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)