def __init__(self, parent, path):
# take data and use datamanager to return imageSize, and ints.
# Attributes
self.path = path
self.imageNum = 0 # current image in the data to be viewed
self.imgSize = DataManager.getImgSize(path, split=True)
self.imgSizeX = self.imgSize[1]
self.imgSizeY = self.imgSize[0]
self.imgSize = DataManager.getImgSize(path, split=False)
self.setSize = DataManager.getSetSize(path) # Number of images in set
self.currentPixel = None # Tk.Frame obj
self.currentPixelPos = None # int position of pixel in current image
# Pixel holder
self.wrapper = Tk.Frame(parent)
self.wrapper.grid(row=0, column=0)
self.digitDisplay = Tk.Frame(self.wrapper, width=235, height=235)
self.digitDisplay.grid_propagate(False)
for i in range(self.imgSizeY):
self.digitDisplay.grid_rowconfigure(i, weight=1)
for i in range(self.imgSizeX):
self.digitDisplay.grid_columnconfigure(i, weight=1)
self.digitDisplay.grid(row=0, column=0)
# EntryBox
self.pixelLabel = Tk.Label(self.wrapper, text='No pixel selected')
self.pixelLabel.grid(row=1, column=0, sticky='nswe')
# self.pixel is a 2d array containing Tk.Frames. [0] = imageNum, [1] = frames
pixel = []
for i in range(self.setSize):
pixel.append([])
self.data = DataManager.getImage(self.path, i)
for j in range(self.imgSizeX * self.imgSizeY):
val = int.from_bytes(self.data[j:j + 1], byteorder='big')
pixel[i].append(self.newPixel(val, j))
self.pixel = pixel
# Free up some ram
self.data = None
return
def newImg(self, path):
# Destroy old pixels
for i in range(self.setSize):
self.data = DataManager.getImage(self.path, i)
for j in range(self.imgSizeX * self.imgSizeY):
self.pixel[i][j].destroy()
# New attributes
self.path = path
self.imageNum = 0 # current image in the data to be viewed
self.imgSize = DataManager.getImgSize(path, split=True)
self.imgSizeX = self.imgSize[1]
self.imgSizeY = self.imgSize[0]
self.imgSize = DataManager.getImgSize(path, split=False)
self.setSize = DataManager.getSetSize(path) # Number of images in set
self.currentPixel = None # Tk.Frame obj
self.currentPixelPos = None # int position of pixel in current image
# self.pixel is a 2d array containing Tk.Frames. [0] = imageNum, [1] = frames
pixel = []
for i in range(self.setSize):
pixel.append([])
self.data = DataManager.getImage(self.path, i)
for j in range(self.imgSizeX * self.imgSizeY):
val = int.from_bytes(self.data[j:j + 1], byteorder='big')
pixel[i].append(self.newPixel(val, j))
self.pixel = pixel
# Free up some ram
self.data = None
return
def train(
self,
data,
expecteds,
window,
normalise=False,
):
# Get image size, and num of images from data
imgCount = DataManager.getSetSize(data)
imgSize = DataManager.getImgSize(data)
# Get label file ready
expecteds = gzip.open(expecteds, 'r')
expecteds.read(8) # get past headers
# Get images and train
data = gzip.open(data, 'r')
for i in range(0, imgCount):
# print('Training on Image: ', i+1)
# Build image array
buffer = data.read(imgSize)
image = np.frombuffer(buffer, dtype=np.uint8)
# One hot encode label
label = int.from_bytes(expecteds.read(1), byteorder='big')
expectedOutput = np.zeros(10)
expectedOutput[label] = 1
# Update progress bar
window.progressBar['value'] += 1
window.window.update()
# Do passes
self.forwardProp(image, normalise=normalise)
self.backwardProp(expectedOutput)
# Check if training should be stopped
if window.stop == True:
break
# Setup window things
window.progressLabel['text'] = 'Progress: Complete!'
# Free resources
data.close()
expecteds.close()
return
