def __loadNetwork(self):
file = filedialog.askopenfile(title='Select neural network',
filetypes=(('neural network files',
'*.nn'), ))
if file is None:
return
with open(file.name, 'rb') as f:
nLayers = unpack('B', f.read(1))[0]
neuronsPerLayer = unpack('{}H'.format(nLayers),
f.read(2 * nLayers))
if neuronsPerLayer[0] != 784 or neuronsPerLayer[3] != 10:
messagebox.showerror(
'Error',
'Neural network has wrong number\nof input (784) or output (10) nodes'
)
return
self.network = nn.network()
self.network.setStructure(neuronsPerLayer)
for i in range(len(neuronsPerLayer) - 1):
weights = np.array(
unpack(
'<{}f'.format(neuronsPerLayer[i] *
neuronsPerLayer[i + 1]),
f.read(4 * neuronsPerLayer[i] *
neuronsPerLayer[i + 1]))).reshape(
(neuronsPerLayer[i + 1],
neuronsPerLayer[i]))
self.network.setConnectionWeights(i + 1, weights)
biases = np.array(
unpack('<{}f'.format(neuronsPerLayer[i + 1]),
f.read(4 * neuronsPerLayer[i + 1])))
self.network.setNeuronBias(i + 1,
range(neuronsPerLayer[i + 1]),
biases)
self.__drawNetwork()
def __init__(self):
self.network = nn.network()
self.__mnistLoaded = False
self.__miniBatchSize = []
self.__inputSize = []
self.__learningRate = []
self.__nIterations = []
def __init__(self):
self.__network = nn.network()
self.__trainingLoaded = False
self.__validationLoaded = False
self.__miniBatchSize = []
self.__inputSize = []
self.__learningRate = []
self.__nEpochs = []
self.__regularisationConst = []
def __init__(self, master):
self.master = master
master.title('MNIST Neural Network Test Interface')
# drawing canvas area
pxSize = 15
self.pixelSize = pxSize
self.drawingCanvas = tk.Canvas(width=pxSize * 28,
height=pxSize * 28,
bg='#000044')
self.drawingCanvas.grid(row=0, column=0)
self.drawingCanvas.bind('<B1-Motion>', self.__paintOnCanvas)
self.drawingCanvas.bind('<Button-1>', self.__paintOnCanvas)
self.__addDrawingBackground()
self.processDrawingButton = tk.Button(text='Process Digit',
command=self.__procDrawing)
self.processDrawingButton.grid(row=2)
self.clearButton = tk.Button(text='Clear',
command=self.__clearDrawingCanvas)
self.clearButton.grid(row=1)
# pixel canvas area
self.pixelCanvas = tk.Canvas(width=pxSize * 28,
height=pxSize * 28,
bg='#440000')
self.pixelCanvas.grid(row=0, column=1, columnspan=2)
tk.Label(text='MNIST test index: ').grid(row=1, column=1, sticky='E')
self.testIndex = tk.Spinbox(from_=0,
to=9999,
command=self.__loadMNIST,
width=10)
self.testIndex.grid(row=1, column=2, sticky='W')
self.testIndex.bind('<Return>', self.__loadMNIST)
self.mnistLabelVar = tk.StringVar()
self.mnistLabelVar.set('Label: #')
self.mnistLabel = tk.Label(textvariable=self.mnistLabelVar)
self.mnistLabel.grid(row=2, column=1, columnspan=2)
# neural network area
self.nnCanvas = tk.Canvas(width=pxSize * 43, height=pxSize * 28)
self.nnCanvas.grid(row=0, column=3)
self.nnCanvas.bind('<Button-1>', self.__highlightNode)
self.loadNNbutton = tk.Button(text='Load Neural Network',
command=self.__loadNetwork)
self.loadNNbutton.grid(row=1, column=3)
self.network = nn.network()
self.truthResult = 'drawn'