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|
import torch
from torchvision.transforms import transforms
from transforms import ConvertBCHWtoCBHW
class VideoClassificationPresetTrain:
def __init__(
self,
*,
crop_size,
resize_size,
mean=(0.43216, 0.394666, 0.37645),
std=(0.22803, 0.22145, 0.216989),
hflip_prob=0.5,
):
trans = [
transforms.ConvertImageDtype(torch.float32),
transforms.Resize(resize_size),
]
if hflip_prob > 0:
trans.append(transforms.RandomHorizontalFlip(hflip_prob))
trans.extend([transforms.Normalize(mean=mean, std=std), transforms.RandomCrop(crop_size), ConvertBCHWtoCBHW()])
self.transforms = transforms.Compose(trans)
def __call__(self, x):
return self.transforms(x)
class VideoClassificationPresetEval:
def __init__(self, *, crop_size, resize_size, mean=(0.43216, 0.394666, 0.37645), std=(0.22803, 0.22145, 0.216989)):
self.transforms = transforms.Compose(
[
transforms.ConvertImageDtype(torch.float32),
transforms.Resize(resize_size),
transforms.Normalize(mean=mean, std=std),
transforms.CenterCrop(crop_size),
ConvertBCHWtoCBHW(),
]
)
def __call__(self, x):
return self.transforms(x)
|
