n", "1. Das Auswählen von umgebungen von der Weltkarte und das Bestimmen eines Zielpunktes.\n", "2. Das Generieren von künstlichen Scenarios.\n", " \n", "Hier wird die Annahme getroffen das sich ANNs von einem Datensatz auf dem anderen Übertragen lassen.\n", "Der Aufwand für künstliche Scenarios wird hierbei als geringer eingestuft und daher gewählt." ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "## Vorbereitungen\n", "\n", "Folgende Python Bibliotheken werden verwendet:\n", "\n", "1. `tensorflow`\\\n", " Die `tensorflow` Bibliothek ist das Werkzeug welches verwendet wurde, um neuronale Netz zu modellieren, zu trainieren, zu analysieren und auszuführen. Tensorflow wird mit den kürzel `tf` abgekürzt.\n", "\n", "2. `pyrate`\\\n", " Die `Pyrate` Bibliothek ist Teil des ROS Operating Systems, welches den roBOOTer betreibt. Kann Routen zu Scenarios finden.\n", "\n", "3. `Shapley`\\\n", " Die `shapley` Bibliothek wird genutzt, um geometrische Körper zu generieren, zu mergen und an den Roboter zum Labeln weiterzugeben.\n", "\n", "4. `pandas`\\\n", " Die `pandas` Bibliothek verwaltet, speichert und analysiert daten. `pandas` wird üblicherweise mit `pd` abgekürzt.\n", "\n", "5. `numpy`\\\n", " Eine Bibliothek um Mathematische operations an multidimensionalen Arrays auszuführen. `numpy`wir üblicherweise mit `np` abgekürzt.\n", "\n", "6. `matplotlib`\\\n", " Wird genutzt um Diagramme zu plotted. Das modul `pyplot` wird hier vermehrt genutzt und mit dem kürzel `plt` abgekürzt.\n", "\n", "6. `PIL`\\\n", " Eine Library um Bilder manuell zu zeichnen.\n", "\n", "7. `humanize`\\\n", " Konvertiert Zahlen, Daten und Zeitabstände in ein für menschen einfach leserliches Format.\n", "\n", "8. `tqdm`\\\n", " Fügt einen Fortschrittsbalken zu vielen Problemen hinzu.\n", "\n", "9. `black`\\\n", " Der `black` code Formatier wurde genutzt um den Code in diesem Notebook zu Formatieren." ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "#### Imports\n", "Importiert die Imports the necessary packages from python and pypi." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "import sys\n", "\n", "# Pins the python version executing the Jupyter Notebook\n", "assert sys.version_info.major == 3\n", "assert sys.version_info.minor == 10\n", "\n", "import os\n", "from typing import Optional, Final, Literal\n", "import glob\n", "import pickle\n", "\n", "from tqdm.notebook import tqdm\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import pandas as pd\n", "from PIL import ImageDraw, Image\n", "from shapely.geometry import Polygon, Point, LineString\n", "from shapely.ops import unary_union\n", "# os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"-1\" \n", "import tensorflow as tf\n", "import humanize" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Definiert den Pfad an dem das Jupyter Notebook ausgeführt werden soll.\n", "Importiert die pyrate module. Wird nur ausgeführt, wenn innerhalb des Pyrate Containers ausgeführt." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "C:\\Users\\phorstenkamp\\PycharmProjects\\ml-programmierproject\n" ] } ], "source": [ "# Import route generation if started in the docker container\n", "if os.getenv(\"PYRATE\"):\n", " %cd /pyrate/\n", " import experiments\n", " from pyrate.plan.nearplanner.timing_frame import TimingFrame\n", "\n", "# Protection against multi execution\n", "if not os.path.exists(\"experiments\"):\n", " %cd ../" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "if os.getenv(\"PYRATE\"):\n", " # Sets the maximum number of optimization steps that can be performed to find a route.\n", " # Significantly lowered for more speed.\n", " experiments.optimization_param.n_iter_grad = 50\n", "\n", " # Disables verbose outputs from the pyrate library.\n", " experiments.optimization_param.verbose = False" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "# Activate pandas for tqdm\n", "tqdm.pandas()" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "#### Parameter und Settings\n", "\n", "In der nachfolgenden Sektion werden verschiedene Parameter gesetzt. Zum Beispiel die Skala auf der Routen generiert werden, das äußere Limit für mögliche Ziele und die Minimaldiestanz von Zielen zum Startpunkt." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "# The scale the route should lie in. Only a mathematical limit.\n", "SIZE_ROUTE: Final[int] = 100\n", "\n", "# The outer limit in with the goal need to be placed.\n", "# Should be smaller than\n", "SIZE_INNER: Final[int] = 75\n", "assert SIZE_ROUTE > SIZE_INNER, \"The goal should be well inside the limit placed \"\n", "\n", "# The minimum distance from the start that should\n", "MIN_DESTINATION_DISTANCE: Final[int] = 25\n", "assert (\n", " SIZE_INNER > MIN_DESTINATION_DISTANCE\n", "), \"The goal should be well closer to the outer limit the\"\n", "\n", "# The size the ANN input has. Equal to the image size. Should be an element of $n^2$ to be easier compatible with ANNs.\n", "IMG_SIZE: Final[int] = 128\n", "\n", "# The size an image should be in to be easily visible by eye.\n", "IMG_SHOW_SIZE: Final[int] = 400\n", "\n", "# The number of Files that should be read to train the ANNs\n", "NUMBER_OF_FILES_LIMIT: Final[int] = 500\n", "\n", "#\n", "NO_SHOW = False\n", "GENERATE_NEW = True\n", "\n", "# The path of all the collected files\n", "DATA_COLLECTION_PATH: Final[str] = \"data/collected.pickle\"\n", " \n", "# The \n", "BATCH_SIZE: Final[int] = 32\n", " \n", "os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "## Szenarien und Routen Generieren\n", "\n", "Um das neuronale Netz zu trainieren werden Datensätze benötigt. Für die Abschätzung der Routen wird eine Karte mit Hindernissen und eine zugehörige Route benötigt. Hier wurde die Designentscheidung getroffen die Karten nicht auszuwählen, sondern zu generieren.\n", "\n", "### Generieren von Karten\n", "\n", "Eine Karte ist für das Sailing Team Darmstadt eine Mange von statischen und dynamischen Hindernissen. Statische Hindernisse sind Inseln, Landmassen und Untiefen und Fahrverbotszonen. Dynamische Hindernisse sind andere Teilnehmer am Schiffsverkehr und Wetterereignisse.\n", "In dieser KI wird sich auf statische Hindernisse beschränkt. Daher ist eine Scenario eine Mange an Hindernispolygonen.\n", "Um das Generieren der Polygone einfacher zu regeln und größere statistische Kontrolle über die den Generationsvorgang zu haben sind alle generierten Basispolygone als Abschnitte auf einem Umkreis definiert die Zufällig über die Karte verteilt werden.\n", "\n", "Ein einzelnes Polygon wird hier folgendermaßen generiert:\n", "1. Die Anzahl der Kanten/Ecken wird festgelegt.\n", "2. Ein lognormal verteilter Radius wird zufällig ausgewählt.\n", "3. Auf dem Radius werden n winkel abgetragen.\n", "4. Die Winkel werden sortiert damit sich das Polygon nicht selbst schneidend.\n", "5. Die durch Radius und Winkel entstehenden Punkte werden in das kartesische Koordinatensystem umgewandelt.\n", "6. Der zufällige Offset / Polygon mittelpunkt wird aufaddiert.\n", "7. Aus den so generierten `np.ndarray` wird ein `shapely.geometry.Polygon` erstellt.\n", "8. Polygonen die den Mittelpunkt berühren oder einschließen werden ersatzlos gelöscht.\n", "\n", "So wird eine festgelegte Anzahl von Polygonen generiert.\n", "Setzt man vor dem Generieren des ersten Polygons eines Scenarios eine random seed über `np.random.seed` so erhält man zu jedem seed ein eindeutiges mange an Polygonen wenn auch alle anderen Parameter übereinstimmen. Diese Polygon-mange hat nun mit hoher Wahrscheinlichkeit überlappende Polygone. Dies ist für den Algorithmus des Sailing Teams Darmstadt e.V. ein Problem. Die Shapley Bibliothek besitzt eine Union function die Vereinigungsmengen von Polygonen bildet wenn möglich. So erhält man eine reduzierte mange an Polygonen. Diese kann später an einen Solver übergeben werden." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "# https://stackoverflow.com/questions/16444719/python-numpy-complex-numbers-is-there-a-function-for-polar-to-rectangular-co\n", "def polar_to_cartesian(\n", " radii: np.ndarray,\n", " perigons: np.ndarray,\n", "):\n", " \"\"\"Transforms polar coordinates into cartesian coordinates.\n", "\n", " Args:\n", " radii: A array of radii.\n", " perigons: A array of angles in perigons [0, 1[.\n", "\n", " Returns:\n", " An array of cartesian coordinates.\n", " \"\"\"\n", " return radii * np.exp(2j * perigons * np.pi)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "image/svg+xml": [ "" ], "text/plain": [ "" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "def random_polygon(\n", " radius_mean: float = 2,\n", " radius_sigma: float = 1.5,\n", "):\n", " \"\"\"Generates the simplest of polygons, a triangle with a size described by a random polygon.\n", "\n", " Args:\n", " radius_mean: The average radius defining a circumcircle of a triangle.\n", " radius_sigma: The variance of a radius defining a circumcircle of a triangle.\n", "\n", " Returns:\n", " A single polygon.\n", " \"\"\"\n", " # define the number of corners\n", " number_of_corners = np.random.randint(3, 10)\n", "\n", " # generate cartesian coordinates from a radius and a sorted list of perigons.\n", " array = polar_to_cartesian(\n", " np.random.lognormal(radius_mean, radius_sigma),\n", " np.sort(np.random.rand(number_of_corners)),\n", " )\n", "\n", " # add an offset\n", " offset = np.random.randint(low=-SIZE_ROUTE, high=SIZE_ROUTE, size=(2,))\n", " return_values = np.zeros((number_of_corners, 2), dtype=float)\n", "\n", " return_values[:] = offset\n", " return_values[:, :] += np.array((np.real(array), np.imag(array))).T\n", " return Polygon(return_values)\n", "\n", "\n", "np.random.seed(42)\n", "random_polygon()" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "### Parameter zum Generieren der Karte\n", "\n", "Die folgenden Parameter wurden für das Generieren von Karten genutzt:\n", "* `radius_mean = 2` \n", "* `radius_sigma = 1`\n", "* `number_of_polygons = 40`" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "def generate_obstacles(\n", " seed: Optional[int] = None,\n", " number_of_polygons: int = 40,\n", " radius_mean: float = 2,\n", " radius_sigma: float = 1,\n", ") -> dict[str, Polygon]:\n", " \"\"\"Generates a set of obstacles from a union of triangles.\n", "\n", " The union of triangles meas that if polygons overlap o polygon containing the union of those polygons is returned.\n", " Args:\n", " seed: A seed to generate a set of obstacles from.\n", " number_of_polygons: The number of polygons that should be drawn.\n", " radius_mean: The average radius defining a circumcircle of an obstacle triangle.\n", " radius_sigma: The variance of a radius defining a circumcircle of an obstacle triangle.\n", "\n", " Returns:\n", " A list of unified obstacles.\n", " \"\"\"\n", " # sets a seed\n", " if seed is not None:\n", " np.random.seed(seed)\n", "\n", " # generate a list of polygons\n", " polygons = []\n", " for _ in range(number_of_polygons):\n", " poly = random_polygon(radius_mean, radius_sigma)\n", " # skip polygons that are to close to the start int point P(0, 0)\n", " if poly.contains(Point(0, 0)):\n", " continue\n", " if poly.exterior.distance(Point(0, 0)) < 1:\n", " continue\n", " # append to polygon list\n", " polygons.append(poly)\n", "\n", " # build unions of all polygons\n", " polygon_list = list(unary_union(polygons).geoms)\n", " return {str(i): p for i, p in enumerate(polygon_list)}" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "### Generieren des Zieles\n", "\n", "Zu jedem Scenario gehört neben einer Situation auch ein Ziel. Auch zum Generieren eines Ziels wurde zu erste der gleiche seed gesetzt wie für den Karten Generator. Danach wird eine zufällige Position mit Abstand zum Kartenrand ausgewählt.\n", "Die so generierte Zielposition wird danach auf Plausibilität überprüft. Folgende Prüfungen finden statt:\n", "1. Es wird sichergestellt dass, das Ziel nicht in oder an einem Hindernis liegt.\n", "1. Eine Minimaldistanz in x und y wird sichergestellt. Leider ist hier ein Fehler passiert. Anstelle die Summe der absoluten Distanz zu prüfen wurden die Distanzen für X und Y separat geprüft was verhindert, das Ziele über, unter und neben dem Startpunkt gefunden werden können. Zielpunkte werden nur in den äußeren vier Quadranten gefundene. Bedauerlicherweise ist dies erst aufgefallen als schon zu viel Zeit vergangen war und die Daten nicht neu generiert werden konnten. Dies sollte aber zumindest das Konzept dieser KI nicht beeinflussen. Wohl aber ihre direkte anwendbarkeit." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "POINT (-61 31)\n" ] } ], "source": [ "def generate_destination(\n", " obstacles: dict[str, Polygon],\n", " seed: Optional[int] = None,\n", ") -> Point:\n", " \"\"\"Generates for a map.\n", "\n", " Can be used to generate a valid destination for list of obstacles.\n", " Args:\n", " obstacles: A list of obstacles.\n", " seed: The seed determining the point.\n", "\n", " Returns:\n", " A goal that should be reached by the ship.\n", " \"\"\"\n", " # sets the seed\n", " if seed is not None:\n", " np.random.seed(seed)\n", "\n", " # generates the point\n", " point: Optional[Point] = None\n", " while (\n", " point is None\n", " or abs(point.x) < MIN_DESTINATION_DISTANCE\n", " or abs(point.y) < MIN_DESTINATION_DISTANCE\n", " or any(obstacle.contains(point) for obstacle in obstacles.values())\n", " ):\n", " point = Point(np.random.randint(-SIZE_INNER, SIZE_INNER, size=(2,), dtype=int))\n", " return point\n", "\n", "\n", "print(generate_destination(generate_obstacles(42), 42))" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [] }, { "cell_type": "code", "execution_count": 10, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "def plot_situation(\n", " obstacles: dict[str, Polygon],\n", " destination: Point,\n", " obstacle_color: str | None = \"RED\",\n", " route=None,\n", " legend: bool = True,\n", " title: str | None = None,\n", ") -> None:\n", " \"\"\"PLots the obstacles into a matplotlib plot.\n", "\n", " Args:\n", " obstacles: A list of obstacles.\n", " destination: The destination that should be reached by the boat.\n", " obstacle_color: The color the obstacles should have. Can be None.\n", " If none all obstacles will have different colors.\n", " route: The route that should be plotted.\n", " legend: If true plots a legend.\n", " title: The title of the plot.\n", " Returns:\n", " None\n", " \"\"\"\n", " # Create a plot in the defined size\n", " plt.axis([-SIZE_ROUTE, SIZE_ROUTE, -SIZE_ROUTE, SIZE_ROUTE])\n", "\n", " # Sets a title if one is demanded\n", " if title:\n", " plt.title(title)\n", "\n", " # Plots the obstacles.\n", " if obstacles:\n", " for polygon in obstacles.values():\n", " if obstacle_color is not None:\n", " plt.fill(*polygon.exterior.xy, color=obstacle_color, label=\"Obstacle\")\n", " else:\n", " plt.fill(*polygon.exterior.xy)\n", "\n", " # Plots the wind direction\n", " # The following code for an arrow was taken modeled after:\n", " # https://www.geeksforgeeks.org/matplotlib-pyplot-arrow-in-python/\n", " plt.arrow(\n", " 0,\n", " +int(SIZE_ROUTE * 0.9),\n", " 0,\n", " -int(SIZE_ROUTE * 0.1),\n", " head_width=10,\n", " width=4,\n", " label=\"Wind (3Bft)\",\n", " )\n", "\n", " if route is not None:\n", " if isinstance(route, np.ndarray):\n", " plt.plot(route[:, 0], route[:, 1], color=\"BLUE\", marker=\".\")\n", " else:\n", " if isinstance(route, TimingFrame):\n", " plt.plot(\n", " route.points[:, 0], route.points[:, 1], color=\"BLUE\", marker=\".\"\n", " )\n", " else:\n", " raise TypeError()\n", "\n", " # Plots the estimation\n", " if destination:\n", " plt.scatter(*destination.xy, marker=\"X\", color=\"green\", label=\"Destination\")\n", " plt.scatter(0, 0, marker=\"o\", color=\"green\", label=\"Start\")\n", "\n", " if legend:\n", " # https://stackoverflow.com/questions/13588920/stop-matplotlib-repeating-labels-in-legend\n", " handles, labels = plt.gca().get_legend_handles_labels()\n", " by_label = dict(zip(labels, handles))\n", " plt.legend(by_label.values(), by_label.keys())\n", " return None" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Die aus den Seeds 0 - 11 generierten Karten werden unten angezeigt um Beispiele der von der KI zu Lösenden Scenario zu zeigen.\n", "Wird dieses Notebook im Pyrate Docker Container ausgeführt werden auch die Routen eingezeichnet." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "f7d2138f40624f98a3a2d8e735e1c3db", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/12 [00:00" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "if not NO_SHOW:\n", " # create a subplot with 12 routes.\n", " plt.figure(figsize=(17.5, 25))\n", " for seed in tqdm(range(12)):\n", " plt.subplot(4, 3, seed + 1)\n", " generated_obstacles = generate_obstacles(seed)\n", " generated_destination = generate_destination(generated_obstacles, seed)\n", " route_generated = None\n", "\n", " # try to generate a route\n", " try:\n", " route_generated, _ = experiments.generate_route(\n", " position=Point(0, 0),\n", " goal=generated_destination,\n", " obstacles=generated_obstacles,\n", " wind=(18, 180),\n", " )\n", " except Exception:\n", " route_generated = None\n", "\n", " # plot the situation\n", " plot_situation(\n", " obstacles=generated_obstacles,\n", " destination=generated_destination,\n", " obstacle_color=\"RED\",\n", " route=route_generated,\n", " title=f\"Seed: {seed}, Cost: {route_generated.cost:.3f}\"\n", " if route_generated\n", " else f\"Seed: {seed}\",\n", " legend=(seed == 0),\n", " )\n", " plt.show()" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "### Das Normieren der Scenarios\n", "\n", "Um für ein neuronales Netz Verständlich zu sein ist es immer einfacher, wenn ein Input normieren ist. Hier wurde sich entschieden die Scenarios, als Bilddaten zu normieren. 128 x 128 Pixel sind wesentlich gleichförmiger als eine Mange von maximal 40 Polygonen mit unterschiedlichen Formen. Daher verwandelt die folgende Funktion die mit den Oben definierten Funktionen genierten Scenarios Datensätze in eine Bildform. Rot ist dabei das Hindernis. Grün das Ziel und Blau die Route. Entweder als Linie oder als Punkt, wenn die Route sich ändert.\n", "Für diesen code wurde sich am folgenden Beispiel orientiert. https://programtalk.com/python-examples/PIL.ImageDraw.Draw.polygon/" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "def generate_image_from_map(\n", " obstacles: dict[str, Polygon],\n", " destination: Point,\n", " route=None,\n", " route_type: Literal[\"line\", \"dot\"] = \"dot\",\n", ") -> Image:\n", " \"\"\"Generate an image from the map.\n", "\n", " Can be used to feed an ANN.\n", " - Obstacles are marked as reed.\n", " - The destination is marked as green.\n", " - The points where the route will likely change are blue.\n", "\n", " Args:\n", " obstacles: A dict of obstacles as shapely Polygons. Keyed as a string.\n", " destination: A destination that should be navigated to.\n", " route: The calculated route that should be followed.\n", " route_type: How the route is drawn. If 'line' is selected the complete route is selected.\n", " If 'dot' is selected the turning points a drawn in.\n", " \"\"\"\n", " # generate an empty image (All black)\n", " img = Image.new(\n", " \"RGB\",\n", " (IMG_SIZE, IMG_SIZE),\n", " \"#000000\",\n", " )\n", " draw = ImageDraw.Draw(img)\n", "\n", " # draw in all obstacles in red\n", " for polygon in obstacles.values():\n", " draw.polygon(\n", " list(\n", " (np.dstack(polygon.exterior.xy).reshape((-1)) + SIZE_ROUTE)\n", " / (2 * SIZE_ROUTE)\n", " * IMG_SIZE\n", " ),\n", " fill=\"#FF0000\",\n", " outline=\"#FF0000\",\n", " )\n", "\n", " # draw in a route if possible. Does so in blue\n", " if os.getenv(\"PYRATE\"):\n", " if isinstance(route, TimingFrame):\n", " route = route.points\n", " if route is not None:\n", " route = ((route + SIZE_ROUTE) / (2 * SIZE_ROUTE) * IMG_SIZE).astype(int)\n", " # draws the route as collection of lines\n", " if route_type == \"line\":\n", " draw.line([tuple(point) for point in route], fill=(0, 0, 0xFF))\n", " # draw the route as a collection of points. The starting point is seen as redundant and left out.\n", " elif route_type == \"dot\":\n", " for point in route[1:]:\n", " img.putpixel(point, (0, 0, 0xFF))\n", " else:\n", " raise ValueError(\"Route type unknown.\")\n", " # draws in the destination in green\n", " img.putpixel(\n", " (\n", " int((destination.x + SIZE_ROUTE) / (2 * SIZE_ROUTE) * IMG_SIZE),\n", " int((destination.y + SIZE_ROUTE) / (2 * SIZE_ROUTE) * IMG_SIZE),\n", " ),\n", " (0, 0xFF, 0),\n", " )\n", " return img" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "def generate_example_image(route_type: Literal[\"line\", \"dot\"]):\n", " \"\"\"\n", " Generates an example image with the seed 42.\n", "\n", " Args:\n", " route_type: How the route is drawn. If 'line' is selected the complete route is selected.\n", " If 'dot' is selected the turning points a drawn in.\n", "\n", " Returns:\n", " The example image.\n", " \"\"\"\n", " # generate obstacles and a destination\n", " obstacles = generate_obstacles(42)\n", " destination = generate_destination(obstacles, 42)\n", " # try to generate a route\n", " try:\n", " route, _ = experiments.generate_route(\n", " position=Point(0, 0),\n", " goal=destination,\n", " obstacles=obstacles,\n", " wind=(18, 180),\n", " )\n", " except Exception:\n", " route = None\n", "\n", " # draw the scenario\n", " return generate_image_from_map(\n", " obstacles=obstacles,\n", " destination=destination,\n", " route=route,\n", " route_type=route_type,\n", " )" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Nachfolgend werden zwei solcher Scenarios Bilder gezeigt. Zuerst aber wird zum Vergleich das Scenario mit dem Seed 42 als Karte dargestellt, um den Unterschied zu zeigen." ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "if not NO_SHOW:\n", " # set the default seed of 42\n", " seed: int = 42\n", " # create a figure\n", " plt.figure(figsize=(8, 8))\n", " wind_dir = 180\n", " # generate obstacles and a destination\n", " generated_obstacles = generate_obstacles(seed)\n", " generated_destination = generate_destination(generated_obstacles, seed)\n", " route_generated = None\n", " # try generating a route\n", " try:\n", " route_generated, _ = experiments.generate_route(\n", " position=Point(0, 0),\n", " goal=generated_destination,\n", " obstacles=generated_obstacles,\n", " wind=(18, wind_dir),\n", " )\n", " except Exception as e:\n", " route_generated = None\n", " # plotting the situation\n", " plot_situation(\n", " obstacles=generated_obstacles,\n", " destination=generated_destination,\n", " obstacle_color=\"RED\",\n", " route=route_generated,\n", " title=f\"Seed: {seed}, Cost: {route_generated.cost:.3f}\"\n", " if route_generated\n", " else f\"Seed: {seed}\",\n", " legend=seed == 0,\n", " )\n", " plt.show()" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Zeigt das Scenario mit dem Seed 42 mit eingezeichneten Wendepunkten, wenn dieses Notebook im Pyrate Docker Container ausgeführt wurde. Wichtig zu beachten ist in dieser Darstellung die Drehung des Vorzeichens der Y Achse was zu einer Horizontalen Spiegelung der Darstellung führt." ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAGQCAIAAAAP3aGbAABNnElEQVR4nO3dV3NcV5b2+R+8IQGSoPeg96KRoXyppOqSyna/buZ+YmK+wHyN+QpzPRPvzLzVXdWqkqpKruRJih70BAmSIGhBACThzVxkH0SCQAKZyJMW+x+MkJB5eM5m4pwn9157rfWQNmv53znHRNZ/7vJ/sD/9a5c+jfyvnInj01vgf37gf2NpoX+hgYJQWegBLBQmGKC70MMIBEqa6vQPHWKUiTiuOsEYw3GcqlQY5z5nqKKFNbRQUehRBQKlRQaCNcAw43FcdYIRBuI4VakwSjufcI6XeJdlQbACgQzJQLAaqY1pDVlBDQ1xnKpUGKODTmroYxsHCj2kQKDkmFuw6ljBCtazlcY4rlrLBl6miW4e8iyO0xY5Y4wxRDejVBV6PCXKBKMLLJ4QmGRuwWriCEfZzHaWxXHVRvZTQyc/8e3CEKxJ6mLS/YVJQvT7Cz2MQEGYW7AWs4/fsIVaauO4aj27aOUJuMiNOE5bElRSG1MocGFSSQ21YZK1IEkrhtXMBpbEd9VK6qijmZaMAmllQS9XWUszy2gK2SWZsIhWXuYhPfQwWuARlTNNLGcxQzyKZhgFZG6teB4lNOSCRHLDgpreT3CLz2hnJ0fZHwQrE1byJsvp4Din6Cv0kMqYDbzDTh7wJccKPZ65BauS0ZxpyrOFN7GfoJNufuBtVrOHmkKPqoRYwWu8xEWecSkIVi5Zx895lxs85CfGCjqelIJVSxOLaWVVzp6oClrYwTOe83RhJGcNMghu8yxMrzKkhiUsYXBBxhPyTD1rWEc9+zlIz7RjRnlKX160LOWveymHOMAmDrI4N5evZQe/Yg+XOLmQou+ooj6mfYxAIBckZhJo5mVGZ5pS9HKSY3mZbcwmWC/ze9azOMeCtYZe/srdBSZYDWGCkAX9jIT91hwzTC8jVPESrTNNo+5TwZXCClYta9lHUy4vX0kzzaznSo6vVYQM0cUNmmmgPiwPM2EsQ7WqYxF1jPAsWpUHZqSeBupYTz1j1LAsRRrmai6xd6a3JhikP75QdUrBGmAsv89P48KbbtzjO/rYxH52UVfoIZUxqznKJu5xjKuFHk/RUsF6DrCFnWyeqypjUZSqeWjaW+Nc4SRdMY0tpUSMMshzFsV0pTmJq7K6hOjiK05xkFq2BMHKJZv5Fa9yge4gWKmpYBMf8C5NLEujjGwHy2daEo7xGQ9yJ1jV1FITha5iaSYzyQRDKYRpgK4FlpCF51FEs4Z3Cr1hXIpMpL5Fa6lLetKq2M0R9lPPMU7zLLohAy+whB28lPbxqVaLeMwp2pNu77EsPvYXBauFXWxjC7uon9dJUzHBNdronfbWMKd5EOvlSogxqvM4mS0PxhmOFH8669nP2ujHSl6PfkysDYfo4PwC2+dJh8QHG1c4qJV3WZw0TenK4mN/UbBW8ha/YBUr4q7RHeAM/8rtaW+NR20bFiaN1IX00QxJtIFMVYOxnd9yMPqxghU0g3qOsoWTDAbBmokYy8tX8XMOJs2Fz2Txsb8oWM3s4M0smlWNM5pidXOT83xP53xPXq5M8JR7UbygKvT2S4NEBukauhiNlKuKalrYw2szhYETf3ETm6imjfNJyZAT0d0bbzCkVEh8eokNwWrG4miCtJjtU1+pm/axTzL5JZTq858hhtWcXWu9p1zm5kxfffc4u4CnUbPwhFPUsY6tbF5g3Q3nRxP76aODC9E39hr2sZlXWT/XGdbzKgNJ68o+rnJ1QQpWFRvZyjoOsSZn35rTP/ZJ+rnGldQRrhl2CbPcqnvEP/icoZlG0xlq62fiAd9wle18xMogWGnQwlFaucp/jwRrK//MAdamkdbXxOtsZiR65Q4fc2thlIi9QDXb+BVHWM66nAnW9I99kkf8mc70BSvRD/Nx1HF8zhFPTNupaedECsEKpKKPPi7ziD1h3yo9FrGd7azhPCcYYjdvJYWuZqc+OsMkN7nFKa7PugVZllSyhpd5L8cXmv6xT3Kfu5xOXdD+omD1cI4lrGUDG+baKHxEO/eTXjnJ1aBW8+UZ4yEbK0PWcph7jPAKG7I71QE+oJUObsw0CyhXKmhgeUHHsJq9vMfmFAe8KFgP+ZYbbON9WuYSrNt8wsmkV+7PtAkYSJOG6E8gfep4hRWMsSm7utcaDtBEB3/j/kwpOIGcspv6meLxCWaYYfVynn1s4fVZTz3EVb7l86QXF9pEOl5qGKEvaFYmVLEzWmJUZJdAVMkWWrnLQ84sJMFKeP0+LvQwNrIh/V3CSblJ/J4Sj809OmYK6Q9xYmoOayBLnnOVr1nPGtYE5UqPivhciBKh23Xs423WRK+P8Yi7RdAmOEeMc4+fmIiC7ssLkV4ze+g8ZS1hI0tZCq7wJ+5OO2aUmzzKcoCBJLr5kfts5h3eDoJVICrZQxXd0SvDnODL8hWsUa7zZ05ziPeK0pw8pWA1UMUIw1zgrymKRWdJNQ7Mg6ec5yJbWcHhQo9nIbOJ9UlZPolEh7aCDSfnjHGbLmoYZHdRxnZSCtZzrvM9g5zh5oLMTMk/44wzwn36Q3usglI99fFooKXcN3AnvX4fF+vznlKwHvN1lOd5YeH1USg4tTSEcugiY3TBdECqLtYvy5SC9SRqwTHBcAir550GKhdSElDxM8jQwngQKqkv1m6aKUc1Rn+YWBWOYTqjbfWlLI271U8gUxZOvk4iNaQqvo3XVIzSzZNMvpiLU0YDnnKaITZxmFeT9tcDgVxTnZft6WHO8EMmyW5BsIqUZ5zlKusQeQsFAvlhIi+L38ec4A/cS/uvBMEqUsZ4xjP6eRhyRwL5pY+bXGMRTSzKPCGrn765YkoXaeNiJg5GQbCKnQpq4m79GgjMwgS3+YI7bOUwezJvh9vFj3M5fXRxIUO/tSBYxU7CSq8495gDZck4t+nhB95kKTszF6wb/JWvZz1mKHUbmVQEwSoBergZOa02htbvgdwzmSGwlmdUMM5z+tPLRBukjXO0xz2wIFjFzgAX+Zjz7JrqBBMI5JoqmqljlDZOppcBP8LJmaqPsycIVrHTTxudrORDVgfBCuSRpqjT9HNO8H+nl4IwTm/qnlbZEASr2BnlEY+4xa6QyhvIL4nczm5ucI7jhe7fHQSrZEjcKOVdfBsoNrr4mofcp63QaiUIVgmxiIYgWIH8kuiB/h2DdBV6MIJglRDVDPGIgcjwMuQ6BHJNT25CUfMmCFbJMMJNvqKLjWxjdaGHFAjkmSBYJcMwl+hjBe/QEAQrsPAIglUyjHKXu9SxlKOFHk8gkH9CGKT0GGIo972KAi/QQG342AtNEKySJJitFoTa8MAUmvD5lx4NVBSrR0AZM0R/6PNTaEIMq/QoEsPLBcIoD7jLI84l2RQGCkIQrNKjJAwvy4bE5uyXXOF2bgp6A+kTBKv0KAnDy7JhMv3teLANLgKCYJUkk4aXTxgNW1e5JNEH6mEpBA2bWccSntFVpqvXIFilTV3onpx7KkvkOVnHr9jNTT4NghUoNiqpXTBexIUi0VO/JJJItvEL3uQsNzhZ6PHkgiBYpU0vV1lLM8toCokquaEI9zSW0MKi6McqDrKTpezgJa5l6O+Q6Lr3OMO/lWeCYJUwE9ziM9rZyVH2B8FaMGzmbbZGP1ayl5VgKW+wKBNHZVFf468zcQnMP0GwSpgJOunmB95m9bzsmAKlSCU7+YhXolcqqI8mXLUcyXz7eJAGrgfBCuSOwWgCf5tnpTC9GqUnMmJpZkkpjLmoaKKZVexnT4oG/wnniObMT76PA5k3wEqY/j7NSz/SIFhlQhX11BZ6GHMyyAlOUc2rvBUEK0O28xpbORQtAGNkC79kS4Z/6ynnOM2DuMcznSBYZUJDifwuu/mOP0S9ng+wvMAjKiXq2cvv2EdTDjJa1vI+r2f4tx5Qy80gWIH0GaKLG9QXeiSzc5FznKeafVxkZ2QQG+7FF6imkfqkxOA17OMlNubmio3zEsGVHM/X7D7cJGXCPb6jr+iD7re4Cka5wB/Zyh72saLAQys6lrKPPUm5C0t4pfjmpJWM5asSIAhWmdDFV5wq+pBQP4+i/79OLxv4NeuDYE1jKa/y66RYVQ3Lii9S+ZzBfFVZBsEqLiqj2PkEwwymvTP9nOe5HVr8POEJDzlQCpV6+aeBjRxmaaFHMjsTLGY9PYwwPJd4VVNLbZSOO+cdnpy1GwSruKjjELsY4wKnF0B7gGEqSqT2Jc8MMFF886np1LOLD9nJdS7PFX1fyX52UcMII7NqVgXV1ESBvCBYxcUS3uQ3DPMHrtBX6CHlmkVRu/TACwwzwPOir29vZD9reMDf6Z5LsFbxLr+mkWGGZq2HraCWuig4W4yCVRX9iZFxRhmL9ZzZk2gDkPwv3cph3maIdr7jStSGqVybXlUxwENWRb/3Ig/DzU5l9K+YXMhMRO2A0ixTnzzDShqK76adTg1rWUs/HTTNdXw9K2llWSZFmolPr+gEq4I1bGN9rBWnd7lUfDUHTeyiNenXsI2dVFPNXn7JVq5xJS9pxAVhkGt8xg02sa34dsEyYgm72JY0LeqPFkpP0jvDMraxia1sL/o8lWQaqUrjRu3lAl+wMarWnvP46zxEcQrWZv6J12P9pj3GQPEJ1gre5f0oixLNtEb/v5P/Sgd/prN8BaufczxkDT+jqcQFazlv8uukTc9H/JlHaQvWKt7mZ6xhTdGvB5Pppz+NZg/3+JyL7OH3fDDX8af4hHMoTsFaySE+iHWGVcUF2uhnIr/Lq4roz3S28spUwUomcb+2cpfT9EUjL7O14TC3uEUzq3mz0OPJknrWsTepyq+L05lMlJrZzXvzKgYsLMNUs4SqWe/VHno4Tyfr2cW61M/IAO18w7coQsFKLPXr4+5AtJnXGKCLdrpiPfks1LCOTSyb6d0j7EihVpOsZi/vsZbbtJdvBkAf/cUXsmnI0I6wn5scT5onPuYm/WmfYZTaElQr1LCJt2ihi1tJOXcz0slpVrKZVlpn+pwT28eTn17RCRYGcvBMLucdtnKWj/MoWLXs5hfsnOnd1enVWOymnjt8zqPyFazETlCxRdwzHdVjvuF20pRqkA4ep32GxP0/WFLRqwSJu72Ro/zA3+YSrH5+4hHb+Ij1Kb68k22Di06wEm19xhmLdaNwMQfYz1KucTZf6QKT3zmvzfRuqmnwC2xkA0/o5Qz3Yx5jsZDpXCY/ZDrv6+UsZ6fuEsqkk/UiKkpTsBJ3+8YokjVnj+YRrnKNm6znYFIAd5IhhpJ0qlgEq5KVkSfoIVbGvSSclIZWjvCIu9zJ/VQrob/LshPfxOCXs4e3WBSNP80gbqlQQVUxJWR1RXfIJXoz+Yvz67K/nI1RBGBz0deEpiJxry5meXqCm4hz3eEc/+Aum9gAerjJPS4k3erFIljVbOPn7GM9m3PWRXspb7CaK/w1L2vD8fg2+LbxWw5xgi/LTrBQXUwp75f5K1e5lZfGKRv5kDdZxYa5IpvFT2Umj/AQZ+hnS1RYWsFd/sIZOpL294tFsKrYyFu8Ny3vLl7qo1aNm+jkbI7dkCYYiS/qtI5VUc1gW0znLB4mGM0kOJ1Tumnj75yL0j5zzTIO8AENaccKipZx+jL5np7gOh1sYAOvsILrfME3U/1ri0WwEtVkK3L/BVtJJTXs5lW6uM0D7he3WUiChJTXlWln4bEoA2CMFlbmcadslPs8SHrGHkZmWcl3RQtrWcxT7tMda4rJIPe5wTKWJrWUKSHGeMxDHnMpk1bLie+qUTo4x3e0cJLr077si0WwJqIKhrzRxM9YRTv/4KtSEKxJhopmJhIjQ1wGpzjEW3kUrCFO8U3SKvs5F3k69bBWPqSVdj7nSayC1cnn3GIn73AgvjPnjcRv8FuucYO7mZ9hhDOMR3YY07dWi0WwxLp0SpNWNnCd+xzP76WzYZCRcrSnH6GdOyxmiB3sztelH3CSPybFNCcYmmaTlTCqeYkfuRq3U2kXj/mO11jG7hKMuyd+g59xghGGMj9DBVfpoJKRmeYQxSJYI5lUh2bDMN3RF2kdtXQXZb7iLFTQwi566ONxucy2JqI97Kc8ytBTb35M3gyJKohrM120iqUsZzkvs5elrM3Bki3RaOU5lznLZlbTkiLluDhJhK7uZu67M8lEkhHUjBSLYI0ymBfVeM5xjjNILTX0cGba5L+YqWIrH7Gbs3xNR6GHFDu1eamhm7wZbnAhhUTWsZ+32cXBpArB3BVIPeZ7nrItdQZf0VKR4+hqsQiWDPdB580DfuB/0BvtxSR2pkoofbyKVlbTTwsdZSdYdfnKxpq8GR6lnqXWsJVf8FrSjlBO/dwHOMWlKM95X+kE4CuoyfG+WYEFq5LFNLGEzSyO6bT9UYLydM7SxqWYLjQniXVuvN/GFVGxQgt7OcA9nqb+J5ccFfTSzuocXyjNm2E8CrD2MswwV3KZBDdKH31Ucp7dbKCZplLYGi7zGVYtOzhMK3tYE9Npu6Kw6HQ6uBLTVdLhGYO5jM1t5Oes5jI/cj1nF8onY9zgb1zL8YXSuRkS8vQX2qL2mKNc5nbu22b08BMTbOXVJFf6hUxRCNavOMyiNHoVpskN/srXM701mN+mw7nOAEx01HqZf/CgXARrlBs8yn1SXjo3wxAXuEM9E9F8uZ+nud8jGo5ywbZRy66id6PIAwUWrCqWsyNzd+xkEm3DJiOmg7RxjvYYBjhPKqNV23LW5LKKtT46+RP2cT1aGJZQSG46EzzjWaGHkWCc3gxrCeNiLDIWes5+DrCNBhYV69owD2HowgfdK7NOKWrndFIPgxFOzitpLUYaInPQjVO3lnLHOt6igRucTLEcDpQoiS4djWzlJQ4VayOHxVN9qnNBgQUr+1K7ES7wr1GStOgrsSfrsWVDI/v4F3axJC+pNEt5k338xNMgWOXFOBfoYiPDbC1WwarMfQyk8II1lon13ngU+JyMd3bRxklu5GSA8yThI5KYw+eHetazngnOcZHH0ZZWHtJxA2lSR12Uxj2U9p0/ziMecZ/tHI4yP2qLo+BhPPrnPOFRjkvcCixYzxnKJF80MZ+6mORy/ISTeen+kREFbO20nneo5xZtUz+rQMFp5SBL6ODkXA05p9NHG3/hGrvYH18mUDYkfI8u08lPOW5/UmDBSngFpr89/JQT/Cny/MEwD+ZVtZRTEkvdgmRFNUVrw0v8DzqCYBUTe/ivbORbujIXLFyhlzVR36hiEKx+zvPvXKE76dnMBQUTrISB6DKWTZuJzGJ6eoOzfJdjFc+exFI3D9Vw06mKCtCesaTg30gBRHf7cvbxOhsZ5DuuRSGR9JftD3nIddZxhBVUUV3QfcNh7vBTXjIcC3Y/b2InG3mFdVPf6uYyt2aaeXXQVvRqVVh6ucM9rtFRfHPPhUnibt/EEVaBzbxDHbe4nPlUa4DLfM59WqO9nUIRb5fK2SmMYFVGHop72cD6qe928Rlfz/S185Q7eRpjqZJwqfyae9wJ68EiYPJu38PGqGnMCn7Bfr6mb15rw3b+neO8z/KCClYF1fnauMy3YCV2Pdexj3fYg6nVdmNc4xiflZ1jaH7o4Ryf5jehPzAjyXf72+xNequJ/exjiHNcToqBpGmXm1gb1tE8zW9mFu/eXJAQrPw0oc+rYC2O7BI38ybbQR8Xk9I+x/me9hJXq3x+57xANcNBrYqAxsifbROHpi0jElSwlTeiop8EjzPx+h3iKt9OXZGtZisrsxl9sZJXwWrmKB+yLcnI6BJ/5Hx0zAR3k0wySpREn42CCFaiJKi+pDo+lyXNHOHn0Td0qvZea3if3Unf0Bcy9Pq9zSecSnrlCL8LgpU99WzkZbZGrzzlHF/yY9Jh6cyHi5zxvFdZT/KciSBYRUAjO/k5W2ddoC3lMIeSXlmRodfvIx5PPf8Au9lX+l5h08mrYA1zj4tRX6FBejjJzZLqUJwOw3TwA49Zy4bcz7aecJdHnKczk+KBQI4YpZZlcyUcTNey1gy9fqd/wbdzgmZWszH3U606qvMVMsurYPVynB4WR64+A7QXuu4vF/Rzjues510+zL1g3eVLTnCX9visWwPz5jkD85rnLs3a6/cR/+AW+/gw94LVSG2+EsHyKljPoh6Pk2I8kS+XyjwzGDkdtdDA/tzfNA85wR95XqYfacmR8EOdh2Bl7/X7lNOci7K0XspxZ7HneSxZzatgTUTWIGXPpDFkFxc5xmjUGytHt06iR0VIqS041axmFa1smtfMetLrdwsv0cEtHvAgbVEYj6bYic5L61jD6ri/NYeikuxO2vNViBYqN3LONf6dc7wWGZHngsZyjLCWInUc5u0ouz2bJrpNvMKiJK/fTGcxT/iebnbwXtyC9ZRT/EAH13LZ5D6ZIFg5p5NHUdhu17Q6pLgYixIpwuZgYVnFEX7P+qgDzLypYS/buE5vtMTLiAHOcDEKShyI1Uz7GW18zI2okVEeCIKVcxK/y6dc5NTUfJwmlmdScJ9Y9M1YbXOZ7tJPByldGljGEvayj+1x+DZXRi2wd7CPl7nOE7rT3gUeY4ABrnKO7WyMauOzj5GP0sPt/PaPDoKVP27y6dReoLt5l51pn6GDb1L0qr9Fe4i1F46VvBaVyOyN22W+kYNMcJMf+DbztJU+TkTdSt/kjZg29XJt6jWdIFj54x5f8UPSKz9jfdqCNc4VPuHETO8OMRAEq3Cs4DV+z/IceFZXsouN3GGUS5lHuIdpo51tLGIvy+MYVS2LctwA6wWCYOWPoWnNXi5wns1Je0l1LI2cfp9GGbYJejnPxXkl5gRyTT1r2JGbGUcFiyIfvH28lDSDSzgM9c4VQhrnKU8Z5jxn2UYTzVk0Wa6iKsywFhRdfE1PUmg20eB4F2jnm6TGIwkH83x+mwUyIg8NEurZy+94NXplmHP8kPaN8ZQz1LCVI7yWxbb1ojzmi04SBKuQ9PID55Nu9AOsZRcTXORfkyJWiS/J8jCjLz8S1aPP4jMDTsV2ViVN1Qf5mI60BStxX3WygQl2ZiFYBdnhCYJVSIajrkbJtLGboWjqXmz+GoEZSfSHyUMMsWmaJiZKcB4xxPO58lomfWG72c2FyPS3cS4tGI0MeidzwRIqmeeWtkGwiouHfB9lyZ8oxyrLQOzs4nfs4gonuZJefunzKIvqEvs5MtfcMBGROJ8kiI84kXlqWJYEwSouBvkxuufST7cJLGTW80ve5u88ysRD9yqPWc3v2DyXYD3me/6U1PRmkPt5L7MPglVcjNAV9gFLk3x2JU6mhiU0siTDxPonPOEWmznC0iSf1zGGporRFc5yfGotcBVNc+0zZmQZOydBsAKBGKiiLspHyTOPuEInJ7mXeSx8hMv8jTvs4TD1POcUV5LOdpXL0zoXJMxcl6Y++QTtnIsvFBsEKxCIgYrIHzD/XONf+YFu7s9r8+4mH3OMf2Yb9XTzFZ8khcP6poWrVnKU36ZoV59gnC/pDoIVCBQVw/Rwj2VRRmVOl4eTjeSec5Hv+TaLs3VHZqAJd5gmrnOS72f9W81s5TU2zHpYIvPrKiOpDZLTJwhWIBADTzhFHevYyuYc98wbiapH7/I9t+I45ziX+TvtXOD6XMdXUJtGHdJ+fslS7nCZm9nFs4JgBQIx8IBvuMp2PmJljgVrmEt8wnnux9e48Qb/RjNP6Jzr4DQNn9fxa17hR/7A7SBYgUDB6aMvMp3fk/vN/lE6OcbxWE87PY15FhJtdVMljk7awVawmjU8iqOtTRCsQCBOnjGe++6v9Uyk6IyWN2Y333xEOw+iY2po42HWrd+DYAUCcdIQ/ckp9Xm5yuxUzmpvnrB3PRltQVTxgPasE7KCYAUCcVLDCH05VpM+hgv99I5FbsEt094a4irf8nnSixNxeCQHwQoE0mUlm2mmlzs8mOnxe85VvmY9a3Lgk9QVuateKpC1+CQJU9FvucumKLmhh5t0cSI3LXCDYAUC6bKF37GNK3zKw5kEq5sfuc9m3uHtuAXrMn/lauT9VUCecpInbObXrKeCu/yF09xMauUWI0GwAoG0SPQp/gUHp3UxS+Zp1Bh2Kys4HOsYumnj75wrArvc51ziKhvYwCus4Dpf8A1juSndD4IVKE9aWB2rq1UdR9hFAytSz5vGGWeE+/TH1JBzPDJSvcVZbhSHmdukL3IH5/iOFk5yPY3krHkTBCtQnrTyPjviO2ENB1kGxtIIHtfSEFM59BhtfEU7F3kaxzljZIQzjNPAdR7n8lpBsAJlSA27+Cdei++cFUmzqodp9KpuoHJae4P50c0ZPuY6QzGdM0YquEpH9O/N6ewvCFagiFhCSxyzkmZeYuesnU/mwQi36eZiGra1w3RyJmnGUcUyWqZ2rernMX2znu0W57lafHOrBBMM5muVGgQrUERs5m22Zn2eevbHYb33Atf4hou0c3suwXrKaYaSRLORV3l7qmA95GvOzpoC/oQzwX8EQbACxUMlO/mIV+I4VeyJ4MNRo7uvGaJ/LsF6xlmuJj1jSxhjZxQIS3CLL/l01i2/hAFElkUt5UEQrMB8qI5sOGtjymDGEvazh7UxDDB+RunlFvfSO36MZzxLeqWLNs4m2aCOcY4L3Il5sGVLEKzAfGjkEK+xmhGG48gJauAQK7M+T+7IXpev8BcuRD+Oc4Hb2Y5rAREEKzAfGiIL4t0MxyRYlTSl0RCuUCSaE2S5zLxNb1LBcKLjQmErbEqLIFiB+ZBoYZ5INWopkFtMnqmM+hNkwwuLxECmxJKIG1hwDHCZT/hXzhV6MPmhjvq5LK0CuSbMsALzoZ9TdEQ2nMtntU4pG8LXe8EJghWYDyNRddt11nFgarZnDXUlfm9NTIvNDfCgOIr4FjIlfVMFCs+kDefN6JUKtnKAVQUcVtZUcJO2pB4pw5wudEeXQBCsQLbc5OOkvgiVvEdLiQvWGBf5A1ejV8bpzsSjIZALgmAFsqV7ms1UM4fYQQ3VpRConog8PifTrBJJnj8mCVaaVFBNdeR1OhpHSm1gkiBYgfi5wTcMs4HdrCn0eOZkhCtcS6rX6+Zk2kntydSxj62Mc4ULhW6zV2YEwQrEz30+5zxHaSgFwXrOT/w5KWI1ROe8QuxNvMmHjPAn2gttxlVmBMEKxE8vvbQxzl72JSWIV0R/Csj04sdbnOYr7s90fEZj3szLvM8Qt/lu6qIyrrrLBUsQrEAO6eAYDUkNVZbSyqbCDQnPaKczqen4DS6kUCusYWvazWp2sDPqFbGX99kZvTXMbdpz2UG47AmCFcghj/ma9qT7bAu/LrRgJUb1VZKhfE9SWsZ0tvEb9qZ38mVsif5/J/81qeveMz7nURCsLAiCFcghzzjH+aRX9tPKQVYXakzRvO+TJOGYZZnWzC7e5Wh6J09ePG5gfdKZe+jlTOqpXGBOgmAFcsh0IUhEi9axifWsz329Sze3pzojHONKiiLkymhUk00jmjhC67ySM16IfC1nD28l5axN8IA79GZ+8oVJEKxAXknsx/WylV+wemq/4Fxwh085k/TKXTpSHFzNAT5I2tmsY2t8veG38dska4xxjvFpEKy0CYIVyCuJUp5rbGMVL+W4anqca3zFF1NfTOXxuZKX+DCpr3yikU5cua/rWJXU7HiMWq5wJabzlz1lKFiVLGMlS5Je7OFe+B4rAibdN29ynu8j5Vod0734kPtJqU9DnORaijh3HatZmXTpjVGULd5+8JNM174dHKEvScX6uD+teCCQoAwFq4ptvMXupBfP81kQrGJigDOM0Mrb/Dyme/EKX3Ir+nGUq6kLABdzlDeSWk0smZo1lgfW8wFbkoJ9V/k8CFYKylOwNvEe7ya9uJKOpF7agYIzEblvJiLc+5KyAeZNH238hbakF4cZSnH8Gl7jPyWFqCqpzW9eawuv83LSK8fo5FzxGaYWA2UoWJUsZu3UQOkuXuIu3dHucqjwKiyT7psDtHEyaR1XyRKWJ/U+n5FRunmS9GA/4BxX6Znp+EaW05ykR4fZS2vW/5ZsqJ72EO7kJTqSer0P8YTu4PRVloKFiWm/2tW8y0quc4wzIXmvaBjhAv+alJlVwxHemasIcZgz/JC00n/K2dSeDit5h5eSEik2sCPL0eeA5bxBU1Il40O+57sgWGUpWIlWIS/oUTOvcYCTdHMhCFYx0c69JLe+egbYNpdgPeYEf0jqqTDGQFL++gskAgUfJoW9a4vSpKeBw+xOkqeb9NM2NZtsYVKGgmWmGVYNS1jCVlpKoUPTgqJ/mg97G+dYxmKWUsMYPfQlBacv0sbFmXoqJMICTdRFr1RxgL1syNm/Ii6qaU5KLkUD+6N1YoJxntK38OJcZStYqSotGqkpdLeAwJzc4K90cJB3WcYQJ/gp6RHt4kKKDjC17OBwkjxVsJeN+Rh7/DRxkOGkGdYAp/hx4W18l6dgzUI/I6G/R9HTxeccp4/dLKObH/jvSQo1lDpclRCsX3EoeqWCRVOnLSVEBbtZlyTWCTfW9iBY5UFVFBAZ5RmDSQrVTnfYIix6EovEe5zjAs1ciP4/HSpoYUdSwnpJUxkFNCYZ5zp7krZWJxhioNx9fcpQsCpoiHIanvMjF5JCWre4tvBW/qVLYm3Yzu1M6leepQ69lweV7OSjpGZb49zgHO1lvYAoQ8FCTbT785B/8HHSlKqfnnK/m8uJLj7lGwYycawZY3haIL/M2ExT0gxrnH/Qy40gWKXFOM+5xwqucGZqpX6gtHiWog/MjFRGHq7LaCnLmzuJFxaJ6GJpuW8oleHvdIx2/sYFLnG90OMJ5I16trOL9bxMS6HHk2dqF0C+TnkK1mV6aKSXu4UeTyBvNLKf37KTFlYWejx5ZiB125yyIaVgla4f5DgPgqX4gqSWDbycFIpeOCQe0rKv3UkpWMEPMlByVFCT3+YwgTyTUrCCH2Sg5EiUkZZ3ItIC50XBmvSMnN0PcpJgDBkoHhKClar7VaAMeFGw6tnKRval9oOcZIwubiUZfAcCBWSAkQUQx1nIvChYzbzO+2xM7Qc5yTA/8LcgWIHiYDAUipY7LwrWRl7mQ5al9oOcJFG4dDLXYwwE0mMJDQsgF2kh8x+C1cgG1nKIPSyfelBFivTZxUnd+wOBQtHAGtawnh3hnixr/kOwlvAG77GBbZn8/cFyr9gKFD8Jc+a32UzrwktwX1D8h2Bt5Ci/Z1Emye8DkRNkIFBAFrGbX7I1VtPTQBFSfRS8wu7Mv5oqWckBhujhIT0h5BnIO1U0s2Yul51AGVD9v4D182p1lrAs/RUHOMe39AbBChSC8dDjbGFQ/T8l/pPUrj99EpalaxhiCTc4H/PwAoG5GV8A3a8CCaqXZvGXK6illsWspC7UGwYKRCi3KCA1UQOyKnp5mMtig9jay4wEp79AYEHSyBGO0sgpPsukN2ymxCNYCdvxUBIRCCxAGjjAv9BCE23FL1jjNNHKdp7zlOdhih7IF2Phy7KgVNPCFpawjwNRY+veHJgnxCNYlWzkfTbQzkkuhV2bQL54znDQrIIyEmnTZj6ilXP8kIOpVjyCVcFGlnKU73jC1SBYgXxR3rYLxU/C9qWblaziF7zMx3QUrWChMXLWuseSsB4MpE0VDTRSM+tm36RL6OQB1TRSzxZWRNa5gfyTaEOWaCefaEi1ltvs5xFDPI+vq2JOTCiGQxO1QNo0coDDrGSU4RTJMbc4z9Ukn4Wl7GMPGznA4ryNODCVRHpT49QXD/Iv7OQKJ7kS05o9fsHqDzalgUxI7DH9Z3YyzHAK65dj9NM+VbBe5desZylN+Rpw4AUS3VxeKOFcw4e8zt95lKJf8TyIX7BqWMHayC58OCwPA7NSSQPLWD3rsq6P5VQmvdLIJg6zNNdDDMzKKH3coTnpYa+KpGBJrP0R4hesVRyljjtc5nqYcAVmZYjrfMEddqV26Kqhcmp8vWK+JWWBeBnkMp9yjpGo6WsDi6njJPfim7XEL1jreI+XOAfuBMEKzMpzTtLJWn7FElbPdNjgNHPMyRLC4OtVWPo5zz3qGWKIcepopJZu7hezYDXTzDaqOB6aEwXmYphOOmlgOftpporqqQvA6e4SE1GQPlBYRuiiK/oxEdLKUVpcDq3q65gINfSBtBngMp9zn1Z2sWSu44PlRLGxlD000UlbDs6fQ8HqZyB8AQYyoZ1/5zjvs3yqYE1MSxAdYiwIVpHxMv+NDXzPAO1xnz+HgjVBI8t5Erp/BNLjIQ+po5mDtCY5+1Yk3UIVVNJCw9RlYyB2KlJ70ExnGS/zT2yljrN0ZHi5OY2ZcyhYSzlAL13cpjN4iAfSY4irfMsgG9lJI4uiyEgjrWxiO1tDW+SIKupyEDJezFbWp6cUTRxiLWjlzcyrpgbp5NZMLqgJcihYK3mLLVznM7qDYAXS5jafcIafszISLIyzjNf4JWvZGLYIk6jNgWAt5x1+ll4uVS1boyNX8gv2Zni5J3zFs4II1lKWsJ82bvBj7q4UKDse8TiqFnyN9VEh4TiL2Ms/0ZLJaqXsmeB5DjoObOY1Pkr7i2EyV66ZIxzO8HL3eMjx1AfkULAmb6al1ITmDYFMSAQyhrnCd/RzKUrnaWApKwo9wiJhnIfc5TGneRhHsLiC5axjOUfZOa86zfl9lyxn0azzxBwK1iSDDPA8D1cKlB23+ZifeMxNJqilguFgiAlGozqBNjrpiEmwNvMeh9jA5qxPmD5D09KDXyAfgjVEBY2h6Xsgcx7xLZWMR7dyNeP0B8ECY9zmW75kLKY8jwrW8DofUZMfjYjon6sXYz4G08hWjtLJo6hFTiCQDmPTus2EhsjJTDDAo1hnA2NUs6wQHXtqqZ51LZkPwUps67TQwY98HwQrkAUhwT2ZGVu7ZE9/gR7SRPnhLLl1+RCsJRxkDzd4xjke5eGqgTKlJhSoTqUmB7kdldHSLM95uUURw6qKGqduZFl+l8SBsmERy2hmL6vCXTSVuHI7FkcVUTvmKuSMl2F66ImyRmcpQM7r7308RB8C82UtR9nPJnaGiHtuWMe77GULm/KY4/aU05zgNhfpSX1kXgUr2DEF5s0a3uRXNNMQLCdywzY+4D3qaMijYCUiRX/kBoPFM8PKNJesjqUsYoSe1Nn6gYXAIjawpdDDKD8qWUxTVJeylzV5H8MIj2hPwxYsr4K1aK4tgBdYzrvs5DHfcSqHQwsUO1WhbDA31LKDw2zhQFS6XBDS2fnNq2BluhW9PpqgdtATBGthMxYSj3NDQrB+xWEW5zfWPkkltSxKI38gH4I1Sj+D3OBRGkWFtZFB5l4OsJ0lkQPdQ/pDF9MFyXPucINmGsNsKz6qWMGuQi+3K9PLVsmHYPXQxkVuc5Zncx2/nCPs5CAbwFJeYYAbnOZ8bscbKEbu8R19bOEIOwo9nrKhgrrScXXMk2Ad5890phc738D7fMAyWkBVJF4XGOZy6P2w8OjiK07xMk1BsOIj4eVRKr3q8iFYA9zm1KzpFRXUUEsduzjEwaR3K1nFKhpo4zydDEeGQoGFwPOo4UcFL7GXFuoiv8LAvBmnh1usooa6AiXlptlFPR9ja4j6gcxCFZvYzQaO0JrisNW8QSUdXKCN3tiHGyhu7nGMKjawi+00FnpIJc0I7XxGB1vYzbq8j2GckfRi0/kQrFoaWDTrgKrYxq94hRZWpTisnlfYQTv/xu0gWAuPZ/xIOzv5LeuCYGXHEJfpZjk/o7kQgoWx9OI8ORSs8ag3yEMG5toCSCz6DvDarIdVRJ2XR1kW0p0XJEPcinwKDoVoZtaM8YAHVLJm1rhN7qiiiTVJmSsTkXq8EPPJoWA94Tq3aOfaXFG9CupZNtc5x+jgNje4HhJzFjZD0W0TiIVxBqd1H8sPi9jDL3kQvTLMLa7zeOqRORSsB3zDV9zjXhoL1HRKo5/yPZ9GvmFhPbiQSWRjBcGKi4rcGIWlQxOHWZs0BXnGVzzNp2D1cYkv6Uvj4ISp/YOpAp9s4jjBOB2c4K/cz8WIAyVFFYN0szbY58RBfeG2XBvYMjVztY/7fDftyBwKVjXD6akVxrjLj1MnYuuivjxjXKedy1wIahUAT7nA39lIK60hvyFrEm6sxUBz5Lb1AjkUrIZoxp5OTtoY1xjmWNKLb0Qh9mF+4mNuczM3ow2UHN0co5OtfMT6onnYSpQKqov+M8yhYD1nIhPBukvX1In9BK+wnS5O8yndoZl3ICIxw7rINtZzMHX6XiAdEkaQc1bO5Yc+embaAq7+HLSwYV7mlN3cnhYYS3CRTkbTPtX0VNfr/EAFd2grmk7wy1jHipnCkwPRDkPYvswPiXvmDuf4B52sZ33Id5kX49zjJyaSjFTzHBkcjp6ge1yaaVet+v8E+/nlvATrDp9yZqa3Eh25Zk9wn517/I0L9HExi/PEyzre45WZuvQmNka/DoKVX4Y4Qz+t/JzlQbDmRcKT9c+c5hDv0ZJ3weqPvnvauZWU5TBJ9R/AQ1o5nGHYcpxrfMUXKd6dbiqXET38QFVUn1kkrOQVfj9Th5NE/5yTBRjUgmaC63SwjiUcKJ3eA0VFwpO1ixoG2V2I8Msg1/iMthTqUZ2YC1znVIqwZUO0AsIT7iatcoc4ybWcTSjGs5ug5Yg6WqI2Ei+whuZgQpV3Et9no3TQxo/00cLKQliBljQJjRjicYFWCVUM8DB14Ps/gu6P+ZbHMwXh1/JhJFgdfMKN6K1RrqbRhrnMGE893RsJ3SMKyhgX+QM/8TJvBcGaL9UFyhFZRMOslkj/IVDPOM2FmY7YzkaOUMdVPuV00rvDC8/GOfEVNDhTjnV/sAUqKBXc5G40/91T6C6aJUol9QVqMjNMxaztZP9jVGOpWw9f4xzHqeUMVwtUHllUpOrdUxVSrgvKBEMM8ZTuYop7lhb5v4fHeUI3d7g962p0bhl9xnFGqOI8T2IcZtmxiLogWEVAVeQMECgJxrnAd9zM3kh1nHNcBwMLbwGYEaNhPVgcLA7W0CVFL2f4N65nb6Q6ztNgYjorwzzlGTe5FzS9CJigm6ssjqyrgn5lREXaNjbZMEYfT7nO+bnmVgkKElkrN3o4zTluc6ZoihsWMsNc5S9c4gCvs7LQQyotqvNipDbMWU7Szpn0ZkVBsGKgh5/4I508C4JVBCQE6x5L+A2bg2AVJT38xP/LHfqKx4Si7BnkLm1h4ZwD6llEbWRSMJDebT1OH310spkLrKKexrJbG1bmZlPvKXfoTOq5EuMlRiJn5Quc52zkh5QOQbBiYCKqQwrESwWbOcx6HnKKi5knK1znM7rYyRHW5mSkBaOO+riDTRN08hUP2cx+dsSqFI84z2XaactErQTBioVKaueyBQrMgwq28GsOc5l+rmQuWHf5G8f5gFVlJ1hykJI+EXl8HOMojWyNVSke8h2f8oDuDP9uEKz58MIkvJLq8FHmhhb2sp9aPpvXw5mIKnawnMNspY5aaoo1Y26MYYbTW/wO8CBu3+aJpMSAJTyOO1mnn5v8NK9K4fCUZUxVNA+fpLGI7/6SZjzKWBY5EmfzId/kHzxjA7tpLda7fyBaMaWTHzPM6ZnasMRFojw23rYNiQ4L8+trUJy/sqKmctqnVh3FPgOxM5lGOMBIdk/OA77gDK9Qw8Zivfuf8D1/Tm8PZ5zuXDYgqM/6e2I6dZGzckbRqwTF+SsraobopjspUeUBz0LQPVaqqKaGpdEycCjrT/gZ10AdbxS6JmEsdV1EO6f5tjjaQMboo5NoczLGI4bmKz1BsDLmISeQtEF+Jw2n2ED6VNPKLjZwlI2INbQ8TFVeEiNTkWiV1869md69zOXiUCtRACSWz+oh17nNFW7O17I7CFbG3OVLziftJT9Lzyk2kCZV7OCfOcrKaF8v4bMby9qksdD2q4lmxH/h1Ezv9nA7zwNKTWV8/aYTD87XPOJuiGHljSehZUWOqWQZ23gpynGb4CH98UV/n/OMxqyzLidS9xqapGLaVSbtHr7M4tL5IWEtGstn1c05vsiu2DYIVqDoGOchbdQxzCAjnKEzpkDhY05Tz1q2ZpeZ9Yz2udyh6lnPRpqjVxqoKJpF3+xMflar2cS6LCZcVVG3smwIghUoOka5wh/4Nik4/ZBbMQnWXb6I6qJ/k51gPeZrvpp1gbOMd1mUJFiikpfiZ/Kz2sMvWJGFYMXyTw6CFSg6xrjF7WmuunMuvtLkMd2c4QnbeWmqlGREB8f4ZNbp0hpW8lrSK4mJRkmYlUx+Vt3snG+kPMFA1P44m6llEKxAMRKXNs1+8pucZAXraY2cVu7RkXaK0DGuzNWfI9GsORHm74mapp3LvCqlIEx+Vr2MZl46PsEjunjMSe5lnU0SBCuwcOnhe+6zl99HgnWFP3E3vTPcpWOuYxpYEvli3OUvnOF22pcoEhK9LjLtOj1BB19xmru0Z91oPwhWYOEyGDW67GI3hxjiAn/lanpnmMXzbZIGaqLDrvMF30SxuRKiNrKqyUizJrjHD3zCSJQ4mg1BsAILl/GoXLGdU6xjmDPcjHULb5hbHGcJJ7leIvuDL/CUq3yfntVjVdQYI1Fj2xdfV8sgWIGAXr7jMWNciDsHuJ+T9FPHdR7HevK88ZBvuZdeGKuWd/mIGlpitS8KghUIGIqMhCcYjrssNNF94SoVjJRsCVc3P3E2vdzRBuo4TFPUHr4ypuLNshasCpaygsUM8JAnha55LXFqWcrSpK/ZMXp5UprLnEnGUxsJx3LywZLVqUlGMwm69XCBkwxyJVbr5XIXrB18wHZu8zk/zLeEKQCaOMQr0Z4XBjjDMW4VcFiB4uMaf+QYd7kRX5JKuQvWRt7nDc5xk+OFHlKJs5iX+D2bolf6qKM9CFZgKrd5Qg3DPA+ClS6JTaAhhnPQOXHhUctKdiTNsNayrkSqTAL5JEer4LIWrAlu8gmXucvV0GQvWyqom7axHbtrSyCQirIWrHGu8Yh6hqLigkAWTDDEs6QZFgbDF0EgX5S1YEly/1h41NBIAxP08zyODdJhHnJ1agzrbolvEQZKiHIXrAXMMo6wixFOcywOwXrGWWqn7RI+yvrMgUA6BMEqW5bzFh8xSA0X4kiHecppbs6UhxUI5IEgWGVLI5s5wgiX2cFVhrOznxnmQS5d8AKB2QmCVbYkuqFXUsch/hvtXKQtrOACJUsQrLJllD6esIxdrOQOf6IrCFagZAmCVbaMRwtALKKRKpZn3jQyECgegmCVLdUsjrqV34uqZ+bs5xsIFDNBsMqWKhZHrYjO8/9xjbsl248pEBAEq4xJdDV5yiBn+TvXCz2kQCBLgmCVLb2cYwlDnKKr0OMJBLInG+vpQFGzhC2sZ5SbXAsVf4HSJwhW2VIR/RE66wTKhSBYgUAMNLOWVdRSRVXSozXEXe4spDL8StawgcU84WZ8xVshhhUIxMBK3uJ1mqinjsrorW6+4G8LSbCq2c0v2cgF/i0IViBQVLRwmN+yjMqpM6wuOvm+kKPLN1W08nMOsJrznI/pzEGwAoEYaGAta8EwnUluJw94vMDMT4apZikNbOMID3gSh3FVEKxAIAaqkzpHn+FvdEc/Pudi0o8LgTH66AMt/Iy1XORbTgXBCgQKzlhUttnLt/xfdEZvTSQVdS4cRukFi3iVg/yD25xlJIvTBsEKBGLgGe2c5hHnuLrwFCrBElpoYSuLQBWNNLKahqyTAYNgBQIxcJ8vuMUzzixUtcJm3mYn26OI3iQjDGQ3vRIEKxCIhQd8HTXOf07FgszUrWQnH/Eq9dPcKgfjcBUIghUIxMDwAtsHTKaaJppZyUH2smamwxaxib308pRn89KvIFiBQCArGjnEa7Syj9UpDlvDO6zgJqdom5c1dBCsQCCQFQ3s5XfspW7aSnCSNbzNYU7xjKtBsAKBQP6poIpaamcVlIZIyxLO4fMrYw6CFQgEsmKAy3zCFXayL+pzOwvD823VHQQrEAhkRT+n6GA1v2EVm+c6fni+CVlBsMqfymi6XjnrYSMMMZqnQQXKh5HIXvc66zjIEmqoS6Ev1bSwmScMMZLJdmEQrPJnMTvYSVPqYyZo51xwdQ5kQcJj/G/cZgu7WTfTYS28DDq5zDX6075EEKzyp4kj/CrF3ZNgnC/pDoIVyI6bfMwxfkZzilsu0TtsD1f4d+4GwQokU89mXmXDrIf1cZqrjDAaGsAH5kU33VxmTVT8PJ3FLGYLTZymJpPzB8Eqf6pYxIq5DtvC29Ryl3ZuB80KzJdxRtNQojomMszGCoK1IBhPQ31W8z77Oclf6AqCFZgvlTRQP9dh/QwEwQq8wCh9dLE1yUdnOktYwj4qODXXlmIgMAt1jNPH2FT3phcYp4EWuphIr1w8CFb5088VvqCd9WyadbsQi6kNfkqBLBjjLj8ywDq2smymw1ZxhGfc5iY308gmDYJV/vRxkgds4GcsnkuwEtlYC7A7SiAuxrjGMCd4k8YUgrWS99hBO5/SHQQrIJphXWUtK3l1ruOHQvQqkB2JGVYX1VSwl90p5uxrWMMyLqQR8xIEa4GQCBA85nkQo0BemIia2V/j2FSjxkmqqI82pu+l11AsCNYCoi76xgsE8kYXn3F1phuvkmqqo24zqfK2kgmCtYBoTKOiMBCIl26Oc3LWYyYYS6+ONQhW4EUSWX8LtuFvIF7GY72Xwtdt4EXGGAyhrkBREgQr8CKVGZZ3BQJ5IywJAy/SzDZe5gk99IbZVqBoCIIVeJG1/Ix1tHOMMwwUekiBQIIgWIEXWUMzRzhJNxeCYAWKhiBYgRdJ9FPGJpoLPJZAYAoh6B5IyThD83U3CQRyQRCsQEr6GSn0GAKBZMKSUDUNNFIdFUCNM0B/OVrIVGTyHVXHGnbxOOq1FrYLA4UlCJYmDnGQpYwwTD/nOcnTQo8tXiqoTcPkcpJVvMtybnGKc2X3gQRKjiBY/2Eq81/YyDBDPOFPdJTd81mR4Qwr4W5yhIuMcq3sPpBAyTG3YFVSF7WgHGYwE9fDkqCKRlpYE30co9GcYrJ8fMZudmMMlVTN3Si93GFJtBVYNevxtdGHs4yGEO8MFAFzC1YT+9hJBZc5VXZZOf1c5u+0s4dWqnmZXvYzGtleTaeL89zI83CzYJDLfMpVdrGfxXMdf5UbXOM6Q3kaZiCQkrkFq5mj/JpqPqa97ASrlx+5wUZ+z3Ka2EEzfdEiccbNsjMMlpRgJWJz91jNr1k/l2A94ks+4R73eZ6fUQYCqZlbsBrYwuvUc5fvpvbZSnSxKelF4iAddHCdtexlP1UsZ+Ws66A62jhPT4ZXHIv+5JkRuujiGus4MpdZ4XVO8EXZfUUFSpe0Ylj10Vfxfv6J1uitUW5yOb1WgcVPN238nWvUUUc9rWxLcfx6XmUgw6nHBJ1c527hjB4GuMzndM562GUuB7UKFBNzC9Y4gwxTy3b+he7orSE+53G5CBYu85wmqqiigff5T6yf6eAmXmdzhtmV4/zAaOTFVija+Xe+mfWYHm7nZzSBQHrMLVijPOYWW2ngUNJbQ/RxhptRymWpe0MlVkyTJLZHd7FmJj/IerazPcNLJLy5TxS6t/pDHhZ0AIHAPJhbsJ5Hy4cbbJ26PqpjB29F4a12nuRupIVgiKt8y+CsfpAZUUFLeo5GgUDgBeYWrKec5CEbeJ/FrE56dyMfcZDv6C87wcJtPuHMrH6QgUAgP8wtWP1c5RprWcXLUwVrBcsjo+ALXCr9VeELPOJxGn6Q6TNBN4PxjC4QWFikVZozacP5bFoKZUVUobad1xhKSnHo4XbpB0qm+0GuZCMtGZ5nnIfc5TGneVh2yh4I5IEMaglnt+FcywfsSHoOE0nVpS5Yk0z6QR7io8wFa5TrfEEbnXQEwQoEMicDwZrdhrOFVzmS9MoxbnK2XBJ5Jv0ge9nO/gxr68a4zbd8GWWNBsEKBDIltm4NlVFf3Um2coi7SSX+AzzgQWlmxk/6QV7jJCtYyeq0p1q1jPC4XOQ7ECgIOWwvs4w3aEkqmr3PP/iqNAVrkof8gy728H7agpVIQ63L7dACgTInh4LVwEH2JK192unlHPdzd9Xc08dPnOM11nMgbdvRiSBYgUB2ZCZYlZn8hcScoiHplR3s42VuRa+M8YTukuoqNUY//VzhLJuTrGXqaGFZUnhrjN7IkbQ9NMALBLIjA8GqzLDB7nQaOchEUn5pP8f5pqQEa5LHfM/TpLT1lbzJG0mCNcxljtPO1al1P4FAIFMyEKyEO0M2TVEq2cXGpGSuXqq4Upop8gOc4lKSPLWyiL0sj15JJHB9ykkG6S/IQAOBciEDwRrlIZepYDFNmUdkKljEoqRX1rKPlxjmGb0lNdUapY++pFcGOM9ZtrGEZqp4zm3uFWyYgUCcVLMsCoP00ZNfL7gMBGuAC9Ryhn0cTtF0JVN28it2cI4fSjzR9ClnqGEbb3CUxSwJVh+BMqKBt3idMY7zbX6f2QwepX7auMUKfs2GmARrI0s4ysd0lLhgTXCRTjaxiAM0sniuTsSBQAmxnDf5n6OJ1dkiEawaGmlggn6eRxtevdzjpfjCMYnneR0d7J36jx/ieUl5H4xHH1EP57nECu6X1Do3EJiRahZTzw7Wsoj+WWv1cjeMmVnGEXYxwmmOJWV75qisZBsfTJ21tXOSjhxcK9c85TTNNNNW4tPGQACLeZ3drGKIv/CEUzzL7zBSCtZy3uIjBqnhQpLVwiLqcuBSt45/4vWkV76luzQFCxe4TzVPeVzowQQCWbKK9/glQ3zN37hHd+YOLFmSUrAa2MwRRrjMdq5EvqE5MtScHuvp5zRXkrpHjTHMcCkU9zziUaHHEAjMj2rqppZw7OQQh3nEJ/yU5O2Q54HNTD9DVFDHXn7DTs5yPtrLz8Ne5gbepJoxaqjmMW1cDB55gUAuaeEAW5NCVPvZgyh1vFBh2ZSCNUAPT2hhB4u4CS4zQn9ebPWW8TZ7It2s5Rr/g44gWIFALlnPB7yXtJxaHsWXnzNOY96jVwleFKzKyOFqBTWRjq5gBeto4xgPaE674jcbEh6uW6IfE4ZjIa0pEMgRVVRTww6O8MbUd8ci1+G+nMWF5uTFZ38Z29gUGeQk57Iv5yC/oocjSdUn+aGDdq7QUVKJDoFACbGS3WzgtaSJQoIR2rjGda4WzpTgRcFaxdv8jNWsnVrqXMEBljLECtbkcZTdfMZfucudsB4MBHLDZj7kKKumes3gFl/xOffoKlxV7IuCtYTdvJfUMiWZjWzM/Zime7Je4jv+MrVwLxAIxELCSqaRnbzBz2Y65hFtfFnoZ/BFwaphaQq1yhs9tHM3SbMucLnQn1QgUK6sYStreY3NKY6pZrgInsFijF/f43O+S0q2ekx7IUcUCJQz2/gNL7E+dWw60YyzvtCWmi8K1gg99BVukjVBO9/z56TMiYngMRMI5IZmdvEuR6O14Yw8Z6IIBauXS3yZXoOBqijdIRYD9+7IePUY1/KYmVbJetbP1Ex1jEfcLc3+goHA7KxlA+s4QitVMx3zhLs84jyd03yU88+LgvWAb7g1zbNrRmp5hfdiEqw7fMppbuW3lXA1B/hgpn3PYU7wZRCsQDmyi1+yk60sTXHMXb7kBHdpL4K+Iy8KVqIC+2x6XSMSBhP74hjHONf4ii8Yy6+Qr+QlPmTrtLcSHoJteRxMIJAfWtjHLzgQ5YrPyENO8MeowVQe6ltm50XBGmc87TrBAbqzTuPs5j4POcm1PPqMVrOaVWxjP61TDX4SNLAqyWMiEChRJu/2yZVT4nt6y1y3d6LFW0HqnGck213C6qyT9G/yORe5mt++UXUc5m1a2TeTWiXI/h8YCBScybt9MnqziD00zfUXG4vMTDMrwaqnLvVkMh0SvWv+xjGG81tzs4oj/J711KZeAj/Nb4/9QCAXTN7ta6NXKqY1kJmRRKOUgm8OTpKVYFVE1ZLz4Em0GDzLlTy2AWtkOcvYwwG2z/Q7G4vaHD/hehEkywUC86M2cvbdy74Ud/t0JnjGE55yme5iSirKVrCqUy+mZucq33Kd8/ltyLmGt3mVTexN8fsb5grHgvtpoMRZxKu8ypbUd/t0JrjFMS5ETQcKHmufJCvBSuRzzuMf85w2PuY8A3kMtGM5r/CfaEn9+xsJ7qeBsmAVr/OfWZGJZ/sEnXzF36PHs3wEK7FoWk0jTSk+lDH6eJqUrHCf81HX8zwzzmjUZ3mW6Fsft4L7aaA0qWUJi3mJfezO8K9X0U8nnTkZXVZkJVhj3OBvXGcnh9k5U/R6mLOcTAoG9XIy7+3rEzziBwbZzCH2znTM4ty4bAQC+WEJr0ch2p3zOkN9cZYZZzmqUW7wiEX8nBVsn2na0sNP/L9J86lRnhYoa/Y+X/JTJFXbUuza1mQyhQ4Eioq1vMNvsui8Ul2s6YfZLgmfRa2dt0zbTRulPzK4P8/Z4mi8N8ggDxiO+upvYFEkT4M851FwPw2UILU0Us9e9qdYPczCBINR0KqTfqqKKXqVILZ539g0660BTnGe67QVh1ol85gTVLOV16Lfbic/0s6ZYNIVKDWWc4Sd7GVb5n99jJucp4MLdBZTNsMksQlW/bTF4GO+50/cL6bU/kmGOcMtdtIUCdY1/sQZekPBc6DU2MD7fMDSeVkujNHOJ/zIU56UsWBVUUMNFYwzxBBXOMvxYs0UH+UBD3jKKxymjouc5EqhxxYIzEnt1DqTKnZxiIPzPeEE3Vwu7mr/2GZYdSylkkFOc5GLkYlhkfOYn1hMNT8UItMiEJgH69mfVGpTGbW1mjf11BRf0OoFYhOsGhaBPr7n33hYIg//CCe5QyUPQ5pooETYzm+T5lMVtLAqu3PWFf3meDyCNcEQTxigndN8My0GX7SMc4c7hR5GIJAO1VTRwh5e41DWJ5yIGl09p7foH9t4BCvRfu9L7tHO5aL/ZwcCJcomdrKRVyPv+CwZ4VbkU3Uivy2e5kFsS8JLjLGSPjriOmkgEEiikj38nj2sTaObVToMc4lPOB85GBQz2QpWRfRniHOxjCgQCEwj8ZStYx9vZ54UOgujdHKM4/GdM3dkK1hr2M5S7nIuZIcHAjmgklZaowLYWFaCk9QzUXx53anIVrC28i9s5zT9XIxhSIFAYAo1kU/KNjbHvZFXH5mklgRZCVYdu3iPgyzlXBCsQCAHrI2c6LbN6nU6P/oYLtbeDNOZzzirWcU6VnKETVSxhVfpSdof7ImMUQOBwDyoiSx+t3GADbG2PBrmXvTnUun0AZ+PYNWym/fYxfZoq2IZP2NjUv3RZT4NghUIzJd6jvBzWtkRt3tNP+f4B+3c4kGsJ88d8xGsGlr5Ga9SHZ2ikcO8lHTYMW5yNr8dkAOBsmENR/g166iOeyU4yDU+o604HFLTZD6CNUodK6YG6iqnudtv5RB3eRq9MhDVG4e00kDgBRpYw/KkeuYd7GNzdk56qahigIdF49+VJvMRrOcMpOEhuIw3aEk68j7/4KsgWIHANJbxNq8lffGvYE9u1AqLaJg2ySh+5hnDkoZgNXCQPUlRrXZ6OVciRdGBQD7ZwJv8c9LCpYpaJuJeDCYYpqJ0shkmyUCwqlnKUlbSmkYySNW0/I7EFPdlbkWvjEWOqiHjNLAwSTj7NnM4KrjJKcP00EMnt0swvpyBYDWyj1fZzC5WZn6xRg5G5mAJ+jnON0GwAguVlbzDS2zPrptVmjzlNCe4zcUCOVdlQwaC1cAefsMe6ueVblvJLjYmGRT2UsWV0I84sFDZxHt8SGPUUS6nPOMcf+RGaZoEZxbDWkorq+d7sQoWTf2trGU/h6eG4RN9eUqluCkQmAeNNNPEAfayIV/XHaeb9pJNkMxAsJ4zlIMNvn38F45GP05wgR+4EDYTA+XLWo6yi71szON1F1Gbmyh+fshAsCYYycEcchMrkxaJY/yVO6EsMVDWbOGXvMui+Xqdzo8KavOy9swRcwvW5GZfongw9iLJSmqSkk3GqAk28YHyopFGaqIf69nHAbbkawAJV+NBbtBdymuXufVnMfvYwyYOszTuEXTSRlf04zhnuVuUnmiBwPxIVH1MBn9rOMK6PA6ghzYucpuzkVt7KTK3YDVxiN/RGuVhxcsF/h9ORz9O0MfjIFiBcqGGvfwLu6JXKlmSg0dpFno4zp/ppCepWq7kmFuwalnPwVhT2iYYZpjHnOdYcXs3BgLzoIK66PHZx5E8LgCnM8BtTpVg4tULzC1YA4wnLb9joYKbtNHBMe7FevJAoBioYAd7aeVI1o6BWdJARVmkZ88tWMMM8JwV8V11jIv8gYs8LOUVdSCQikQt7T+zjVVxd7PKlFoaWFSCmaIvkFKwKqmiitUsym5bYTxquDMZluqijR+5msVpA4EiZPLBaWU/b8TtGZER44wyxgMGctb4IZ+kFKwlbGcrm9nH4iyu0cs12pPU/QnHw0owUI5MPjhbODyvktsYecxVbnCDS6XW+mpGUgrWUl7ln1jPquwsG3s4zt94HL0yTFcJVooHAnOyNHpwNrC20OYOD/mOz3nA/dJfD5rl81zENt7IonJwkudc5/vQBiuwAIjxwcmePq7wbel4TMxJypTyGppj2toYoa90utwHAtkQ44OTPSP0lpFa4f8HeGj/kKol/n8AAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "generate_example_image(route_type=\"dot\").resize(\n", " (IMG_SHOW_SIZE, IMG_SHOW_SIZE), Image.Resampling.BICUBIC\n", ")" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Zeigt das Scenario mit dem Seed 42 mit eingezeichneten Wendepunkten, wenn dieses Notebook im Pyrate Docker Container ausgeführt wurde." ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "generate_example_image(route_type=\"line\").resize(\n", " (IMG_SHOW_SIZE, IMG_SHOW_SIZE), Image.Resampling.BICUBIC\n", ")" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "### Massengenerierung von Daten\n", "\n", "Die oben definierten Funktionen generieren immer einen Datensatz.\n", "Die folgenden Funktionen definieren einen einzelnen Datensatz als `pd.Series` einer einzelnen Zeile in einem `pd.DataFrame`. Die so erzeugten Datensatze werden in `pd.DataFrames` zusammengefasst. Hier wurde eine Anzahl von 50 Datensätzen auf einmal gewählt. Diese werden dann gespeichert, um danach mehr Daten zu generieren. Da der Wegfindealgorithmus immer noch experimentell ist, werden Wege die nicht gefunden worden oder bei deren finden ein Fehler auftritt werden mit `NaN` gefüllt." ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "def generate_all_to_series(\n", " seed: Optional[int] = None, image: bool = False\n", ") -> pd.Series:\n", " \"\"\"Generates everything and aggregates all data into a `pd:Series`.\n", "\n", " Args:\n", " seed:The seed that should be used to generate map and destination.\n", " image: If an image should be generated or if that should be postponed to save memory.\n", " Returns:\n", " Contains a `pd.Series`containing the following.\n", " - The seed tha generated the map.\n", " - The destination in x\n", " - The destination in y\n", " - A list of Obstacle polygons.\n", " - The route generated for this map by the roBOOTer navigation system.\n", " - Optionally the image containing all the information.\n", " Can be generated at a later date without the fear for a loss of accuracy.\n", " \"\"\"\n", " # generate obstacles\n", " obstacles = generate_obstacles(seed)\n", " # find a destination\n", " destination = generate_destination(obstacles, seed)\n", "\n", " # find a possible route\n", " try:\n", " route, _ = experiments.generate_route(\n", " position=Point(0, 0),\n", " goal=destination,\n", " obstacles=obstacles,\n", " wind=(18, wind_dir),\n", " )\n", " except Exception:\n", " route = None\n", "\n", " # collect all generated data in a `pd.Series`\n", " return pd.Series(\n", " data={\n", " \"seed\": str(seed),\n", " \"obstacles\": obstacles,\n", " \"destination_x\": destination.x,\n", " \"destination_y\": destination.y,\n", " \"image\": generate_image_from_map(obstacles, destination, route)\n", " if image\n", " else pd.NA,\n", " \"route\": route.points if route else pd.NA,\n", " \"cost\": route.cost if route else pd.NA,\n", " },\n", " name=str(seed),\n", " )" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Nachfolgend wird ein kurzes Beispiel eines solchen `pd.DataFrame` angezeigt." ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "a213b11143904833af23d70963e1ae17", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/12 [00:00\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
