mmselfsup/openselfsup/datasets/rotation_pred.py

36 lines
883 B
Python

import torch
from .registry import DATASETS
from .base import BaseDataset
def rotate(img):
'''
img: Tensor(CHW)
'''
return [
img,
torch.flip(img.transpose(1, 2), [1]),
torch.flip(img, [1, 2]),
torch.flip(img, [1]).transpose(1, 2)
]
@DATASETS.register_module
class RotationPredDataset(BaseDataset):
"""Dataset for rotation prediction
"""
def __init__(self, data_source, pipeline):
super(RotationPredDataset, self).__init__(data_source, pipeline)
def __getitem__(self, idx):
img, _ = self.data_source.get_sample(idx)
img = self.pipeline(img)
img = torch.stack(rotate(img), dim=0)
rotation_labels = torch.LongTensor([0, 1, 2, 3])
return dict(img=img, rot_label=rotation_labels)
def evaluate(self, scores, keyword, logger=None):
raise NotImplemented