def LoadFromNpys(self, dir, classes):
self.imgDataWrappers = np.empty(0,
dtype=ImgDataWrapperMultiTypesMemory)
npysImgs = CommonUtil.GetFileFromThisRootDir(
os.path.join(dir, "arrImgs"), ".npy")
npysMasks = CommonUtil.GetFileFromThisRootDir(
os.path.join(dir, "masks"), ".npy")
if len(npysImgs) != len(npysMasks):
print(
"WARNING: Count of img inputs is different from count of mask inputs."
)
for i in range(len(npysImgs)):
# print("Loading",i,":")
# print(" " + npysImgs[i])
# print(" " + npysMasks[i])
imgs = np.load(npysImgs[i])
masks = np.load(npysMasks[i])
# print(imgs.shape)
# print(masks.shape)
if imgs is None:
raise Exception("Imgs is none. No img has been read.")
if masks is None:
raise Exception("Masks is none. No mask has been read.")
self.imgDataWrappers = np.insert(self.imgDataWrappers, len(self.imgDataWrappers), \
ImgDataWrapperMultiTypesMemory(imgs, masks, classes, imgDataFmt=imgs.dtype,
maskDataFmt=masks.dtype, isMaskOneHot=True), \
axis=0)
def SaveToNpys(self, dir):
countWrappers = len(self.imgDataWrappers)
digitWrapperCount = len(str(countWrappers - 1))
dirImg = os.path.join(dir, "arrImgs")
dirMask = os.path.join(dir, "masks")
CommonUtil.Mkdir(dirImg)
CommonUtil.Mkdir(dirMask)
for i in range(countWrappers):
wrapper = self.imgDataWrappers[i]
arrImgs = wrapper.arrImgs
masks = wrapper.masks
fn = str(i).zfill(digitWrapperCount) + ".npy"
pathImg = os.path.join(dirImg, fn)
pathMask = os.path.join(dirMask, fn)
np.save(pathImg, arrImgs)
np.save(pathMask, masks)
def _check_value_type(_input, _value):
try:
if _input.type == bool:
return CommonUtil.get_boolean_value(_value)
else:
return _input.type(_value)
except TypeError as _:
raise _
def InitFromImgsAndMasks(self,
imgs,
masks,
classes,
dirSave,
resize=None,
preproc=None,
imgDataFmt=float,
maskDataFmt=int,
isMaskOneHot=False):
self.pathsImg = None
self.pathsMasks = None
if resize is not None:
# Use pure resizing to preserve data matchiing
imgs = transform.resize(imgs,
resize + (self.imgs.shape[2], ),
order=0,
clip=True,
preserve_range=True,
anti_aliasing=False)
masks = transform.resize(masks,
resize + (self.masks.shape[2], ),
order=0,
clip=True,
preserve_range=True,
anti_aliasing=False)
gc.collect()
if preproc is not None:
imgs, masks = preproc(imgs, masks, classes)
gc.collect()
imgs = imgs.astype(dtype=imgDataFmt)
masks = masks.astype(dtype=maskDataFmt)
# One-hot encoding target
if classes <= 1:
raise Exception("Class count = 1. Unable to run! ")
if not isMaskOneHot:
maxClass = np.max(np.unique(masks))
if maxClass > classes:
raise Exception("Not enough classes! MaxClassValue: " +
str(maxClass))
masks = CommonUtil.PackIntoOneHot(masks, classes)
gc.collect()
if np.any(np.isnan(imgs)):
raise Exception("NAN Warning!")
if np.any(np.isnan(masks)):
raise Exception("NAN Warning!")
# Save to npys
self.__SaveToNPYs(dirSave, imgs, masks)
def __init__(self,
arrImgs,
masks,
classes,
resize=None,
preproc=None,
imgDataFmt=float,
maskDataFmt=int,
isMaskOneHot=False):
self.arrImgs = arrImgs # ndarray[H, W, Type, Slices]
self.masks = masks
if resize is not None:
# Use pure resizing to preserve data matchiing
self.arrImgs = transform.resize(self.arrImgs,
(self.arrImgs.shape[0], ) +
resize + (self.arrImgs.shape[3], ),
order=0,
clip=True,
preserve_range=True,
anti_aliasing=False)
self.masks = transform.resize(self.masks,
resize + (self.masks.shape[2], ),
order=0,
clip=True,
preserve_range=True,
anti_aliasing=False)
gc.collect()
if preproc is not None:
self.arrImgs, self.masks = preproc(self.arrImgs, self.masks,
classes)
gc.collect()
self.arrImgs = self.arrImgs.astype(dtype=imgDataFmt)
self.masks = self.masks.astype(dtype=maskDataFmt)
# One-hot encoding target
if classes <= 1:
raise Exception("Class count = 1. Unable to run! ")
if not isMaskOneHot:
maxClass = np.max(np.unique(self.masks))
if maxClass > classes:
raise Exception("Not enough classes! MaxClassValue: " +
str(maxClass))
self.masks = CommonUtil.PackIntoOneHot(self.masks, classes)
gc.collect()
if np.any(np.isnan(self.arrImgs)):
raise Exception("NAN Warning!")
if np.any(np.isnan(self.masks)):
raise Exception("NAN Warning!")
def __SaveToNPYs(self, dirWrapper, imgs, masks):
self.pathsImg = []
self.pathsMasks = []
suffix = ".npy"
dirData = os.path.join(dirWrapper, "data")
dirMasks = os.path.join(dirWrapper, "masks")
CommonUtil.Mkdir(dirData)
CommonUtil.Mkdir(dirMasks)
slices = imgs.shape[-1]
digitCount = len(str(slices))
for i in range(slices):
filename = str(i).zfill(digitCount) + suffix
pathImg = os.path.join(dirData, filename)
pathMask = os.path.join(dirMasks, filename)
np.save(pathImg, imgs[..., i])
self.pathsImg += [pathImg]
np.save(pathMask, masks[..., i])
self.pathsMasks += [pathMask]
def run(self):
super(CoAPSniffAttack, self).run()
packets = CoAPScanner().scan(
self.timeout,
self.interface,
output_pcap_filename="CoAP_" +
CommonUtil.get_current_datetime_for_filename_format()
if self.save_output else None)
for packet in packets:
self.logger.info(packet)
return packets
def run(self):
self.input_check() # Do the necessary checks
super(MQTTSniffAttack, self).run()
packets = MQTTScanner().scan(
self.timeout,
self.interface,
output_pcap_filename="MQTT_" +
CommonUtil.get_current_datetime_for_filename_format()
if self.save_output else None)
for packet in packets:
self.logger.info(packet)
return packets
def __LoadFromNPYs(self, dirWrapper):
dirData = os.path.join(dirWrapper, "data")
dirMasks = os.path.join(dirWrapper, "masks")
self.pathsImg = CommonUtil.GetFileFromThisRootDir(dirData, ".npy")
self.pathsMasks = CommonUtil.GetFileFromThisRootDir(dirMasks, ".npy")
def create_file_name():
# store the captured packets
return os.path.dirname(
os.path.abspath(__file__)
) + "/../../captured_packets/BLE_" + CommonUtil.get_current_datetime_for_filename_format(
) + ".pcap"