57 lines
3.2 KiB
Markdown
57 lines
3.2 KiB
Markdown
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# Final Report - Intelligent Garbage Truck
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## General information
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This is the final report for our **Intelligent Garbage Truck** AI program. Our program works as following - a **20x20** grid is generated with 20 random dumpsters, the garbage dump and our garbage truck(the agent). All the time we make sure that while they randomly generate they do not overlap each other.
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After that our garbage truck chooses the closest dumpsters to him and collects trah whilst making sure the house is our client. After he collected all trask (aka visited all dumpsters) he immediately goes to the garabage dump and sorts the trash.
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The dumpsters have a predeterminded colour and type but still can contain incorrectly sorted trash.
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## How to run our program
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In order to succesfully open our program one needs to make sure he has the following libraries installed:
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```
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import pygame
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import random
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import numpy as np
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import time
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import collections
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from sklearn.datasets import load_digits
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import sys
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import os
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import random
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import shutil
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from keras.models import Sequential
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from keras.layers import Conv2D, Flatten, MaxPooling2D, Dense
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from keras.preprocessing import image
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from keras.preprocessing.image import ImageDataGenerator
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#import matplotlib.pyplot as plt #optionla for seeing garbage
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import cv2
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import mahotas
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from sklearn.preprocessing import LabelEncoder
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from sklearn.preprocessing import MinMaxScaler
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from sklearn.ensemble import RandomForestClassifier
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from sklearn.datasets import load_digits
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import pylab as pl
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from sklearn.model_selection import train_test_split
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from sklearn.preprocessing import StandardScaler
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import os.path
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import csv
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```
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Also two files need to be unpacked before running: "Garbage classification.rar" and "ClassificationGarbage.rar". Both in the same place where they are.
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After that to run our program the command is :
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```
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python Main.py
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```
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## Implementation of subprojects
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Since there are three people in our group we have created and combined three subprojects with our main program. Two use **Neural Networks** and one uses **Random Forest Classifier**.
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### First subproject
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The first subprojects was created by Patryk Krawiec (the raport can be found [here](https://git.wmi.amu.edu.pl/s444517/AI2020_Project/src/master/Report_Patryk_Krawiec.md)).
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### Second subproject
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The first subprojects was created by Kamila Bobkowska (the raport can be found [here](https://git.wmi.amu.edu.pl/s444517/AI2020_Project/src/master/Report_Kamila_Bobkowska.md)). This project used **Convolutional Neural Networks** to detect what kind of trash is in the dumpster and sorts it accordingly. It was mainly implemented to to the class `Garbagetruck.py` and `dumpster.py` . It used photos of garbage to determine whether it was sorted correctly. The implementation. Along with implementing CNNs the person created a function that assigns trash to dumspters (between 1 to 3 trash correctly sorted and 0 to 2 incorrectly sorted trash). The data set used was from [kaggle](https://www.kaggle.com/asdasdasasdas/garbage-classification)
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### Thrid subproject
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The first subprojects was created by Klaudia Przybylska (the raport can be found [here](https://git.wmi.amu.edu.pl/s444517/AI2020_Project/src/master/Report_Klaudia_Przybylska.md)).
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