obstaclesdestination_xdestination_yimageroutecost
seed
0{'0': POLYGON ((-17.62168766659423 -98.3692662...-66.0-54.0<NA><NA><NA>
1{'0': POLYGON ((-97.82715137072381 -82.2211677...-38.065.0<NA><NA><NA>
2{'0': POLYGON ((-46.23706006792075 -76.7569948...73.049.0<NA><NA><NA>
3{'0': POLYGON ((-7.4210414351932155 -83.111096...31.056.0<NA><NA><NA>
4{'0': POLYGON ((-77.97638439917915 -70.2390972...47.054.0<NA><NA><NA>
5{'0': POLYGON ((-71.45682729091783 -138.627922...-67.037.0<NA><NA><NA>
6{'0': POLYGON ((-76.20025009472265 -92.9434076...-67.055.0<NA><NA><NA>
7{'0': POLYGON ((10.806865516434499 -102.670968...67.0-52.0<NA><NA><NA>
8{'0': POLYGON ((-38.740101054728726 -89.986420...58.061.0<NA><NA><NA>
9{'0': POLYGON ((-28.332925461055822 -73.516031...45.0-63.0<NA><NA><NA>
10{'0': POLYGON ((-42.90670292182745 -82.5864109...38.048.0<NA><NA><NA>
11{'0': POLYGON ((-124.01583316741481 -73.449792...-48.0-31.0<NA><NA><NA>
\n", "" ], "text/plain": [ " obstacles destination_x \\\n", "seed \n", "0 {'0': POLYGON ((-17.62168766659423 -98.3692662... -66.0 \n", "1 {'0': POLYGON ((-97.82715137072381 -82.2211677... -38.0 \n", "2 {'0': POLYGON ((-46.23706006792075 -76.7569948... 73.0 \n", "3 {'0': POLYGON ((-7.4210414351932155 -83.111096... 31.0 \n", "4 {'0': POLYGON ((-77.97638439917915 -70.2390972... 47.0 \n", "5 {'0': POLYGON ((-71.45682729091783 -138.627922... -67.0 \n", "6 {'0': POLYGON ((-76.20025009472265 -92.9434076... -67.0 \n", "7 {'0': POLYGON ((10.806865516434499 -102.670968... 67.0 \n", "8 {'0': POLYGON ((-38.740101054728726 -89.986420... 58.0 \n", "9 {'0': POLYGON ((-28.332925461055822 -73.516031... 45.0 \n", "10 {'0': POLYGON ((-42.90670292182745 -82.5864109... 38.0 \n", "11 {'0': POLYGON ((-124.01583316741481 -73.449792... -48.0 \n", "\n", " destination_y image route cost \n", "seed \n", "0 -54.0 \n", "1 65.0 \n", "2 49.0 \n", "3 56.0 \n", "4 54.0 \n", "5 37.0 \n", "6 55.0 \n", "7 -52.0 \n", "8 61.0 \n", "9 -63.0 \n", "10 48.0 \n", "11 -31.0 " ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "if not NO_SHOW:\n", " df = pd.DataFrame(\n", " [generate_all_to_series(i, image=False) for i in tqdm(range(12))]\n", " ).set_index(\"seed\")\n", " df.to_pickle(\"test.pickle\")\n", "if os.path.exists(\"test.pickle\"):\n", " df = pd.read_pickle(\"test.pickle\")\n", "else:\n", " df = None\n", " print(\"No data generated or cached!\")\n", "df" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "\n" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Die folgende Zelle ist Verantwortlich für das massenweise Generieren von Trainingsdaten. Sie kann entweder so eingestellt werden das nur eine einzige Batch aus 50 neuen Datensätzen generiert werden soll oder eine ganze Reihe von Batches. Sind nicht alle anforderungen zun Ausführen der Zelle erfüllt, wird sie automatische übersprungen." ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "# Skips the following cell if the code can't be executed.\n", "if os.getenv(\"PYRATE\"):\n", " save_frequency = int(os.getenv(\"save_frequency\", \"50\"))\n", " start_seed = int(os.getenv(\"seed_start\", \"0\"))\n", " continues = bool(os.getenv(\"continues\", \"false\"))\n", "\n", " # try finding a block of seeds that is not used\n", " files = glob.glob(\"data/*.pickle\")\n", " seed_groups = {int(file[9:-7]) for file in files}\n", " for next_seeds in range(start_seed, 1_000_000, save_frequency):\n", " # skip if the seed block already exists or is generated by another instance if this notebook\n", " if next_seeds in seed_groups:\n", " continue\n", "\n", " # start generating routes for the seed block\n", " print(f\"Start generating routes for seed: {next_seeds}\")\n", "\n", " # reserving the seed block by looking down the seed block with an empty file\n", " tmp_pickle_str: str = f\"data/tmp_{next_seeds:010}.pickle\"\n", " pd.DataFrame().to_pickle(tmp_pickle_str)\n", "\n", " # generate the data\n", " df = pd.DataFrame(\n", " [\n", " generate_all_to_series(i, image=False)\n", " for i in tqdm(range(next_seeds, next_seeds + save_frequency, 1))\n", " ]\n", " ).set_index(\"seed\")\n", "\n", " # saves the data and delete the temporary file\n", " pickle_to_file = f\"data/raw_{next_seeds:010}.pickle\"\n", " df.to_pickle(pickle_to_file)\n", " os.remove(tmp_pickle_str)\n", "\n", " # break the loop if only a single block of data should be generated.\n", " if not continues:\n", " break" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "### Daten Zusammenfassen\n", "\n", "Nachdem man den generierenden Teil des Codes für eine Weile hat laufen lassen, erhält man eine vielzahl einzelner Dateien. Diese werden nachfolgend zusammengefasst. Diese so zusammengefasste Tabelle wird nachfolgend bereinigt.\n", "Direkt nach dem Zusammenfassen der Daten werden alle einträge für die keine Routen gefunden wurde weggelassen.\n", "\n", "Dies kann folgende Gründe haben:\n", "* Startpunkt $P(0, 0)$ ist von Hindernissen eingeschlossen\n", "* Der Zielpunkt ist von Hindernissen eingeschlossen\n", "* Fehler im Algorithmus der die Routen generiert" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "1023e2613a834adc908af154412557f0", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/500 [00:00\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
obstaclesdestination_xdestination_yimageroutecost
seed
0{'0': POLYGON ((-17.62168766659423 -98.3692662...-66.0-54.0<NA>[[0.0, 0.0], [-6.514627334268863, -5.502693040...100.151629
1{'0': POLYGON ((-97.82715137072381 -82.2211677...-38.065.0<NA>[[0.0, 0.0], [-38.0, 65.0]]75292.761936
2{'0': POLYGON ((-46.23706006792075 -76.7569948...73.049.0<NA>[[0.0, 0.0], [43.20648551245758, 31.2114102262...18967.522925
3{'0': POLYGON ((-7.4210414351932155 -83.111096...31.056.0<NA>[[0.0, 0.0], [5.303962239032221, 10.6856391688...63200.630758
4{'0': POLYGON ((-77.97638439917915 -70.2390972...47.054.0<NA>[[0.0, 0.0], [4.691900284503645, -5.4114328014...28914.654143
.....................
25045{'0': POLYGON ((-80.44890007800937 -70.4569634...-67.0-27.0<NA>[[0.0, 0.0], [-4.984525555905634, 5.2282410983...309.600598
25046{'0': POLYGON ((-63.55966988255701 -93.6258511...-44.0-65.0<NA>[[0.0, 0.0], [-4.3999999999999995, -6.50000000...191.114502
25047{'0': POLYGON ((-63.7334990739641 -93.02063274...-34.047.0<NA>[[0.0, 0.0], [-14.236853557702911, 5.258136784...38963.48483
25048{'0': POLYGON ((-66.53560391342282 -88.9214851...-34.029.0<NA>[[0.0, 0.0], [-34.0, 29.0]]152.757587
25049{'0': POLYGON ((-31.03667561920566 -52.0295076...49.059.0<NA>[[0.0, 0.0], [49.0, 59.0]]1438.645384
\n", "

23280 rows × 6 columns

\n", "" ], "text/plain": [ " obstacles destination_x \\\n", "seed \n", "0 {'0': POLYGON ((-17.62168766659423 -98.3692662... -66.0 \n", "1 {'0': POLYGON ((-97.82715137072381 -82.2211677... -38.0 \n", "2 {'0': POLYGON ((-46.23706006792075 -76.7569948... 73.0 \n", "3 {'0': POLYGON ((-7.4210414351932155 -83.111096... 31.0 \n", "4 {'0': POLYGON ((-77.97638439917915 -70.2390972... 47.0 \n", "... ... ... \n", "25045 {'0': POLYGON ((-80.44890007800937 -70.4569634... -67.0 \n", "25046 {'0': POLYGON ((-63.55966988255701 -93.6258511... -44.0 \n", "25047 {'0': POLYGON ((-63.7334990739641 -93.02063274... -34.0 \n", "25048 {'0': POLYGON ((-66.53560391342282 -88.9214851... -34.0 \n", "25049 {'0': POLYGON ((-31.03667561920566 -52.0295076... 49.0 \n", "\n", " destination_y image route \\\n", "seed \n", "0 -54.0 [[0.0, 0.0], [-6.514627334268863, -5.502693040... \n", "1 65.0 [[0.0, 0.0], [-38.0, 65.0]] \n", "2 49.0 [[0.0, 0.0], [43.20648551245758, 31.2114102262... \n", "3 56.0 [[0.0, 0.0], [5.303962239032221, 10.6856391688... \n", "4 54.0 [[0.0, 0.0], [4.691900284503645, -5.4114328014... \n", "... ... ... ... \n", "25045 -27.0 [[0.0, 0.0], [-4.984525555905634, 5.2282410983... \n", "25046 -65.0 [[0.0, 0.0], [-4.3999999999999995, -6.50000000... \n", "25047 47.0 [[0.0, 0.0], [-14.236853557702911, 5.258136784... \n", "25048 29.0 [[0.0, 0.0], [-34.0, 29.0]] \n", "25049 59.0 [[0.0, 0.0], [49.0, 59.0]] \n", "\n", " cost \n", "seed \n", "0 100.151629 \n", "1 75292.761936 \n", "2 18967.522925 \n", "3 63200.630758 \n", "4 28914.654143 \n", "... ... \n", "25045 309.600598 \n", "25046 191.114502 \n", "25047 38963.48483 \n", "25048 152.757587 \n", "25049 1438.645384 \n", "\n", "[23280 rows x 6 columns]" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "DATA_COLLECTION_PATH: Final[str] = \"data/collected.pickle\"\n", "\n", "# Load a cached result should it not be demanded to generate all data new.\n", "if os.path.exists(DATA_COLLECTION_PATH) and not GENERATE_NEW:\n", " collected_data = pd.read_pickle(DATA_COLLECTION_PATH)\n", "else:\n", " # Read the first n files\n", " # The number of files read can be defined with the constant: NUMBER_OF_FILES_LIMIT\n", " # The dataframes read are concatenate directly after\n", " collected_data = pd.concat(\n", " [\n", " pd.read_pickle(filename)\n", " for filename in tqdm(glob.glob(\"data/raw_*.pickle\")[:NUMBER_OF_FILES_LIMIT])\n", " ]\n", " )\n", "# Prints a short summary of the data.\n", "number_of_maps = len(collected_data.index)\n", "print(f\"{number_of_maps: 8} maps collected\")\n", "collected_data.dropna(subset=[\"route\"], inplace=True)\n", "number_of_routes = len(collected_data.index)\n", "print(f\"{number_of_routes: 8} routes collected\")\n", "collected_data.to_pickle(DATA_COLLECTION_PATH)\n", "collected_data" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "### Daten Filtern\n", "\n", "Die so erzeugten Daten sind ungefiltert. Sie müssen nun überprüft werden. Dazu wurden einige hundert Datensätze geplottet. Einige Muster sind dabei aufgefallen. Die nachfolgenden Filter resultieren aus diesen Mustern.\n", "\n", "#### Die Route verlässt die Karte\n", "\n", "Das Generieren von Heatmaps von Segelrouten erfordert, das sich das mögliche Ergebnis sinnvoll darstellen lässt. Dazu muss die Route vollständig im definierten Bereich liegen. Alle Routen, die die Karte verlassen werden, weggelassen." ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "23280 - 102 = 23178 sets of data remaining.\n" ] } ], "source": [ "def check_route_in_bounds(route):\n", " \"\"\"\n", " Check if a route exists and is in bounds.\n", "\n", " Args:\n", " route: An `np.ndarray` of points the builds the route.\n", "\n", " Returns:\n", " A non-existing route or a route that leaves the area routes should stick to return `False` otherwise, `True` is returned.\n", " \"\"\"\n", "\n", " # CHecks if the route exists\n", " if route is None:\n", " return False\n", " if route is pd.NA:\n", " return False\n", " # Checks if the route is of the right data type.\n", " if not isinstance(route, np.ndarray):\n", " return False\n", " # Checks if a position is out of bounds.\n", " if np.array(\n", " abs(route) > SIZE_ROUTE,\n", " ).any():\n", " return False\n", " return True\n", "\n", "\n", "# Count the number of data points there are before this filter is used.\n", "data_before = len(collected_data.index)\n", "\n", "# Filtering\n", "df_filter = collected_data[\"route\"].apply(check_route_in_bounds)\n", "filtered = collected_data[~df_filter]\n", "collected_data = collected_data[df_filter]\n", "\n", "# Count the number of data points there are after this filter is used.\n", "data_after = len(collected_data.index)\n", "\n", "# Print a short report over the changes to the dataset.\n", "print(\n", " f\"{data_before} - {data_before-data_after} = {data_after} sets of data remaining.\"\n", ")\n", "\n", "# delete variables that where only used inside this cell\n", "del data_before, data_after, filtered, df_filter" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "#### Routen auf Fehler überprüfen\n", "\n", "Ein bug in der Routenfindung hat zu selbstschneidung der Routen geführt dieser wurde beim Sailing Team Darmstadt e.V. behoben. In den ersten ca. 27000 datensätzen gibt es dennoch Selbstschneidungen der Routen. Diese werden hier erkannt und da nicht Representative und nicht richtig aus diesem Datensatz herausgenommen." ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "23178 - 2080 = 21098 sets of data remaining.\n" ] } ], "source": [ "def check_route_self_crossing(route):\n", " \"\"\"\n", " Check if a route has self intersections.\n", "\n", " Args:\n", " route: An `np.ndarray` of points the builds the route.\n", "\n", " Returns:\n", " `True` if the route is self intersecting.\n", " \"\"\"\n", " if isinstance(route, float):\n", " print(float)\n", " return not LineString(route).is_simple\n", "\n", "\n", "# count the number of data points before this filter was applied.\n", "data_before = len(collected_data.index)\n", "\n", "# filter the data\n", "collected_data = collected_data[\n", " ~collected_data[\"route\"].apply(check_route_self_crossing)\n", "]\n", "\n", "# count the number of data points after this filter was applied.\n", "data_after = len(collected_data.index)\n", "\n", "# print a short report over the changes to the dataset.\n", "print(\n", " f\"{data_before} - {data_before-data_after} = {data_after} sets of data remaining.\"\n", ")\n", "\n", "# delete variables that where only used inside this cell\n", "del data_before, data_after" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "#### Filter der Routen nach Kosten\n", "\n", "Einige der Routen haben trotz einer Erfolgreichen wegfindung enorm hohe kosten. Kosten werden beim Generieren der route mitberechnet und sind was bei dem Routen generierenden Gradientenabstiegsverfahren optimiert worden. Sie setzen sich zusammen aus Segelzeit und Risiken. Außerordentlich hohe Kosten legen daher entwendet nahe, dass keine gute Route gefunden werden konnte oder das die gefundene Route zu einem schlechten Lokalen Minimum konvergiert hat. Daher werden die teuersten $5\\%$ der Routen weggelassen.\n", "\n", "Die folgende Route berechnet das $95\\%$ Quantil und errechnet wie viele Einträge über $95\\%$ liegen." ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1054 entries over the 0.95 quantile at 39452.885\n" ] } ], "source": [ "QUANTILE_LIMIT: Final[float] = 0.95\n", "if \"DATA_UPPER_LIMIT_QUANTIL\" not in locals():\n", " DATA_UPPER_LIMIT_QUANTIL: Final[float] = collected_data[\"cost\"].quantile(\n", " QUANTILE_LIMIT\n", " )\n", " OVER_QUANTILE: Final[int] = int(len(collected_data.index) * (1 - QUANTILE_LIMIT))\n", "# noinspection PyUnboundLocalVariable\n", "print(\n", " f\"{OVER_QUANTILE} entries over the {QUANTILE_LIMIT} quantile at {DATA_UPPER_LIMIT_QUANTIL:.3f}\"\n", ")" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Der folgende Codeschnipsel berechnet das Histogramm der Kosten. Wie wenig repräsentativ die höchsten $5\\%$ der Kosten sind, ist direkt ersichtlich." ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "collected_data[\"cost\"].plot.hist(bins=15, log=True)\n", "plt.axvline(x=DATA_UPPER_LIMIT_QUANTIL, color=\"RED\", label=\"95% Quantil\")\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Nachfolgend werden einige der Route mit sehr hohen Kosten gezeigt. Die Meisten kommen dem Land sehr nahe oder Segeln sehr stark gegen den Wind." ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "153f22c0c53d498c80fef9e08c241c30", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/12 [00:00" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(15, 25))\n", "for count, (seed, row) in tqdm(\n", " enumerate(\n", " collected_data[collected_data[\"cost\"] > DATA_UPPER_LIMIT_QUANTIL]\n", " .sort_values(\"cost\")\n", " .iloc[0 :: int(OVER_QUANTILE / 12)]\n", " .iloc[:12]\n", " .iterrows()\n", " ),\n", " total=12,\n", "):\n", " plt.subplot(5, 3, count + 1)\n", " plot_situation(\n", " destination=Point(row.destination_x, row.destination_y),\n", " obstacles=row.obstacles,\n", " obstacle_color=\"RED\",\n", " route=row.route,\n", " title=f\"Cost: {row.cost}\",\n", " )\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Die Daten werden nun beim $95\\%$ Quantil der Kosten gefiltert." ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
obstaclesdestination_xdestination_yimageroutecost
seed
0{'0': POLYGON ((-17.62168766659423 -98.3692662...-66.0-54.0<NA>[[0.0, 0.0], [-6.514627334268863, -5.502693040...100.151629
2{'0': POLYGON ((-46.23706006792075 -76.7569948...73.049.0<NA>[[0.0, 0.0], [43.20648551245758, 31.2114102262...18967.522925
4{'0': POLYGON ((-77.97638439917915 -70.2390972...47.054.0<NA>[[0.0, 0.0], [4.691900284503645, -5.4114328014...28914.654143
5{'0': POLYGON ((-71.45682729091783 -138.627922...-67.037.0<NA>[[0.0, 0.0], [-42.539218405821984, 15.14880405...186.095369
6{'0': POLYGON ((-76.20025009472265 -92.9434076...-67.055.0<NA>[[0.0, 0.0], [-7.80975254664349, 3.41866699781...23898.229531
.....................
25045{'0': POLYGON ((-80.44890007800937 -70.4569634...-67.0-27.0<NA>[[0.0, 0.0], [-4.984525555905634, 5.2282410983...309.600598
25046{'0': POLYGON ((-63.55966988255701 -93.6258511...-44.0-65.0<NA>[[0.0, 0.0], [-4.3999999999999995, -6.50000000...191.114502
25047{'0': POLYGON ((-63.7334990739641 -93.02063274...-34.047.0<NA>[[0.0, 0.0], [-14.236853557702911, 5.258136784...38963.48483
25048{'0': POLYGON ((-66.53560391342282 -88.9214851...-34.029.0<NA>[[0.0, 0.0], [-34.0, 29.0]]152.757587
25049{'0': POLYGON ((-31.03667561920566 -52.0295076...49.059.0<NA>[[0.0, 0.0], [49.0, 59.0]]1438.645384
\n", "

20043 rows × 6 columns

\n", "
" ], "text/plain": [ " obstacles destination_x \\\n", "seed \n", "0 {'0': POLYGON ((-17.62168766659423 -98.3692662... -66.0 \n", "2 {'0': POLYGON ((-46.23706006792075 -76.7569948... 73.0 \n", "4 {'0': POLYGON ((-77.97638439917915 -70.2390972... 47.0 \n", "5 {'0': POLYGON ((-71.45682729091783 -138.627922... -67.0 \n", "6 {'0': POLYGON ((-76.20025009472265 -92.9434076... -67.0 \n", "... ... ... \n", "25045 {'0': POLYGON ((-80.44890007800937 -70.4569634... -67.0 \n", "25046 {'0': POLYGON ((-63.55966988255701 -93.6258511... -44.0 \n", "25047 {'0': POLYGON ((-63.7334990739641 -93.02063274... -34.0 \n", "25048 {'0': POLYGON ((-66.53560391342282 -88.9214851... -34.0 \n", "25049 {'0': POLYGON ((-31.03667561920566 -52.0295076... 49.0 \n", "\n", " destination_y image route \\\n", "seed \n", "0 -54.0 [[0.0, 0.0], [-6.514627334268863, -5.502693040... \n", "2 49.0 [[0.0, 0.0], [43.20648551245758, 31.2114102262... \n", "4 54.0 [[0.0, 0.0], [4.691900284503645, -5.4114328014... \n", "5 37.0 [[0.0, 0.0], [-42.539218405821984, 15.14880405... \n", "6 55.0 [[0.0, 0.0], [-7.80975254664349, 3.41866699781... \n", "... ... ... ... \n", "25045 -27.0 [[0.0, 0.0], [-4.984525555905634, 5.2282410983... \n", "25046 -65.0 [[0.0, 0.0], [-4.3999999999999995, -6.50000000... \n", "25047 47.0 [[0.0, 0.0], [-14.236853557702911, 5.258136784... \n", "25048 29.0 [[0.0, 0.0], [-34.0, 29.0]] \n", "25049 59.0 [[0.0, 0.0], [49.0, 59.0]] \n", "\n", " cost \n", "seed \n", "0 100.151629 \n", "2 18967.522925 \n", "4 28914.654143 \n", "5 186.095369 \n", "6 23898.229531 \n", "... ... \n", "25045 309.600598 \n", "25046 191.114502 \n", "25047 38963.48483 \n", "25048 152.757587 \n", "25049 1438.645384 \n", "\n", "[20043 rows x 6 columns]" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "collected_data = collected_data.loc[collected_data[\"cost\"] < DATA_UPPER_LIMIT_QUANTIL]\n", "collected_data" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Ein neues Histogramm der Kostenfunktion wird geplottet." ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "collected_data[\"cost\"].plot.hist(log=True)\n", "plt.title(\"Route costs cut at the 95% quantile\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "#### Filter der Routen nach Komplexität" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Gegenüber den Routen mit zu hohen Kosten stehen die Routen mit zu geringen Kosten. Daher werden als nächsten Routen mit zu niedrigen Kosten betrachtet.\n", "Nachfolgend ist eine Auswahl solcher günstiger Routen angezeigt. Es fällt auf das all diese Routen direkt sind.\n", "Eine betrachtung der Verteilung der Routenpunkte ist daher notwendig." ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(17.5, 25))\n", "for count, (seed, row) in enumerate(\n", " collected_data[collected_data[\"cost\"] < DATA_UPPER_LIMIT_QUANTIL]\n", " .sort_values(\"cost\")\n", " .iloc[1:600:51]\n", " .iterrows()\n", "):\n", " plt.subplot(4, 3, count + 1)\n", " plot_situation(\n", " destination=Point(row.destination_x, row.destination_y),\n", " obstacles=row.obstacles,\n", " obstacle_color=\"RED\",\n", " route=row.route,\n", " title=f\"Cost: {row.cost:.3f}\",\n", " legend=count == 0,\n", " )\n", "plt.show()\n", "del seed" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "def get_route_points(data):\n", " \"\"\"\n", " Counts how many stops are made inbetween.\n", "\n", " Args:\n", " data: a `pd.DataFrame` collecting all the data.\n", " Returns:\n", "\n", " \"\"\"\n", " complexity = data[\"route\"].apply(lambda r: r.shape[0] - 2)\n", " complexity.name = \"route complexity\"\n", " return complexity\n", "\n", "\n", "route_points = get_route_points(collected_data)\n", "route_points.plot.hist()\n", "plt.title(\"Route complexity in intermediate points\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Bei der oben angezeigten Komplexität wird, deutlich das diese teilweise etwas noch ist. Hier wird ein Limit von 15 eingeführt." ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "20043 - 979 = 19064 if only routes with less then 15 course changes remain.\n" ] } ], "source": [ "routes_before = len(collected_data.index)\n", "collected_data = collected_data[route_points <= 15]\n", "routes_after = len(collected_data.index)\n", "print(\n", " f\"{routes_before} - {routes_before - routes_after} = {routes_after} \"\n", " f\"if only routes with less then 15 course changes remain.\"\n", ")" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "get_route_points(collected_data).plot.hist(bins=15)\n", "plt.title(\"Route complexity in intermediate points\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Die nun reduzierte Anzahl der Routen enthält eine zwar Representative mange an sehr einfachen Routen. Da das Ergebnis dieser Routen aber eine lehre, Heat Map für Kursänderungen ist, muss hier deutlich reduziert werden sodas sie nur einen angegebenen anteil am Gesamtvolumen ausmachen. Dieser Anteil wurde hier auf $5\\%$ gesetzt." ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Limiting simple cases to 5.0% of the total routes. Reducing simple routes to 11.3% of their volume.\n" ] } ], "source": [ "# Define the upper limit of the percentage easy routes should reach\n", "LIMIT_SIMPLE_CASES = 0.05\n", "values = get_route_points(collected_data).value_counts().sort_index()\n", "chance_limit = (\n", " (len(collected_data.index) * LIMIT_SIMPLE_CASES * (1 - LIMIT_SIMPLE_CASES))\n", " / values.get(0, 1)\n", " if 0 in values.index\n", " else 0\n", ")\n", "print(\n", " f\"Limiting simple cases to {LIMIT_SIMPLE_CASES * 100:.1f}% of the total routes. Reducing simple routes to {(chance_limit * 100):.1f}% of their volume.\"\n", ")" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Der folgende Abschnitt setzt das oben aufgestellte limit um." ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "np.random.seed = 0\n", "collected_data = collected_data[\n", " (\n", " (get_route_points(collected_data) > 1)\n", " | (np.random.random(len(collected_data.index)) < chance_limit)\n", " )\n", "]\n", "del chance_limit" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Die so veränderte distribution der Routenkomplexität sieht dann so aus." ] }, { "cell_type": "code", "execution_count": 34, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "get_route_points(collected_data).plot.hist(bins=15)\n", "plt.title(\"Complexity Distribution after an enforced limit to trivial solutions.\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Das `pd.DataFrame` welches die gefilterten Daten sammelt, sieht dann wie folgt aus:" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
obstaclesdestination_xdestination_yimageroutecost
seed
0{'0': POLYGON ((-17.62168766659423 -98.3692662...-66.0-54.0<NA>[[0.0, 0.0], [-6.514627334268863, -5.502693040...100.151629
2{'0': POLYGON ((-46.23706006792075 -76.7569948...73.049.0<NA>[[0.0, 0.0], [43.20648551245758, 31.2114102262...18967.522925
4{'0': POLYGON ((-77.97638439917915 -70.2390972...47.054.0<NA>[[0.0, 0.0], [4.691900284503645, -5.4114328014...28914.654143
8{'0': POLYGON ((-38.740101054728726 -89.986420...58.061.0<NA>[[0.0, 0.0], [-8.211437427025228, -1.293253961...16899.906926
12{'0': POLYGON ((-78.64598261951151 -82.5905995...55.0-72.0<NA>[[0.0, 0.0], [7.15433954975134, 5.559264844101...177.415475
.....................
