class C2Pipe(Pipeline):
def __init__(self,
batch_size,
num_threads,
device_id,
pipelined=True,
async=True):
super(C2Pipe, self).__init__(batch_size,
num_threads,
device_id,
exec_pipelined=pipelined,
exec_async=async)
self.input = ops.ExternalSource()
self.decode = ops.HostDecoder(output_type=types.RGB)
self.rcm = ops.FastResizeCropMirror(crop=[224, 224])
self.np = ops.NormalizePermute(device="gpu",
output_dtype=types.FLOAT16,
mean=[128., 128., 128.],
std=[1., 1., 1.],
height=224,
width=224,
image_type=types.RGB)
self.uniform = ops.Uniform(range=(0., 1.))
self.resize_uniform = ops.Uniform(range=(256., 480.))
self.mirror = ops.CoinFlip(probability=0.5)
self.iter = 0
def __init__(self, batch_size, num_threads, device_id, pipelined = True, exec_async = True):
super(C2Pipe, self).__init__(batch_size,
num_threads,
device_id,
exec_pipelined=pipelined,
exec_async=exec_async)
self.input = ops.ExternalSource()
self.decode = ops.ImageDecoder(device = 'cpu', output_type = types.RGB)
self.rcm = ops.FastResizeCropMirror(crop = (224, 224))
self.np = ops.CropMirrorNormalize(device = "gpu",
dtype = types.FLOAT16,
mean = [128., 128., 128.],
std = [1., 1., 1.])
self.uniform = ops.Uniform(range = (0., 1.))
self.resize_uniform = ops.Uniform(range = (256., 480.))
self.mirror = ops.CoinFlip(probability = 0.5)