.idea/.gitignore

@@ -1,3 +0,0 @@
-# Default ignored files
-/shelf/
-/workspace.xml

.idea/.name

@@ -1 +0,0 @@
-astar.py

.idea/SI_projekt_smieciarka.iml

@@ -1,8 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<module type="PYTHON_MODULE" version="4">
-  <component name="NewModuleRootManager">
-    <content url="file://$MODULE_DIR$" />
-    <orderEntry type="jdk" jdkName="Python 3.9" jdkType="Python SDK" />
-    <orderEntry type="sourceFolder" forTests="false" />
-  </component>
-</module>

.idea/inspectionProfiles/Project_Default.xml

@@ -1,29 +0,0 @@
-<component name="InspectionProjectProfileManager">
-  <profile version="1.0">
-    <option name="myName" value="Project Default" />
-    <inspection_tool class="PyPackageRequirementsInspection" enabled="true" level="WARNING" enabled_by_default="true">
-      <option name="ignoredPackages">
-        <value>
-          <list size="16">
-            <item index="0" class="java.lang.String" itemvalue="scipy" />
-            <item index="1" class="java.lang.String" itemvalue="pygame" />
-            <item index="2" class="java.lang.String" itemvalue="opencv-python" />
-            <item index="3" class="java.lang.String" itemvalue="scikit-learn" />
-            <item index="4" class="java.lang.String" itemvalue="h5py" />
-            <item index="5" class="java.lang.String" itemvalue="kiwisolver" />
-            <item index="6" class="java.lang.String" itemvalue="torch" />
-            <item index="7" class="java.lang.String" itemvalue="numpy" />
-            <item index="8" class="java.lang.String" itemvalue="torchvision" />
-            <item index="9" class="java.lang.String" itemvalue="mahotas" />
-            <item index="10" class="java.lang.String" itemvalue="tensorflow" />
-            <item index="11" class="java.lang.String" itemvalue="PyQt5" />
-            <item index="12" class="java.lang.String" itemvalue="matplotlib" />
-            <item index="13" class="java.lang.String" itemvalue="grpcio" />
-            <item index="14" class="java.lang.String" itemvalue="sip" />
-            <item index="15" class="java.lang.String" itemvalue="Pillow" />
-          </list>
-        </value>
-      </option>
-    </inspection_tool>
-  </profile>
-</component>

.idea/inspectionProfiles/profiles_settings.xml

@@ -1,6 +0,0 @@
-<component name="InspectionProjectProfileManager">
-  <settings>
-    <option name="USE_PROJECT_PROFILE" value="false" />
-    <version value="1.0" />
-  </settings>
-</component>

.idea/misc.xml

@@ -1,4 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.9" project-jdk-type="Python SDK" />
-</project>

.idea/modules.xml

@@ -1,8 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="ProjectModuleManager">
-    <modules>
-      <module fileurl="file://$PROJECT_DIR$/.idea/SI_projekt_smieciarka.iml" filepath="$PROJECT_DIR$/.idea/SI_projekt_smieciarka.iml" />
-    </modules>
-  </component>
-</project>

.idea/vcs.xml

@@ -1,6 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<project version="4">
-  <component name="VcsDirectoryMappings">
-    <mapping directory="$PROJECT_DIR$" vcs="Git" />
-  </component>
-</project>