25037{'0': POLYGON ((-70.1543216286469 -126.2833218...-62.038.0<NA>[[0.0, 0.0], [-7.838432819436369, -0.057524750...18101.3419
25044{'0': POLYGON ((-94.3612368741144 -96.08652939...70.054.0<NA>[[0.0, 0.0], [-2.122974900266036, 8.5821312954...18061.452073
25045{'0': POLYGON ((-80.44890007800937 -70.4569634...-67.0-27.0<NA>[[0.0, 0.0], [-4.984525555905634, 5.2282410983...309.600598
25046{'0': POLYGON ((-63.55966988255701 -93.6258511...-44.0-65.0<NA>[[0.0, 0.0], [-4.3999999999999995, -6.50000000...191.114502
25047{'0': POLYGON ((-63.7334990739641 -93.02063274...-34.047.0<NA>[[0.0, 0.0], [-14.236853557702911, 5.258136784...38963.48483
\n", "

11883 rows × 6 columns

\n", "
" ], "text/plain": [ " obstacles destination_x \\\n", "seed \n", "0 {'0': POLYGON ((-17.62168766659423 -98.3692662... -66.0 \n", "2 {'0': POLYGON ((-46.23706006792075 -76.7569948... 73.0 \n", "4 {'0': POLYGON ((-77.97638439917915 -70.2390972... 47.0 \n", "8 {'0': POLYGON ((-38.740101054728726 -89.986420... 58.0 \n", "12 {'0': POLYGON ((-78.64598261951151 -82.5905995... 55.0 \n", "... ... ... \n", "25037 {'0': POLYGON ((-70.1543216286469 -126.2833218... -62.0 \n", "25044 {'0': POLYGON ((-94.3612368741144 -96.08652939... 70.0 \n", "25045 {'0': POLYGON ((-80.44890007800937 -70.4569634... -67.0 \n", "25046 {'0': POLYGON ((-63.55966988255701 -93.6258511... -44.0 \n", "25047 {'0': POLYGON ((-63.7334990739641 -93.02063274... -34.0 \n", "\n", " destination_y image route \\\n", "seed \n", "0 -54.0 [[0.0, 0.0], [-6.514627334268863, -5.502693040... \n", "2 49.0 [[0.0, 0.0], [43.20648551245758, 31.2114102262... \n", "4 54.0 [[0.0, 0.0], [4.691900284503645, -5.4114328014... \n", "8 61.0 [[0.0, 0.0], [-8.211437427025228, -1.293253961... \n", "12 -72.0 [[0.0, 0.0], [7.15433954975134, 5.559264844101... \n", "... ... ... ... \n", "25037 38.0 [[0.0, 0.0], [-7.838432819436369, -0.057524750... \n", "25044 54.0 [[0.0, 0.0], [-2.122974900266036, 8.5821312954... \n", "25045 -27.0 [[0.0, 0.0], [-4.984525555905634, 5.2282410983... \n", "25046 -65.0 [[0.0, 0.0], [-4.3999999999999995, -6.50000000... \n", "25047 47.0 [[0.0, 0.0], [-14.236853557702911, 5.258136784... \n", "\n", " cost \n", "seed \n", "0 100.151629 \n", "2 18967.522925 \n", "4 28914.654143 \n", "8 16899.906926 \n", "12 177.415475 \n", "... ... \n", "25037 18101.3419 \n", "25044 18061.452073 \n", "25045 309.600598 \n", "25046 191.114502 \n", "25047 38963.48483 \n", "\n", "[11883 rows x 6 columns]" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "collected_data" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "### Das konvertieren in trainierbare Daten\n", "\n", "Die bisher erstellten und gefilterten Daten müssen nun mit der oben definierten methode zum Generieren von Bildern `generate_image_from_map` transformiert werden. Die so transformierten daten werden dann zusammengefasst und in ein `tf.Dataset` konvertiert werden welches von Pandas genau für solche Fälle vorgesehen wird. Es gibt dort auch andere Methoden wie zum Beispiel die methode `tf.keras.utils.image_dataset_from_directory`. Bei diesem Problem besteht aber die Hoffnung, das auch ohne solche Methoden der RAM ausreicht und die Daten nicht immer wieder neu von der Festplatte gelesen werden müssen." ] }, { "cell_type": "code", "execution_count": 36, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "def generate_image_maps(row, route_type: Literal[\"dot\", \"line\"]):\n", " \"\"\"Generates the image version of the route.\n", "\n", " Adds another dimension to prepare vor concatenation in a later step.\n", " Divides by 0xFF to contain only 0 and 1 and values.\n", " Color channel zero contains obstacles.\n", " Color channel one contains the destination.\n", " Color channel two contains the route either as course change points or as continues lines.\n", "\n", " Args:\n", " row: The row of the pd.DataFrame that should be used to generate an image.\n", " route_type: Defines if the route should be drawn as a collection of course change points or continues lines.\n", " Returns:\n", " The image modified for concatenation and scaled to be easily used for pandas.\n", " Cast as uint8 for a minimal memory consumption.\n", " \"\"\"\n", " # expands the dimension by one\n", " img = np.expand_dims(\n", " # converts the image into a numpy array\n", " np.asarray(\n", " # generate the situation image form a map\n", " generate_image_from_map(\n", " obstacles=row.obstacles,\n", " destination=Point(row.destination_x, row.destination_y),\n", " route=row.route,\n", " route_type=route_type,\n", " )\n", " ),\n", " axis=0,\n", " )\n", " # integer divide to ensure all values are between 0 and 1\n", " img = img // 0xFF\n", " return img" ] }, { "cell_type": "code", "execution_count": 37, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "# drop the image column to save some space in the dataset\n", "if \"image\" in collected_data.columns:\n", " del collected_data[\"image\"]" ] }, { "cell_type": "code", "execution_count": 38, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "# save the collected and filtered data into a pickle file to load again later and flush the ram a bit.\n", "DATA_WITH_IMG_PATH: Final[str] = \"data/collected_and_filtered.pickle\"\n", "collected_data.to_pickle(DATA_WITH_IMG_PATH)" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "61be15a689ca481e8fa703626c66dbcb", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/11883 [00:00= 0 else 0`\n", "* LeakyRelu `y = x if x >= 0 else b * x` wobei $x$ eine Zahl viel kleiner als 1 ist.\n", "\n", "BatchNormalization normalisiert die Ausgabewerte einer Schicht über eine Training Batch, indem der Durchschnitt jeder Ausgangsschicht auf 0 geschoben wird und auf die Varianz 1 skaliert wird[5]. Beim Ausführen des Models wird die in der letzten Epoche festgelegte Gesamtbeschreibung und Skalierung genutzt. Dies sorgt zusammen mit dem DropOut Filter im Upsampler für ein konsistentes Lernen und verhindert das Overfitting.\n", "Interessanterweise erhält jedes Upsampling Schicht sowohl dass, vorangegangene Schicht als auch das Symmetrisch Downsampling Schicht als Input." ] }, { "cell_type": "code", "execution_count": 44, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "# Source: https://www.tensorflow.org/tutorials/generative/pix2pix\n", "def downsample(filters, size, apply_batchnorm=True):\n", " \"\"\"Create a downsample layer.\n", "\n", " A downsample layer contains:\n", " * tf.keras.layers.Conv2D\n", " * An aktivation Function\n", " * Optional a batchnorm\n", " * A activation function (LeakyRelu)\n", " Args:\n", " filters: The number of features that should be gernated.\n", " size: The number of features / pixels should be reduced.\n", " apply_batchnorm: If True the Batchnorm is applied. Batch norms are used by default.\n", " Returns:\n", " A sequentail model contain the keras generated layers.\n", " \"\"\"\n", "\n", " initializer = tf.random_normal_initializer(mean=0.0, stddev=0.02)\n", "\n", " result = tf.keras.Sequential()\n", " result.add(\n", " tf.keras.layers.Conv2D(\n", " filters,\n", " size,\n", " strides=2,\n", " padding=\"same\",\n", " kernel_initializer=initializer,\n", " use_bias=False,\n", " )\n", " )\n", "\n", " if apply_batchnorm:\n", " result.add(tf.keras.layers.BatchNormalization())\n", "\n", " result.add(tf.keras.layers.LeakyReLU())\n", "\n", " return result" ] }, { "cell_type": "code", "execution_count": 45, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "# Source: https://www.tensorflow.org/tutorials/generative/pix2pix\n", "def upsample(filters, size, apply_dropout=False):\n", " \"\"\"Create a upsample layer.\n", "\n", " A downsample layer contains:\n", " * tf.keras.layers.Conv2D\n", " * An aktivation Function\n", " * Optional a batchnorm\n", " * A activation function (LeakyRelu)\n", " Args:\n", " filters: The number of features that should be used to upsample the layer.\n", " size: The number of\n", " apply_dropout: If True a dropout layer ist used.\n", " Returns:\n", " A sequentail model contain the keras generated layers.\n", " \"\"\"\n", " initializer = tf.random_normal_initializer(0.0, 0.02)\n", "\n", " result = tf.keras.Sequential()\n", " result.add(\n", " tf.keras.layers.Conv2DTranspose(\n", " filters,\n", " size,\n", " strides=2,\n", " padding=\"same\",\n", " kernel_initializer=initializer,\n", " use_bias=False,\n", " )\n", " )\n", "\n", " result.add(tf.keras.layers.BatchNormalization())\n", "\n", " if apply_dropout:\n", " result.add(tf.keras.layers.Dropout(0.5))\n", "\n", " result.add(tf.keras.layers.ReLU())\n", "\n", " return result" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "#### Model erstellung\n", "Erstellt ein erstes model des Generatos wie oben beschrieben. Ein Schematisches Layout findet sich darunter." ] }, { "cell_type": "code", "execution_count": 46, "metadata": { "pycharm": { "name": "#%%\n" }, "scrolled": false }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "" ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ "def model_generator():\n", " \"\"\"Creates an initial sequential model.\n", " \n", " Returns:\n", " A Sequential model.\n", " \"\"\"\n", "\n", " inputs = tf.keras.layers.Input(shape=[IMG_SIZE, IMG_SIZE, 2])\n", "\n", " # down_stack = [\n", " # downsample(64, 4, apply_batchnorm=False), # (batch_size, 64, 64, 128)\n", " # downsample(128, 4), # (batch_size, 8, 8, 512)\n", " # downsample(512, 4), # (batch_size, 4, 4, 512)\n", " # downsample(512, 4), # (batch_size, 2, 2, 512)\n", " # downsample(512, 4), # (batch_size, 1, 1, 512)\n", " # downsample(512, 4), # (batch_size, 1, 1, 512)\n", " # downsample(512, 4), # (batch_size, 1, 1, 512)\n", " # ]\n", " #\n", " # up_stack = [\n", " # upsample(512, 4, apply_dropout=True), # (batch_size, 4, 4, 1024)\n", " # upsample(512, 4, apply_dropout=True), # (batch_size, 4, 4, 1024)\n", " # upsample(512, 4, apply_dropout=True), # (batch_size, 4, 4, 1024)\n", " # upsample(512, 4), # (batch_size, 16, 16, 1024)\n", " # upsample(128, 4), # (batch_size, 32, 32, 512)\n", " # upsample(64, 4), # (batch_size, 64, 64, 256)\n", " # ]\n", "\n", " down_stack = [\n", " downsample(64, 4, apply_batchnorm=False), # (batch_size, 64, 64, 128)\n", " downsample(128, 4), # (batch_size, 8, 8, 512)\n", " downsample(128, 4), # (batch_size, 4, 4, 512)\n", " downsample(256, 4), # (batch_size, 2, 2, 512)\n", " downsample(256, 4), # (batch_size, 1, 1, 512)\n", " downsample(512, 4), # (batch_size, 1, 1, 512)\n", " downsample(512, 4), # (batch_size, 1, 1, 512)\n", " ]\n", "\n", " up_stack = [\n", " upsample(512, 4, apply_dropout=True), # (batch_size, 4, 4, 1024)\n", " upsample(256, 4, apply_dropout=True), # (batch_size, 4, 4, 1024)\n", " upsample(256, 4, apply_dropout=True), # (batch_size, 4, 4, 1024)\n", " upsample(128, 4), # (batch_size, 16, 16, 1024)\n", " upsample(128, 4), # (batch_size, 32, 32, 512)\n", " upsample(64, 4), # (batch_size, 64, 64, 256)\n", " ]\n", "\n", " initializer = tf.random_normal_initializer(0.0, 0.02)\n", " last = tf.keras.layers.Conv2DTranspose(\n", " 1,\n", " 4,\n", " strides=2,\n", " padding=\"same\",\n", " kernel_initializer=initializer,\n", " activation=\"sigmoid\", # was tanh\n", " ) # (batch_size, 256, 256, 3)\n", "\n", " x = inputs\n", "\n", " # Down sampling through the model\n", " skips = []\n", " for down in down_stack:\n", " x = down(x)\n", " skips.append(x)\n", "\n", " skips = reversed(skips[:-1])\n", "\n", " # Up sampling and establishing the skip connections\n", " for up, skip in zip(up_stack, skips):\n", " x = up(x)\n", " x = tf.keras.layers.Concatenate()([x, skip])\n", "\n", " x = last(x)\n", " \n", " # drop the chanel dimension\n", " reshaped = tf.keras.layers.Reshape((128, 128))(x)\n", "\n", " return tf.keras.Model(inputs=inputs, outputs=reshaped)\n", "\n", "tf.keras.utils.plot_model(model_generator(), show_shapes=True, dpi=64)" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Um mehr controlle über den Lernprozess zu haben werden drei Coallbacks verwendet. Der EarlyStopping callback verhindert vor allem das Verschwenden von Rechenzeit indem er den Lernvorgang abbricht wenn eine weile keine Verbesserung gefunden wurde. Verschlechtert sich die beobachtete Metric wird der Lernvorgang abgebrochen." ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "early_stop = tf.keras.callbacks.EarlyStopping(\n", " monitor=\"mean_squared_error\",\n", " min_delta=0.00001,\n", " patience=5,\n", " verbose=0,\n", " mode=\"auto\",\n", " restore_best_weights=True,\n", ")" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Um den Lernforgang mit zu Loggen und anschließend zu Kontrollieren wird der Lernforgangn im Logverzeichtnis für Tensorboard mitgeschrieben. Auch profilingdaten werden erfasst." ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [], "source": [ "tf_board = tf.keras.callbacks.TensorBoard(\n", " log_dir=\"./log_dir\",\n", " histogram_freq=100,\n", " write_graph=False,\n", " write_images=False,\n", " write_steps_per_second=True,\n", " update_freq=\"epoch\",\n", " profile_batch=(20, 40),\n", " embeddings_freq=0,\n", " embeddings_metadata=None,\n", ")" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Die Lernrate kann mit der nachfolgenden Methode gesenkt werden damit eventuelle Platues überwunden werden können." ] }, { "cell_type": "code", "execution_count": 49, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "reduce_learning_rate = tf.keras.callbacks.ReduceLROnPlateau(\n", " monitor=\"some metric\", factor=0.2, patience=3, min_lr=0.001, verbose=1\n", ")" ] }, { "cell_type": "code", "execution_count": 50, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "0e9e9175dfe14e5280b5c25ecf51d1a4", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/3 [00:00" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(17.5, 25))\n", "np_array = np.flip(collected_routes[1, :, :, :], axis=0)\n", "\n", "for chanel in tqdm(range(3)):\n", " plt.subplot(1, 4, chanel + 1)\n", " plt.imshow(np_array[:, :, chanel], interpolation=\"nearest\")\n", "plt.subplot(1, 4, 4)\n", "plt.imshow(0x88 * np_array[:, :, 0] + 0xFF * np_array[:, :, 2], interpolation=\"nearest\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%%\n" } }, "source": [ "### Train Validate Test split\n", "\n", "Der Datensatz wird in Trainingsdaten, Validationdaten und Testdaten unterteilt. Folgenden Anteile werden ausgewählt:\n", "\n", "* $60\\%$ Trainingsdataen\n", "* $20\\%$ Validationdaten\n", "* $20\\%$ Testdaten\n", "\n", "Das Dataset von tensorflow ist theoretisch noch zu viel mehr im stande. Zum beispiel könnte man es nutzen um alle Datensätze zwei mal pro Epoche aufzurufen und einmal zu Vertikal zu Spiegeln. Dies würde die Datenmänge verdoppeln ohne den RAM zusätzlich zu belasten. Dies sprängt hier aber leider etwas den Rahmen." ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Compiliert das model und initialisiert die Schichten." ] }, { "cell_type": "code", "execution_count": 52, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 1/100\n", "298/298 [==============================] - 44s 126ms/step - loss: 0.0322 - binary_crossentropy: 0.0322 - mean_squared_error: 0.0064 - mean_absolute_error: 0.0205 - val_loss: 0.0217 - val_binary_crossentropy: 0.0217 - val_mean_squared_error: 0.0031 - val_mean_absolute_error: 0.0042\n", "Epoch 2/100\n", "298/298 [==============================] - 38s 126ms/step - loss: 0.0123 - binary_crossentropy: 0.0123 - mean_squared_error: 0.0029 - mean_absolute_error: 0.0057 - val_loss: 0.0186 - val_binary_crossentropy: 0.0186 - val_mean_squared_error: 0.0030 - val_mean_absolute_error: 0.0040\n", "Epoch 3/100\n", "298/298 [==============================] - 41s 137ms/step - loss: 0.0116 - binary_crossentropy: 0.0116 - mean_squared_error: 0.0028 - mean_absolute_error: 0.0056 - val_loss: 0.0125 - val_binary_crossentropy: 0.0125 - val_mean_squared_error: 0.0029 - val_mean_absolute_error: 0.0044\n", "Epoch 4/100\n", "298/298 [==============================] - 40s 135ms/step - loss: 0.0113 - binary_crossentropy: 0.0113 - mean_squared_error: 0.0028 - mean_absolute_error: 0.0055 - val_loss: 0.0228 - val_binary_crossentropy: 0.0228 - val_mean_squared_error: 0.0031 - val_mean_absolute_error: 0.0050\n", "Epoch 5/100\n", "298/298 [==============================] - 38s 129ms/step - loss: 0.0110 - binary_crossentropy: 0.0110 - mean_squared_error: 0.0027 - mean_absolute_error: 0.0055 - val_loss: 0.0131 - val_binary_crossentropy: 0.0131 - val_mean_squared_error: 0.0028 - val_mean_absolute_error: 0.0044\n", "Epoch 6/100\n", "298/298 [==============================] - 38s 126ms/step - loss: 0.0108 - binary_crossentropy: 0.0108 - mean_squared_error: 0.0027 - mean_absolute_error: 0.0054 - val_loss: 0.0132 - val_binary_crossentropy: 0.0132 - val_mean_squared_error: 0.0028 - val_mean_absolute_error: 0.0048\n", "Epoch 7/100\n", "298/298 [==============================] - 36s 122ms/step - loss: 0.0105 - binary_crossentropy: 0.0105 - mean_squared_error: 0.0027 - mean_absolute_error: 0.0054 - val_loss: 0.0167 - val_binary_crossentropy: 0.0167 - val_mean_squared_error: 0.0029 - val_mean_absolute_error: 0.0046\n", "Epoch 8/100\n", "298/298 [==============================] - ETA: 0s - loss: 0.0103 - binary_crossentropy: 0.0103 - mean_squared_error: 0.0027 - mean_absolute_error: 0.0053Restoring model weights from the end of the best epoch: 3.\n", "298/298 [==============================] - 36s 120ms/step - loss: 0.0103 - binary_crossentropy: 0.0103 - mean_squared_error: 0.0027 - mean_absolute_error: 0.0053 - val_loss: 0.0144 - val_binary_crossentropy: 0.0144 - val_mean_squared_error: 0.0028 - val_mean_absolute_error: 0.0045\n", "Epoch 8: early stopping\n" ] } ], "source": [ "if 'generator' in globals():\n", " # myVar exists.