def test_getitem(self):
import torchvision.transforms as t
from reid.datasets.viper import VIPeR
from reid.utils.data.preprocessor import Preprocessor
root, split_id, num_val = '/tmp/open-reid/viper', 0, 100
dataset = VIPeR(root, split_id=split_id, num_val=num_val, download=True)
preproc = Preprocessor(dataset.train, root=dataset.images_dir,
transform=t.Compose([
t.Scale(256),
t.CenterCrop(224),
t.ToTensor(),
t.Normalize(mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225])
]))
self.assertEquals(len(preproc), len(dataset.train))
img, pid, camid = preproc[0]
self.assertEquals(img.size(), (3, 224, 224))
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