def get_data(name):
isTrain = name == 'train'
augmentors = fbresnet_augmentor(isTrain)
datadir = args.data
return get_imagenet_dataflow(datadir,
name,
BATCH_SIZE,
augmentors,
dir_structure='original')
def get_data(train_or_test):
isTrain = train_or_test == 'train'
datadir = args.data
ds = dataset.ILSVRC12(datadir, train_or_test,
shuffle=isTrain, dir_structure='original')
augmentors = fbresnet_augmentor(isTrain)
augmentors.append(imgaug.ToUint8())
ds = AugmentImageComponent(ds, augmentors, copy=False)
if isTrain:
ds = PrefetchDataZMQ(ds, min(20, multiprocessing.cpu_count()))
ds = BatchData(ds, BATCH_SIZE, remainder=not isTrain)
return ds
def get_data(train_or_test):
# completely copied from imagenet-resnet.py example
isTrain = train_or_test == 'train'
datadir = args.data
ds = dataset.ILSVRC12(datadir, train_or_test, shuffle=isTrain)
augmentors = fbresnet_augmentor(isTrain)
augmentors.append(imgaug.ToUint8())
ds = AugmentImageComponent(ds, augmentors, copy=False)
if isTrain:
ds = PrefetchDataZMQ(ds, min(25, multiprocessing.cpu_count()))
ds = BatchData(ds, BATCH_SIZE, remainder=not isTrain)
return ds
def get_data(name, batch):
isTrain = name == 'train'
augmentors = fbresnet_augmentor(isTrain)
datadir = args.data
return get_imagenet_dataflow(datadir, name, batch, augmentors)