\n", " print(\"Generator exists. Deleting for reset\")\n", " del generator\n", "\n", "generator = model_generator()\n", "early_stop = tf.keras.callbacks.EarlyStopping(\n", " monitor=\"val_loss\",\n", " min_delta=0.00001,\n", " patience=5,\n", " verbose=2,\n", " mode=\"auto\",\n", " restore_best_weights=True,\n", ")\n", "\n", "generator.compile(\n", " optimizer=tf.keras.optimizers.RMSprop(),\n", " # Loss function to minimize\n", " loss=\"binary_crossentropy\",\n", " # tf.keras.losses.SparseCategoricalCrossentropy(),\n", " # List of metrics to monitor\n", " metrics=[\n", " \"binary_crossentropy\",\n", " \"mean_squared_error\",\n", " \"mean_absolute_error\",\n", " ], # root_mean_squared_error\n", ")\n", "\n", "history = generator.fit(\n", " collected_routes[:, :, :, :2],\n", " collected_routes[:, :, :, 2],\n", " validation_split=0.2,\n", " epochs=100,\n", " use_multiprocessing=False,\n", " workers=1,\n", " callbacks=[early_stop, tf_board, tf.keras.callbacks.TerminateOnNaN(),],\n", " # tqdm_callback,\n", ")" ] }, { "cell_type": "code", "execution_count": 53, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.plot(history.history[\"loss\"])\n", "plt.plot(history.history[\"val_loss\"])\n", "plt.title('model loss')\n", "plt.ylabel('loss')\n", "plt.xlabel('epoch')\n", "plt.legend(['loss', 'val_loss'], loc='best')\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%load_ext tensorboard" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%tensorboard --logdir log_dir" ] }, { "cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [], "source": [ "def plot_predicted_data(model, data, tt: Literal[\"Test\", \"Train\"], pos=0):\n", " plt.figure(figsize=(20, 25))\n", " if tt == \"Train\":\n", " pos = abs(pos)\n", " else:\n", " pos = -abs(pos) - 1\n", " data = data[pos, :, :, :]\n", " predicted = generator.predict(\n", " np.expand_dims(\n", " data[:, : , :2], 0),\n", " verbose=\"0\",\n", " steps=None,\n", " callbacks=None,\n", " max_queue_size=10,\n", " workers=1,\n", " use_multiprocessing=False,\n", " )[0]\n", " plt.subplot(1, 4, 1)\n", " plt.imshow(data[:, :, 0] * 2 + data[:, :, 2], interpolation=\"nearest\")\n", " plt.subplot(1, 4, 2)\n", " plt.imshow(data[:, :, 0] * 2 + predicted[:, :], interpolation=\"nearest\")\n", " plt.subplot(1, 4, 3)\n", " plt.title(f\"Predicted head map for {tt} Nr: {abs(pos)}\")\n", " plt.imshow(predicted[ :, :], interpolation=\"nearest\")\n", " plt.show()\n", " " ] }, { "cell_type": "code", "execution_count": 80, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAA2EAAAEiCAYAAABwX9rUAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAAA6F0lEQVR4nO3de5hlVXnn8d9bVX2xQYRWw9AXgQQ0MQ4XQcQxmfiIGRBbZYxjcBJFY0J8xhkNj4nXmZjMaGImTtSMiUq8QCIjKhIlHaVFokmMgnYrIQgirQTp5iqKF2i6u+q888de69SuXed+9tlnnb2/n+epp/rc19l16u3a+7fftczdBQAAAACoxty0BwAAAAAATcJOGAAAAABUiJ0wAAAAAKgQO2EAAAAAUCF2wgAAAACgQuyEAQAAAECF2AkDAADAKmZ2kZm9Ofz7583s5ope183suC63fd7Mfn3a45gmM3uqmd1iZj82s3OmPZ7IzN5gZu+b9jhmBTthAAAAM8rM/tXM9oU/yO8OO06Hlv067v6P7v64AcbzEjP7QtmvjxX+p6R3ufuh7v6JcZ7IzD4dPjs/NrODZnYgd/k9wzyXu/+Bu4+0gxw+t25mp+WuO87MRl7QOBw4+HHhy83slwZ8fPGxS2b2f0cdTxE7YQAAALPt2e5+qKQnSjpV0n8v3sHMFiofFSblaElfH+WBxc+Buz8z7MwdKukSSf87Xnb3l3d73IR8T9KbB7mjZXrux4QDB4fm3t82ST+WdOUgr1F47L+RtE/SxwZ57CDYCQMAAKgBd98r6dOSniC1T6d7hZndIumWcN02M7vOzO43sy+a2Qnx8WZ2spl91cx+ZGYfkbQ+d9vTzGxP7vJWM7vczO41s/vM7F1m9jOS3iPpKSE5uD/cd52Zvc3MvhPSuveY2cNyz/U7Znanmd1hZr82wFs92sz+KYzzM2b2qNxznR7e1/1m9s9m9rTcbS81s5vC475tZr+Zf9JhxhFOi3xzeK0fm9nfmNkjzewSM/uhmX3FzI7J3f+dZnZ7uG2Xmf187rbfM7PLzOwjYWxfNbMTu7zutyT9pKS/Ca+7zsw2mdkVZvY9M9ttZr/R4bk/ZGY/lPSSAbZvfGynz0+/9/Gh8O9jwuPPCz/375rZG/u85MWSTjCzX+gyns+b2VvM7J8kPRi2wzDOk3SZuz8w5OMk6Zck3SPpH0d4bEfshAEAANSAmW2VdLakr+WuPkfSkyU93sxOlvQBSb8p6ZGS3ivpivCH/FpJn5D0V5I2Kjvi3/G0LTObl7Rd0m2SjpG0WdKl7n6TpJdL+lJIEA4PD3mrpMdKOknSceH+vxue6yxJvy3pFyUdL+kZA7zV/yzppZJ+QtLa8HiZ2WZJf6ssTdkYrv+4mT06PO4eZWnIYeHxbzezJ44xjnMlvSi8n5+S9CVJHwyvfZOkN+Xu+5Xw/jdK+n+SPmZm63O3P1fZNo+3f8LM1hRf0N1/StJ3FNJPd98v6VJJeyRtkvR8SX9gZk8vPPdlkg5XlnYN4xyFz8+A76Po5yQ9TtIZkn437Kh386CkP5D0lh73eZGk8yU9XNJtZrbdzF7X702Y2SHKts3F/e7bxXmS/tLdRz49soidMAAAgNn2iZA6fUHS3yv7Qzb6Q3f/nrvvU/bH63vd/Vp3X3L3iyXtl3R6+Foj6R3uftDdL1P2B3cnpyn7g/933P0Bd3/I3Tv2gZmZhde9IIzjR2F854a7vEDSB939hpBQ/N4A7/eD7v7N8J4+qmynQJJ+VdKn3P1T7t5y96sk7VS2Yyp3/1t3/5Zn/l7SZyTFJGfUcXzL3X+gLIH8lrt/1t0Xle1QnRzv6O4fcvf73H3R3f+PpHXKdk6iXe5+mbsflPQnylLI0/sNIOx4P1XSa8PP4TpJ75P04tzdvuTunwjbZN8A7ysv//kZ5H0U/b6773P3f5b0z5I6Jnw575X0GDN7ZpfbL3L3r4fXP+ju29z9rQO8j+dJ+q6y34+hmNnRkn5Bo+/AdcROGAAAwGw7x90Pd/ej3f2/FP7Qvj3376MlvTqcqnd/2HHbqmyHapOkvYUj/bd1eb2tkm4LOxv9PFrSBkm7cq95Zbhe4XXzY+z2mnl35f79oKQ4EcnRkv5T4f39nKSjJMnMnmlm14TT9u5XtnMWT2UcZRx35/69r8Pl9gQpZvbb4VTIH4TXfkTutZV/bXdvaTnZ6meTpLhzmx/75k7PPYIVjx3gfRR1+1l1FJK9/xW++o5nCOMkWS+S9AV3v3XE1+6InTAAAID6yv/Rebukt4Qdtvi1wd0/LOlOSZtDchU9pstz3q4sreg0WUPxj9zvKtsh+dncaz4iTHag8LpbB3jNQdwu6a8K7+8Qd3+rma2T9HFJb5N0ZDhV8lOS4vstcxwrhL6p1yhL244Ir/2D3Gsr/9qWTTixRdIdAzz9HZI2mtnDc9c9RtLe3OVxTqFrP3bA91GGDyo7dfJ5vcYzqJAWPk3SX444nher5BRMYicMAACgKf5C0svN7MmWOcTMnhX+gP+SpEVJrzSzNWb2PGWnHXbyZWU7LW8Nz7HezJ4abrtb0pbQYxZTnb9Q1n/1E1LWu2VmZ4b7f1TSS8zs8Wa2QSv7qIb1IUnPNrMzzWw+jOtpZrZFWe/YOkn3SloMp7v9h9xjyxxH0cOVbdt7JS2Y2e8q60vLO8XMnhd2bH9L2Wmi1/R7Yne/XdIXJf1heL8nSHqZsm1RtkHex9hCwvomSa8t6SlfJOmL7v6t/JXhs9Fzp87M/p2yVLG0WREjdsIAAAAawN13SvoNSe+S9H1JuxVmy3P3A8qSh5comyr8lyVd3uV5liQ9W9kkG99RdurcL4eb/07Z9Ol3mdl3w3WvDa91TZih77MKfUTu/mlJ7wiP2x2+j/r+blc2CcUblO0o3C7pdyTNhdP1XqlsZ+v7yib3uCL32NLG0cEOZadgflPZqYIPafVpdZ9Utg2/r2yn4XmhP2wQL1Q2Qcodkv5a0pvc/bPjD3uVQd5HWWI625Nl65y9oc/duiVZW5XtwPZynqTLC6d7lsJKnOQDAAAAwBDM7PckHefuvzrtsTSJmb1P0sfcfcc0Xp+F+wAAAAA0irv/+jRfn9MRAQAAAKBCE9sJM7OzzOzmsHJ330XUAGASqEUAUkAtQjfu/nucitg8E+kJCyupf1PZquN7lC3290J3v7H0FwOALqhFAFJALQJQNKkk7DRJu93922G2nUuVzVYDAFWiFgFIAbUIwAqTmphjs1ZOWblH0pO73XmtrfP1OmTV9Y894cFV133z+g0dn6PTfavUbVxIzzCfFX6uw/mRvv9dd3/0tMeRU0otOv6EB1Zdd8v1q+/X7b5V6jYupGeYzwo/1+HUtRYBmC29atHUZkc0s/MlnS9J67VBT7YzVt1nx47rVl135qaTOj5fp/tWqdu4kJ5hPiv8XIfzWb/stmmPYViD1KLtV+5add22zad0fL5O961St3EhPcN8Vvi5DqeutQjAbOlViya1E7ZX2QJo0ZZwXZu7XyjpQkk6zDYO3Ji2447rJKX3x3EcV5Ta+JqkzM9Iqp83DGxitWj73uwP6NT+OI7jilIbX5OU+RlJ9fOGgU2sFgGYTZPqCfuKpOPN7FgzWyvpXOVWJQeAilCLAKSAWgRghYkkYe6+aGb/VdIOSfOSPuDuX5/EaxUTqFR0G9ckEhXSmkxxm5NOospaVEygUtFtXJNIVEhrMsVtTjqJKmsRgNkwsZ4wd/+UpE9N6vkBYBDUIgApoBYByJvaxBy9DJJupZqA9VNmOtMt+SHxWYneMIxqkHQr1QSsnzLTmW7JD4nPSvSGAQCiSfWEAQAAAAA6SDIJa5JOiV6/tGVWU8BJi9uN7QMMr1Oi1y9tmdUUcNLidmP7AAC6YScsQd1OWWTnYjCcMlgOTsFEt1MW2bkYDKcMloNTMAHUEacjAgAAAECFSMJmSL9EjMQCZSBxRT/9EjESC5SBxBVAnZGEAQAAAECFkkrCOAK/Urdki8SremzzZuEI/Erdki0Sr+qxzQGgHkjCAAAAAKBCSSVhAKaHJBpACkiiATQBSRgAAAAAVIgkDGg4EjAAKSABA9AkJGEAAAAAUCGSMKCh+iVgnWaEjI9htkgAZemXgHWaETI+htkiAcwqkjAAAAAAqFBSSVg8ut70HhVSBkxTt89f/vey7olYPLre9B4VUgZMU7fPX/73kkQMwKwiCQMAAACACiWVhAGYvGLSXNc0C0DaikkzaRaAJiEJAwAAAIAKJZWENb0XDKjCsMlXE38vm94LBlRh2OSL30sAdUISBgAAAAAVSioJazp6c9LT5J/JIAlY3WdJbCp6c9LT5J/JIAkYsyQCmDVJJGGPPeHBRp7yBCAtx5/wAKc8AQCAiUtiJwwAAAAAmoLTEQGsQCoNIAWk0gDqjCQMAAAAACpEEgZA0nAJGBNxAJiUYRIwJuIAMKtIwgAAAACgQiRhiSBZwLSQgCGPZAHTQgIGoElGTsLMbKuZfc7MbjSzr5vZq8L1G83sKjO7JXw/orzhAsBK1CIAqaAeARjUOEnYoqRXu/tXzezhknaZ2VWSXiLpand/q5m9TtLrJL12/KECmIYZSL+oRUADzEj6RT0CMJCRkzB3v9Pdvxr+/SNJN0naLOm5ki4Od7tY0jljjhEAuqIWAUgF9QjAoErpCTOzYySdLOlaSUe6+53hprskHVnGawAoV79esBlIwFahFgGzp18v2IwkYKtQjwD0MvbsiGZ2qKSPS/otd/9h/jZ3d0ne5XHnm9lOM9t5731L4w4DQMNRiwCkYpR6lK9FB7W/opECmJaxkjAzW6OsyFzi7peHq+82s6Pc/U4zO0rSPZ0e6+4XSrpQkk49cX3HP44AlK9bAjaLyVdUVi065cR11CKgIt0SsFlNvqJR61G+Fh1mG6lFQM2NMzuiSXq/pJvc/U9yN10h6bzw7/MkfXL04QFAb9QiAKmgHgEY1DhJ2FMlvUjSv5jZdeG6N0h6q6SPmtnLJN0m6QVjjbDmZjl9qLMm/Vxq8F6pRSWY9fShrpr0c6nJe6UeARjIyDth7v4FSdbl5jNGfV4AGAa1CEAqqEcABlXK7IgAlsWeq9QSplTHBWAyYs9VaglTquMCgCqNPTsiAAAAAGBwJGHAhKSWPKUyDgDVSi15SmUcADBN7IRNybT+IE5tx6DO2MaYBdP6gzi1HYM6YxsDQHo4HREAAAAAKkQSBuSMk16RMgIoyzjpFSkjAKSPJAwAAAAAKkQS1hAxpSleJrUpR3H7AugspjTFy6Q25ShuXwBAmkjCAAAAAKBCJGGAhk8EOyVfpIoAxjVsItgp+SJVBID0kYQBAAAAQIVIwio2rbQkvm6ZvWHF55rFJGjUMXfbnsCsmFZaEl+3zN6w4nPNYhI06pi7bU8AQNpIwgAAAACgQiRhDVNMfkZJcuqQgJWlye8dGEcx+RklyalDAlaWJr93AJhFJGEAAAAAUCGSsIoNkzxNImUp9oAVe5t6vWbdErBZHz8wjmGSp0mkLMUesGJvU6/XrFsCNuvjBwAMjyQMAAAAACpEEtYQ/RK4YRKwWUcCBkxPvwRumARs1pGAAUBzkYQBAAAAQIVIwmpu3BSrbikYgOkYN8WqWwoGAGg2kjAAAAAAqBBJWE31S7AGmQ0x3j7ofQGgqF+CNchsiPH2Qe8LAEDq2AmroUFOIRxmh4qdLwCjGOQUwmF2qNj5AgDUBacjAgAAAECFSMJqhEk0BsPplcBkMYnGYDi9EgCaiyQMAAAAACpEElYjJDuDidtp0skhPw80FcnOYOJ2mnRyyM8DANJDEgYAAAAAFSIJAyakyh49UjcA3VTZo0fqBgCDGTsJM7N5M/uamW0Pl481s2vNbLeZfcTM1o4/TADojVoEIAXUIgCDKON0xFdJuil3+Y8kvd3dj5P0fUkvK+E1gNLVKT3accd1zI5JLcKMqlN6tH3vLmbHpBYBGMBYO2FmtkXSsyS9L1w2SU+XdFm4y8WSzhnnNQCgH2oRgBRQiwAMatwk7B2SXiOpFS4/UtL97r4YLu+RtHnM12gs0o3JO3PTSbVKxBrsHaIWTQzpxuRt23xKrRKxBnuHqEUABjDyTpiZbZN0j7uP9D+zmZ1vZjvNbOe99y2NOgwADUctApCCMmvRQe0veXQAUjPO7IhPlfQcMztb0npJh0l6p6TDzWwhHPXZImlvpwe7+4WSLpSkU09c72OMo/ZiGkZig34a+lkprRadcuI6alEPMQ0jsUE/Df2slFaLDrON1CKg5kZOwtz99e6+xd2PkXSupL9z91+R9DlJzw93O0/SJ8ceJQB0QS0CkAJqEYBhTGKdsNdKutTM3izpa5LeP4HXaKRif1jD0o6JituyLj14DU3EiqhFE1LsD2tY2jFRcVvWpQevoYlYEbUIwCql7IS5++clfT78+9uSTivjeQFgGNQiACmgFgHoZxJJGCpC2lG+uiViVYnba/6o6Y4D00HaUb66JWJVidtr/aYpDwQA+ihjsWYAAAAAwIBIwoAa23HHdaUmpSSEAEaxfe+uUpNSEkIAs44kDOigzos4j7MIeJ23C5CiOi/iPM4i4HXeLgCagZ0wAAAAAKiQuU9/PcBTT1zvX96xddrDmHkkFJPTpNPwhvkcFbfL/FG7d7n7qeWOqDqnnLjOv3jl5mkPY+aRUExOk07DG+ZzVNwu6zfdOtO16DDb6E+2M6Y9DABj+qxf1rUWkYQBAAAAQIWYmAPACsMsfbD6PrvLHg6Ahhpm6YPV97l1AiMCgPKQhAEAAABAhdgJq5FxZr1Db02cFZDPE0Y1zqx36K2JswLyeQJQR+yEAQAAAECF2AmrIdKLyWliIgaMivRicpqYiAFAnbATBgAAAAAVYnbEmhpmhjugEz47KMMwM9wBnfDZAVBHJGEAAAAAUCF2wmqOGe4mg94wYDjMcDcZ9IYBwGxiJwwAAAAAKkRPWEPQIzYZcXvWKW3kM4JJokdsMuL2rFPayGcEQJ2RhAEAAABAhUjCGoZEbDLO3HRSsmnYoD/rVMePeiIRm4xtm09JNg0b9Ged6vgBoEwkYQAAAABQIZKwhiIRQxGfBUwDiRiK+CwAaAKSsIZjCvvypDhtfWrjAbphCvvypDhtfWrjAYBpYycMAAAAACrE6YhAyVKYtp4EDEAK09aTgAFAZyRhAAAAAFAhdsIAAAAAoELshAEAAABAhegJAyZkGr1h9IIBKJpGbxi9YADQ21hJmJkdbmaXmdk3zOwmM3uKmW00s6vM7Jbw/YiyBgsAnVCLAKSCegRgEOOejvhOSVe6+09LOlHSTZJeJ+lqdz9e0tXhMhKV4tpWdVPFNubnSC2adSmubVU3VWxjfo6SqEcABjDyTpiZPULSv5f0fkly9wPufr+k50q6ONztYknnjDdEAOiOWgQgFdQjAIMapyfsWEn3SvqgmZ0oaZekV0k60t3vDPe5S9KR4w0RQDcNT78iahEwZaRfbdQjAAMZ53TEBUlPlPRudz9Z0gMqxOvu7pK804PN7Hwz22lmO++9b2mMYQBoOGoRgFSMXI/yteig9lcyWADTM85O2B5Je9z92nD5MmWF524zO0qSwvd7Oj3Y3S9091Pd/dRHP3J+jGEAs4G+rYmhFgFDoG9rokauR/latEbrKhswEmGWfaExRt4Jc/e7JN1uZo8LV50h6UZJV0g6L1x3nqRPjjVCAOiBWgQgFdQjAIMad52w/ybpEjNbK+nbkl6qbMfuo2b2Mkm3SXrBmK8B1EoZ64eRqK1CLQKGVMb6YSRqHVGPMLh+6Ve83TueUY8ZNtZOmLtfJ+nUDjedMc7zAsAwqEUAUkE9AjCIcZMwABUiAQPGFI8qWzgbv8VkLKMgAQPGYwvhT/BQi/zggT4PKCRmJGMzj50wVGL320+XJB13wTVTHkk6hjktkZ0vYHy2sKDdf5QFFD/1ampRNMxpiex8AeOb27BBn979RUnSmZtPHu1JOE1x5o0zOyIAAAAAYEgkYahETMBIxFYrY6IOAD3MZUsP2Lp1Ov5/XC9J2v+MLNFZv3O3JGnphz/O7uut8H2CR5cTPYJdxkQdADoIv/O2sCb7/vBDdfaJvyhJuv2Nx0uSjv3QHknS0t67JEm+FE6VjjWpz3Nn9+1TU4qnNMbTsnu9RmJ1qk5IwgAAAACgQiRhDTWtHiMSseHQC4a6q6THKBzlbT34YPvI7/ov3yJJWvy3PylJmr/+W9l9HngwPKhwZHgSR4OHOYI9ZfSCASNYNZlGVleW7r1Ptib7E/zYi78jSdp7zmMkSZsvX8zu8937soccXOz4HD1fb9h6YrlMpvj8TAgyMSRhAAAAAFAhkjCgYsXer5h25XvDSMCAybC57KiuL2ZHlxduvC274chHSZLm7rwnu/3Awex77MsoJmN5gx4ZLk6Pnz/i3G3B1gkedS72fsW0K98bRgIGlMdby7/PFn7nfd8+SdLm7XslSft+5ihJ0vp/yWqUP5jd7g/tz773WlUj1pS+C0BnNcjm51c8zlu+fF3xqWMtTLSndRaRhAEAAABAhUjCMBUp9IZVlTh1m/Ww22uTggEl6XA0uH0kOvRZxKO7FpKx2KcRkzLzcLS609HnbkeCux0pbl9eOQPj9r27tG3LqeGxxWOj5c3W2G3Ww25pFykYMKb4extnaJ2z3E3htn0PZd9DzXnYTVkKr/Xrsu/7swRM8ysT9Hyq1rVPrNvsh/E5lrTqdm8VUrL2c/nK+5KIjY0kDAAAAAAqRBKGSsXkKxo2ARsmvRpk3a14nzLTp36vS9IFVCyXLrWPRLeP/IajvSER81Z2vS2ERKx9tDmu2ZNLr7olRYUjw4Osu7V9z05J6pGI9dHhqHS/1yXpAioWf6/nrN0T1v6dDbXGY/K1GNKz9euz65dCzQqJ2Yo1Dbv2lPaZ5bVTxB+ui/fs1iPW1mvtMVKynkjCAAAAAKBCJGGYuHz6NWrvVz5dGiThGuf5pdHSqkmMa9QxkLYBWt2D1SNdas/81VrZ99BOwnIJWDRIwjWsmIhFfdOqERKwKsQxkLYByqVWMTXqkS6FpMtDr1isTbGHrF2r8inTJBKnVnzdHjPD5hX7z0jB+iIJAwAAAIAKkYRhYoaZ+TCFFClv0EQptXFHJGKAeq+VE/oc2mv1hKO2V972ZUnSUjia29J0j+a2E6XYK9bnfqkhEUOjFdcG7HSX0H+qMDNruzcsJmIHDmTXTytZKrxue7zFu7VIvoZFEgYAAAAAFSIJQ2nGmfkwJjapJktR6uMrbseq1kIDZl1MxM7ckiU222//8jSH0104ov6p278iafpJXTcx+YpJWM/ZJIEmizO2xtSsGI8k1lsVE6/2mophzcXYQ4bBkYQBAAAAQIVIwhqmzFRk3DW/ZkGZvVXTSqToD0OKKk1FQnpkc7b873jUubAGjs0POBNYxYrriI2TgE0rkaI/DI1R6Edtr0+Y70WNtSf2ixX6VG3tWkkJ9IQVxdkP27M0plkzZwE7YRjaMBNuDCvV0xKLOzKpja8bdryAzuJEHPFPpXhqTRR3dopTxk9be2escLpf6tjxQpO1T+GLx3zm5vI3ZrfFHbd12c6XxRq1b192t7hI87T5yolDek6AhJ44HREAAAAAKkQShqHFBGySiRjGQwIGdJCbJtqKixy3j1TPr/g+F7KyVCfASB0JGJA7HbF9hbVrTKxLvhQSsfg9nI7YPi2x0yLNKUhtPDOEJAwAAAAAKkQShpFNMhFLtfdqVnvDACjrvYhHnWO/RSs76ryqvyEcpT5765MkpTdlfXGSi1npDQMaIaZDcTH4mLRbuH5paXlijjixRZji3R96KLvvmjXZ97A4si1kl/3ggYkOHdUhCQMAAACACpGENcQ4PULTnOI8tcRplG1AfxawbJweoaGnOG/3KsQplJeno7fijF4hEWtPEx37McL9tm09LRtDIonYKNuR/iygYsUa5LHuzC2n8Tbf8TEeapIdsiF7RKhNrR+Huy0eLLzGlBRr6bTHM0NIwgAAAACgQiRhNVdmClNMo+JzN3m2xNSSOiBVZaYwxf6nQZ/bWy6bCz1gYaIxmw/HIuc6H5OMiVi8NZnZEgtHn+kNA9IXe8PkLguzHcZKEnu/NF+oRaE2tROxcHXrRz/KHj+t9cPiotIhoVt+b0vTGc8MGisJM7MLzOzrZnaDmX3YzNab2bFmdq2Z7Tazj5jZ2rIGCwCdUIsApIJ6BGAQIydhZrZZ0islPd7d95nZRyWdK+lsSW9390vN7D2SXibp3aWMFgMpuwepW9qzOhnLvtdxtkT6utJFLUpX2T1I3dKevslYe6ay1c9ZnCWxPWNZnDVxbmVS9qyjs96wv7nt2qHHX4b2e4vvhf6LpFCP0FGxN6zlyy2qsfb4yr6xdt9qXB+sPXNrSMby64dNsQ4sJ2Ct3nfEKuP2hC1IepiZLUjaIOlOSU+XdFm4/WJJ54z5GgDQD7UIQCqoRwD6GjkJc/e9ZvY2Sd+RtE/SZyTtknS/u8cTVPdI2jz2KDGQqtOabq9X7BHLX1dXZ246ib6wKaEWpafqWfgGny2xJW+Fo8hz8Yh0WDcsHJK0eEQ5Hp1eKvQ3hKRsTjb9vrAOtm0+hb6wKaIeYSDeyhIs5XqqlsJsiCFZ8rmYynfusbK12bphemh/Gn1YpPJDGzkJM7MjJD1X0rGSNkk6RNJZQzz+fDPbaWY7770vgQ8PgJlELQKQinHqUb4WHdT+CY4SQArGmR3xGZJudfd7JcnMLpf0VEmHm9lCOOKzRdLeTg929wslXShJp564nt3nMaSSgBXl06+y+sSqTpzG2bb0kVWmtFp0yonrqEVjSDYBywt9C10TMYWj06H/Ynktn5V9GmdvfVKla4Z17XMb5bGYpJHrUb4WHWYbqUU15i2XhVoTe6rabZ5xrcL9YUc89ql6oW/VQg1bsyA/EPvJKvjYrFoXjF6wUY3TE/YdSaeb2QbL/lc6Q9KNkj4n6fnhPudJ+uR4QwSAnqhFAFJBPQIwkHF6wq41s8skfVXSoqSvKTuC87eSLjWzN4fr3l/GQLFaqglYJ2WuJTbtmRK7SXVcdUctmr6ZSMCk7ChxPIrbNxELR6eL64i118ZpaduWUyVJ2/fsHG08E8KaYdNDPUJPuVkSY+1RSMQ0F2pLvGtMxGJf6prwJ3voFbM12ePnlpbUin1kBw9MauSYgLEWa3b3N0l6U+Hqb0s6bZznBYBhUIsApIJ6BGAQY+2EYTpmudeo08yJ+etTMcvbGKjKTPYatdcM65KIxbV75gp9D/H+c/F+c5LPa9JmchsD6M1d7TXDQm9XnIm13SPWXhesUGfmCtevWZAdCAn+YqxrFfSGMRvi2NgJmwF13CEo7nSNcppiqqf/1fHnBUg12yHosjMWF0qNpyVqvscfNeGPp9RPSwSQsG6nRsedsnjgJ96/VahFLV81WUcSU9ajr3EXawYAAAAADIEkLGFNSlTKnLhjHE3a5sCgmpSotE8F6nem4fz88pFpX17AWVIpizg3aZsDjVRM4+PVMemKizfPx0mDwvULMa0Pt69b237sXEjPWvtLnLLeCmcDcBpiaUjCAAAAAKBCJGEJanIaM8rEHan2hgGzrhFpTJ/eMPeVizSvEKetD/0YZ299kiRVuogzgBmXm7ZeUq6va2VvWLxshUmCfHFRWsj+nLf167LvIUUrZcr6OB5VuCB0Q5CEAQAAAECFSMIS0uQErKiM2ROH0eRtP0qC2OTt1QSNSMCKConY8jTRPfog2gs3hway4qxlI2jktg9GWVy6ydsLNVNIxNqLOcfrDy5m39fEXrGwaLOZtBBSMV+ZiPniwcJzD6FT+p+/nkRsbCRhAAAAAFAhkrBEkCz0lu8V65aG0Rs2mlG2W7wvn9v6IVkoiGv4hL4M63EU2OZLXDesgUeb42dvmEQs3pfPLWqrVUjj9+/PLsZFmzsk8LZ2TfY9pGW+uDj+OIq1qIE1qmwkYQAAAABQIZKwKSFBGM1xF1zTd+bEYZIdfg7LituCRLEZSBAKuvRlxN6weETZzJZnR4zC5Xj0eZhErP1z6NaH0SDFz+QovWLAzCvO1BpnSYy9qCERizMjSmrP1BrTMVu7NjxVqGutpf6vW+x1jcPxPj1iq8ZPQtYPSRgAAAAAVIgkrGIkL+OreubEphokUaQ3bHaRgA0pHpUOyZjPSe3jv4UjxsWj0QOJR5OteGy0VRhH844uD9IrRm8YamPAmVo9zJZoLZfWhfXBFgp/1h8MvWEhRfP9gyRhcyu/d+s98y7rmmFgJGEAAAAAUCGSsIqRHJQvP3Ni/nK/JIefwWCYdbKeSA4G5IXesHzo1YpHggs9FIUkrF9v2LbNp8gWCv0XxaPO7YSsucnYKLMnArVRnKk1n3rFXq+lUCfibWuynjBbCo+Na4116w0z01yYWbH9sqHG2FwhrfeVSV2n52pSfRoFSRgAAAAAVCiJJOyb12/QmZtOatSRdhKx8nVLxDCYfp/J/PV1/V295fpDtG3zKY060k4i1kWhL6M4U5k0v+q+XjjqG9cN86U+xzvNlo8mF/sqCrM1dnps5/vPrn6fyfz1TfpdRcN0m6lVIcXK96K2OszemhNTM1uTffcDsZ6trHM2P79cx2IfWbE22cpkLH6P41sef4u1xPogCQMAAACACiWRhEVNXKeIRGzyij1NoyQ6df75FLfBIJ/JuveJNXGdIhKxIbVcHg9jxh6NLndtrxu29TRJ0qdu/4ok6eytT4pP1r6upd5HjGN/WdcZyfJHwGfs6HPx92yQzyR9Ymis0JPq7rJYB0JI5jq48r4xtQrrhrWTs1i7YqrmLfmBA+HfXeqHh4QsnA0QH2tzK2vRymSsub2svSS1E1ZU9z/08nbccV2t/9CvUr+JOppu0N+n4v06bb+mbNMm/aG3fe8udsTyuk0XPddqT1e/PIVz4Q+NuHhz+3L2r2cdk9WmOMmHL7b67nx1E/8A6no6Y8IG/X0q3q/T55PPLGpr1SnJ4Xc+TLZhOihXmIreutSReDriurAzthBPSzyw8qX27x9+Bynu4Fl4zjiRh5Yn//ABZsZvIk5HBAAAAIAKzcROWBOOtjfhPVbtuAuu0XEXXKPdbz+9nYphdE1IpPtpwtH2JrzHkbiHr1Z2yk7L5UtL2ek84cuXWoWvpfbpPlKWWtn8fHbkeK7byYuDsTnLGuJtTrK55ecOl7MvW/lVE01IpIFVQg3yVvbVrkVL2SmEK74WF1d86eCB7GuplX3Nz0nzc7I1C+3JOqQe0813EGtQu/aEL1tYyJK2VfWoQ21quJnYCQMAAACAukiiJ+yxJzyoHTt690TVrT+M5Ks6TF2fKeN3Z5A+sVl2/AkPaPuVvXui6tYfRvI1olzvVex3sPnCfULPmCv2SJQgTshhnY+h2pwNdTR7Gsr43RmkTwyopeIC8nOt3IQcmXatiT2j7QfHPrLCn/+xf3XO+reVxgSruDh98W7z8/IwMPOV1Y8esQxJGAAAAABUKIkkLOp1pD4ecZ/1RKxuycEs6ZSI9Zq+Hv3Vdbv1OlIfj7jPeiJGcjCiTjOHxZkTY/+X5Y5Q5x8aj/4W+8Fsrj31/PY9OyXlpqLP3Sf7Ziufo1fq1W0a+xpiiQU0RqxBcar4fMoUf+fDos3xvu3Fm+diOq+V18fLC7n+sEI9i+bWrlnxXPE52os8x1liW63l2ywuXF+IwBq+mDNJGAAAAABUKKkkrJdpJl9lLCJdt6RgmsZNX/KJWBPWEKvidye+xvxRE3+pqZtm8lXGItIkBeVZlb60j+oWezYKyVdMr+L6OnML7eueffSTs+uKbRZdesA6ia+XWm9YFb878TXWb5r4SwFpyKdIxYWUQ0+WxwWVY0oVE6rwsPZizWvXSmvCmmMHw4LPc4XaE5/LVqbyFp46raqTtr5V3cw+YGb3mNkNues2mtlVZnZL+H5EuN7M7E/NbLeZXW9mT5zk4AE0C/UIQAqoRQDGNcihtYsknVW47nWSrnb34yVdHS5L0jMlHR++zpf07nKG2d+Zm04qPc0o4zknMS6UgzXEZtJFSrwebdt8SulpUxnPOYlxoSCuJda+nFtTrFMq1fJ2Ambzc9lXWGPH1q7NvuKaO3FtsfiVe+wKvRIz1uYp00VKvBahwYq1p7CW4aq7u7d7umztmuzr0EOyrw0Py77Wrcu+Yk2Kj+2yLmKnWROL6xs2Xd8t4O7/IOl7haufK+ni8O+LJZ2Tu/4vPXONpMPNrAEnKAGoAvUIQAqoRQDGNWpP2JHufmf4912Sjgz/3izp9tz99oTr7lRFypg9cZzkitSrOmXMzFecMbF4/ayb1VlEh5RkPSpj9sRxkitSr+r0nZkvzk4YZzErHgFuuTS/cvYyFWYcWzUD2QCzIy73hk1/lsRZnUV0SEnWIjRQrBPF4Ltdi+LthfW73JcfEutUrDUdErTsKUKdKfaO5V4nPmd7TcUwc2x7xtiGzpI4dhbo2f8IQ281MzvfzHaa2c5772PVNgDjG6UeUYsAlG3cWnRQ+yc0MgCpGDUJu9vMjnL3O0Okfk+4fq+krbn7bQnXreLuF0q6UJIOs40+bJrRLwUZJREjAZsNk1grrph81TUZq6mx6lGxFg2bIPVLQUZJxEjAZkPXn22Xo8zLtxeOKNvccuLV6ny02bsdIS7OvChJWtmLYZY9tn3UWYWj4ShLqbVo0oNFA3SbqTXWmZhe5evOwbDG2HwhdS/WrdjzFa43FdL5+Xlpfm7ldaFnzA9kMy/GWWCX1yRrViI2ahJ2haTzwr/Pk/TJ3PUvDjMBnS7pB7loHgAmgXoEIAXUIgADs65H1+IdzD4s6WmSHiXpbklvkvQJSR+V9BhJt0l6gbt/z7ITQ9+lbMagByW91N139hvEYbbRn2xnjP4uBtApNRk3vdpxx3V9n6NbWkNyNr7itp3kNo3J2CwmYlX2hc0ftXuXu586qeefdD2qohZ1SsTGTa+2793V9zm6JXEkZ+MrbttV29Q694KtWj8sf5+OCVf+KVf3cqy6Phzlbh9ljkeh41HpYn/IhFXZF7Z+063UIiAq1KD2umBxja94udVa1Zdqa/qcNFfscY31Zn5+uY7F1w8JmB84kH1fir1h4TEV16QqfNYv61qL+p6O6O4v7HLTquoQzoF+xXDDA4DBUI8ApIBaBGBco/aEzZx8H1FZiUn+eQZNG0jAylPltizOojiLiRjSkO8jKiuFyj/PoGkDCVh5+m7L9lHdcJQ3HDlekUjFI9Rh1jC1Zw1bmYwVE7Coff3c3PJR53BEuz0zWfu+9IgBjVKsQXGm1lasRaEPzFvtXq9VM7IWk7Fiap/vBZOkhQVZ7AkL17kVetPijIsP7V8xLl9cHOVdzpzG7IRF4/zh3pDpvtHDLE5pP+5EJsP9zuwe6TWaaJydoIZM911fPaaKjztmVmyGj38stc8U6r/ocvuPqMIfVVpaOQtoe2fMJzs76LjLNgz3O3PrSK8BNMFynWmtur59kCbWmsJkQXEq+jipRqxNbR1Psw47cAvhQfPrs+8HD4bnCKclxp2v9umJ9T4wxHLVAAAAAFChxiVh08JpiPXSaUr7lNOwPD6LzcZpiFNUPKqbT7MK6ZgXT0cM5ydamH7e48mFhaPOvfKx9mlE8XSh0By/PLxqT0vkswhUrHBa4uo6szxJhsVTA4sTb3ioGwuhnsRkrJ20h/utNXl4jnZdipN+hETMFgq7IQdC4h+nya/5qdIkYQAAAABQIZKwAdALhn6Ou+Ca5CftIAGbffSC1Uyvo7tW6AmLD4lrms6tbKxv366l9nTT7Yb62G8Rnzo0y9vatdkV7emi43NN9ugzCRgwZat+t1f3qS6nZCvv207IYl9ZqCe+Zs3K+y0uLids8fUK/agK6bw97GFhGPE54yrO4bWWlmqZhpGEAQAAAECFSMIqUuXCwpiOcaexTz1JQz30XVgYaejWP+bFXo7CbIqabydfKsyg2G2BZ4Uj2BYut/sxJjxbIoBE5OtNcebVYhrfWtmnWlxguZ1imUlhtkMvLrExV+wzC489ZEN2c0jMWvvD1PVLS7kaWJ9EjCQMAAAAACpEEjYlJGP1NWgi1m2tsVmaaRGzj2RsRhQWTF2+PiRjrThDmS+v7xP7L+KR6ajQy9FeZDXMVBaPVrcOaNVRbgA1163WtG/vvOi8hWSsXSnm52XxvjERizWm3SMWbo/rh8Xn2pD1iM2F2tWS2v1kXqM1xEjCAAAAAKBCJGEDiCnVJGdJ3HHHdaRhNdMtEeuXkM3CTIuYjphSTXKWxO17d5GGpWyAXrFV6/uEo80+txgeUjjCHfoz2usDhaPPc2vXyONjFw92fn0A9dRrXUOpe69YK/SUtlyKaXucOfGh0OMV1ywsrkE2v7JmxXR+bsMGeZzFdd9D4QVnv2eVJAwAAAAAKkQSlhD6xOppnFkTScQwDfSJzZAO6/10W98nTmbW7hHz1WsDSbmeDgCIuqXgvdY0LPaUhp4vDz1i7bUKi+uHhRle27fPdelPm3EkYQAAAABQIZKwIVTRG5ZHMlYvw6RZxfSMRAx5VfSG5ZGMzZAVR6u7JF2Lna+P2sec5+eZHRFAb11rQy6Vb628T7tvdd++7Hvx9rmV64nZ2jXLr9MlwZ9FJGEAAAAAUKHaJWExPapjakQy1jwkX7Mrpkd1TI1IxmZE39nNOh/Bbq/Ds7REAgZgfN3WFpvr0U8mycNsinbgwHJdqhGSMAAAAACoUO2SsCpU3RvWTZ1TPwD9Vd0b1k2dU79aGTTVIv0CMK58HYkpfGtpxeVVS33Fx3RY/7Dj88642u6ENWkHhdMUgXQ1aQeF0xQBAKsUd5z67UjVaEerF05HBAAAAIAK1SYJm8apgWduOmnqpyR2kh8TqRhQrWmcGrht8ylTPyWxk/yYSMUAAFhGEgYAAAAAFar9TtiOO65LMq0CRsHneXZt37srybQKGAWfZwAYT+13wgAAAAAgJbXpCQPqrJh+NWn2TwDpKKZfTZr9EwDKRBIGAAAAABWqfRJGUoBZRv9XfZAUYJbR/wUA5eqbhJnZB8zsHjO7IXfdH5vZN8zsejP7azM7PHfb681st5ndbGZnTmjcABqGWgQgFdQjAOMa5HTEiySdVbjuKklPcPcTJH1T0uslycweL+lcST8bHvPnZjZf2mg7mOZscaQUmLaGzZZ4kRKuRdOcLY6UAtPWwNkSL1LC9QhA+vruhLn7P0j6XuG6z7j7Yrh4jaQt4d/PlXSpu+9391sl7ZZ0WonjBdBQ1CIAqaAeARhXGT1hvybpI+Hfm5UVnmhPuK5y9IJhljUo3SpTkrWIXjDMsoalW2VKsh4BSMdYO2Fm9kZJi5IuGeGx50s6X5LWa8M4wwDQcNQiAKkYtR5Ri4BmGXknzMxeImmbpDPc3cPVeyVtzd1tS7huFXe/UNKFknSYbfRO9xkFCRhm3SgpWJPXDUu1FpGAYdaNkoI1fd2wcerRpGoRgDSNtE6YmZ0l6TWSnuPuD+ZuukLSuWa2zsyOlXS8pC+PP0wAWI1aBCAV1CMAw+ibhJnZhyU9TdKjzGyPpDcpm/FnnaSrzEySrnH3l7v7183so5JuVBbFv8LdlyY1eKBO6APrjVoEVIM+sP6oRwDG1XcnzN1f2OHq9/e4/1skvWWcQQFAEbUIQCqoRwDGVcbsiFNRTA2a2AvTC9tjdpSZgDW5N2xaiqlBU3thumF7zI4yE7Cm94YBQD8j9YQhbfwBjoYt4oxE8Qc4GriIMwAMhJ0wAAAAAKjQzJ2OyGmI3bEtZgtJ1WzjNMTu2BazhaQKAKpHEgYAAAAAFZq5JIy0ZzW2yWypMgHbccd1fD4mhLRnNbbJbKkyAdu+dxefDwDIIQkDAAAAgArNXBKWglR6eUg4ZlP8uaXyOcLsSqWXh4RjNsWfWyqfIwBoEpIwAAAAAKiQufu0xyAzu1fSA5K+O+2xdPAoMa5hMK7h1G1cR7v7o8seTFWoRSNhXMNhXMOhFqWnbp+VSWNcw6nbuLrWoiR2wiTJzHa6+6nTHkcR4xoO4xoO40pPqu+dcQ2HcQ2HcaUn1ffOuIbDuIbTpHFxOiIAAAAAVIidMAAAAACoUEo7YRdOewBdMK7hMK7hMK70pPreGddwGNdwGFd6Un3vjGs4jGs4jRlXMj1hAAAAANAEKSVhAAAAAFB7SeyEmdlZZnazme02s9dNaQxbzexzZnajmX3dzF4Vrt9oZleZ2S3h+xFTGt+8mX3NzLaHy8ea2bVhm33EzNZOYUyHm9llZvYNM7vJzJ6SwvYyswvCz/AGM/uwma2fxvYysw+Y2T1mdkPuuo7bxzJ/GsZ3vZk9seJx/XH4OV5vZn9tZofnbnt9GNfNZnbmpMaVghRqURhHsvWIWjTUuJKoRWEsydUjalF31KKBxpZcLQrjSK4eUYtGGtPEa9HUd8LMbF7Sn0l6pqTHS3qhmT1+CkNZlPRqd3+8pNMlvSKM43WSrnb34yVdHS5Pw6sk3ZS7/EeS3u7ux0n6vqSXTWFM75R0pbv/tKQTw/imur3MbLOkV0o61d2fIGle0rmazva6SNJZheu6bZ9nSjo+fJ0v6d0Vj+sqSU9w9xMkfVPS6yUp/A6cK+lnw2P+PPzO1k5CtUhKux5RiwaQWC2S0qxHncZELaIWDSrFWiQlVo+oRSOPafK1yN2n+iXpKZJ25C6/XtLrExjXJyX9oqSbJR0VrjtK0s1TGMsWZR/Kp0vaLsmULRi30GkbVjSmR0i6VaGvMHf9VLeXpM2Sbpe0UdJC2F5nTmt7STpG0g39to+k90p6Yaf7VTGuwm3/UdIl4d8rfh8l7ZD0lCp/phV+dpKsRWEsSdQjatFQ40qqFoXXS64eUYs6vm9qUf9xJFeLwusmV4+oRaONqXDbRGrR1JMwLX84oj3huqkxs2MknSzpWklHuvud4aa7JB05hSG9Q9JrJLXC5UdKut/dF8PlaWyzYyXdK+mD4XSA95nZIZry9nL3vZLeJuk7ku6U9ANJuzT97RV12z4p/R78mqRPh3+nNK5JS/K9JlaP3iFq0UBmoBZJ6dcjalEmifdKLRpIcvWIWlSKidSiFHbCkmJmh0r6uKTfcvcf5m/zbJe30ukkzWybpHvcfVeVrzuABUlPlPRudz9Z0gMqxOtT2l5HSHquskK4SdIhWh0xJ2Ea26cfM3ujstNPLpn2WJBWPaIWDWeWapGUXj2iFqWFWjSw5OoRtWg8k6xFKeyE7ZW0NXd5S7iucma2RlmRucTdLw9X321mR4Xbj5J0T8XDeqqk55jZv0q6VFn0/k5Jh5vZQrjPNLbZHkl73P3acPkyZYVn2tvrGZJudfd73f2gpMuVbcNpb6+o2/aZ+u+Bmb1E0jZJvxKKYBLjqlBS7zXBekQtGk7qtUhKtB5Ri9J6r9SioaRYj6hFI5p0LUphJ+wrko4Ps7SsVdbsdkXVgzAzk/R+STe5+5/kbrpC0nnh3+cpOx+6Mu7+enff4u7HKNs2f+fuvyLpc5KeP8Vx3SXpdjN7XLjqDEk3asrbS1ncfrqZbQg/0ziuqW6vnG7b5wpJLw4zAZ0u6Qe5aH7izOwsZad2PMfdHyyM91wzW2dmxyprjv1yVeOqWBK1SEqzHlGLhpZ6LZISrEfUIknUop5SrUVhbCnWI2rRCCqpRWU0s437JelsZTOPfEvSG6c0hp9TFn9eL+m68HW2svOMr5Z0i6TPSto4xe30NEnbw79/MvzQd0v6mKR1UxjPSZJ2hm32CUlHpLC9JP2+pG9IukHSX0laN43tJenDys6/Pqjs6NjLum0fZU3FfxZ+B/5F2SxGVY5rt7JznONn/z25+78xjOtmSc+s+udZ8Wdn6rUojCPpekQtGnhcSdSiMJbk6hG1qOe2oRYNNr6kalEYR3L1iFo00pgmXossPBkAAAAAoAIpnI4IAAAAAI3BThgAAAAAVIidMAAAAACoEDthAAAAAFAhdsIAAAAAoELshAEAAABAhdgJAwAAAIAKsRMGAAAAABX6/0OBdRCgVrsNAAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "for i in range(10):\n", " plot_predicted_data(generator, collected_routes, \"Train\", i)" ] }, { "cell_type": "code", "execution_count": 79, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAA2EAAAEiCAYAAABwX9rUAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAAA7pUlEQVR4nO3de7hkdX3n+89337ppLkKLMjSXBgVNjAKaHsEj5jhiRIhGTo5jcExERRmek4nGJxchOY8685gZc8yJOk/m2EFRSWQAJUbxEjuAmgkzQtJoS1AEGmNLc21pWy5923vX9/yxfr/aVWtX7V1V61Jr1Xq/nqefvev+q8v+dq31Wd/fz9xdAAAAAIByTI17AAAAAADQJGyEAQAAAECJ2AgDAAAAgBKxEQYAAAAAJWIjDAAAAABKxEYYAAAAAJSIjTAAAAD0ZGafNrMPhN9fZmZ3l/S4bman9Lnsm2b29nGPY5zM7KVmdq+ZPWlmF4x7PBgeG2EAAAA1ZmY/MrN94Qv5I2HD6bC8H8fd/8HdnzvAeN5iZrfk/fjo8p8k/bm7H+buX8hyR2b2t+Gz86SZzZvZwY7Tm0e4v/eb2WdWuc6PzOxRMzu047y3m9k3R3gK8fa/Yma3mNkeM3vYzD5hZodnuL8/DRu6T5jZD8zszaPeVy9shAEAANTfa939MEkvkrRJ0v+dvoKZzZQ+KhRlo6TvjXLD9OfA3c8LG3OHSbpa0v8TT7v7pTmMtZ9pSe8a5IoDfnafJukDkjZI+nlJx0n60Mijk56S9NpwvxdJ+qiZ/W8Z7q8LG2EAAAATwt0fkPS3kp4vtQ+n+y0zu1fSveG815jZtpAY/C8zOy3e3sxeaGbfDnv/r5O0tuOyl5vZzo7TJ5jZ581sl5k9ZmZ/bmY/L2mzpJeEJGVPuO6akCz8OKR1m83skI77+n0ze8jMHjSztw3wVDea2f8M4/w7Mzu6477OCs9rj5l918xe3nHZW83srnC7H5rZv++802HGEQ6L/EB4rCfN7Etm9nQzu9rMHjezfzKzkzqu/1Ezuz9cdruZvazjsveb2fVmdl0Y27fN7PQ+j3ufpGdJ+lJ43DVmtsHMbjCz3Wa23cze0eO+P2Nmj0t6ywCvb7ztSp+V95jZA2G8d5vZOWb2akl/KOnXw9i+u8Ldf0jS75nZkX0ee9lndyXu/t/d/Wvuvtfdfyrp45JeOuhz7XF/73P3H7h7y91vk/QPkl4y6v2lsREGAAAwIczsBEnnS/pOx9kXSDpT0vPM7IWSPinp30t6uqS/kHRD+CI/J+kLkv5K0npJn5P0f/Z5nGlJX5a0Q9JJSlKHa939LkmXSvpWSFKODDf5oKTnSDpD0inh+u8N9/VqSb8n6ZclnSrplQM81X8n6a2SnilpLtxeZnacpK8oSUTWh/P/2syeEW73qKTXSDoi3P7DZvaiDOO4UNJvhufzbEnfkvSp8Nh3SXpfx3X/KTz/9ZL+u6TPmdnajstfp+Q1j5d/wcxm0w/o7s+W9GOF9NPdD0i6VtJOJSnQ6yX9ZzN7Req+r5d0pJK0a1WrfFaeK+k/SPrX7n64pHMl/cjdvybpP0u6Loyt54ZksFXSNxXeuz4uUPjshjHtMbOzBxm/pF/SiGlhWthh8K/zuj+JjTAAAIBJ8IWQOt0i6e+VfBGO/ou773b3fZIukfQX7n6buy+6+1WSDkg6K/yblfQRd5939+uVbDj08mIlX/h/392fcvf97t6zD8zMLDzuu8M4ngjjuzBc5Q2SPuXud7r7U5LeP8Dz/ZS73xOe02eVbNxI0m9I+qq7fzUkGDcq+bJ/viS5+1fc/T5P/L2kv5MUE6lRx3Gfu/9MSQJ5n7vf5O4LSjaoXhiv6O6fcffH3H3B3f9fSWskdfbY3e7u17v7vKQ/U5JCnrXaAMKG90slvSe8D9skfUJSZw/Tt9z9C+E12TfA85JW/qwshvE/z8xm3f1H7n7fgPfb6b2SfrtjIzmt87Mrdz+y3+esk5n9spJDCN87wph62Szpu5K25HR/bIQBAABMgAvCF9SN7v5/pb5o39/x+0ZJvxsShT1hw+0EJRtUGyQ94O7ecf0dfR7vBEk7wsbGap4haZ2k2zse82vhfIXH7Rxjv8fs9HDH73slxYlINkr6t6nnd7akYyXJzM4zs1vDYXt7lGycxUMZRxnHIx2/7+txuj1Bipn9XjgU8mfhsZ/W8djqfGx3b2kp2VrNBklx47Zz7Mf1uu8h9P2suPt2Sb+jZEP1UTO71swGGWsXd79TSaJ6WZ+rDD1uMztLSZL4ene/Z8DbbLalyUj+MHXZh5Qc3vuG1N9GJmyEAQAATLbOL473S/rjsMEW/61z92skPSTpuJBcRSf2uc/7JZ1ovSdMSH9R/YmSDZJf6HjMp4WJIBQe94QBHnMQ90v6q9TzO9TdP2hmayT9taQ/lXRMOFTyq5Li881zHF1C/9cfKEnbjgqP/bOOx1bnY5vZlKTjJT04wN0/KGm9dc8EeKKkBzpOj7LxsNJnJfZgna1kY80l/cmIj/U+Se9Q90bjSOMOh1DeIOlt7n7zoLdz90s7JiNpp8hm9h8lnSfpVe7++DBjWQ0bYQAAAM3xcUmXmtmZljjUkqm9D1fSz7Qg6Z1mNmtmv6bksMNe/lHJRssHw32sNbM4CcIjko4PPWYx1fm4kv6rZ0pJ75aZnRuu/1lJbzGz55nZOnX3UQ3rM5Jea2bnmtl0GNfLzex4Jb1jayTtkrRgZudJelXHbfMcR9rhSl7bXZJmzOy9SvrSOv2imf1a2LD9HSWH/t262h27+/2S/pek/xKe72mSLlbyWmTR97NiZs81s1eEDdv9SjayW+F2j0g6KWxIriqkatdJemeWwZrZ85UkrL/t7l/qcfn7bYgp8M3sciW9h69098eyjK0XNsIAAAAawt23Kkkd/lzSTyVtV5gtz90PSvq1cHq3pF+X9Pk+97OoZPruU5RMErEzXF+Svq5kAoOHzewn4bz3hMe61ZIZ+m5S6Idy97+V9JFwu+3h56jP734lk1D8oZINnvsl/b6kqXC43juVbGz9VMkX7Bs6bpvbOHrYomQD4R4lhwru1/JD7b6o5DX8qZLJPn4t9IcN4o1KJkh5UNLfSHqfu9+UZcArfVaUbMx+UEnK+bCSCVIuD5d9Lvx8zMy+PeDD/SdJh652pXC44Mv6XPy7Sg5xvbLj0MLOiTROkPQ/BxyPlPQtnihpe79DFbOwHA9tBAAAADAkM3u/pFPc/TfGPZZJZWbbJJ1TRKo1ChbtAwAAADDR3P2McY+hE4cjAgAAAECJCtsIM7NXW7J69nYz6zftJAAUiloEoAqoRViJu7+fQxGbpZCeMEtWUb9HyYrjO5Us9PdGd/9+7g8GAH1QiwBUAbUIQFpRSdiLJW139x+GmXauVTJTDQCUiVoEoAqoRQC6FDUxx3HqnnZzp6Qz+115ztb42tVnpQRQcU/opz9x92eMexwdqEVAA1GLAFTBSrVobLMjmtklki6RpLVapzPtnHENBUBObvLrd4x7DMOiFgGTh1oEoApWqkVFHY74gJIF0aLjw3lt7n6Fu29y902zWlPQMPK15cFt2vLgtnEPA8DgJrIWbd5xizbvuGXcwwAwuImsRQBGV9RG2D9JOtXMTjazOUkXqmNFcgAoCbUIQBVQiwB0KeRwRHdfMLP/IGmLpGlJn3T37xXxWEUi9Wqu+N6fu+GMsY4D2UxKLSL1aq743l+68ewxjwRZTEotApCfwnrC3P2rkr5a1P0DwCCoRQCqgFoEoFNhizVPMnrDmoP3GlVGb1hz8F4DwGRhIwwAAAAASsRGGAAAAACUaGzrhNUBkzI0T79DD5moA+PEpAzN0+/QQybqAIDJQBIGAAAAACViIwwAAAAASsRGGAAAAACUiI0wYAhMWQ+gCpiyHgDqjY0wAAAAACgRG2HACEZJxEjRAORtlESMFA0Axo+NMAAAAAAoEeuEAQVZbc2xNNYgA1CE1dYcS2MNMgAoHkkYAAAAAJSIJAxQ/3Rq0Nudu+GMzP1enbcnFQOaadRerXi7Szeenbnfq/P2pGIAUAySMAAAAAAoEUkYMIB+yVRMr/Ke9ZC+MQC99EumYnqV96yH9I0BQDFIwgAAAACgRCRhaLR04kTSBGAc0okTSRMATDaSMAAAAAAoEUkYGm3U5CvvHjAAzTZq8pV3DxgAoBwkYQAAAABQIpIwjMWwSVLTe7Wa/vyBogybJDW9V6vpzx8A8sJGGEqVx6LI48RhiMBkyGNR5HHiMEQAqDcORwQAAACAErERhlJseXBbLikSSRSALDbvuCWXFIkkCgCQBRthAAAAAFAiesJQuLzTq3H0h5HAAfWXd3o1jv4wEjgAmAwkYQAAAABQIpIwFKbo9KgqMyYCqLai06OqzJgIAKiPkZMwMzvBzL5hZt83s++Z2bvC+evN7EYzuzf8PCq/4QJAN2oRgKqgHgEYVJYkbEHS77r7t83scEm3m9mNkt4i6WZ3/6CZXSbpMknvyT5U1MUk9U+N+7mQ8g2EWoSeJql/atzPhZRvYNQjAAMZOQlz94fc/dvh9yck3SXpOEmvk3RVuNpVki7IOEYA6ItaBKAqqEcABpVLT5iZnSTphZJuk3SMuz8ULnpY0jF5PAbQT5G9YfE+x52IYTDUooKYdZ92H884Kq7I3rB4n+NOxDA46lEO0rXHUtmBt4a/T+oXKiLz7Ihmdpikv5b0O+7+eOdl7u6Sen7azewSM9tqZlvndSDrMAA0HLUIQFWMUo+oRUCzZErCzGxWSZG52t0/H85+xMyOdfeHzOxYSY/2uq27XyHpCkk6wtazWwIDo08KadSinIW9zzYzm/yc7t5f5wsLyc9Wn5drpb3TE7QXmj4p9DJqPaIWpZjJpqeTX9esSX6uXdN1Fd+3P/m5uJicka5JPWpRu26NkqK174S3B9llmR3RJF0p6S53/7OOi26QdFH4/SJJXxx9eACwMmoRgKqgHgEYVJYk7KWSflPSP5vZtnDeH0r6oKTPmtnFknZIekOmEaLRqpJ60RtWadSiPHXufZ5N/ouwuSQR88VWOD8kZPPzyflxr3B7L3Rye3mrR1o25N7niuxxrkrqRW9Y5VGP8mJTSwnYunXJz8OSn5pP0nhbu1aS5PuTREwhEYu1qm1+vl2nzGIS1t1vlq5VNmU9z5e3lveqpVWkbqHaRt4Ic/dbJPX7FJ4z6v0CwDCoRQCqgnoEYFC5zI6IfG3/8Fldp095961jGkn5qpJ8pZWdgFX1dUBDhCSs/XN2TpJkSQC2lIyF3jCL/Rhx72/YS+2Li+3L2mlZvG5K3/6yYZOzznFkUJXkK63sBKyqrwMmn01PL6Xxa5Ia1Dr0kK7r+CEhlT+40P0z1BPbGxKy+Xl5SO7baVmoU/F0est5eXIWa9H0CvUqDj78bPWud4CUw+yIAAAAAIDBkYRVUDr5qlsyNkj/VF2SHnrA0ETL9hDH/ofQI6GQhNlU2I8XesQUZ02MsysuWHse7nZaNpP8t5Pu2bDp+ODd53urx77CeJ24ZlCfWc4G6Z+qS9JDDxiaxhcX1QqzH9rBJMWairVoJikYC+tC7ZlJakHrkCQpm9ofalioWbZ/uh1OtetTrB+pdN7TyVhIxDpnYFxWr/qsX+axP5ZEDD2wEVYDk7JRVidsfAFLhwj6wYPJGamNLUs3p4fpoy0cAeQ2teyLzrIvOOnHjM3y8XpTy68ZN8yWLptOXd59+NB0uNo7TqzHBlcnNr7QOHEjqeNvP9YNf/Kp5LJDkwk6pg4sdN3GQ4maPzKZsGN2T7iDqal2vWrvEDqQ1LX2YYrx4eNh2Oma1T5Mu+PKrVb7/jvHodTh1x4fgo0xdOBwRAAAAAAoEUlYDeWRjMWkp8iUigQMqCF3ycPe2rBXtxUOBbJ4CGHcuxv3LLcn8Aj/pYRDDm1mWh4P15nq3rsdm96vuvtGSdKbn/VvVh+bxQQsdQhQvO+4FzqMMz6Nd2x8Wbh+6nlWGAkYGqvz8L+YWoW/9dbevcnJkM7HZTLi3/5UmMBjOqTyviapRa21M5qKqVVrpus27XoR7zvUM09PONSZek13p+/xdPs+4+XxKIKYzvea9j7WyIrXJOSPJAwAAAAAStToJGxyUo9tkpaSp85krF8q1m/yjDqmV3mYnM8C6qhKqcd0v2atDnHvXWpfsGbDXuDfOOUVyfUOP6y92GrsmYj9ZbFX7KLn/rIk6TM/TBKx+bA3+C0n/e9d993VGxb3Oqf3RsfrtgcafuvoEVvqF6tmb0aVPgvAWHUmQ+Hv1Q+G1ComTHHijtlUuhUXlI+p/L86Wq3Dkj6x1mxSe6afitcJ9SSmVKHvzOMRANOpvKLVWqpBsb6Fx1GqhzXeZzpdM/elPrc4EZJIxJqGJAwAAAAAStTIJGxSU4+l57WtZyomLU/G0olYr9dmktOxKn4WJvn1Rrcqph6LPXbCptOxVupnFFOsT9x7syRprZnefMZrJUkWpo62uaRnoz11ffj5m6eeI0n65D03SZKu/NHfdz3GlKSLQzpmnuq7aE+h3z1DmcU9yrbUIxb7ydqzMFZkr3MVPwt1mb4fDZL+e00nZPH8AweSnyFxnzp4UFMbjpEktY4+XJK0eFiSYsU8fSqm5HGpjfTPjj4uS/WJxbTMpma7xxcSOY+JXLyvg/NLU+a3kzA0DUkYAAAAAJSocUlYFZOPIizNfth9fkzGVkvEet1X+rp115TPAqqpislHP73SMal//1hMr/a669PbviRJessLzk/ODD0UFvcQh+vGu3prSMQ+FdK0Th8P6Vjce9hOxmIfRr/ZEqMpk9qLP3fPADnORKxOnwWgkvr9/YakrLVvv6YeeFiSNLsQzjs8SecXD13TdZNYT2Iy1go9Yu2aoY6etNjXFddObK8lFnrGYq/YdCqln5mRxxStPWNirE2pYwwqktYjfyRhAAAAAFCixiRhTU09lqdYyc/VErF+t+99n2csu06VNfWzgGqYpNQjJmQrzah4MOzFvfKOr0iS1oa06k1nvEbSUiKmsL5P3DP4tp97laSlfolP3Pf19n3G/cQxGYuW1gPrTsSWrenTeR1Pd7aVZ5I+C0CltRbV2p/0ifmDSSI2dUgyW+LMM49Ozj8kqUGtw9dJkqZDEjY1F1L7vfuSn/v2tSdXba8lFhOx8HDt2RDj2oZx9sZ2Mjbd0cPavf5hRSduRQFIwgAAAACgRBObhJF29JbuFeuXiEXnbjhj1dey3+V1S8jGhddpsjUh7VipZyw9k+JiSJ6u3vZlSdKbXhhmTzzs0ORnnEUsJGO+P1kH6O3PfkU7DeuXXX18xz90ne7ZO9be69ynD6PB/RfMhoiJ1uqeSXExpOwxJ7cwe+L8MUmvmK9JLpnal5ye+llYP2y3qbV3b/J7TMJSdSP2iMUesPb6YLPh58xMOwmLMyu2EzDrPQMkJg9JGAAAAACUyLwCe/2OsPV+pp2Ty32RgA0nvZ5Yv0RMyvbaViHtqfpnowqvUVY3+fW3u/umcY9jVHnWoiYkYIPo1y8W9wAeGnvENl0gqaNHLPRQaF+ShPmBg+29z3EdsmG7uaaUJGpdPPZhpPY2F/h/Y9U/G5OQiFGLsKo4U2Ho35o6PFk/zI9LErHFI5JZE1shEZv9aVKLph7fK9/90+Q6jz+Z3FdrwLSq4zHj2oltsa8szLzYXpfMSenrbKVaRBIGAAAAACWamJ6wqqccVTVMj9hKa4lVWd3Gi3qrespRtn4zKMYU66mwl/ea278oSXrjL75O0tJsYgozmNn0tCz0Wbz9WS+XJF3xw28O9FjpxxwXPhtAhYRkKabgcT2wqYcelSRN65mSpMVnJv2qB9cnydXs7LSmDyRp1VSYcbG1f8AkLD5my7XCpLKSOvpW271i41/TEPkiCQMAAACAEtUuCSPVKEa/ROy+X9+c+b7H1etUt8/K0ntwxljHgcGQagxntURsb+ipuHrrFyRJb3pRSMRmkn6Mr9z+NT3ZSnoy9oZdw/uH3CH8jo0vk01352HtvosC1e2zEsc7Cb1hwKrSiVjo85oKtWGNJ4lYa23ylXnq8X3yg/Pd9zFkSmVTJs1330cV5mhAuWqxEVa3L9N1lt4Ye7YubR+amMf7UMZCz3xeUJS6fZmuon4bY/Pty8MU9t9ODk9802m/Ikk6/xf+Tbtx/ervfS25blgatX0g0OrH97Q3uq4MCz3HTbJ3nBg2OOKXKUvd2QhfkPi8ADUSp7APNWjxZ49LkqZD3Zk+en1y+ZTJ1iaTdmg+OSzRFlMT/PSbTKNdX5YORGvFDbrUwvFxwpD2ws/tHUZM1DEpOBwRAAAAAEpUqSSMBKM6lt6LbXq2LpW0lI71O2xulJQrz0Pw+PwgLyQY45OesOMv70gWdZ61KV3486+SJL3pBedJkq65M0nELnxOMpV3nNr5E2HCjnbKFRdrnp5u721OT9Lx8R8n7/k7Nr4s83Pg8wPUmHcnTnFpDNuVnG9r5qQwvbwd+TRJ0lRYZF4xtXoiOaQxPd18O91au2bpcMQ+qVn7NlN9In4m6qg9kjAAAAAAKFGlkjBUU5ycIyZiz74uTGOv7mnsxzWF/aQlYFse3MbkHGi8mFTtD3t59/ui/ur7SfL15tNeI0n6d2GB56mnJws8+xNPSJLefmqSjH0qLOoc9z5ryuTzzV2EeVibd9zC5BxortSEHf5USMT2H5CFKertmKOTy44PCzwfOidJmn1oT3J+WNS5FRadn1oTesmmTJ6a2yMtnYAtm7KeBKz2SMIAAAAAoEQkYRhYTMRiStNvYedhUpwsic+kJWAAluvs3YqpWOwTe/OLLpAk2dqp8DNZ2DnuXXzbc16ZnB+CMHfv21+xNDvi8GOctAQMQIdUj5gvtKR9ye/26GPJz7l/lVz2tCTpWnxassDzdCu5XrtnLFrsqGztmRL7LCcfLm/PvIiJkTkJM7NpM/uOmX05nD7ZzG4zs+1mdp2ZzWUfJgCsjFoEoAqoRQAGkUcS9i5Jd0k6Ipz+E0kfdvdrzWyzpIslfSyHx0FF9FvYOZ2I9TJq8tU5iyIJGPqgFtVAen2wYaT7xD77nS9Jkn79pf823HmIvKx7/2J7EdSWt2ccizMmtmcmi+OKt/Xee6XbsyieeDYJGPqhFk2ijh6s9sLOsdfrsT3JBevXJT9nQno1m/qaHdYE60y12j2rvnwNseT8VC2iF2xiZErCzOx4Sb8i6RPhtEl6haTrw1WuknRBlscAgNVQiwBUAbUIwKCyJmEfkfQHkg4Pp58uaY+7L4TTOyUdt9qdPOe0vdqyZVvGoWAS9VpHrF+aNkkJWZ7rpzXER5RDLdr4gie0+SukG0VaDDtx80jE5uMe4oVUr0Tsv5gK+xk79zpPpfY2e/dAYlK2dEZyujMBi/rNHDhJCVl8LsySOLCPKIdahIpLzZwYE66phdA3FsvKXDJzazulnwofA1/KQJaSsJjYh/uIp9uzIfbpGUNtjZyEmdlrJD3q7rePePtLzGyrmW3d9RjNhgBGk2ct2r2b/+QAjCbPWjSvAzmPDkDVZEnCXirpV83sfElrlRz7/FFJR5rZTNjrc7ykB3rd2N2vkHSFJG06fS0HuKLLKElQExIy9JRbLXrBabPUooJlScDS5hX2Roe90Iop14HkC2x7L3U63ZKW7VVuJ2Dx/BUSsNU0ISFDT7nVoiNsPbWoDkK98H37JEnTjyc9Yh5SeHv8qeR0uyaF+tLqqD/9erzi+mSxjtELNnFGTsLc/XJ3P97dT5J0oaSvu/ubJH1D0uvD1S6S9MXMowSAPqhFAKqAWgRgGEWsE/YeSdea2QckfUfSlQU8BiZUEb1QdU7I6A3LhFo04RbjnuH5g8nP0FvRORviMqvMfpglAVtNnRMyesMyoRZNqtgbFn5O7U2SsHYvWOzvWkzVm6mODKTVnb7H65KATb5cNsLc/ZuSvhl+/6GkF+dxvwAwDGoRgCqgFgFYTRFJGDC0cSQ+nY9Vh1QMQLf2pGGhJ8xmkj3GyazgkqbDWj0rJGPpXrAiErDVdKZLdUjFAKTE/q0nkx4wO+SQ5PzYGxaTsY4+1XZdSs202LmGGCZbpnXCAAAAAADDIQnDyGJ69Ozrzsp8X+Pueapz3xjQBIvef2bFq+6+UZJ00c+9SpJks+G/ttAjZnEPc+duxz47m8tMwHqpc98Y0FQxUfe9ySyJFtcqXLsmOT2bJGHtLN5cFmdWbPXpT439q0pdTo/YxGAjDFhBVTbOmKADWL7Qc6t9fvdhPe2FURe7G96t1Vo6BKifeChjxb7oVGXjjAk6gB68e+r5dp0JO4RsPizS3J6gY3HZjqD2YdRhqY1lC8dj4nA4IgAAAACUiCQMyIDJPYByDLXIc9yD3O8wH6njUJ/JaIJncg9g/LyduqfS+fRkGyulXBNWm9AfSRgAAAAAlIgkDBhBTMA6e7Wq0j8GVFm6rytXqanp2wuixok5evR5Wey/qOlO55iAdfZqVaV/DGiMkF7Fvi6Ly2OkJglSetHmFe+y3rUJqyMJAwAAAIASkYQBOdjy4La+SVieCRmzJALLTbdnFQv7FePU9HFvdOgNM7OlNCzsZW63XcQ+DB98T3UVbd5xS98kLM+EjFkSgRWEGuRzYXbENXPJz3YqP9WuPXFJjXZtimlZrEnWvaA8JgdJGAAAAACUiCQMyCDdGzbKbSN6x9AkhfSGxdkQ48KpK/VfxNnJ+s1EVtH1wvpJ94aNctuI3jFgRDGNj+n7QqhBBw52X8+9nWy161S6n2xhodixYuxIwgAAAACgRCRhQE6y9mv1ul2/dIzeMGDJYjqtaoVUKyZj4fJesyNGkzQTWdZ+rV6365eO0RsGaKlfK1VzNB/SrNgLttid1ktLMyp6ajZXTD6SMAAAAAAoEUkYkINzN5zRTqfyTKlWm1mRRAx1t5gKpzL1iMU9yK10MtajNyzOjhj7x9K3qalLN57dTqfyTKlWm1mRRAxYSro89oDFRCz2mMaU3lt961Q7se/Xr4qJQRIGAAAAACUiCUNmp7z7VknS9g+f1XW66YpMqUi+MKlWmjWx32VxP3HcC22hP8PiWj1hz7K1Wku/xz4MhdOxJ6w1GeuFdSoypSL5ApZ47P0KMxtOLYTqNDeb/OxM5a07CWuXtXgf7WXCJqdfFd1IwgAAAACgRCRhyCwmPs++7qzxDmTM+q0ZRt8WMLp0z1gvcd/yp+77uiTp4tNfm5wxG9bdCZf7woIs1R/WXpMn7GW2qVbX6bqtFyb1XzOMvi2gIO0+rnDyYNIT5qG+aCZJ5a29huFijxgkuY5mk9TM5ueT61o7EgvXS83AiNoiCQMAAACAEpGEATnrl4gBGNwgCVj/G4cYayr8FzfV0UQW1+JJz0SWZvXvDeuXiAEoiHevA2YHQpq1di45PyRimp7usR5Yul8Vk46NMOSOCTp647BEoFjtrzSzceMrfOHpNf182BiLhyfGJni1Jn9aaA5LBHJmvdfWiBtfviZshPmBjtuEWjOVOuQ5TMShMLFQPJ8JOiYPhyMCAAAAQIlIwpA7pqxPMFEHMCbxUKC5OEV9OERoenppiuip7n2QyxKxCdrbzEQdQMHSizIHFpbNaK2dCaeTwmKzs1KYxj4mXukF4+MkHu0p63MfNMaNJAwAAAAASkQShtz0S8C2f/isxqZhKyERA0az0oLOkqSZ8F9b7KkIKZeZLe1NTjfFh+tae1KP5vRfkIgBOQvpe7snbCYshTEXErGOxCwu7BzZXLhNPCNMd790AzKxSUESBgAAAAAlIglD4U55962N7g9bbcp6EjEgH9Pxl1aIr8JCqebJf3Vd+4/TizDHHrHYf9FrRsWaW23KehIxIKN2b1ioJwtJPWmFJMzmYko/Jc2Hq8Yp6WMsEhP8VH/ZJNakpsuUhJnZkWZ2vZn9wMzuMrOXmNl6M7vRzO4NP4/Ka7AA0Au1CEBVUI8ADCLr4YgflfQ1d/85SadLukvSZZJudvdTJd0cTqPhTnn3rY1MwYax5cFtLPA8OmpRAy1696LO82rvXJYk+dysfG42WSB1ZrrrtjY9nfybm5XNzS6/c2+Ff964HozNO25hgedsqEcN54uL8sXFJM0y0/wRs5o/YlaLa6a1uGY6qSnhMs3OSrOzsnWHyNYdsnR+qD2tg/NqHZxPEv5WA5pUG2TkjTAze5qkX5J0pSS5+0F33yPpdZKuCle7StIF2YYIAP1RiwBUBfUIwKCy9ISdLGmXpE+Z2emSbpf0LknHuPtD4ToPSzom2xBRN6wT1ttqvWEYGbWo4dKzJfq+/ZIkm4nrhIUrzM3K4kRjs+G/v6kwK6KSC1r7wkxlE5x+rdYbhkyoR2jPjqg9j0uSWnPrJUkLhyZ1Z/bQQ9rrgPkha5Lrhppke5P65fsPdN8XJk6WwxFnJL1I0sfc/YWSnlIqXvfkf76e/5OZ2SVmttXMtu56jHgVwMhyq0W7d/OfHYBMRq5HnbVoXgdKGSyA8cmyEbZT0k53vy2cvl5J4XnEzI6VpPDz0V43dvcr3H2Tu296xtOne10FmEjnbjhjxZkQScqGllstWr+eVTsmQWvfPrX27ZMe/on08E9kC4uyhUVpYUGtAwfUOnBA/tRe+VN72z1hi48/qcXHn5QvLCxbt2dSXbrx7BVnQiQpG8nI9aizFs1qTWkDRgFiP9fuPWrt3qPD7tylw+7cpZn9i5rZvyjbd0D+xBPyJ56Qdu+Rdu9Ra91c8u+hR5J/e/eqtXdvI/tSm2Lkbxzu/rCk+83sueGscyR9X9INki4K510k6YuZRggAK6AWAagK6hGAQWVdJ+y3JV1tZnOSfijprUo27D5rZhdL2iHpDRkfAzXV2RtGX9hwWDtsaNQiLM2UGPYat558SpI0vTZJFeyQQ2TzScplc3PJVQ+G+RSZdawn1g4bCfUIkiRfSOqLP/ITSdL0UYdJkhaffrimQ8+XH3qIJGlqb9KXungg9oKRfk26TBth7r5N0qYeF52T5X4BYBjUIgBVQT0CMIisSRjQRnoznEFmS+Q1BYaXTm8WHtmVXPDiX9DMA+G/vbCXeWHnA6WPr2oGmS2RRAwYQTuVf1KSZHfcI0l65OJf1DO+G2pRmCXRvvXd8seHsWIjDIU75d23Ml19RmyMARmEQw2n7tiue957uiTpWZd9a5wjqi02xoARhI0xP5gccnjs5+7VV797oyT+X28ypgIDAAAAgBKRhKEUJGD9sYgzUI7W3r0kYCtgEWegHIu7di0lYBZXmWcijqYhCQMAAACAEpGElazfsb+kIBgEvWHIS7+eHlIQDILeMGAEvdIuErDGIgkDAAAAgBKRhBVsteQrXt55PVKxZhqmN6zIRIy0bTKtlnzFyzuvRyrWTMP0hhWZiJG2oZHoEWsMkjAAAAAAKBFJWEEGTRF6pQ70jTXbuRvOGPi9JhHDagZNEXqlDvSNNdulG88e+L0mEQNyQgLWGCRhAAAAAFAikrCcjZoabHlw26q3JSFDP3mmViRfk2HU1GDzjltWvS0JGfrJM7Ui+QIwyUjCAAAAAKBEJGEZVSE16DUG0rF6G2amRECqRmrQawykY/U2zEyJAIDBkYQBAAAAQIlIwjIYJQVbKdkosq+HRKUZmNGwmUZJwVZKNors6yFRaQZmNASAlZGEAQAAAECJSMJGUHTKUESaUebMiqQx+Rm1N4z3oBmKThmKSDPKnFmRNCY/o/aG8R4AQG8kYQAAAABQIpKwAUxymsDaY5NtkPXnUB+TnCaw9thkG2T9OQBoEjbCVjDuL6/jPKSsztPe9xvnuN/PLLJMWc+hifU37i+v4zykrM7T3vcb57jfzyyyTFnPoYkAsITDEQEAAACgRCRhPVQtMahKklH1ae+rNp4isIhzs1QtMahKklH1ae+rNp4isIgzAGRDEgYAAAAAJSIJ0/gTprqq26QeVUkUx6Xpz78Oxp0w1VXdJvWoSqI4Lk1//gAgkYQBAAAAQKkanYSVmQjkkQ7VJcmo+vgmAbMlTpYyE4E80qG6JBlVH98kYLZEABgNSRgAAAAAlKiRSVjdEwCSjN5WS4d4vbrxORq/uicAJBm9rZYO8Xp143MEoIkyJWFm9m4z+56Z3Wlm15jZWjM72cxuM7PtZnadmc3lNVgA6IVaBKAqqEcABjFyEmZmx0l6p6Tnufs+M/uspAslnS/pw+5+rZltlnSxpI/lMtoM2NvfHE16r/NYN6zuiVjdahF7+5ujSe91HuuGTUIiVrd6BGB8svaEzUg6xMxmJK2T9JCkV0i6Plx+laQLMj4GAKyGWgSgKqhHAFY1chLm7g+Y2Z9K+rGkfZL+TtLtkva4+0K42k5Jx2UeZQZ13bs/iLonGKiWun6e6lKL6rx3fzWTkGCgOur8eapLPQIwfiMnYWZ2lKTXSTpZ0gZJh0p69RC3v8TMtprZ1l2PLY46DAANl2ct2r27VdAoATRBlnrUWYvmdaDAUQKogiyzI75S0r+4+y5JMrPPS3qppCPNbCbs8Tle0gO9buzuV0i6QpI2nb7WM4xjRXXdu7+SSXouyEcevWE1llstesFps4XVojrv3e9nkp4L8pFHb1jNjVyPOmvREba+sFoEoBqy9IT9WNJZZrbOzEzSOZK+L+kbkl4frnORpC9mGyIArIhaBKAqqEcABpKlJ+w2M7te0rclLUj6jpI9OF+RdK2ZfSCcd2UeA81qEhKxOo8d5WjibIl1q0WTkIjVeewoR1NnS6xbPQIwPpkWa3b390l6X+rsH0p6cZb7BYBhUIsAVAX1CMAgMm2EVdFqScCWB7eVuoc/SyJRlyQCk6luiVjVrJYEbN5xS6l7+LMkEnVKIjB56piIAcBqar8R1u8LYr+NsTp9oeRLMEaV50QdfA4H0+8LYr+NsTp9oeRLMEaV50QdfA4BTJKsizUDAAAAAIZQ2yRs0L3yk7D3niQCVbDSobzxMzp9bHnjqYpB98pPwt57kghUwUqH8sbP6CknljkiABgeSRgAAAAAlKh2G2HnbjijsYnQlge3NXUxXoyoqX8rZbh049mNTYQ277ilyYvxYgRN/VsBgH5qtxEGAAAAAHVWi56wOu7NJ7HCJEr3Jzbtc17HvfkkVphE6f5EPucA6oYkDAAAAABKZO4+7jFo0+lr/R+3nLDideqShpWZDNTlNUE1lPHZnD52++3uvqnwByrIC06b9S985egVr1OXNKzMZKAurwmqoYzP5iknPlzrWnSErfcz7ZxxDwNARjf59X1rEUkYAAAAAJSIjbAaY7ZEDKPJM4uiWMyWiGE0eWZRAIjYCAMAAACAEtVidkRp+axsq12vSQZ9bQBkl56VbbXrNcmgrw0AAE1HEgYAAAAAJapNEhaR+izHa4FhNHWNr7yR+izHa4FhsMYXgCYjCQMAAACAEtUuCcMSEjAAVUACBgDAcEjCAAAAAKBEldgIu+eOdQOnOqutdcRaSMBg+FtZbsc/Hz5wqrPaWkeshQQMhr8VAE1UqcMRmzBhQB7PkS/OQLGaMGFAHs+RL84AAIymEkkYAAAAADSFufu4x6AjbL2faecsO3+SE7FhkHyhDHn8vU0fu/12d9+UfTTj0a8WTXIiNgySL5Qhj7+3U058eCJrEYB6ucmv71uLSMIAAAAAoESV6glLa0KPWC8kXyhT0/6+RtGEHrFeSL5Qpqb9fQFoNpIwAAAAAChRpZOwpu6hj8+bRAxFaurf1yiauoc+Pm8SMRSpqX9fAJqNJAwAAAAASlTpJKzp0kkFyRjyQAKGYaWTCpIx5IEEDECTrZqEmdknzexRM7uz47z1Znajmd0bfh4Vzjcz+69mtt3M7jCzFxU5eADNQj0CUAXUIgBZDZKEfVrSn0v6y47zLpN0s7t/0MwuC6ffI+k8SaeGf2dK+lj4ORT21PdGMlYvRfb2Nfhv5NMqsR6xp743krF6KbK3r8F/I59Wyd+NAEyWVZMwd/8fknanzn6dpKvC71dJuqDj/L/0xK2SjjSzY3MaK4CGox4BqAJqEYCsRu0JO8bdHwq/PyzpmPD7cZLu77jeznDeQ0LumEWxmtIpFQlm4ahHY8YsitWUTqlIMAtHLQIwsMyzI7q7S/Jhb2dml5jZVjPbOq8DWYcBACPVI2oRgLxRiwCsZtQk7BEzO9bdHwqR+qPh/AckndBxvePDecu4+xWSrpCkI2z90BtxWELSUi8kmLnLVI+oRfkhaakXEszcUYsADGzUJOwGSReF3y+S9MWO898cZgI6S9LPOqJ5ACgC9QhAFVCLAAxs1STMzK6R9HJJR5vZTknvk/RBSZ81s4sl7ZD0hnD1r0o6X9J2SXslvbWAMWMVnckYaUt5hp2xkARzeNSjeulMxkhbyjPsjIUkmMOjFgHIatWNMHd/Y5+LzulxXZf0W1kHBQC9UI8AVAG1CEBWo/aEFaLBax8VhrSlPobpFYvX4W+mGA1e+6gwpC31MUyvWLwOfzMAMJxKbYSheGyUFSPPjSEOJ0UTsFFWjDw3hjicFACKk3mKegAAAADA4EjCGo5krNqYzh5NQTJWbUxnDwD5IgkDAAAAgBKRhEESScuoypoYg8QSTUHSMpqyJsYgsQSAfJCEAQAAAECJSMIajkSlnpiaHpOGRKWemJoeAEZDEgYAAAAAJapkElZEOtNr7aUmpgkkX/lo4meniYpIZ3qtvdTENIHkKx9N/OwAwCQgCQMAAACAElUqCSsypel1301KxEjA8lH2Z6VJn9EqKTKl6XXfTUrESMDyUfZnpUmfUQAoA0kYAAAAAJSoUkkY8kcCVk+8b5g0JGD1xPsGAMUgCQMAAACAEpGETSiSlHyV2ZPV+d7RC4a6I0nJV5k9WZ3vHb1gAJAvkjAAAAAAKBFJmAafga7qM9WRftVTr/etqp8xFGvQGeiqPlMd6Vc99XrfqvoZA4C6IwkDAAAAgBKRhI2gaokYCVhxinyP+71vVflcofqqloiRgBWnyPe43/tWlc8VAEwiNsJqjI2vemNjC5OCja96Y2MLAMrH4YgAAAAAUCKSsAzO3XDGWNKMcSdg8TmPexxFIqVCnVy68eyxpBnjTsDicx73OIpESgUAk4kkDAAAAABKRBLWYZQJN9Jp0DgmcigaqRBQrlEm3EinQeOYyKFopEIAgElBEgYAAAAAJSIJy1me09ePI/kaZtyT2BuW5/tGgohxynP6+nEkX8OMexJ7w/J830gQAaB6SMIAAAAAoEQkYQMYJenJshBvmckSaU23UVOsXu9ZlkSMNA29jJL0ZFmIt8xkibSm26gpVq/3LEsiRpoGAMVYNQkzs0+a2aNmdmfHeR8ysx+Y2R1m9jdmdmTHZZeb2XYzu9vMzi1o3AAahloEoCqoRwCyMndf+QpmvyTpSUl/6e7PD+e9StLX3X3BzP5Ektz9PWb2PEnXSHqxpA2SbpL0HHdfXOkxjrD1fqadk/nJ5K3MnqctD24r7XGKMkm9YdFqr9cgzzlLEpblPsZh+tjtt7v7piLuu8m1qMyep807bintcYoySb1h0Wqv1yDPOUsSluU+xuGUEx8urBZJxdejqtYiAMO5ya/vW4tWTcLc/X9I2p067+/cfSGcvFXS8eH310m61t0PuPu/SNqupOgAQCbUIgBVQT0CkFUePWFvk3Rd+P04JYUn2hnOW9FzTturLVvKSYKqKu/nXpfkpOrSvVlZ+gOzvCf0iA0kcy3a+IIntPkr5SRBVZX3c69LclJ16d6sLP2BWd4TesQGlrkeAZhsmWZHNLM/krQg6eoRbnuJmW01s627HlvxCCEAWFFetWj37lb+gwPQKKPWo85aNK8DxQwOQGWMnISZ2VskvUbSOb7UWPaApBM6rnZ8OG8Zd79C0hWStOn0tS5Vb92pqoxjUGWnJHV7fbKoynMlEVsuz1r0gtNmXareulNVGcegyk5J6vb6ZFGV50oi1luWetRZi46w9Ss37AOovZGSMDN7taQ/kPSr7r6346IbJF1oZmvM7GRJp0r6x+zDBIDlqEUAqoJ6BGAYqyZhZnaNpJdLOtrMdkp6n6TLJa2RdKOZSdKt7n6pu3/PzD4r6ftKovjfWm02sl7Se/mrkkJUxbhTEN6PYg3y+jYxERtHLUrv5a9KClEV405BeD+KNcjr29REbBz1CMBkWXUjzN3f2OPsK1e4/h9L+uMsgwKANGoRgKqgHgHIKo/ZETO75451pCsrGHfawXuTjyLSqyYmYkXa8c+Hk66sYNxpB+9NPopIr5qaiAHAqCqxEYaVjeOLNhtexcvzNa7r4s6ol3F80WbDq3h5vsZ1XdwZAMqWaYp6AAAAAMBwSMIgieSrTGW81hymiLoi+SpPGa81hykCQG8kYQAAAABQIjbCauTcDWfknqIUcZ+oDt5bFOHSjWfnnqIUcZ+oDt5bAOjGRhgAAAAAlIiesIYhGWke+sNQRSQjzVNGf9i0FXbXAJArkjAAAAAAKJG5+7jHIDPbJekpST8Z91h6OFqMaxiMaziTNq6N7v6MvAdTFmrRSBjXcBjXcKhF1TNpn5WiMa7hTNq4+taiSmyESZKZbXX3TeMeRxrjGg7jGg7jqp6qPnfGNRzGNRzGVT1Vfe6MaziMazhNGheHIwIAAABAidgIAwAAAIASVWkj7IpxD6APxjUcxjUcxlU9VX3ujGs4jGs4jKt6qvrcGddwGNdwGjOuyvSEAQAAAEATVCkJAwAAAICJV4mNMDN7tZndbWbbzeyyMY3hBDP7hpl938y+Z2bvCuevN7Mbzeze8POoMY1v2sy+Y2ZfDqdPNrPbwmt2nZnNjWFMR5rZ9Wb2AzO7y8xeUoXXy8zeHd7DO83sGjNbO47Xy8w+aWaPmtmdHef1fH0s8V/D+O4wsxeVPK4PhffxDjP7GzM7suOyy8O47jazc4saVxVUoRaFcVS2HlGLhhpXJWpRGEvl6hG1qD9q0UBjq1wtCuOoXD2iFo00psJr0dg3wsxsWtJ/k3SepOdJeqOZPW8MQ1mQ9Lvu/jxJZ0n6rTCOyyTd7O6nSro5nB6Hd0m6q+P0n0j6sLufIumnki4ew5g+Kulr7v5zkk4P4xvr62Vmx0l6p6RN7v58SdOSLtR4Xq9PS3p16rx+r895kk4N/y6R9LGSx3WjpOe7+2mS7pF0uSSFv4ELJf1CuM3/F/5mJ06FapFU7XpELRpAxWqRVM161GtM1CJq0aCqWIukitUjatHIYyq+Frn7WP9JeomkLR2nL5d0eQXG9UVJvyzpbknHhvOOlXT3GMZyvJIP5SskfVmSKVkwbqbXa1jSmJ4m6V8U+go7zh/r6yXpOEn3S1ovaSa8XueO6/WSdJKkO1d7fST9haQ39rpeGeNKXfZ/SLo6/N719yhpi6SXlPmelvjZqWQtCmOpRD2iFg01rkrVovB4latH1KKez5tatPo4KleLwuNWrh5Ri0YbU+qyQmrR2JMwLX04op3hvLExs5MkvVDSbZKOcfeHwkUPSzpmDEP6iKQ/kNQKp58uaY+7L4TT43jNTpa0S9KnwuEAnzCzQzXm18vdH5D0p5J+LOkhST+TdLvG/3pF/V6fKv0dvE3S34bfqzSuolXyuVasHn1E1KKB1KAWSdWvR9SiRCWeK7VoIJWrR9SiXBRSi6qwEVYpZnaYpL+W9Dvu/njnZZ5s8pY6naSZvUbSo+5+e5mPO4AZSS+S9DF3f6Gkp5SK18f0eh0l6XVKCuEGSYdqecRcCeN4fVZjZn+k5PCTq8c9FlSrHlGLhlOnWiRVrx5Ri6qFWjSwytUjalE2RdaiKmyEPSDphI7Tx4fzSmdms0qKzNXu/vlw9iNmdmy4/FhJj5Y8rJdK+lUz+5Gka5VE7x+VdKSZzYTrjOM12ylpp7vfFk5fr6TwjPv1eqWkf3H3Xe4+L+nzSl7Dcb9eUb/XZ+x/B2b2FkmvkfSmUAQrMa4SVeq5VrAeUYuGU/VaJFW0HlGLqvVcqUVDqWI9ohaNqOhaVIWNsH+SdGqYpWVOSbPbDWUPwsxM0pWS7nL3P+u46AZJF4XfL1JyPHRp3P1ydz/e3U9S8tp83d3fJOkbkl4/xnE9LOl+M3tuOOscSd/XmF8vJXH7WWa2LryncVxjfb069Ht9bpD05jAT0FmSftYRzRfOzF6t5NCOX3X3vanxXmhma8zsZCXNsf9Y1rhKVolaJFWzHlGLhlb1WiRVsB5RiyRRi1ZU1VoUxlbFekQtGkEptSiPZras/ySdr2Tmkfsk/dGYxnC2kvjzDknbwr/zlRxnfLOkeyXdJGn9GF+nl0v6cvj9WeFN3y7pc5LWjGE8Z0jaGl6zL0g6qgqvl6T/KOkHku6U9FeS1ozj9ZJ0jZLjr+eV7B27uN/ro6Sp+L+Fv4F/VjKLUZnj2q7kGOf42d/ccf0/CuO6W9J5Zb+fJX92xl6LwjgqXY+oRQOPqxK1KIylcvWIWrTia0MtGmx8lapFYRyVq0fUopHGVHgtsnBnAAAAAIASVOFwRAAAAABoDDbCAAAAAKBEbIQBAAAAQInYCAMAAACAErERBgAAAAAlYiMMAAAAAErERhgAAAAAlIiNMAAAAAAo0f8POhOS6B+cjBUAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAA2EAAAEiCAYAAABwX9rUAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAAA0P0lEQVR4nO3de7QlZXnn8d9zTt+4iNBqGLobhQiaEEeBMIpLM+MSk8aOEcY4ipMLGhLiGhMv4xXNiiYrF52YiBkzGuKNRCIoGiGmtQNeclUUsIMoIg1e6OZ+VaFp+pzzzB/1vvvUqbPvtXfVW7u+n7VY5+y9a1e9VXv3w3nrV+9b5u4CAAAAAFRjru4GAAAAAECb0AkDAAAAgArRCQMAAACACtEJAwAAAIAK0QkDAAAAgArRCQMAAACACtEJAwAAQFdm9mEz+4Pw+8+Y2fUVbdfN7Jger33RzH697nbUycyeYWY3mNmPzOz0utuD0dEJAwAAaDAz+66Z7Q1/kN8eOk4HT3o77v4v7v7EIdrzUjP710lvHyv8vqT3uPvB7v6pMisys8+E786PzGy/mT2ce/y+Mdb3NjP7yIBlvmtmd5jZQbnnft3MvjjGLuTX+xgz+1szu9/M7jWzC0qu7zlmdrWZPWBmu83sRWXWl0cnDAAAoPl+wd0PlnSipJMk/U5xATNbU3mrMC2Pk/SNcd5Y/B64+3NDZ+5gSRdI+j/xsbu/fAJt7WVe0quGWXCE7+4nJd0m6bGSfkzSO8drmmRmx0n6W0lvkfRISU+RdNW46yuiEwYAADAj3H2PpM9IepLUuZzuFWZ2g6QbwnPPM7OdZnafmf27mT05vt/MTghn/n9oZhdJ2pB77Vlmtjv3+Egz+6SZ3Wlmd5vZe8zsJyW9T9LTQ5JyX1h2vZm908y+H9K695nZAbl1vd7MbjWzW8zs14bY1ceZ2b+Fdv6jmT06t66Tw37dZ2b/YWbPyr32MjO7LrzvJjP7zfxKR2lHuCzyD8K2fmRmf29mjzKzC8zsB2b2VTM7Krf8u83s5vDaVWb2M7nX3mZmF5vZRaFtV5vZU3ps90ZJPy7p78N215vZJjO71MzuMbNdZvYbXdb9ETP7gaSXDnF843v7fVfeaGZ7QnuvN7NTzOxUSW+W9OLQtv/os/o/kfQ6Mzu0x7ZXfXcHtPXnJB0p6fXufr+773f3rw27r138jqS/dPfPuPuCu9/t7jeWWN8KdMIAAABmhJkdKWmbpPwfn6dLepqk48zsBEkflPSbkh4l6S8lXRr+kF8n6VOS/kbSRkkfl/SLPbYzL+nTkr4n6ShJmyVd6O7XSXq5pC+FJOXQ8Ja3S3qCpOMlHROW/92wrlMlvU7Sz0o6VtJzhtjV/ynpZcrSjnXh/TKzzZL+QdIfhH14naRPmNljwvvukPQ8SYeE97/LzE4s0Y4zJP1K2J/HS/qSpA+FbV8n6a25Zb8a9n+jsoTl42a2Iff6acqOeXz9U2a2trhBd3+8pO8rpJ/uvk/ShZJ2S9ok6YWS/sjMnl1Y98WSDlWWdg004LvyREm/Jem/uPsjJG2V9F13/6ykP5J0UWhb145kcKWkLyp8dj2crvDdDW26z8ye2WPZkyVdL+n8cFLgq2b234bZ1z7rk5l9PXTMP2JmG0usbwU6YQAAAM33qZA6/aukf1L2h3D0x+5+j7vvlXS2srP7V7j7orufL2mfsj84T5a0VtK5IUW4WFnHoZunKvuD//Xu/oC7P+TuXceBmZmF7b4mtOOHoX1nhEVeJOlD7n6tuz8g6W1D7O+H3P3bYZ8+pqxzI0m/LGm7u2939yV3v0zZH/vbJMnd/8Hdb/TMP0n6R0kxkRq3HTe6+/3KEsgb3f1yd19Q1qE6IS7o7h8JacqCu/+ppPWS8mPsrnL3i919v6Q/U5ZCnjyoAaHj/QxJbwyfw05J75f0q7nFvuTunwrHZO8Q+yX1/64shvYfZ2Zr3f27Y6ZEvyvpt3Od5KL8d1fufmiv75mkLZJ+TtIXJP0nSX8q6ZJ8SjqiLco62L+orFN+gKT/O+a6VqETBgAA0Hynhz9QH+fu/6vwh/bNud8fJ+m1IVG4L3TcjlTWodokaY+7e2757/XY3pGSvhc6G4M8RtKBkq7KbfOz4XmF7ebb2Gubebflfn9QUpyI5HGS/kdh/54p6QhJMrPnmtmXw2V79ynrnMU/0sdpx+253/d2edyZIMXMXhcuhbw/bPuRuW0rv213X9JysjXIJkmxc5tv++Zu6x5Bz++Ku++S9GplHdU7zOxCMxumrSu4+7XKEtU39VhklHbvVZbGfSCcRLgwvP8Zg95o2eWxcTKSN+fWFzv7P1J24mDbCO3pi04YAADAbMt3qm6W9Iehwxb/O9DdPyrpVkmbQ3IVPbbHOm+W9FjrPmGCFx7fpewP2p/KbfORYSIIhe0eOcQ2h3GzpL8p7N9B7v52M1sv6RPKJms4PFwquV1S3N9JtmOFMP7rDcrStsPCtu/PbVv5bZvZnLIk5pYhVn+LpI1m9ojcc4+VtCf3uPiZDKPfd0Xu/rfu/kxlnTWX9I4xt/VWSb+hlZ3Gcdp9TZflh3q/u788NxlJTJGL6xvnGPZEJwwAAKA9/krSy83saZY5yMx+PvwB/yVJC5JeaWZrzewFyi477OYryjotbw/r2GBmMXG4XdKWMMYspjp/pWz81Y9J2dgtM9salv+YpJea2XFmdqBWjqMa1Uck/YKZbTWz+dCuZ5nZFmVjx9ZLulPSgpk9V9nla9Ek21H0CGXH9k5Ja8zsd5WNS8v7aTN7QejYvlrZpX9fHrRid79Z0r9L+uOwv0+WdJayY1FGz++KmT3RzJ4dOrYPKetkL4X33S7pqNCRHCikahdJemXJ9v6dpMPM7Mzw2b9QWUf236TOBCVfHGF9H5L0MjP78fB9eJOy1G4i6IQBAAC0hLtfqSx1eI+keyXtUpgtz90flvSC8PgeSS9WNuV3t/UsSvoFZZNsfF/ZpXMvDi9/Xtn06beZ2V3huTeGbX3Zshn6LlcYD+Xun5F0bnjfrvBz3P27WdkkFG9W1uG5WdLrJc2Fy/Veqayzda+yyT0uzb13Yu3oYoeySzC/rexSwYe0+lK7S5Qdw3uVjUV6QRgfNoyXKJsg5RZlnZG3uvvlZRrc77uirDP7dmUp523KJkg5J7z28fDzbjO7esjN/b6kgwYtFC4X/Jlur7n7PZKer2yij/uVdZpOc/f4HTxSoUM2DHf/oKS/lnSFss9sn8p3FDts5WW/AAAAAKpkZm+TdIy7/3LdbZlVZrZT0inufnfdbZEkbtoHAAAAYKa5+/F1tyGPyxEBAAAAoEJT64SZ2amW3T17l5n1mnYSAKaKWgQgBdQi9OPub+NSxHaZypgwy+6i/m1ldxzfrexGfy9x929OfGMA0AO1CEAKqEUAiqaVhD1V0i53vynMtHOhsplqAKBK1CIAKaAWAVhhWhNzbNbKaTd3S3par4XX2XrfMHhWyol4wpMfrGQ7ZXz7mgPrbkLlip9LG4/BJMXjWfVx/KHuvcvdH1PpRvtLthYd++QHKtlOGTdcU82xSEnxc2njMZikeDyrPo7UIgAp6FeLapsd0czOlnS2JG3QgXqanVLJdnfs2FnJdsrYuun4uptQueLn0sZjMEnxeFZ9HC/3i79X6QYnoK5atP2zw946pT7bNp9YdxMqV/xc2ngMJikez6qPI7UIQAr61aJpdcL2KLshWrQlPNfh7udJOk+SDrGN3KxM7ex47LhlZ91NmGn549vG75eoRWNpY8dj+570O8VNlj++bfx+iVoEoGBaY8K+KulYMzvazNZJOkO5O5IDQEWoRQBSQC0CsMJUkjB3XzCz35K0Q9K8pA+6+zemsS0Ay7oliy1NwCRRi4C6dEsWW5qASaIWAVhtamPC3H27pO3TWj8ADINaBCAF1CIAebVNzIGV2ppWtHW/J62YgHFcMa62phVt3e9JKyZgHFcA6G5aY8IAAAAAAF20Lgnbuun4pGbkI7HAJPA9ap5tm09MakY+EgtMAt8jABhO6zphqeCPZgAp4I9mAACqx+WIAAAAAFAhOmEAAAAAUCE6YQAAAABQITphGNqOW3ZWNqlJldsC0Czb91xd2aQmVW4LANAedMIAAAAAoELMjliTmPKkMkviKKnToGXH2SdSL6AeMeVJZZbEUVKnQcuOs0+kXgCAKpCEAQAAAECFSMJabhoJ1DgpX1w2tYSwDjtu2dnq/Uc7TSOBGifli8umlhDWYfueq1u9/wAwTSRhAAAAAFAhkrCWqmIMVplErO3Kfj4cRzRFFWOwyiRibVf28+E4AkB3JGEAAAAAUCGSsCnplUTUPeapjlkIGeME1KdXElH3mKc6ZiFkjBMAIBUkYQAAAABQIZKwCRuU+FSdCHH/LaCdBiU+VSdC3H8LAIBlJGEAAAAAUCGSsBmVWgJW91i4JuEYYZakloDVPRauSThGADA9JGEAAAAAUKFWJmHFpGESqVFK6UVqKVgeiRiwrJg0TCI1Sim9SC0FyyMRAwDUqZWdsGjWOl9NQmcMWDZrna8moTMGAKgDlyMCAAAAQIXohJVAilPejlt2Jn35JNAEpDjlbd9zddKXTwIAZgudMAAAAACoUKvHhM0aEiUAKSBRAgCgP5IwAAAAAKgQSdgYGAs2ORxLYHyMBZscjiUAoEpjJ2FmdqSZfcHMvmlm3zCzV4XnN5rZZWZ2Q/h52OSaCwArUYsApIJ6BGBYZS5HXJD0Wnc/TtLJkl5hZsdJepOkz7n7sZI+Fx4naeum40dKYkZdvmqptw+YksbXom2bTxwpiRl1+aql3j5gihpfjwBUY+xOmLvf6u5Xh99/KOk6SZslnSbp/LDY+ZJOL9lGAOiJWgQgFdQjAMOayJgwMztK0gmSrpB0uLvfGl66TdLhk9hGnZqWLuXby4yJq8Vj0rTPFYPNei1qWrqUby8zJq4Wj0nTPlcMZ9brEYBySs+OaGYHS/qEpFe7+w/yr7m7S/Ie7zvbzK40syv3a1/ZZgBoOWoRgFSMU4+oRUC7lOqEmdlaZUXmAnf/ZHj6djM7Irx+hKQ7ur3X3c9z95Pc/aS1Wl+mGaXN8liqVPcthXaREs6OWalFszyWKtV9S6FdpISzZdx6lFItAjB9ZWZHNEkfkHSdu/9Z7qVLJZ0Zfj9T0iXjNw8A+qMWAUgF9QjAsMqMCXuGpF+R9HUz2xmee7Okt0v6mJmdJel7kl5UqoU1qjupmaTivrQxBeq2z4wPmwkzX4vqTmomqbgvbUyBuu0z48NmxszXIwCTMXYnzN3/VZL1ePmUcdcLAKOgFgFIBfUIwLAmMjvirIhpSBtSojbt6yRM4jiRtmFYMQ1pQ0rUpn2dhEkcJ9I2AKhf6dkRAQAAAADDIwnrok2JRdWJWJ3Htriv/dpCQogUtCmxqDoRq/PYFve1X1tICAFgNtEJg6R2TdzR5I7noDa36QQCZlObJu5ocsdzUJvbdAIBAMbB5YgAAAAAUCGSMHQ1SxN3zMI+AG01SxN3zMI+AAAmgyQMAAAAACpEEoa+tm46Pvnp2VNNuqocn8VYMMy6bZtPTH569lSTrirHZzEWDACGQxIGAAAAABVqTBI2zLTimI42zZyYulkaq9dUw0wrjulo08yJqZulsXoAUAeSMAAAAACoUGOSsIhErH6kMfXj+18/ErH6kcbUj+8/AIyHJAwAAAAAKtSYJIwz/+kZdqxY2z67tu1v23DmPz3DjhVr22fXtv0FgCYhCQMAAACACjUmCUP6qh4rxpg0AN1UPVaMMWkAgFGRhAEAAABAhUjCMHFtHRPV1v0GUtXWMVFt3W8AaBKSMAAAAACoEJ0wAAAAAKgQnTAAAAAAqBBjwtA4qc6KGNvF2DCgHVKdFTG2i7FhAJAukjAAfe24ZWeyHV8A7bF9z9XJdnwBYFR0wgAAAACgQlyOCEzYrFyWWEy/hknD5o+YTlsAjG5WLksspl/DpGHrNk2rNQAwGSRhAAAAAFAhOmFAyzHmC0AKGPMFoE3ohAEAAABAhRgTBkxJ6mPDxhnzBaB5Uh8bNs6YLwBoutJJmJnNm9nXzOzT4fHRZnaFme0ys4vMbF35ZgJAf9QiACmgFgEYxiQuR3yVpOtyj98h6V3ufoykeyWdNYFtAJJIayZhhseAUYtQGdKa8mZ4DBi1CMBApTphZrZF0s9Len94bJKeLenisMj5kk4vsw0AGIRaBCAF1CIAwyo7JuxcSW+Q9Ijw+FGS7nP3hfB4t6TNJbcBNFoqY8NmNP2KzhW1COgrlbFhM5p+ReeKWgRgCGMnYWb2PEl3uPtVY77/bDO70syu3K994zYDQMtRiwCkgFoEYBRlkrBnSHq+mW2TtEHSIZLeLelQM1sTzvpskbSn25vd/TxJ50nSIbbRS7QDLZJPk5qS7JCATR21CJXLp0lNSXZIwKaOWgRgaGMnYe5+jrtvcfejJJ0h6fPu/kuSviDphWGxMyVdUrqVANADtQhACqhFAEYxjZs1v1HS/zazXcquhf7AFLYBYAgtSMH6oRYBiWhBCtYPtQjAKhO5WbO7f1HSF8PvN0l66iTWCwCjoBYBSAG1CMAgE+mEtdmud50sSTrmNV+uuSXt0ZR0p86xYE05RpgQM8nChQ2+FH4ypGTampLu1DkWrCnHCBMyNy+bn89+D7XIFxf7v4dahZaaxuWIAAAAAIAeSMJKiglYTMR6vQ5UgQSsZczCzznZ2lDOw1lnXwpnl2MyVsTZZ0wRCVjLzGXpl61do7n16yVJvhBujbY//CzUok6NUo8atWJh6hVmD52wCenV2Zpm56zXuie1/hSl2slgGnrUIlyCOLdhvWzdWkmSL4Y/aB5+eOWyhU7ZwEuEJP7w6SPVTgbT0KNS4URQPAk094iDZQcflD23L6tBvndvtmyoQbH2WKgvXqhVy52zvAEdtVir4ompbq/H16hrSASXIwIAAABAhUjCpmyUhGzc9Krb+5gwZDpi4lVMnnbcsrOWNIwEDJLk+xdWnQG2deuyX2LiZSEB83DmuriO/NnneNlQv7PKqFVMvIrJ0/Y9V9eShpGAtVSsBTHl2vuQbM2a8FL2nB1wQPZ4ISRgS6EmxcsUo6VQdxZzqVfnEsb58LBQewbVqij/enFZ6hlqQhIGAAAAABUiCatJv/RqmGXzz7ch9ao78RmUclWVgtV9HJCYeBZ4LlfK57JzaxbP9hbPSsezzeH5zlng/Bix4uQexe0NOuucP7M8Y+Mw6k58BqVcVaVgdR8HpCWO85qb39B5LiZinXFj8XGsQWtDzSnUIIsTeix5Z7xYp35ZYWzr0oAsIT8ZSPE2Hp3nR6hnwASRhAEAAABAhUjCEjLJGRbblJJNQ92zHRaRgKGvLrOJdWY/nBtwri3cWNVyiVVcWzzr3FlXrzPJRd3OLPdKxGYsKZu0umc7LCIBQz++uLg83nSpcOP4+G+9UJM6tWdtNsNrJ71fWFheV0znOylZSPznYiIWkrI5W/G4U7NWbLDwXCfhH5CUUaMwYSRhAAAAAFAhkrAGGDUhmyWpJ0DTTsxS33+kwRcXpX3h7G1ItorpmM2Hc27xLHQ8uxvHYRwQxnLkZixzxfv59Di7PCgR66bX+IvEZyxLPQGadmKW+v4jDf7wfi394IeStGqWxKgzNizUpM5yYfZEPfLg7PmHHl5O5eOtxOK9xUJtKiZinW3Mra4z3e8/ptXJWM+kjEQMk0USBgAAAAAVIglrsGHGeTV9bNg4SVOZ9GjY7ZGAIQmdM7JL8ji5YTEBi2MkFgpJWXw9nN31vQ9lj9esWR4nFsZ0dM5GDzPeYkX7xkjKlhsW1pHGWedxkqYy6dGw2yMBQxLibIWLy2NIbT6k6qFudGpNfH1dNgasM84r1pP7fpD9POAA2fr12TKxDoRlLdSoYiI2qH3ZZqzwknd9fvn1QvJvlkxdQrORhAEAAABAhUjCWqLpidgoJpmejZJITSodIwXDyPJnZWMk1jnrHJ6PZ5mXimeSw1ng+PaFhVWzmBXHdphy9xTTgLEWvdKwXilamfQsMZNMz0ZJpCaVjpGCYWixBvnicu1ZKMw6GJOm8LiTiMUxYrHehD9Nfe/e3Gshne8ydjV7ISRxxYQql9pbvAigUGOscHXA8j71qUWJJfVoJpIwAAAAAKgQSRig1SlWHWkUCRgmqnhvnl73wolnpePyi4vL9+2ZWzmjYmeMWGEdq8aK5fWaSbHYnl7L52dNbMFZ52KKVUcaRQKGUnrUHi/OZBjHWi2uTNY7j31puS6FJKzzcz4mb4UxsEuFRCymb7natLpOxTFs84X3FO9FlqtVzJiICSAJAwAAAIAKkYTNuNXpSvb48Xq5pNkeG9YUJGCYql5npTtjxcI4L19OnJaTrvBa5wxxHLMRX155lrnXmAtJ+uz3v9a1eVs3n7ByGx1hzFo8a+1Lyd9LrOlIwDBVXkyUFlc8r8U4g2t4fm5Omg9pe3xu7brsZxgr1qkI83GcWVg+JGKdGjEvKaZki4XtxubFzc6vDduK91wstC+37LJi0k9twmAkYQAAAABQIZKwGRfHOhXTlhtf/D5Jy4lY1PZkrMpUigQMlSqeme2ZjM0tj9mIJ4w7bynMmhjPLMfTecX7h+XONMfEa8eelYlYfLx1y09nb1278n9LyzMxzq9MxVbsw+ydda4ylSIBw1T0/HdZSKB6JWPz88s1ZjHWnLDOWCfm51a81UKy73OFjKE47qxr+1aOJ5sL9zHr1LV4P7OlXPuL6d4Mze6K6aMT1nLFTlcbprCvG50vJKFPp8wLNz6NHaF4mWLxlqadztl8nBa/26QbXf4I6qKzrrXhD6D4x9PS0vIfQcVLFVW49AhDofOFWvTo/HRejvVnaWH55vLF98RLpTtT2MeqFKayj4vFmjE/36lxNrcQVtHjJE7hZJIdlN0wWvv3Zz8Xl6R9+8KyhUsVfeUNqYvtBfK4HBEAAAAAKkQS1hK9LkuMj+Prbbqpc16V6VSvzwKoVX4Cj+KA9eJUzfEk71wxE+u23pWpWM/LEndfJUk69XFPzRYPQVjnTLhZbkKQlTeNXk7ump+IVZlOxenwScRQqz630+jc0Dmm33E6+fjWpThxR2F6+aKlpdwkHT3SsvB63GZ83uYOyH5uCDeKXlhY3k5MvB7ev+K9Kl46DXRBEgYAAAAAFSIJQ1fFRCz/3CypM40iEUOS3FdPBR9filPRF2+2Wjz7nL9BahxXEYd2DBga1jnzHc9w5wfgF8eH5MdorFh38xKxOtMoEjEkoVsiVpzkJ9QcL9xguZiYxRoUx5j63Fxn/FYcR9YZU1qc4CdOtvFQNu7LDwxJ2AEhCVu7ZnksWky+Yrq2P0vPlpZiqhZ3jinssRpJGAAAAABUiCSsZYYdGxbl069pjBPrtd02IRFDcvqM0cgexrO44exznGXMuiRj3m2mxOHHhnWmw1+zJk58JutMCx3OPhemox7n7HNMgWIq1EYkYkhCl/GpxWnsi2PEVr03JlP5VL9Y1+YKdas4S2McG/ajB8JiYbkN66U4fX2cOj+OJ4szMHbGisV1FfdxuNliMdtKJWFmdqiZXWxm3zKz68zs6Wa20cwuM7Mbws/DJtVYAOiGWgQgFdQjAMMwL3FdqpmdL+lf3P39ZrZO0oGS3izpHnd/u5m9SdJh7v7Gfus5xDb60+yUsduB8RXTl2ESqTKJ2KC0p8pEbJLJ0yTb3eREbP6IXVe5+0lVb5daNGU9xogV0y0rjg3Lv945o12YNSz8P2hVLQo3b57bkN2jJ0vCesyAFs9Y95ihbPnx8tnnQWlPlYnYJJOnSba7yYnYuk031VKLpMnUI2pRUKw9vWpOrA2dt628sby6JGKduhDrR3xc+LvY1q7LVvXIR2SPN2zoJGEebxYdZ2xdWJmexXsbehgrFmdc9IcfZlxYS1zuF/esRWMnYWb2SEn/VdIHJMndH3b3+ySdJun8sNj5kk4fdxsAMAi1CEAqqEcAhlVmTNjRku6U9CEze4qkqyS9StLh7n5rWOY2SYeXayKqNMwYrW4zJ+af77feSWy/rNSTpq2bjk++jYmhFk1bcSxFr8WWCmeQ5/rcI6fHOIxo1diw+fnOWLDO4LC5wtnvA8Ljh+OsiSvHXfjS4tDpThVjxFJPmrZtPjH5NiaIejRJQ45PNQvLhWSsc5XX4spZFLuKtSiuozBeyxdCwr4vG+Bl69cv15aYxIVZXOOYMB16SLbsA3vD62H5Bx/Mlnv44d7tQWuUGRO2RtKJkt7r7idIekDSm/ILePavoGveamZnm9mVZnblfu0r0QwALUctApCKsesRtQholzJJ2G5Ju939ivD4YmWF5nYzO8LdbzWzIyTd0e3N7n6epPOk7NrnEu1ACWVm5ismX5OcPZFZEzECalFVep2Vjmzweb3iuLF40rlXLYpnofWQOmebNR/u97MuLFRMxDbE+4mF5UIythjXNQJmTcSIxq5H1KI+BiRinccxxCrWIluduHfGjc2H9CymW6vuG5b9XHrgweX3bsjuGWZxbFh8z5r5FevwWLPCvQzjGFfft68zPgztNXYS5u63SbrZzJ4YnjpF0jclXSrpzPDcmZIuKdVCAOiDWgQgFdQjAMMqe5+w35Z0QZj95yZJL1PWsfuYmZ0l6XuSXlRyG6jBOElUcaxYPhEbNXGbRgLWpHFW3DtsZNSiKhVn9eqRjC3f26fLzIlDivcR27rlpzvjL+KaPAyrsDWF9sRtrQn/i9vyqOzpmx4e+V5Y00jAmjTOinuHjYV6NC09EjFflYCFsWBxjNiilutHj7GtK5btJsyu6g/t66zDY9q+FGrfARtWNjckYx4Ssx/9ZFaLDv7nB7R4330r9wmtU6oT5u47JXWbdpF5VQFUhloEIBXUIwDDKJuEYUZMMnnpNnviJMaJtRGJGBqhVzKWX2RpwNne8J74nY/Jy3w8s720KC8M6eokYvEsdLgn0PI9grKz0PbgQ5KkB5/9n3XA57/evx3oikQMSRkxjbd5Ld83sDgnSq/7G/aIxHxhv5b2Ze+JuZuH99iDe1e0pzMrY0jE1t+dxfc3vvYn9Pg//ZYkafHee7tuB7OPThj62nHLzrEvDcx3vGKHbOum5fV20/bLEHuhM4ZG6fyBNMwU9d3NF17fccvOzg2c4x9TncH28YasoTMWt25x4Hu4geraHy7o2390vCRp2+asY9arU9H2yxB7oTOGJPW6jUbucsWel0Qv9ahFxQk6VrwndOg6N2kON2GOf1bHSx/j63uz2S7nFrLLFTfcZdr+jS9IYgKyNiszRT0AAAAAYEQkYVihmLhM6gxNHZcjzmJqRCKGRnHvfYPn4vT2Batq0eYTFJO1VVcJLcYp69cub1fq3FDVf/BDSdL8V+7SMf9S/f2XZjE1IhFDkvpcpui9Ei/1momjuI6Yts0tJ2zxpsvxkuiQiNmBB2Svx8f7s59r9twjSdr8we9q67nH998uZh5JGAAAAABUiCQMXU37GmWugS6HRAyNUXL65SwBK65zZSLWGfy+uPKM9tKDD4bFQxuWVp/x5ibM5ZCIIWn5+uOFmzGPKk70kx9bFtP2UGM6aXzhRsxLd90dmhBq1/6Hx2sDZgpJGAAAAABUiCQMM6dN6RCJGGbWMGerYyK2EH8WX6/3JqhtSodIxNAYQ9xSY+XrK/OK7rfbCInY3pC27X2osM2l7ttGq5GEAQAAAECFSMIwM5qaBnVr96hj5kjEMHO63fenIWeRm5oGdWv3qGPmSMTQOL3uMdZ5PaRY+URswOyuTalVqBdJGAAAAABUqLFJ2KTvYwVUrV9qNW6iRSJWvXjGn1n2poQzylPXL7UaN9EiEUPjDJuI5ZcFSiAJAwAAAIAKJZGEPeHJD2rHjp11NyM5xTSD1K+7pqU+VbSXRGw8xz75AW3/LGfui4ppBqlfd01LfapoL4kYGoeUCxUhCQMAAACACjW+E7bjlp0ze7Z/66bjV6Rfs7yvmA7S0+ps33P1zJ7t37b5xBXp1yzvK6aD9BQAVmp8JwwAAAAAmiSJMWEYDqnGSqSCQD1INVYiFQQAjIokDAAAAAAqRBLWACRg3TED4HA4TpgUErDumAFwOBwnAFg2M50wbt7cXnV2Mpr0fZvGcVq9/7smtu6m4ubN7VVnJ6NJ37dpHKfV+3/TxNYNANPA5YgAAAAAUKGZScIwG8okmk257K6aRGo6229S8geUUSbRbMpld9UkUtPZfpOSPwDohiQMAAAAACo0M0kYZ+hnSxsSsboNe5z4tzUaztDPljYkYnUb9jjxbwvALCEJAwAAAIAKzUwShtkwydSluC6Sse6KiRjJFzDZ1KW4LpKx7oqJGMkXgFlGEgYAAAAAFWp8EsZZewyLsWL98W+pHM7aY1iMFeuPf0sA2qBUEmZmrzGzb5jZtWb2UTPbYGZHm9kVZrbLzC4ys3WTaiwAdEMtApAK6hGAYYzdCTOzzZJeKekkd3+SpHlJZ0h6h6R3ufsxku6VdNYkGgpMytZNx5P6zBBqEZpq2+YTSX1mDPUIwLDKjglbI+kAM1sj6UBJt0p6tqSLw+vnSzq95DYAYBBqEYBUUI8ADDR2J8zd90h6p6TvKysw90u6StJ97r4QFtstaXPZRnZDmoGy+P7MhrprEWkGyuL7MzvqrkcAmqPM5YiHSTpN0tGSNkk6SNKpI7z/bDO70syuvPPuxXGbAaDlJlmL7rp7aUqtBNAGZepRvhbt174pthJACsrMjvgcSd9x9zslycw+KekZkg41szXhjM8WSXu6vdndz5N0niQdYhudVAJ1qHPGxF7f+Wm1pbjeGfo3N9FaRCqBOtQ5Y2Kv7/y02lJc74z9mxu7HhVrUXVNBlCHMmPCvi/pZDM70MxM0imSvinpC5JeGJY5U9Il5ZoIAH1RiwCkgnoEYCjmPv7JFjP7PUkvlrQg6WuSfl3Zdc4XStoYnvtld++bqx9iG/1pdsrY7QBmVUyvyqRWoyZrZbZ1uV98lbufNPYKxkQtAqYrpldlUqtRk7Uy26qrFkmTqUfUImA29KtFpW7W7O5vlfTWwtM3SXpqmfUCwCioRQBSQT0CMIxSnTAA0zVD47YANNiMjdsCgNqVvU8YgMRxOwcAKeB2DgCwjE4YAAAAAFSIThgAAAAAVIhOGAAAAABUiIk5gJYo3piacWIA6lC8MTXjxAC0EUkYAAAAAFSIJAyYsNSTplTbBWCyUk+aUm0XAFSBJAwAAAAAKkQSBkxITMCKj1NLnlJtF4DJiAlY8XFqyVOq7QKAKpCEAQAAAECFSMIwc4qJVN2JT53JU/FYAKhOMZGqO/GpM3kqHgsAaDuSMAAAAACoEEkYZl5VSVRx/VUmYCReQPqqSqKK668yASPxAoDhkIQBAAAAQIVIwjCyps2uV1c7p7FdEi9gWdNm16urndPYLokXAJRDEgYAAAAAFSIJw9CaksLEBKop7QUwmqakMDGBakp7AQDVIQkDAAAAgAqRhGGgXolS6mPDUm3XOEj1gN6JUupjw1Jt1zhI9QBgMuiEAQ3Qa/p7AKhSr+nvAQCj4XJEAAAAAKgQnTD0NUzisuOWnSQzFdu66fiZutwSGGSYxGX7nqtJZiq2bfOJM3W5JQBUhU4YAAAAAFSIMWHoimSrGRgrhllHstUMjBUDgNGQhAEAAABAhUjCsEKZJCX1KevbYJgbVfP5oAnKJCmpT1nfBsPcqJrPB0CbkYQBAAAAQIVIwoAZlE+7SCgB1CWfdpFQAsCygUmYmX3QzO4ws2tzz200s8vM7Ibw87DwvJnZn5vZLjO7xsyotAAmhnoEIAXUIgBlDXM54oclnVp47k2SPufux0r6XHgsSc+VdGz472xJ751MMzFtk7zXF/cNS8uM3VPsw6IezbRJ3uuL+4alZcbuKfZhUYsAlDCwE+bu/yzpnsLTp0k6P/x+vqTTc8//tWe+LOlQMztiQm0F0HLUIwApoBYBKGvcMWGHu/ut4ffbJB0eft8s6ebccrvDc7cKSSKxwgygHs0AEivMAGoRgKGVnh3R3V2Sj/o+MzvbzK40syv3a1/ZZgDAWPWIWgRg0qhFAAYZNwm73cyOcPdbQ6R+R3h+j6Qjc8ttCc+t4u7nSTpPkg6xjSN34lBOFQkYs/KhIqXqEbWoXlUkYMzKh4pQiwAMbdwk7FJJZ4bfz5R0Se75Xw0zAZ0s6f5cNA8A00A9ApACahGAoQ1Mwszso5KeJenRZrZb0lslvV3Sx8zsLEnfk/SisPh2Sdsk7ZL0oKSXTaHNAFqKegQgBdQiAGUN7IS5+0t6vHRKl2Vd0ivKNgoAuqEeAUgBtQhAWeOOCUtGcWwT44/6q3I2RD4LtElxbBPjj/qrcjZEPgsAQGoa1wkb1Ino9XrbOwR0voDJGtSJ6PV62zsEdL4AAJjAFPUAAAAAgOE1JgkbN8khlclwHIDJGDfJIZXJcBwAACAJAwAAAIBKNSYJGxXJD4AUkPwAAIAikjAAAAAAqNDMJWEkYABSQAIGAAB6IQkDAAAAgAo1JgmLCRf3AQNQp5hwcR8wAAAwLpIwAAAAAKhQY5KwXkjAAKSABAwAAAyLJAwAAAAAKtTYJIwEDEAKSMAAAMCoSMIAAAAAoEKNS8JIwACkgAQMAACMiyQMAAAAACrUuCQMSEn+vnXTSGnj+kmAAfSTv2/dNFLauH4SYACYDJIwAAAAAKgQSRgwAWWSqnyaBgBllEmq8mkaAGC6Zr4T1u0P3Cov7Spun8vKZsM4lwnS2Wq3bn/gVnlpV3H7XFY2G8a5TJDOFgDUj8sRAQAAAKBCM5uE9Uodpp1EDUo7SMaard/nO82kiwk6mqtX6jDtJGpQ2kEy1mz9Pt9pJl1M0AEAk0ESBgAAAAAVmtkkLCI5wDQxzgvDIjnANDHOCwCahSQMAAAAACo0c0lY08bONK29bUHChbKaNnamae1tCxIuAJhNJGEAAAAAUKGZS8JST5RSb1+bkHZhmlJPlFJvX5uQdgFA+wxMwszsg2Z2h5ldm3vuT8zsW2Z2jZn9nZkdmnvtHDPbZWbXm9nWKbUbQMtQiwCkgnoEoKxhkrAPS3qPpL/OPXeZpHPcfcHM3iHpHElvNLPjJJ0h6ackbZJ0uZk9wd0XJ9vseoxyjy8Sr/TlP6OmpGItH0P4YVGLJI12jy8Sr/TlP6OmpGKMIaQeAShnYBLm7v8s6Z7Cc//o7gvh4ZclbQm/nybpQnff5+7fkbRL0lMn2F4ALUUtApAK6hGAsiYxJuzXJF0Uft+srPBEu8NzMymfnsRkoqUJReMVP7emJGNYobW1KJ+exGSixQlFoxU/t6YkY1iltfUIwHBKdcLM7C2SFiRdMMZ7z5Z0tiRt0IFlmgGg5ahFAFIxbj2iFgHtMnYnzMxeKul5kk5xdw9P75F0ZG6xLeG5Vdz9PEnnSdIhttG7LZOKYVKRUcaLIX29Pj8SsvS0qRYNk4qMMl4M6ev1+ZGQpalMPWpSLQJQ3lj3CTOzUyW9QdLz3f3B3EuXSjrDzNab2dGSjpX0lfLNBIDVqEUAUkE9AjCKgUmYmX1U0rMkPdrMdkt6q7IZf9ZLuszMJOnL7v5yd/+GmX1M0jeVRfGvaOvsPyRjs4mxY/WhFo2HZGw2MXasXtQjAGUN7IS5+0u6PP2BPsv/oaQ/LNMoACiiFgFIBfUIQFmTmB0RXZB8tUNd9xqbxP3CWn7PsdYg+WqHuu41Non7hXHPMQBtRCesj1H+qOYPWaR+qSKXyDbXKH9U84csUr9UkUtkAWDMiTkAAAAAAOMhCSuBJAH9TDMZG+W7x2WHs48kAf1MMxkb5bvHZYcAsIwkDAAAAAAqRBLWR0wOSBIwCZO4AfSw38H8OvneNl9MDkgSMAmTuAH0sN/B/Dr53gLAMpIwAAAAAKgQSdgQSBIwTdMYO8Z3djaRJGCapjF2jO8sAHRHEgYAAAAAFTJ3r7sNMrM7JT0g6a6629LFo0W7RkG7RjNr7Xqcuz9m0o2pCrVoLLRrNLRrNNSi9Mzad2XaaNdoZq1dPWtREp0wSTKzK939pLrbUUS7RkO7RkO70pPqvtOu0dCu0dCu9KS677RrNLRrNG1qF5cjAgAAAECF6IQBAAAAQIVS6oSdV3cDeqBdo6Fdo6Fd6Ul132nXaGjXaGhXelLdd9o1Gto1mta0K5kxYQAAAADQBiklYQAAAAAw85LohJnZqWZ2vZntMrM31dSGI83sC2b2TTP7hpm9Kjy/0cwuM7Mbws/DamrfvJl9zcw+HR4fbWZXhGN2kZmtq6FNh5rZxWb2LTO7zsyensLxMrPXhM/wWjP7qJltqON4mdkHzewOM7s291zX42OZPw/tu8bMpnaH0x7t+pPwOV5jZn9nZofmXjsntOt6M9s6rXalIIVaFNqRbD2iFo3UriRqUWhLcvWIWtQbtWiotiVXi0I7kqtH1KKx2jT1WlR7J8zM5iX9haTnSjpO0kvM7LgamrIg6bXufpykkyW9IrTjTZI+5+7HSvpceFyHV0m6Lvf4HZLe5e7HSLpX0lk1tOndkj7r7j8h6SmhfbUeLzPbLOmVkk5y9ydJmpd0huo5Xh+WdGrhuV7H57mSjg3/nS3pvRW36zJJT3L3J0v6tqRzJCn8GzhD0k+F9/y/8G925iRUi6S06xG1aAiJ1SIpzXrUrU3UImrRsFKsRVJi9YhaNHabpl+L3L3W/yQ9XdKO3ONzJJ2TQLsukfSzkq6XdER47ghJ19fQli3KvpTPlvRpSabshnFruh3Ditr0SEnfURhXmHu+1uMlabOkmyVtlLQmHK+tdR0vSUdJunbQ8ZH0l5Je0m25KtpVeO2/S7og/L7i36OkHZKeXuVnWuF3J8laFNqSRD2iFo3UrqRqUdhecvWIWtR1v6lFg9uRXC0K202uHlGLxmtT4bWp1KLakzAtfzmi3eG52pjZUZJOkHSFpMPd/dbw0m2SDq+hSedKeoOkpfD4UZLuc/eF8LiOY3a0pDslfShcDvB+MztINR8vd98j6Z2Svi/pVkn3S7pK9R+vqNfxSenfwa9J+kz4PaV2TVuS+5pYPTpX1KKhNKAWSenXI2pRJol9pRYNJbl6RC2aiKnUohQ6YUkxs4MlfULSq939B/nXPOvyVjqdpJk9T9Id7n5VldsdwhpJJ0p6r7ufIOkBFeL1mo7XYZJOU1YIN0k6SKsj5iTUcXwGMbO3KLv85IK624K06hG1aDRNqkVSevWIWpQWatHQkqtH1KJyplmLUuiE7ZF0ZO7xlvBc5cxsrbIic4G7fzI8fbuZHRFeP0LSHRU36xmSnm9m35V0obLo/d2SDjWzNWGZOo7Zbkm73f2K8PhiZYWn7uP1HEnfcfc73X2/pE8qO4Z1H6+o1/Gp/d+Bmb1U0vMk/VIogkm0q0JJ7WuC9YhaNJrUa5GUaD2iFqW1r9SikaRYj6hFY5p2LUqhE/ZVSceGWVrWKRvsdmnVjTAzk/QBSde5+5/lXrpU0pnh9zOVXQ9dGXc/x923uPtRyo7N5939lyR9QdILa2zXbZJuNrMnhqdOkfRN1Xy8lMXtJ5vZgeEzje2q9Xjl9Do+l0r61TAT0MmS7s9F81NnZqcqu7Tj+e7+YKG9Z5jZejM7Wtng2K9U1a6KJVGLpDTrEbVoZKnXIinBekQtkkQt6ivVWhTalmI9ohaNoZJaNInBbGX/k7RN2cwjN0p6S01teKay+PMaSTvDf9uUXWf8OUk3SLpc0sYaj9OzJH06/P7j4UPfJenjktbX0J7jJV0ZjtmnJB2WwvGS9HuSviXpWkl/I2l9HcdL0keVXX+9X9nZsbN6HR9lg4r/Ivwb+LqyWYyqbNcuZdc4x+/++3LLvyW063pJz63686z4u1N7LQrtSLoeUYuGblcStSi0Jbl6RC3qe2yoRcO1L6laFNqRXD2iFo3VpqnXIgsrAwAAAABUIIXLEQEAAACgNeiEAQAAAECF6IQBAAAAQIXohAEAAABAheiEAQAAAECF6IQBAAAAQIXohAEAAABAheiEAQAAAECF/j9rvgstIwdAdwAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(128, 128, 