README.md

@@ -1 +0,0 @@
-<h1>Projekt SI - Smieciarka</h1>

TSP.py

@@ -1,115 +0,0 @@
-
-from ortools.constraint_solver import routing_enums_pb2
-from ortools.constraint_solver import pywrapcp
-from bfs import distance, bfs
-from house import create_houses
-
-
-def create_data_model(multi_trash, truck):
-    data = {}
-    graphrow = []
-    graph = []
-    lista = multi_trash
-    for i in range(8):
-        list1=multi_trash
-        if (i == 0):
-            pos = truck.pos
-        else:
-            pos = lista[i-1].pos
-        for j in range(8):
-            if(j==0):
-                endpos = truck.pos
-            else:
-                endpos = list1[j-1].pos
-            if(i==j):
-                graphrow.append(0)
-            else:
-                dist=distance(pos, endpos)
-                graphrow.append(dist)
-
-        graph.append(graphrow.copy())
-        graphrow.clear()
-    data['distance_matrix'] = graph.copy()
-    data['num_vehicles'] = 1
-    data['depot'] = 0
-    print(data['distance_matrix'])
-    return data
-
-
-def print_solution(manager, routing, solution):
-    index = routing.Start(0)
-    plan_output = []
-    route_distance = 0
-    while not routing.IsEnd(index):
-        plan_output.append(manager.IndexToNode(index))
-        previous_index = index
-        index = solution.Value(routing.NextVar(index))
-        route_distance += routing.GetArcCostForVehicle(previous_index, index, 0)
-    plan_output.append(manager.IndexToNode(index))
-    print(plan_output)
-    return plan_output
-
-
-def tsp(x, y):
-    data = create_data_model(x, y)
-
-    manager = pywrapcp.RoutingIndexManager(len(data['distance_matrix']),
-                                           data['num_vehicles'], data['depot'])
-
-    routing = pywrapcp.RoutingModel(manager)
-
-
-    def distance_callback(from_index, to_index):
-        from_node = manager.IndexToNode(from_index)
-        to_node = manager.IndexToNode(to_index)
-        return data['distance_matrix'][from_node][to_node]
-
-    transit_callback_index = routing.RegisterTransitCallback(distance_callback)
-
-    routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)
-
-    #search_parameters = pywrapcp.DefaultRoutingSearchParameters()
-   # search_parameters.first_solution_strategy = (
-       # routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC)
-    search_parameters = pywrapcp.DefaultRoutingSearchParameters()
-    search_parameters.local_search_metaheuristic = (
-        routing_enums_pb2.LocalSearchMetaheuristic.GUIDED_LOCAL_SEARCH)
-    search_parameters.time_limit.seconds = 30
-    search_parameters.log_search = True
-
-    solution = routing.SolveWithParameters(search_parameters)
-
-    if solution:
-        sol = print_solution(manager, routing, solution)
-
-    return sol
-
-def tspmove(order, truck, Ltrash):
-    houses = create_houses(40)
-    path = []
-    endpos=truck.pos
-    for i in range(1, 8):
-        startpos = endpos
-        endpos = Ltrash[order[i]-1].pos
-        #print(i,startpos,endpos)
-        x = bfs(startpos, truck.dir_control, endpos, houses)
-        #print("$$$$",x)
-        for i in x:
-            if(i==97):
-                truck.rotate(-1)
-            elif(i==100):
-                truck.rotate(1)
-        path.append(x)
-    x = bfs(endpos, truck.dir_control, truck.pos, houses)
-    for i in x:
-        if (i == 97):
-            truck.rotate(-1)
-        elif (i == 100):
-            truck.rotate(1)
-    path.append(x)
-    #print("###############################\n", path)
-    truck.dir_control=0
-    truck.direction = [1, 0]
-    return path
-
-

