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)