3)\n" ] }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAA2EAAAEiCAYAAABwX9rUAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAAA2cUlEQVR4nO3de7glVXnn8d97Tt9oGoRWw9BcGhLQBA2iwyg+rTOMJNNojDKOUcwNDQnjaPASjYLOE5yMSXA0EdNekEQFIxEQjRJFW0RJIhEiaAdRBBq1oWluyh2aps857/xRq/apXWfXvu+qVbu+n+fhOWdfa1Wd3S971a/WWubuAgAAAACUY6bqBgAAAABAk9AJAwAAAIAS0QkDAAAAgBLRCQMAAACAEtEJAwAAAIAS0QkDAAAAgBLRCQMAAGgoMzvXzN4dfn++md1Y0nbdzA4reOwKM/v9qttRJTPbYGY3m9nDZnZC1e3B+NEJAwAAiJiZ/cTMdoYv5HeFjtOacW/H3f/F3Z/aR3tebWbfHPf20eZPJX3Q3de4++dHeSMz+3L47DxsZrvN7PHM7bOHeL93mdmnejznJ2Z2t5ntmbnv983siiF2IX39/mZ2iZntCJ3nQ3KPrzSzj5vZg2Z2p5n90QjbWmFmF4f9cDM7Nve4mdl7zOxn4b/3mJkNsg06YQAAAPH7dXdfI+lZko6W9L/zTzCzZaW3CpOyXtL3h3lh/nPg7i8Mnbk1ks6X9P/S2+7+2jG0tcispDf288Q+P7sLkr4i6X8UPP4uSYcrOXb/VdLbzOz4frZf4JuSflvSnR0eO0XSCZKeIelISb8u6X8O8uZ0wgAAAGrC3W+X9GVJT5dal9O93sxulnRzuO/FZrbFzO43s381syPT15vZM83sO2b2kJldKGlV5rFjzWx75vZBZvY5M7snnO3/oJn9kqSzJT03JCn3h+euNLP3mdmtIa0728z2yLzXH5vZHSHF+L0+dnW9mV0Z2vlVM3tS5r2OCft1v5n9ezalMLPXmNkN4XU/MrO2L8aDtCNcFvnusK2HzewfzeyJZnZ+SFu+nU1jzOwDZnZbeOxaM3t+5rF3hWTlwtC275jZMwq2e4ukn5f0j2G7K81sXUiB7jWzrWb2Bx3e+1Nm9qCkV/dxfNPXdvusvN3Mbg/tvdHMjgudmndIemVo2793efv3Snqrme1TsO0ln91u3P0ud/+wpG8XPOUkSf/X3e9z9xsk/Y0GOBa5bT3u7me5+zclzRds6y/dfXv4N/mXg26LThgAAEBNmNlBkl4k6buZu0+Q9BxJR5jZMyV9XMlZ+SdK+qikS8IX+RWSPi/p7yStlfQZFaQKZjYr6YuStkk6RNIBki4IX25fK+lbIUnZJ7zkTElPkXSUpMPC8/8kvNfxkt4q6VeVJBW/0seu/qak10j6OUkrwutlZgdI+pKkd4d9eKukz5rZk8Pr7pb0Ykl7h9e/38yeNUI7TpT0O2F/fkHStyR9Imz7BklnZJ777bD/ayX9vaTPmNmqzOMvVXLM08c/b2bL8xt091+QdKtC+unuuyRdIGm7pHWSXi7pz83sBbn3vljSPkrSrp56fFaeKukPJf0nd99L0kZJP3H3r0j6c0kXhrZ17EgG10i6QuFvV+AEhc9uaNP9Zva8ftqf25d9Je0vKdsp/HdJTxv0vfr0tFG3RScMAAAgfp8PqdM3Jf2Tki/Cqb9w93vdfaeSy6Q+6u5Xu/u8u58naZekY8J/yyWd5e673f1iFacKz1byhf+P3f0Rd38spAJLmJmF7b45tOOh0L4Tw1NeIekT7n69uz+i5LKxXj7h7jeFfbpISedGSi4Pu9TdL3X3BXe/TMmX/RdJkrt/yd1v8cQ/SfqqpDSRGrYdt7j7A0oSyFvc/WvuPqekQ/XM9Inu/il3/5m7z7n7X0paKSk7xu5ad7/Y3XdL+islKeQxvRoQOt4bJL09/B22SPpbSb+bedq33P3z4Zjs7GO/pO6flfnQ/iPMbLm7/8Tdb+nzfbP+RNKpmU5yXvazK3ffp+hz1kM6RvKBzH0PSNpriPfqd3v5ba0J/xb6QicMAAAgfieEL6jr3f11uS/at2V+Xy/pLSFRuD903A5S0qFaJ+l2d/fM87cVbO8gSdtCZ6OXJ0taLenazDa/Eu5X2G62jUXbzMqOw3lUi1+y10v6jdz+PU9JCiIze6GZXRUu27tfSecsvZRxmHbclfl9Z4fbrQlSzOyt4VLIB8K2n5DZtrLbdvcFLSZbvayTlHZus20/oNN7D6Dws+LuWyW9SUlH9W4zu8DM+mlrG3e/XkmielrBU4ZpdycPh597Z+7bW9JDHZ7bxswOtsWJSh7u9fzM9vLbejj3b6srOmEAAAD1lv3id5ukPwsdtvS/1e7+aUl3SDogd7b+4IL3vE3SwdZ5woT8F82fKumQPC2zzSeEiSAUtntQH9vsx22S/i63f3u6+5lmtlLSZyW9T9J+4VLJSyWl+zvOdrQJ47/epiRt2zds+4HMtpXdtpnNSDpQ0o4+3n6HpLVmlk11DpZ0e+Z231/+M7p9VuTuf+/uz1PSWXNJ7xlyW2dI+gO1dxpHaffSN3G/T8nfN3t55DPUx+Qm7n5rZqKSfmcd/f4w28qiEwYAADA9/kbSa83sOZbY08x+LXyB/5akOUlvMLPlZvYyJZcddvJvSr7UnhneY5WZbQiP3SXpwDDGLE11/kbJ+Kufk5KxW2a2MTz/IkmvNrMjzGy12sdRDepTkn7dzDaa2Wxo17FmdqCSsWMrJd0jac7MXijpv2VeO8525O2l5NjeI2mZmf2J2pMSSfqPZvay0LF9k5JL/67q9cbufpukf5X0F2F/j5R0spJjMYrCz4qZPdXMXhA6to8p6WQvhNfdJemQ0JHsKaRqF0p6w4jtVRhjtzLcXJkbc/dJSf/bzPY1s19U0vE7N/PaJVPN99hW9v1XhGOfdqo/KemPwud8naS3ZLfVDzphAAAAU8Ldr1Hy5fODku6TtFVh1jZ3f1zSy8LteyW9UtLnCt5nXsm024cpmSRie3i+JH1dyVn/O83sp+G+t4dtXWXJDH1fUxgP5e5flnRWeN3W8HPY/btNySQU71DS4blN0h9LmgmX671BSWfrPiWTe1ySee3Y2tHBZiWXYN6k5FLBx7T0UrsvKDmG9ymZ7ONlYXxYP16lZIKUHZL+QdIZ7v61URrc7bOipKNzppKU804lE6ScHh77TPj5MzP7Tp+b+1NJe/Z6Urgk8PldnrJTi5ce/jDcTp0h6RYlx/+fJL03TCSSjqt7SNL3+myvJN0Y3v8AJX/fnUpSQSmZxOQfw/tdr2SymI8O8N6yAS5dBAAAADAgM3uXpMPc/berbksTmdlvK7lc9vSeTy4Ji/oBAAAAmFruPuqlm2PH5YgAAAAAUKKJdcLM7HhLVtfeamZF01ICwERRiwDEgFrUbO7+Li5FRNZExoRZssr6TUpWJN+uZCHAV7n7D8a+MQAoQC0CEANqEYC8SSVhz5a01d1/FGbiuUDJTDYAUCZqEYAYUIsAtJnUxBwHqH1azu2SnlP05BW20lf1nrUSQOQe0n0/dfcnV92ODGoR0EDUIgAx6FaLKpsd0cxOkXSKJK3Saj3HjquqKQDG5Gt+8baq2zAoahEwfahFAGLQrRZN6nLE2yUdlLl9YLivxd3Pcfej3f3o5a2FrwGMw+YdW7R5x5aqmxEDahFQoU3brtSmbVdW3YwYUIsAtJlUJ+zbkg43s0PNbIWkE5VZsRwASkItAhADahGANhO5HNHd58zsDyVtljQr6ePu/v1JbAtAsWwatnHdUZW1oyrUIiAO2TTs1PUbKmxJNahFAPImNibM3S+VdOmk3h8A+kEtAhADahGArMom5gAwOU1MvQDEp4mpFwD0Y1JjwgAAAAAAHdAJAwAAAIAS0QkDAAAAgBLRCQMAAACAEtEJAwAAAIAS0QkDAAAAgBLRCQMAAACAEtEJAwAAAIAS0QkDAAAAgBLRCQMAAACAEtEJAwAAAIAS0QkDAAAAgBJF0Ql7ypGPavOOLVU3A0DDHfzLD2vTtiurbgYAAJhyUXTCAAAAAKApouiE3XTdam1cd1TVzQDQcLd+b41OXb+h6mYAAIApF0UnDAAAAACagk4YAAAAAJSIThgAAAAAlIhOGAAAAACUiE4YAAAAAJSIThgwIZt3bGH9OwCV27TtSta/A4DILKu6AcC0SztidV2GIduRrOs+AFCrI1bXZRiyHcm67gMApEjCAAAAAKBEJGHAhNQ9Nep0KWXdUz2gieqeGnW6lLLuqR4AkIQBAAAAQIlIwgC06WcyERIxAJPWz2QiJGIA6ookDAAAAABKRBIGQFJ/CRgATBrT6QNogqGTMDM7yMy+YWY/MLPvm9kbw/1rzewyM7s5/Nx3fM0FgHbUIgCxoB4B6NcolyPOSXqLux8h6RhJrzezIySdJulydz9c0uXhNgBMCrUIQCyoRwD6MnQnzN3vcPfvhN8fknSDpAMkvVTSeeFp50k6YcQ2AkAhahGAWFCPAPRrLGPCzOwQSc+UdLWk/dz9jvDQnZL2G8c2AExWOtNhP2PDYp0VkVoE1F8602E/Y8NinhWRegSgm5FnRzSzNZI+K+lN7v5g9jF3d0le8LpTzOwaM7tmt3aN2gwADUctAhCLYeoRtQholpE6YWa2XEmROd/dPxfuvsvM9g+P7y/p7k6vdfdz3P1odz96uVaO0oxKbd6xpbRZ5crcFppr47qjok26ilCLktSgrFnlytwWmuvU9RuiTrqKDFuPpqUWAejPKLMjmqSPSbrB3f8q89Alkk4Kv58k6QvDNw8AuqMWAYgF9QhAv0YZE7ZB0u9I+p6ZbQn3vUPSmZIuMrOTJW2T9IqRWlgT+YRqnEkC6ReqUKM0jFqUkU+oxpkkkH6hCjVLw6hHAPoydCfM3b8pyQoePm7Y9wWAQVCLAMSCegSgX2OZHRFLjSMZIwEDMKpxJGMkYAAAjNfIsyMCAAAAAPpHElaSolQrm5CRfAGYtKJUK5uQkXwBADBZdMIqRsdrctJjW6MJJoDK0PGanPTY1myCCQDABHE5IgAAAACUiCQMUyefLpKIAahCPl0kEQMApEjCAAAAAKBEJGE1NMmFofPbqEN61O+4ujKOG9Akk1wYOr+NOqRH/Y6rK+O4AQDiRhIGAAAAACUiCRtRmqZUOcvhKAlPr3Z3e7zuSdLmHVtqvw9AKk1TqpzlcJSEp1e7uz1e9yRp07Yra78PAIDBkIQBAAAAQIlIwqZI2alO1ePGxpE+1n2cWGzrzM3uX3ULEIOyU52qx42NI32s+zix2NaZ+6WDq24BAHRHEgYAAAAAJSIJG5OYxoYNkubE0O6YcBxQdzGNDRskzYmh3THhOADAdCMJAwAAAIASkYSNSZMTlCbvOxCbJicoTd53AEC9kIQBAAAAQIlIwkZAAgQgBiRAAADUC0kYAAAAAJSIJGwIVSdg+dkPx7FeF7MkAvVTdQKWn/1wHOt1MUsiAKAJSMIAAAAAoEQkYQOINSUaJQEbJ9I0oByxpkSjJGDjRJoGAIgdnbAu6Ex0V9T5ozMGjBedie6KOn90xgAAseJyRAAAAAAoEUlYB01OcMaZYpGIAaNpcoIzzhSLRAwAEBuSMAAAAAAoEZ2wjM07tpDaTEAsE4cAdbFp25WkNhMQy8QhAADQCQMAAACAEjV6TBipV3mKFpjGdFj8+26tshm1RepVnqIFpjEdFv++F1faDgDoZeQkzMxmzey7ZvbFcPtQM7vazLaa2YVmtmL0ZgJAd9QiADGgFgHoxziSsDdKukHS3uH2eyS9390vMLOzJZ0s6SNj2M7YkML01mlmw3GO7WLmRExA7WoRKUxvnWY2HOfYLmZOxATUrhYBKN9ISZiZHSjp1yT9bbhtkl6gxesAzpN0wijbAIBeqEUAYkAtAtCvUZOwsyS9TdJe4fYTJd3v7nPh9nZJB4y4jbGqc/JS1SyDk9wuiVi9RTTz5VmqWS2qc/JS1SyDk9wuiVi9RTTz5VmqWS0CUI2hkzAze7Gku9392iFff4qZXWNm1+zWrmGbAaDhqEUAYkAtAjCIUZKwDZJeYmYvkrRKybXPH5C0j5ktC2d9DpR0e6cXu/s5ks6RpL1trY/Qjq5IWEZTVtJBIoYR1KIWkbCMpqykg0QMI6hFLQIQh6GTMHc/3d0PdPdDJJ0o6evu/luSviHp5eFpJ0n6wsitBIAC1CIAMaAWARjEJNYJe7ukC8zs3ZK+K+ljE9hGTyQq9cR6YvUQ0ViwbqKoRSQq9cR6YvUQ0ViwbqKoRQDiMpZOmLtfIemK8PuPJD17HO8LAIOgFgGIAbUIQC+TSMIqRXIyXRgrhroiOZkujBUDAIzTSOuEAQAAAAAGU/skjISkGUjE4lCTsWCVICFpBhKxONRkLBgAFKptErZ5x5bGfiFv8r7TCUBsNm27srFfyJu873QCAACjqG0nDAAAAADqqHaXIzY1AZKW7nv+dlNSIqaxr0ZTPl/9amoCJC3d9/ztpqRETGNfjaZ8vgBMN5IwAAAAAChRLZIwko7+dDpOTUgvmLSjHJt3bGnE56kbko7+dDpOTUgvmLSjHJu2XdmIzxOA6UYSBgAAAAAlijoJI9nAIEjEJi89tk1LxEg2MAgSsclLjy2JGIC6IgkDAAAAgBJF3QnbuO6oxp1xx+j43Exe09aqO3X9Bs64Y2B8biavyWvVAai3qDthAAAAADBtoh4ThuGRBLGeWBmaOkYM/SMJYj2xMjBGDEDdkIQBAAAAQIlq0QnjLDvGgbFik9OUMWKcZcc4MFZschgjBqAuatEJAwAAAIBpQScMjUMiBiAGJGIA0Fx0wgAAAACgRLWZHTFNLpow7qRIE9KbMmfb27juqEZ/njCcNLlo8riTJqQ3Zc62d+r6DY3+PAFAE5GEAQAAAECJapOEpUjEJqvTcS0jlcpvt+jvO+62sJYYhkUiNlmdjmsZqVR+u0V/33G3hbXEAKBZatcJw2R063xMskMUW6enCZ38afy7YXp063xMskMUW6enCZ38afy7AUC/uBwRAAAAAEpU2ySsCYlFGUY5fmVOolG2afl8TepvU/y+WyeyvZg1IbEowyjHr8xJNMo2LZ+vSf1tit/34olsDwDGhSQMAAAAAEpU2yQMo6k64al6+/2qWyI2jakkplvVCU/V2+9X3RKxaUwlAWCcSMIAAAAAoES1T8LqllRUbRLHaZCxYXX9OzGVPXqpW1JRtUkcp0HGhtX178RU9gAwHUZKwsxsHzO72Mx+aGY3mNlzzWytmV1mZjeHn/uOq7EA0Am1CEAsqEcA+jFqEvYBSV9x95eb2QpJqyW9Q9Ll7n6mmZ0m6TRJbx9xOz2RiHU3iePS5PFHsX7epnnGyh6iqUUkYt1N4rg0efxRrJ+3aZ6xsg/R1CMA8Ro6CTOzJ0j6z5I+Jknu/ri73y/ppZLOC087T9IJozURAIpRiwDEgnoEoF+jJGGHSrpH0ifM7BmSrpX0Rkn7ufsd4Tl3StpvtCZiFLElYLEmSMOa1P5M23GaMGpRDcSWgMWaIA1rUvszbcepBNQjAH0ZZUzYMknPkvQRd3+mpEeUxOst7u6SvNOLzewUM7vGzK7ZrV0jNANAw1GLAMRi6HpELQKaxZJaMMQLzf6DpKvc/ZBw+/lKCs1hko519zvMbH9JV7j7U7u919621p9jxw3VjiLTmCAMkkCNc/8nOb6oVzvrNLZp1GPebV+Hfe+yj9/X/OJr3f3oMrcZey2axgRhkARqnPs/yfFFvdpZp7FNox7zbvs67HuXffyqqEXS+OrRJGoRgPJ1q0VDJ2Hufqek28wsLSLHSfqBpEsknRTuO0nSF4bdBgD0Qi0CEAvqEYB+jTo74qmSzg+z//xI0muUdOwuMrOTJW2T9IoRt4EKdEtQtr7/mI73H/bmq8a6nboZdC2xadr3CFCLplRZCUqdkq5eBl1LbJr2PRLUIwA9jdQJc/ctkjpFbGToAEpDLQIQC+oRgH6MmoRFi9nlhtMpncknX0WJ1zgTsmmQ/wxWMavk5h1bSNwqxuxywyGdGZ/8Z7CKWSU3bbuSvymQMlv8fci5GVB/U9sJSzW1M9bvfhd9Qc92qPrtRPXTOUuf06RFhZuwj+itqZ2xfvd7ol/QwxeemTVrdMs7ni5JOvT0b7W1qwkdhCbsI1CJbKeq29NmZyVJs/v9nL707Usl8R2hyUaZoh4AAAAAMKCpT8LQWa8EbJyXEN7yyrMXb7xybG/bSMMku01KHVE/I6UzM7NtN20mnI0OZ5tn1uwZHkjuv/S6y/Xj3V+WJC38ZvLQvPo7g412wyS7TUodMeVyyZctW578EmpQmnjZypXJ/U9em/ycTbKPheWzOv7Q54TXzkuSfG5uki1GhEjCAAAAAKBEjUnCmjo2LNUrBRlHAjbMsSWlGU7TP8911tSxYamRUpD82ef0rPOy5H9ltscekqRPXvdFSdJsLuX68e4F7c7dN6tkUDwpzXCa/nlGQ9lM+BFq0IokCbM9ViWP77N38vP+B5P7H3qk7eULP71XPrc7uZFOzJEm+wvzE2o0YkMSBgAAAAAlakwSltq47qhGpQdlJkyDbKtJf4NYkDrG5dT1GxqVHoycMJktjrtI71q+rPWYJGk+OYP8O0cc33bbdydjLXxu95LpoJv0N4gFqSNqyRbHe6Wpu6W1J4z9sjDmS6HmaFWSjPmux5Ofjz6a3O8LS963dV/rNlPXTzuSMAAAAAAoUeOSMCT6XYB5UkhjxoOxYZh6YZyEzc4uzjyWnileCGeOZ5LziZ47c+whCVs8wzwjaaHtOace8rzwHM46j4KxYZg6+TGoK1YkP5cta41DTWuSwsyGPhPGhs3nUq38zIeziyNWfSFXe0jEGoMkDAAAAABK1MgkrG7pwThSo6qTL0zWIJ9pxobFo27pwUTH8KRnfZfMOrZi8fH8GeHcmWrtTmYb8/n2tKv9NeHco3d5DoY2yGeasWGISr4GhTGnrTW/9kzWHbRls/I0hQ8pli1vzzT8sceSXx5Pa1JI5eczMx+m76swdjWfiGHqkYQBAAAAQIkamYQ1AckXgFooSMBaiVV6xnl2tnXmuHVfKiRkrQQspFycWQbQt7QGzc62/WzVnTQ995nFMWFpLcrXoDQBS8eChee1jVsN9amwTjEWbOqRhAEAAABAiRqThHUaB1O3sWH92vr+Y0i+GoqxYfHrNA6mbmPDxqJXApbenulwrnCmPSXLz4JYPNvYTOZsNmeZJ4mxYYhejzFgrTFb6dpfNrP0telz08QrnSXx8bAuWFpnOqVd3p7cL95PbWoKkjAAAAAAKFFtk7Bh06vNO7YsOfM/LYlYOg6MFAwoz7Dp1aZtVy4589/ERKyVgPXz3HD2uXV2OU3AisZWLDnDzIyIQGPlZ1PNz8TaSsbyt3N5hdmSNbx8d/sYsCUJWK72dBwHRgLWOCRhAAAAAFCiqJOwSSVT0zYWhgQMedl0d1o+51WaVDLVqLEw+bPQSx5vHwtmuTEXln19fj2wQRIvzjaXKpvuNuJzjjiZLUm0loxDTcd3pVrjUkNNWhnWLFy2+Dx/+JHkZ5gNMZ/Ok76jmyg6YU858lFt3ryl6mbU7rJEOl/ohQ7YYA7+5Ye16UvVXwo4VZcl9up85Z+e/yKU0brUJ/056BT0dMAqQwcMpepSdwovgQ4dqNYC8StXtj+e1g93+aPJYsz+6M7k5+4wMUeu46bWnEFdLpWmLjUWlyMCAAAAQImiSMKqUtfLEqtKwPIJYd2OGxCrqbsssdNZ6Pzg9ryZ9kHx+anpfX6+dbb5Q7dc0fbY6w79L8O0EsC0KEq+spNv5Je/yEtT+IJLolvb2PW4tGuXpMxU9CHpspnc1+rW9nPLZ2SXy0BjkYQBAAAAQIkanYSl8olY3caGlYXjAkxWPhGLfmxYv5NtaHEcxuIZ49xCqQUJWDpOw+fnW2eOX3fI8yVJH/7Jv/TXTsZcANOpaBr59OFsnUkTrjTZWsglUTO5RZlz41N9V5J6aW6uNS51iTTpSrdblHaRgkEkYQAAAABQKpKwjNgTsVhmQ2QsGDBZ0SdiPcZfLN7sMC10bvJDm03HaYSf6dnpNAHLL3qakSZi6jUBY25hVQA1l0vAlsx42GnJi+XLF39XSNezL1kWvhKnP0MtSsd9LabyC4t1Kt1+WtfSduTq1cAzuaIRSMIAAAAAoEQkYQCA4fQah5FVNCNZKjc+o9NCzIVnk5cs1sxZZ6AJliy4nN6fT9iz6X1rbFhYDyytH60UKyRej7WvS9iqUe6LCX1eLl3Lp23tD1Knmm6kJMzM3mxm3zez683s02a2yswONbOrzWyrmV1oZivG1VgA6IRaBCAW1CMA/Rg6CTOzAyS9QdIR7r7TzC6SdKKkF0l6v7tfYGZnSzpZ0kfG0tqSxDY2LJaxYECMprkWRTc2rNc4jNbz0nESmfN8+VkPc1pnjPNnkhlLgRqZ5noUldwMhjabH2yamwlxdnYx6ZppXw9syXjT3WHtr7Au4ZKa5L74Gs+t/9UvUjBo9DFhyyTtYWbLJK2WdIekF0i6ODx+nqQTRtwGAPRCLQIQC+oRgJ6GTsLc/XYze5+kWyXtlPRVSddKut/d0wUUtks6YORWViSfiFUlTcBIxIClmlCL8olY1VpnlwuSsI5rfhXNqJieZe41m1indXU4m4zINKEexSCtQbZiRbidyxRaSVnm/vQ1+Vq0LHlOaxbEVsrl4Ueuzix4cQLWa/0vahYyhk7CzGxfSS+VdKikdZL2lHT8AK8/xcyuMbNr7vlZl4GLANDFOGvRffeygCaA4Y1Sj7K1aLd2TbCVAGIwyuyIvyLpx+5+jySZ2eckbZC0j5ktC2d8DpR0e6cXu/s5ks6RpKOfsaoWpwaqHhsGoKOx1aKnH7miFrWoqrFhrbPPy8P/OorSrayQhrXW5knPBO/e3X47f2bZ29fhacPZZMRr6HqUrUV721o+5F2kyZetWpX8XBbS+aLaYLa4/lcqTbp27kxup+uAhdkQvSClly8srVPAEEYZE3arpGPMbLUl/3c9TtIPJH1D0svDc06S9IXRmggAXVGLAMSCegSgL6OMCbvazC6W9B1Jc5K+q+QMzpckXWBm7w73fWwcDa1C0ViwqhIxxoYBSzWhFhWNBatstsT8mK90/Zyi1EtdErBu6+hI7WeaScAQuSbUo0qltSdN5ZfNtt1u1ZPWrIihRs0vLF2LcFe45HN3wXpg3WZA7DcBo2ahi5EWa3b3MySdkbv7R5KePcr7AsAgqEUAYkE9AtCPkTphAIDpN6vkbK6FMRW2amX7E/JpVvaMcXpWOR1vkUvAes4uxplkAKl0DcJQg3yvPdsfTtf2ao01zdSP3JgvPb677bYXpPIDz4CY3y5QgE7YCDauO6qSSTq4LBFA1qnrN0z0ksR08HA6HfSSxU5TrS8r6YD2hcUvPvPhi0u/UzvzJQZATmtyoNWrJUkLK5YnD6RFKtf5ssyCy77r8dbvUnbijVztyZ8g6lSbiiYlom5hAKMu1gwAAAAAGABJWI2RiAEow/Jw0tdW75H8sjIkYukEHDsfS27np3iemyse3M7UzgD6FWqNheRr/klPSH7undQiD48vvz9crrgrudRQO5PJN3znzsU0PpeAte4fpC0kXhgDkjAAAAAAKBFJWAdFU9N3e26VCziXlYil+zjI8QEwvKKp6bs9d5xjw5aHCTlWpOMfwsQcvrzgfx3pGeUwDb0WvHCw+xIDnFlO93GQ4wMgcl0Wf7dlSQKWTsgxvyqpQXN7tNei5elYsJCE+WNJSu+755ZODtRtCvrM/aRemBSSMAAAAAAoEUnYmEwiHeo3XUsTsOztcaZh+XaQiAHx6jsdSs86p1M+Z9Ityy3G/NmbrkhupzORpc9NZx4LFqd6TsdaZFKwMcx+mE/5SMSAGsrXnnTGw7Cwsu0Rxp76Qit9by3OHMalzu2V1KK5PZLXLNuZqy/pTIi7i8enphiniqqQhAEAAABAiUjCIpYmTfmkK49ZEQEUyp11bt2dnlkOqVY665hsppV4pYnYbzzv5clj4S3s0TAbYjiD3JodMYwFayVg2TPLjKsAmqkg+UrXGUzXH0xTLtszWQPMZ0y+56rwe/LauSe0LxS/6t4k8bK5pL7MPPBI8vxdYVbExxfXBus78aJWoSQkYQAAAABQIpKwiOVnO6xqLFbRDJCxjw3LtzfWdgITkZtpzGYKxoCl6++sSs44a3a2NebLW+lYeM5jydnlv7/yIknSq47YmDwvTb7C2ep0W97nxIj9KpoBMvaxYfn2xtpOYKyKxn4tz43zCrXHQv1Y2DskYctntXuvJCWb2zN5rocQbeV9Seq+4pa7w3uFTCEdC5Ym/2nqNtc+frVNmnx1mZ0RmASSMAAAAAAoEUlYRtVJSX7sV9FYr9gTqFjEsIYbMIyxJiXpGeH0ZysRC+lWOFOczmhoy5YtJmDLwlnkdLbDh5PxFg8sJBHXh753qSTpfx32gvb3zmJ8xUTWcAPqopXC52tPmPkwnRWxNfvqQlJvFpYv19zqpAbNr0heMxPGfi2/48HkOffe1/Ya5dO2bjO05lGrUDKSMAAAAAAoEUlYJLqt7VWU5JSdiNU1ecsnYnXdD6AvPdbgScdttX7mzc/L0rV10ve69wFJ0tnfvUSS9Ji3J14f2vp1SdLr00Ss1ZaZ8Q8MU33HVOUTsbruB9BVfkbWtAalsyC2kvbwFXR5+9hThcBqZtecZh8L41PDe6zZmtQiv/X25KlhFsTWplszL+bq3Ozs0nXCSL5QMZIwAAAAAChRo5OwKhORfsd/YfxIxBCbsSQivRKw1u32NXpaZ6vD2WFfMFk4Q5yuBzb/YDL+YnfBieN5hdkQ53aPvh8NQiKGqZSvQbkEzNLka+WK8PxQP8IYVEvHd81ZawzYqp+GWQ93JLMhLjweak0uzfIwC6I/8mhoSnjvBScBQ3RIwgAAAACgRFEkYTddt7otlZjkbHZVpR/DJF/9HodxHK8mpELMlohebv3emrZUYpKz2Y07/WglXOnZ53S8Rbp212xulsRU6+xwSMbm5uSP7EzuejQ5m/yhmy6XtJh4Fdn0k2+23Z6V93xNXhNSIWZLxNTJrLE1s2plclc6++Fea9qfGxIwn22vRa2xqGnNmpvXirkwa2sYlzr/0EPJkxd6jDVNk/30adm6l7aVRAwVi6ITlpfvENSxk1Hl5YaD7Gt6bOt4jIdVl3aievkOwTi+NI93+vlMBye9BCg39XzHaeOlxc5XOlh9YXExU/fkUh8Pl/wM2pFKve6Q5/f9RSc9ttEd4wmqSzuBQvnLoGds8b50mvjlua+aaU1IL3uem2+/nS64LEnhhNDCg0nny+f7nOgntwCzzZh8of3SazpjqBqXIwIAAABAiaJMwvKGuVSxzsnXsKnUMPs8zGuY2AJNNcylihNNOzID4FuLk1pBahUSL/eQeC0UDFJfWJCH+9Kp5we+pPCQ52Xa2N/Z5mGOExNbAHFI64+tWCFbvUfye/7ffno7JF/p5Yfpgsq+kE/n5xcfy01F33/DspdhF6RoJGKoCEkYAAAAAJSoFklYVtF4sSpSmWz6Nc4xX7FPIEECBhSPFysllZlJxnvN7p0MePf5hSVPSdMs7W4fb9F6PD+2osNYi9cd8nxJSyfciAUJGFCRdKxVmH5+dv/9kvvn5pcmSumYr4V0GYxc4jWXS8Tml9YsXxgwpSq6IgCICEkYAAAAAJSodklYXpUJWFkzHsaU/gHorJRUJjPTl6TFcV6PP770ub3OHLcWZ/a29+y2qGnf6V/2JDTjLIDpk1uQOeUPPtRaJiOfrqcJV/qafOLVejxdvHl+IfOcARdazi3F0desivn0jNqFCSMJAwAAAIAS1T4Jq8KkErCiMWC97icRA5olTa8Wdj6W3O5wlrct2er8Ju0307dwL5z5sdf9rUSMM8hAI6S1x++9X5K00GEWw1aylSZe6RiwtDblatFC9v5ha0nuPTu+D8kXKtYzCTOzj5vZ3WZ2fea+tWZ2mZndHH7uG+43M/trM9tqZteZ2bMm2XgAzUI9AhADahGAUfWThJ0r6YOSPpm57zRJl7v7mWZ2Wrj9dkkvlHR4+O85kj4SfqKHUWZC7Oe1pGWYEueKerQ4nmu+/XbbU3oNgSg469vv+mfDvpYZDTElzlUTa1E+PQpJWLdUvjVGLJ++51P6Qcd9ddPPe+TXLwNK1jMJc/d/lnRv7u6XSjov/H6epBMy93/SE1dJ2sfM9h9TWwE0HPUIQAyoRQBGNeyYsP3c/Y7w+52SwgIROkDSbZnnbQ/33SG0KXsNsF7bIylDjTWnHuXP7naLu9Kzuz3OCI+SfA2j1/ZIylBj01+LWulRuNlKvoprUWFiH8sYrFjagcYZeXZET0ZaDvwJNrNTzOwaM7tmt5YO5ASAQQ1Tj6hFAMaNWgSgl2GTsLvMbH93vyNE6neH+2+XdFDmeQeG+5Zw93MknSNJe9vaqT8NUXbyhUXMIjn1RqpHU1uLJjDmC6MpXFcN06I5tajDONTk/k7NHuNYL2CKDJuEXSLppPD7SZK+kLn/d8NMQMdIeiATzQPAJFCPAMSAWgSgbz2TMDP7tKRjJT3JzLZLOkPSmZIuMrOTJW2T9Irw9EslvUjSVkmPSnrNuBtct1SjLglY3Y5rN4Out9bNNByPaRJTPapbqlGXBKxux7WbQddb62Yajsc0iakWVWKQVIsEDOioZyfM3V9V8NBxHZ7rkl4/aqMAoBPqEYAYUIsAjGrYMWGlGzSpmaZkp0z5tKgOx2+SaSOfI+QNmtRMU7JTpnxaVIfjN8m0kc8RAEyXqDth2S/X+S/BsU+5XpfLEHvptB9VHtuqjiudsWbLfrnOfwmOfcr1ulyG2Eun/ajy2FZ1XOmMAcB0GHmKegAAAABA/6JMwkZJO6pOKqYlAeumzEsWYzue05yITfO+DWuUtKPqpGJaErBuyrxkMbbjOc2J2DTvGwCkSMIAAAAAoERRJGFPOfJRbd68pfDx7Jn5omSEs/fVmcTfJLYELK8uqVG3cZX9vGaQ102Dg3/5YW36UnHikT0zX5SMcPa+OpP4m8SWgOXVJTXqNq6yn9cM8joAqAOSMAAAAAAoURRJWJF+zsDHcpY+9uRmHHod6/wxGEcKE7th9rEMnY7jsOldXVK/SernDHwsZ+ljT27Godexzh+DcaQwsRtmH8vQ6TgOm97VJfUDgH6QhAEAAABAiaJMwjqdcW/yOJW6GORvMo3pSuz7VNSuftPHWFO/Sep0xp1xKvEb5G8yjelK7PtU1K5+08dYUz8AGARJGAAAAACUKMokrJtYz8Cn7arbmKaq5P+O03TcYkjEJr3tGPaxarGegU/bVbcxTVXJ/x2n6bjFkIhNetsx7CMADIMkDAAAAABKFFUS1m3MSpPPuE+zaUrA8pqQFuX/frP7V9OOces2ZoUz7tNpmhKwvCakRfm/3y8dXFFDAKBPJGEAAAAAUKIoOmE3Xbe6a1owzUkCpt/mHVumOvGbJrd+b03XtGCakwRMv03brpzqxA8A6iSKThgAAAAANAWdsDHbuO4okjvUCp/Z6XTq+g0kd6gVPrMAmoROGAAAAACUKKrZERG3onFNpCgAylQ0rokUBQBQF3TCJmQaF2+mszWcuhy3URbQXnzt1nE1B2MyjYs309kaTl2O2ygLaC++9uIxtggAxo/LEQEAAACgRCRhADrqlIzVJdUDMD06JWN1SfUAoAhJGAAAAACUiE4YgL6QggGIASkYgGlAJwwAAAAASkQnbMJYCBdADFgIFwCAeNAJAwAAAIASMTsieiLJGw7HDRgvkrzhcNwAID49kzAz+7iZ3W1m12fue6+Z/dDMrjOzfzCzfTKPnW5mW83sRjPbOKF2A2gYahGAWFCPAIyqn8sRz5V0fO6+yyQ93d2PlHSTpNMlycyOkHSipKeF13zYzGbH1loATXauqEUA4nCuqEcARtCzE+bu/yzp3tx9X3X3uXDzKkkHht9fKukCd9/l7j+WtFXSs8fYXgANRS0CEAvqEYBRjWNM2O9JujD8foCSwpPaHu5rvHR80OYdWyptxzDq2GY0ErWoD+n4oE3brqy4JYOrY5vRWNQjAF2N1Akzs3dKmpN0/hCvPUXSKZK0SqtHaQaAhqMWAYjFsPWIWgQ0y9CdMDN7taQXSzrO3T3cfbukgzJPOzDct4S7nyPpHEna29Z6p+cAQC/UIgCxGKUeUYuAZhlqnTAzO17S2yS9xN0fzTx0iaQTzWylmR0q6XBJ/zZ6MwFgKWoRgFhQjwAMomcSZmaflnSspCeZ2XZJZyiZ8WelpMvMTJKucvfXuvv3zewiST9QEsW/3t3nJ9X4Oqrz2DD0h/XBJoNaNF51HhuG/rA+2ORQjwCMqmcnzN1f1eHuj3V5/p9J+rNRGgUAedQiALGgHgEY1VCXIwKj2rjuKBIjAJU7df0GEiMAQOnGMUU90Dc6XgBiQMcLAFAlkjAAAAAAKBGdsIrEcjleLO0AUI1YLseLpR0AAJSBThgAAAAAlIgxYQ2VT7/yt8c9hX5R2saU/UCz5dOv/O1xT6FflLYxZT8AoEwkYQAAAABQIpKwisU6HmucCVU/+zgNiVisf0ugH7GOxxpnQtXPPk5DIhbr3xIAsIgkDAAAAABKZO5edRtkZvdIekTST6tuSwdPEu0aBO0azLS1a727P3ncjSkLtWgotGswtGsw1KL4TNtnZdJo12CmrV2FtSiKTpgkmdk17n501e3Io12DoV2DoV3xiXXfaddgaNdgaFd8Yt132jUY2jWYJrWLyxEBAAAAoER0wgAAAACgRDF1ws6pugEFaNdgaNdgaFd8Yt132jUY2jUY2hWfWPeddg2Gdg2mMe2KZkwYAAAAADRBTEkYAAAAAEy9KDphZna8md1oZlvN7LSK2nCQmX3DzH5gZt83szeG+9ea2WVmdnP4uW9F7Zs1s++a2RfD7UPN7OpwzC40sxUVtGkfM7vYzH5oZjeY2XNjOF5m9ubwN7zezD5tZquqOF5m9nEzu9vMrs/c1/H4WOKvQ/uuM7Nnldyu94a/43Vm9g9mtk/msdNDu240s42TalcMYqhFoR3R1iNq0UDtiqIWhbZEV4+oRcWoRX21LbpaFNoRXT2iFg3VponXoso7YWY2K+lDkl4o6QhJrzKzIypoypykt7j7EZKOkfT60I7TJF3u7odLujzcrsIbJd2Quf0eSe9398Mk3Sfp5Ara9AFJX3H3X5T0jNC+So+XmR0g6Q2Sjnb3p0ualXSiqjle50o6Pndf0fF5oaTDw3+nSPpIye26TNLT3f1ISTdJOl2Swr+BEyU9Lbzmw+Hf7NSJqBZJcdcjalEfIqtFUpz1qFObqEXUon7FWIukyOoRtWjoNk2+Frl7pf9Jeq6kzZnbp0s6PYJ2fUHSr0q6UdL+4b79Jd1YQVsOVPKhfIGkL0oyJQvGLet0DEtq0xMk/VhhXGHm/kqPl6QDJN0maa2kZeF4bazqeEk6RNL1vY6PpI9KelWn55XRrtxj/13S+eH3tn+PkjZLem6Zf9MSPztR1qLQlijqEbVooHZFVYvC9qKrR9SijvtNLerdjuhqUdhudPWIWjRcm3KPTaQWVZ6EafHDkdoe7quMmR0i6ZmSrpa0n7vfER66U9J+FTTpLElvk7QQbj9R0v3uPhduV3HMDpV0j6RPhMsB/tbM9lTFx8vdb5f0Pkm3SrpD0gOSrlX1xytVdHxi+nfwe5K+HH6PqV2TFuW+RlaPzhK1qC81qEVS/PWIWpSIYl+pRX2Jrh5Ri8ZiIrUohk5YVMxsjaTPSnqTuz+YfcyTLm+p00ma2Ysl3e3u15a53T4sk/QsSR9x92dKekS5eL2i47WvpJcqKYTrJO2ppRFzFKo4Pr2Y2TuVXH5yftVtQVz1iFo0mDrVIim+ekQtigu1qG/R1SNq0WgmWYti6ITdLumgzO0Dw32lM7PlSorM+e7+uXD3XWa2f3h8f0l3l9ysDZJeYmY/kXSBkuj9A5L2MbNl4TlVHLPtkra7+9Xh9sVKCk/Vx+tXJP3Y3e9x992SPqfkGFZ9vFJFx6fyfwdm9mpJL5b0W6EIRtGuEkW1rxHWI2rRYGKvRVKk9YhaFNe+UosGEmM9ohYNadK1KIZO2LclHR5maVmhZLDbJWU3wsxM0sck3eDuf5V56BJJJ4XfT1JyPXRp3P10dz/Q3Q9Rcmy+7u6/Jekbkl5eYbvulHSbmT013HWcpB+o4uOlJG4/xsxWh79p2q5Kj1dG0fG5RNLvhpmAjpH0QCaanzgzO17JpR0vcfdHc+090cxWmtmhSgbH/ltZ7SpZFLVIirMeUYsGFnstkiKsR9QiSdSirmKtRaFtMdYjatEQSqlF4xjMNup/kl6kZOaRWyS9s6I2PE9J/HmdpC3hvxcpuc74ckk3S/qapLUVHqdjJX0x/P7z4Y++VdJnJK2soD1HSbomHLPPS9o3huMl6f9I+qGk6yX9naSVVRwvSZ9Wcv31biVnx04uOj5KBhV/KPwb+J6SWYzKbNdWJdc4p5/9szPPf2do142SXlj237Pkz07ltSi0I+p6RC3qu11R1KLQlujqEbWo67GhFvXXvqhqUWhHdPWIWjRUmyZeiyy8GQAAAACgBDFcjggAAAAAjUEnDAAAAABKRCcMAAAAAEpEJwwAAAAASkQnDAAAAABKRCcMAAAAAEpEJwwAAAAASkQnDAAAAABK9P8BOCyOWrW1Nh0AAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "for i in range(10):\n", " plot_predicted_data(generator, collected_routes, \"Test\", i)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "predicted = predicted_test\n", "seed = 1\n", "\n", "plt.figure(figsize=(17.5, 25))\n", "\n", "plt.subplot(1, 4, 1)\n", "plt.imshow(collected_routes[seed, :, :, 0] * 2 + collected_routes[seed, :, :, 2], interpolation=\"nearest\")\n", "plt.subplot(1, 4, 2)\n", "plt.imshow(collected_routes[seed, :, :, 0] * 2 + predicted[seed, :, :] / predicted[seed, :, :].sum() * 100, interpolation=\"nearest\")\n", "plt.subplot(1, 4, 3)\n", "plt.imshow(predicted[seed, :, :], interpolation=\"nearest\")\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "# tf.keras.utils.plot_model(generator)" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "## Ausblick\n", "Minimaldistanz ist or verknüpft nicht and verknüpft." ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "## Literaturverzeichnis\n", "\n", "[1] Jang, Hoyun and Lee, Inwon and Seo, Hyoungseock: *Effectiveness of CFRP rudder aspect ratio for scale model catamaran racing yacht test*, 2017\n", "\n", "[2] Aurélien Géron: *Praxiseinstig Machinen Learning mit Scikit-Learn, Keras uind TensorFlow*, 2020, O.Reilly Verlag\n", "\n", "[3] Jun-Yan Zhu: *Image-to-Image Translation with Conditional Adversarial Networks*, 2018, Available: https://arxiv.org/abs/1611.07004\n", "\n", "[4] Tensorflow: *pix2pix: Image-to-image translation with a conditional GAN* Available: https://github.com/tensorflow/docs/blob/master/site/en/tutorials/generative/pix2pix.ipynb Commit: df4485e052523e0f852e83cea30ad319808bd97b\n", "\n", "[5] Keras: *Keras* Available: https://keras.io/" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "plt.imshow(predicted[seed, :, :] / predicted[seed, :, :].sum(), interpolation=\"nearest\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "@article{article,\n", "author = {Jang, Hoyun and Lee, Inwon and Seo, Hyoungseock},\n", "year = {2017},\n", "month = {09},\n", "pages = {4109-4117},\n", "title = {Effectiveness of CFRP rudder aspect ratio for scale model catamaran racing yacht test},\n", "volume = {31},\n", "journal = {Journal of Mechanical Science and Technology},\n", "doi = {10.1007/s12206-017-0807-8}\n", "}" ] }, { "cell_type": "markdown", "metadata": { "pycharm": { "name": "#%% md\n" } }, "source": [ "Ich würde auch zu 1. tendieren, stimme Ihnen aber zu, dass das Thema sehr umfangreich ist. Könnte man sich nicht einen Teilbereich herauspicken? Ich verstehe nicht viel vom Segeln, daher lassen Sie mich kurz zusammenfassen, was Sie vorhaben: - Sie generieren Trainingsdaten mit dem existierenden aber langsamen GD Algorithmus. Ich nehme an, es handelt sich um lokale Routen in einem relativ kleinen Kartenausschnitt. Lässt es die Laufzeit zu, dass Sie eine große Menge an Routen berechnen. - Sie haben dann eine Karte und als Ausgabe eine Liste der Wendepunkte - Warum wollen Sie daraus eine Heatmap berechnen? Diesen Schritt habe ich noch nicht verstanden - Wenn Sie aus einer Karte eine Heatmap trainieren wollen und dafür genügend Beispiele haben, könnnten GANs hilfreich sein: https://arxiv.org/abs/1611.07004 Ich würde Ihnen raten, das Problem möglichst so zu reduzieren, dass es im Rahmen des Moduls noch handhabbar bleibt. Alles Weitere kann man sich auch für spätere Arbeiten aufbewahren. Das 2. Thema ist auch ok. Aber vielleicht nicht ganz so spannend. Ich überlasse Ihnen die Entscheidung. Freundliche Grüße Heiner Giefers" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.5" }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": false } }, "nbformat": 4, "nbformat_minor": 1 }