astar.py

@@ -1,150 +0,0 @@
-from truck import Truck
-
-class Node():
-    def __init__(self, parent=None, position=None):
-        self.parent = parent
-        self.position = position
-
-        self.g = 0
-        self.h = 0
-        self.f = 0
-
-    def __eq__(self, other):
-        return self.position == other.position
-
-
-def astar(maze, start, end):
-    start_node = Node(position=start)
-    end_node = Node(position=end)
-    x=0
-    open_list = []
-    closed_list = []
-
-    open_list.append(start_node)
-
-    while len(open_list) > 0:
-
-        current_node = open_list[0]
-        current_index = 0
-        for index, item in enumerate(open_list):
-            if item.f < current_node.f:
-                current_node = item
-                current_index = index
-
-        open_list.pop(current_index)
-        closed_list.append(current_node)
-
-        if current_node == end_node:
-            path = []
-
-            current = current_node
-            while current is not None:
-                path.append(current.position)
-                if (maze[current.position[0]][current.position[1]] == 1):
-                    x = x + 1
-                if (maze[current.position[0]][current.position[1]] == 2):
-                    x = x + 3
-                if (maze[current.position[0]][current.position[1]] == 6):
-                    x = x + 20
-                if (maze[current.position[0]][current.position[1]] == 7):
-                    x = x + 5
-                if (maze[current.position[0]][current.position[1]] == 8):
-                    x = x + 1
-
-                current = current.parent
-            return path[::-1]
-            #return x
-
-        children = []
-        for new_position in [(0, -1), (0, 1), (-1, 0), (1, 0)]:
-
-            node_position = (
-                current_node.position[0] + new_position[0], current_node.position[1] + new_position[1])
-
-            if node_position[0] > (len(maze) - 1) or node_position[0] < 0 or node_position[1] > (len(maze[len(maze)-1]) - 1) or node_position[1] < 0:
-                continue
-
-            if Node(current_node, node_position) in closed_list:
-                continue
-
-            if maze[node_position[0]][node_position[1]] == 9:
-                continue
-
-            new_node = Node(current_node, node_position)
-
-            children.append(new_node)
-
-        for child in children:
-
-            for closed_child in closed_list:
-                if child == closed_child:
-                    continue
-
-            if(maze[child.position[0]][child.position[1]]==1):
-                child.g = 1
-            if(maze[child.position[0]][child.position[1]]==2):
-                child.g = 3
-            if(maze[child.position[0]][child.position[1]]==6):
-                child.g = 20
-            if(maze[child.position[0]][child.position[1]]==7):
-                child.g = 5
-            if(maze[child.position[0]][child.position[1]]==8):
-                child.g = 1
-            child.h = ((child.position[0] - end_node.position[0]) **
-                       2) + ((child.position[1] - end_node.position[1]) ** 2)
-            child.f = child.g + child.h
-
-            for open_node in open_list:
-                if child == open_node and child.g > open_node.g:
-                    continue
-
-            open_list.append(child)
-
-
-def main():
-
-    maze = [[9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9],
-            [9, 9, 9, 9, 9, 1, 1, 9, 9, 9, 1, 1, 1, 9, 9, 9, 1,
-                1, 9, 9, 1, 1, 1, 9, 9, 1, 1, 9, 1, 1, 9, 9],
-            [9, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 9, 1, 1,
-                8, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 9],
-            [9, 1, 1, 1, 2, 1, 1, 6, 1, 1, 1, 1, 1, 1, 1, 1, 9,
-             1, 0, 1, 7, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 9],
-            [9, 1, 1, 1, 1, 9, 9, 9, 9, 9, 9, 1, 1, 1, 1, 9, 9,
-             9, 9, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9, 9, 9],
-            [9, 9, 9, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 2, 1,
-             1, 1, 1, 9, 6, 6, 9, 1, 1, 2, 1, 1, 9, 1, 9],
-            [9, 1, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1,
-             1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9],
-            [9, 1, 1, 1, 9, 9, 9, 9, 9, 1, 1, 1, 1, 1, 9, 9, 9,
-             9, 9, 9, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9, 9],
-            [9, 1, 1, 1, 1, 1, 1, 9, 9, 9, 9, 9, 9, 1, 1, 1, 1,
-             1, 9, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 9],
-            [9, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 9, 1, 1, 1, 9,
-             9, 9, 7, 6, 9, 9, 9, 9, 6, 2, 1, 9, 9, 9, 9],
-            [9, 1, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1,
-             1, 9, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 9],
-            [9, 1, 1, 1, 9, 9, 9, 9, 9, 1, 1, 9, 9, 9, 1, 1, 9,
-             9, 9, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 9],
-            [9, 1, 1, 1, 1, 1, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
-             1, 1, 2, 1, 1, 9, 9, 1, 9, 1, 1, 7, 1, 1, 9],
-            [9, 1, 1, 1, 1, 1, 0, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1,
-             1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9],
-            [9, 1, 1, 9, 1, 1, 9, 9, 9, 1, 9, 1, 1, 1, 9, 9, 9,
-             1, 1, 1, 1, 1, 9, 1, 1, 1, 9, 9, 1, 1, 1, 9],
-            [9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 9, 1, 1, 2, 1,
-             1, 1, 1, 9, 9, 9, 9, 1, 1, 1, 2, 1, 1, 9, 9],
-            [9, 1, 1, 1, 9, 9, 9, 9, 1, 1, 1, 1, 1, 1, 9, 1, 1,
-             1, 9, 1, 1, 9, 9, 1, 1, 1, 1, 1, 1, 1, 1, 9],
-            [9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9]]
-
-    start = (13, 7)
-    end = (3, 18)
-
-    path = astar(maze, start, end)
-    print(path)
-    return path
-
-
-if __name__ == '__main__':
-    main()

