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tf_config_image.py
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# 12/5/23 DH:
from tf_config import *
from tf_config_misc import *
import numpy
class TFConfigImage(TFConfig):
def __init__(self) -> None:
super().__init__()
# 15/5/23 DH: Needed for 'saveDigitArrayValues()'
self.tfCfgMisc = TFConfigMisc()
self.createDigitLabels()
# ---------------------------- API --------------------------------
def createImages(self, display=False, number=10):
imgs = self.x_test[:number]
imgValues = self.y_test[:number]
x_testPlusDigit = []
# 'shape' returns a tuple so access first value
imgNum = imgs.shape[0]
print("imgNum:",imgNum)
#imgNum = 1
for elem in range(imgNum):
img = imgs[elem]
# TODO: Add a pixel value set for small expected number onto the original image to create 'y_test'
# Then train the 784-784 DNN to do that for any 'x_test' to create 'x_testPlusDigit'
if elem < 10:
print("y_test[",elem,"]:",imgValues[elem])
if elem == 11:
print("...")
img = img * 255
img = np.asarray(img, dtype = 'uint8')
img = self.addDigitToImage(img, imgValues[elem])
# Test each of the prepared digits
#img = self.addDigitToImage(img, elem)
if display:
#self.displayImg(img,timeout=-1)
self.displayImg(img,timeout=1)
x_testPlusDigit.append(img)
# END: ---- 'for elem in range(imgNum)' ----
self.x_testPlusDigit = numpy.asarray(x_testPlusDigit)
# Now train the 784-784 DNN with 'self.x_test' + 'self.x_testPlusDigit'
def runImageTrainer(self, paramDict):
self.build(paramDict)
self.probability_model = self.tfModel.getProbabilityModel(self.model)
# Put in unaltered MNIST digit
# ---------
softmax2DList = self.probability_model(self.x_test).numpy()
imgList = self.tfModel.model(self.x_test).numpy()
for elem in range(self.x_testPlusDigit.shape[0]):
imgSoftmax = softmax2DList[elem]
imgSoftmax = imgSoftmax.reshape(28,28)
imgModel = imgList[elem]
imgModel = imgModel.reshape(28,28)
print("Displaying altered MNIST image")
self.displayImg(self.x_testPlusDigit[elem],timeout=3)
print("Displaying probability_model() image from orig image")
self.displayImg(imgSoftmax,timeout=3)
print("Displaying model() image from orig image")
self.displayImg(imgModel,timeout=3)
print("Displaying orig MNIST image")
self.displayImg(self.x_test[elem],timeout=3)
if elem < 2:
self.tfCfgMisc.saveDigitArrayValues(imgSoftmax, fileNum=elem)
self.tfCfgMisc.saveDigitArrayValues(imgModel, fileNum=100+elem)
# ---------------------------- Internal -------------------------------
# Override the 'TFConfig.build(paramDict)'
def build(self, paramDict):
self.trainingNum = paramDict['trainingNum']
self.x_trainSet = paramDict['x_trainSet']
self.y_trainSet = paramDict['y_trainSet']
self.epochs = paramDict['epochs']
self.y_trainSet = self.y_trainSet.reshape(self.y_trainSet.shape[0],28*28)
# 14/5/23 DH:
print("self.x_trainSet:",type(self.x_trainSet),self.x_trainSet.shape)
print("self.y_trainSet:",type(self.y_trainSet),self.y_trainSet.shape)
