datasets/imagenetv2.py (31 lines of code) (raw):
import os
from dassl.data.datasets import DATASET_REGISTRY, Datum, DatasetBase
from dassl.utils import listdir_nohidden
from .imagenet import ImageNet
@DATASET_REGISTRY.register()
class ImageNetV2(DatasetBase):
"""ImageNetV2.
This dataset is used for testing only.
"""
dataset_dir = "imagenetv2"
dataset_name = 'imagenetv2'
def __init__(self, cfg):
root = os.path.abspath(os.path.expanduser(cfg.DATASET.ROOT))
self.dataset_dir = os.path.join(root, self.dataset_dir)
image_dir = "imagenetv2-matched-frequency-format-val"
self.image_dir = os.path.join(self.dataset_dir, image_dir)
text_file = os.path.join(self.dataset_dir, "classnames.txt")
classnames = ImageNet.read_classnames(text_file)
data = self.read_data(classnames)
super().__init__(train_x=data, test=data)
def read_data(self, classnames):
image_dir = self.image_dir
folders = list(classnames.keys())
items = []
for label in range(1000):
class_dir = os.path.join(image_dir, str(label))
imnames = listdir_nohidden(class_dir)
folder = folders[label]
classname = classnames[folder]
for imname in imnames:
impath = os.path.join(class_dir, imname)
item = Datum(impath=impath, label=label, classname=classname)
items.append(item)
return items