bfs.py

@@ -1,67 +0,0 @@
-from house import *
-import pygame
-
-
-class Node:
-    def __init__(self, pos, direction, parent=None, action=None):
-        self.pos = pos
-        self.direction = direction
-        self.parent = parent
-        self.action = action
-
-    def __eq__(self, other):
-        if isinstance(other, Node):
-            return self.pos == other.pos and self.direction == other.direction
-        return False
-
-
-def successor(pos, direction, houses):
-    neighbours = []
-    axis = 0 if direction in [0, 2] else 1
-    move = 1 if direction in [0, 1] else -1
-
-    neighbours.append([pos, (direction - 1) % 4, pygame.K_a])
-    neighbours.append([pos, (direction + 1) % 4, pygame.K_d])
-
-    if not axis:  # x
-        new_pos = [pos[0] + (move * 40), pos[1]]
-        if not is_house(new_pos, houses):
-            neighbours.append([new_pos, direction, pygame.K_w])
-
-    else:  # y
-        new_pos = [pos[0], pos[1] + (move * 40)]
-        if not is_house(new_pos, houses):
-            neighbours.append([new_pos, direction, pygame.K_w])
-    return neighbours
-
-
-def bfs(pos, direction, end_pos, houses):
-    visited = []
-    queue = []
-    actions = []
-    queue.append(Node(pos, direction))
-
-    while queue:
-        curr_node = queue.pop(0)
-
-        if not is_house(curr_node.pos, houses) and curr_node.pos == end_pos:
-            while curr_node.parent:
-
-               # print(curr_node.pos, end_pos)
-                actions.append(curr_node.action)
-                curr_node = curr_node.parent
-            return actions
-
-        visited.append(curr_node)
-        for n_pos, n_direction, action in successor(curr_node.pos, curr_node.direction, houses):
-            neighbour_node = Node(n_pos, n_direction, curr_node, action)
-            if neighbour_node not in visited and neighbour_node not in queue:
-                queue.append(neighbour_node)
-
-    return actions
-
-def distance(pos, endpos):
-    houses = create_houses(40)
-    actions = bfs(pos, 0, endpos, houses)
-    return len(actions)
-

catOrNotTest/catOrNotTest.py

@@ -1,75 +0,0 @@
-
-from keras.models import Sequential
-from keras.layers import Dense, Dropout, Flatten
-from keras.layers import Conv2D, MaxPooling2D
-from keras.layers.normalization import BatchNormalization
-from PIL import Image
-from random import shuffle, choice
-import numpy as np
-import os
-
-IMAGE_SIZE = 256
-IMAGE_DIRECTORY = './data/training_set'
-
-def label_img(name):
-    if name == 'cats': return np.array([1, 0])
-    elif name == 'notcats' : return np.array([0, 1])
-
-
-def load_data():
-  print("Loading images...")
-  train_data = []
-  directories = next(os.walk(IMAGE_DIRECTORY))[1]
-
-  for dirname in directories:
-    print("Loading {0}".format(dirname))
-    file_names = next(os.walk(os.path.join(IMAGE_DIRECTORY, dirname)))[2]
-    for i in range(200):
-      image_name = choice(file_names)
-      image_path = os.path.join(IMAGE_DIRECTORY, dirname, image_name)
-      label = label_img(dirname)
-      if "DS_Store" not in image_path:
-        img = Image.open(image_path)
-        img = img.convert('L')
-        img = img.resize((IMAGE_SIZE, IMAGE_SIZE), Image.ANTIALIAS)
-        train_data.append([np.array(img), label])
-  
-  return train_data
-
-def create_model():
-  model = Sequential()
-  model.add(Conv2D(32, kernel_size = (3, 3), activation='relu', input_shape=(IMAGE_SIZE, IMAGE_SIZE, 1)))
-  model.add(MaxPooling2D(pool_size=(2,2)))
-  model.add(BatchNormalization())
-  model.add(Conv2D(64, kernel_size=(3,3), activation='relu'))
-  model.add(MaxPooling2D(pool_size=(2,2)))
-  model.add(BatchNormalization())
-  model.add(Conv2D(128, kernel_size=(3,3), activation='relu'))
-  model.add(MaxPooling2D(pool_size=(2,2)))
-  model.add(BatchNormalization())
-  model.add(Conv2D(256, kernel_size=(3,3), activation='relu'))
-  model.add(MaxPooling2D(pool_size=(2,2)))
-  model.add(BatchNormalization())
-  model.add(Conv2D(64, kernel_size=(3,3), activation='relu'))
-  model.add(MaxPooling2D(pool_size=(2,2)))
-  model.add(BatchNormalization())
-  model.add(Dropout(0.2))
-  model.add(Flatten())
-  model.add(Dense(256, activation='relu'))
-  model.add(Dropout(0.2))
-  model.add(Dense(128, activation='relu'))
-  model.add(Dense(2, activation = 'softmax'))
-
-  return model
-
-
-training_data = load_data()
-training_images = np.array([i[0] for i in training_data]).reshape(-1, IMAGE_SIZE, IMAGE_SIZE, 1)
-training_labels = np.array([i[1] for i in training_data])
-
-print('creating model')
-model = create_model()
-model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
-print('training model')
-model.fit(training_images, training_labels, batch_size=50, epochs=10, verbose=1)
-model.save("model2.h5")

