def __init__(self,
pipeline,
tensor_layout=types.NCHW,
reverse_channels=False,
multiplier=[1.0, 1.0, 1.0],
offset=[0.0, 0.0, 0.0],
tensor_dtype=types.FLOAT):
self.loader = pipeline
self.tensor_format = tensor_layout
self.multiplier = multiplier
self.offset = offset
self.reverse_channels = reverse_channels
self.tensor_dtype = tensor_dtype
self.w = b.getOutputWidth(self.loader._handle)
self.h = b.getOutputHeight(self.loader._handle)
self.n = b.getOutputImageCount(self.loader._handle)
self.bs = pipeline._batch_size
color_format = b.getOutputColorFormat(self.loader._handle)
self.p = (1 if (color_format == int(types.GRAY)) else 3)
if self.tensor_dtype == types.FLOAT:
self.out = np.zeros((
self.bs * self.n,
self.p,
int(self.h / self.bs),
self.w,
),
dtype="float32")
elif self.tensor_dtype == types.FLOAT16:
self.out = np.zeros((
self.bs * self.n,
self.p,
int(self.h / self.bs),
self.w,
),
dtype="float16")
# self.labels = np.zeros((self.bs),dtype = "int32")
if (self.loader._oneHotEncoding == True):
self.labels = np.zeros((self.bs) * (self.loader._numOfClasses),
dtype="int32")
else:
self.labels = np.zeros((self.bs), dtype="int32")
if self.bs != 0:
self.len = b.getRemainingImages(self.loader._handle) // self.bs
else:
self.len = b.getRemainingImages(self.loader._handle)
def __next__(self):
if b.getRemainingImages(self.loader._handle) < self.bs:
raise StopIteration
if self.loader.run() != 0:
raise StopIteration
self.loader.copyImage(self.out_image)
return self.out_image, self.out_tensor
def __next__(self):
if b.getRemainingImages(self.loader._handle) < self.bs:
raise StopIteration
if self.loader.run() != 0:
raise StopIteration
self.loader.copyImage(self.out_image)
if ((self.loader._name == "Caffe2ReaderDetection")
or (self.loader._name == "CaffeReaderDetection")):
for i in range(self.bs):
size = b.getImageNameLen(self.loader._handle, i)
print(size)
self.array = np.array([" "])
self.out = np.frombuffer(self.array, dtype=(self.array).dtype)
b.getImageName(self.loader._handle, self.out, i)
return self.out_image, self.out_bbox, self.out_tensor
else:
return self.out_image, self.out_tensor
def getRemainingImages(self):
return b.getRemainingImages(self._handle)