os.path.sep + Network.DATASET_MEAN).read())
# Create a new image generator
ImageGenerator = ImageDataGenerator(rotation_range=20,
zoom_range=0.15,
width_shift_range=0.2,
height_shift_range=0.2,
shear_range=0.15,
horizontal_flip=True,
fill_mode="nearest")
# Create some preprocessors
PP = Preprocessor.PatchPreprocessor(Width=Network.INPUT_SIZE[0],
Height=Network.INPUT_SIZE[1])
MP = Preprocessor.MeanPreprocessor(rMean=Means["R"],
gMean=Means["G"],
bMean=Means["B"])
RP = Preprocessor.ResizePreprocessor(Width=Network.INPUT_SIZE[0],
Height=Network.INPUT_SIZE[1])
# Check if the database exist
if (not (os.path.exists(Network.DATASET_PATH + os.path.sep +
Network.OUTPUT_PATH + os.path.sep +
Network.TRAIN_HDF5 + ".hdf5"))):
print("[ERROR] Can not find database! Abort...")
exit()
TrainGenerator = IO.HDF5DatasetGenerator(
DB=Network.DATASET_PATH + os.path.sep + Network.OUTPUT_PATH +
os.path.sep + Network.TRAIN_HDF5 + ".hdf5",
BatchSize=Network.BATCH_SIZE,