catOrNotTest/catOrNotTest.pyproj

@@ -1,65 +0,0 @@
-<Project DefaultTargets="Build" xmlns="http://schemas.microsoft.com/developer/msbuild/2003" ToolsVersion="4.0">
-  <PropertyGroup>
-    <Configuration Condition=" '$(Configuration)' == '' ">Debug</Configuration>
-    <SchemaVersion>2.0</SchemaVersion>
-    <ProjectGuid>909f8871-bfd4-48ea-bee8-31c07b881648</ProjectGuid>
-    <ProjectHome>.</ProjectHome>
-    <StartupFile>catOrNotTest.py</StartupFile>
-    <SearchPath>
-    </SearchPath>
-    <WorkingDirectory>.</WorkingDirectory>
-    <OutputPath>.</OutputPath>
-    <Name>catOrNotTest</Name>
-    <RootNamespace>catOrNotTest</RootNamespace>
-    <InterpreterId>MSBuild|env2|$(MSBuildProjectFullPath)</InterpreterId>
-  </PropertyGroup>
-  <PropertyGroup Condition=" '$(Configuration)' == 'Debug' ">
-    <DebugSymbols>true</DebugSymbols>
-    <EnableUnmanagedDebugging>false</EnableUnmanagedDebugging>
-  </PropertyGroup>
-  <PropertyGroup Condition=" '$(Configuration)' == 'Release' ">
-    <DebugSymbols>true</DebugSymbols>
-    <EnableUnmanagedDebugging>false</EnableUnmanagedDebugging>
-  </PropertyGroup>
-  <ItemGroup>
-    <Compile Include="catOrNotTest.py" />
-    <Compile Include="kopiamain.py">
-      <SubType>Code</SubType>
-    </Compile>
-    <Compile Include="retrain.py">
-      <SubType>Code</SubType>
-    </Compile>
-    <Compile Include="test.py">
-      <SubType>Code</SubType>
-    </Compile>
-  </ItemGroup>
-  <ItemGroup>
-    <Interpreter Include="env2\">
-      <Id>env2</Id>
-      <Version>3.7</Version>
-      <Description>env2 (Python 3.7 (64-bit))</Description>
-      <InterpreterPath>Scripts\python.exe</InterpreterPath>
-      <WindowsInterpreterPath>Scripts\pythonw.exe</WindowsInterpreterPath>
-      <PathEnvironmentVariable>PYTHONPATH</PathEnvironmentVariable>
-      <Architecture>X64</Architecture>
-    </Interpreter>
-    <Interpreter Include="env\">
-      <Id>env</Id>
-      <Version>3.7</Version>
-      <Description>env (Python 3.7 (64-bit))</Description>
-      <InterpreterPath>Scripts\python.exe</InterpreterPath>
-      <WindowsInterpreterPath>Scripts\pythonw.exe</WindowsInterpreterPath>
-      <PathEnvironmentVariable>PYTHONPATH</PathEnvironmentVariable>
-      <Architecture>X64</Architecture>
-    </Interpreter>
-  </ItemGroup>
-  <Import Project="$(MSBuildExtensionsPath32)\Microsoft\VisualStudio\v$(VisualStudioVersion)\Python Tools\Microsoft.PythonTools.targets" />
-  <!-- Uncomment the CoreCompile target to enable the Build command in
-       Visual Studio and specify your pre- and post-build commands in
-       the BeforeBuild and AfterBuild targets below. -->
-  <!--<Target Name="CoreCompile" />-->
-  <Target Name="BeforeBuild">
-  </Target>
-  <Target Name="AfterBuild">
-  </Target>
-</Project>