print("self.y_test:",type(self.y_test),self.y_test.shape)
self.model = self.tfModel.createTrainedImageModel(x_trainSet=self.x_trainSet,
y_trainSet=self.y_trainSet,
epochs=self.epochs)
self.modelEval(start=True)
def createDigitLabels(self):
self.digitLabelsDict = {}
# 6 * 7 = 42 pixels
# 13/5/23 DH: Add the digit graphic to the MNIST image to create MNIST training result image (ie 'y_test')
# 784-784 DNN
self.digitLabelsDict[0] = numpy.asarray(
[[ 0, 0,255,255, 0, 0],
[ 0,255,255,255,255, 0],
[255,255, 0, 0,255,255],
[255, 0, 0, 0, 0,255],
[255,255, 0, 0,255,255],
[ 0,255,255,255,255, 0],
[ 0, 0,255,255, 0, 0]])
self.digitLabelsDict[1] = numpy.asarray(
[[ 0,255,255,255, 0, 0],
[ 0,255,255,255, 0, 0],
[ 0, 0, 0,255, 0, 0],
[ 0, 0, 0,255, 0, 0],
[ 0, 0, 0,255, 0, 0],
[ 0,255,255,255,255, 0],
[ 0,255,255,255,255, 0]])
self.digitLabelsDict[2] = numpy.asarray(
[[ 0, 0,255,255, 0, 0],
[ 0,255, 0,255,255, 0],
[ 0, 0, 0, 0,255, 0],
[ 0, 0, 0, 0,255, 0],
[ 0, 0, 0,255,255, 0],
[ 0, 0,255,255, 0, 0],
[ 0,255,255,255,255,255]])
self.digitLabelsDict[3] = numpy.asarray(
[[ 0, 0,255,255,255, 0],
[ 0,255, 0, 0,255,255],
[ 0, 0, 0, 0, 0,255],
[ 0, 0, 0,255,255, 0],
[ 0, 0, 0, 0, 0,255],
[ 0,255, 0, 0,255,255],
[ 0, 0,255,255,255, 0]])
self.digitLabelsDict[4] = numpy.asarray(
[[ 0, 0, 0,255,255, 0],
[ 0, 0,255, 0,255, 0],
[ 0,255, 0, 0,255, 0],
[255, 0, 0, 0,255, 0],
[255,255,255,255,255,255],
[ 0, 0, 0, 0,255, 0],
[ 0, 0, 0, 0,255, 0]])
self.digitLabelsDict[5] = numpy.asarray(
[[255,255,255,255, 0, 0],
[255, 0, 0, 0, 0, 0],
[255,255,255,255, 0, 0],
[ 0, 0, 0,255,255, 0],
[ 0, 0, 0, 0,255, 0],
[255, 0, 0,255,255, 0],
[255,255,255,255, 0, 0]])
self.digitLabelsDict[6] = numpy.asarray(
[[ 0, 0,255,255, 0, 0],
[ 0,255, 0, 0, 0, 0],
[ 0,255, 0, 0, 0, 0],
[ 0,255,255,255,255, 0],
[ 0,255, 0, 0,255, 0],
[ 0,255, 0, 0,255, 0],
[ 0, 0,255,255,255, 0]])
self.digitLabelsDict[7] = numpy.asarray(
[[255,255,255,255,255,255],
[255,255,255,255,255,255],
[ 0, 0, 0, 0,255,255],
[ 0, 0, 0,255,255, 0],
[ 0, 0,255,255, 0, 0],
[ 0,255,255, 0, 0, 0],
[255,255, 0, 0, 0, 0]])
self.digitLabelsDict[8] = numpy.asarray(
[[ 0, 0,255,255,255, 0],
[ 0,255,255, 0,255,255],
[ 0,255, 0, 0, 0,255],
[ 0, 0,255,255,255, 0],
[ 0,255, 0, 0, 0,255],
[ 0,255,255, 0,255,255],
[ 0, 0,255,255,255, 0]])
self.digitLabelsDict[9] = numpy.asarray(
[[ 0,255,255,255, 0, 0],
[ 0,255, 0, 0,255, 0],
[ 0,255, 0, 0,255, 0],
[ 0, 0,255,255,255, 0],
[ 0, 0, 0, 0,255, 0],
[ 0, 0, 0, 0,255, 0],
[ 0, 0, 0, 0,255, 0]])
def addDigitToImage(self, img, digit):
xSize, ySize = img.shape
#if not digit in self.digitLabelsDict:
#digit = 3
xLblSize, yLblSize = self.digitLabelsDict[digit].shape
#print(xSize,ySize,",",xLblSize,yLblSize)
imgLbl = self.digitLabelsDict[digit]
for x in range(xSize):
for y in range(ySize):
if x < xLblSize and y < yLblSize:
img[x+1][y+1] = imgLbl[x][y]
"""
for x in range(xSize):
xStr = ""
for y in range(ySize):
pixVal = "{:4}".format(img[x][y])
xStr += str(pixVal)
print(xStr)
print()
"""
return img