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,
Aug=ImageGenerator,
Preprocessors=[RP, PP, MP],
Classes=Network.CLASSES)
TestGenerator = IO.HDF5DatasetGenerator(
DB=Network.DATASET_PATH + os.path.sep + Network.OUTPUT_PATH +
os.path.sep + Network.TEST_HDF5 + ".hdf5",
BatchSize=Network.BATCH_SIZE,
Preprocessors=[RP, PP, MP],
Classes=Network.CLASSES)
# Create a new model or load an existing checkpoint
if (args["checkpoint"]):
if (os.path.exists(args["checkpoint"])):
print("[INFO] Load checkpoint {}...".format(args["checkpoint"]))
Model = load_model(args["checkpoint"])
