Kornel: added neural web

This commit is contained in:
MonoYuku 2021-06-23 00:09:58 +02:00
parent cdf155d8ca
commit 80e6c700cb
9039 changed files with 399 additions and 4 deletions

1
.idea/.name Normal file
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main.py

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<module type="PYTHON_MODULE" version="4">
<component name="NewModuleRootManager">
<content url="file://$MODULE_DIR$" />
<orderEntry type="inheritedJdk" />
<orderEntry type="jdk" jdkName="Python 3.9" jdkType="Python SDK" />
<orderEntry type="sourceFolder" forTests="false" />
</component>
</module>

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TSP.py
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@ -81,6 +81,7 @@ def tsp(x, y):
if solution:
sol = print_solution(manager, routing, solution)
return sol
def tspmove(order, truck, Ltrash):

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1
bfs.py
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@ -57,6 +57,7 @@ def bfs(pos, direction, end_pos, 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):

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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")

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<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>
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<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>

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