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import os
import json
import torch
import torchvision.transforms as transforms
import os.path
import numpy as np
import cv2
from torch.utils.data import Dataset
import random
from .__base_dataset__ import BaseDataset
class CityscapesDataset(BaseDataset):
def __init__(self, cfg, phase, **kwargs):
super(CityscapesDataset, self).__init__(
cfg=cfg,
phase=phase,
**kwargs)
self.metric_scale = cfg.metric_scale
def process_depth(self, depth, rgb):
depth[depth>65500] = 0
depth /= self.metric_scale
return depth
if __name__ == '__main__':
from mmcv.utils import Config
cfg = Config.fromfile('mono/configs/Apolloscape_DDAD/convnext_base.cascade.1m.sgd.mae.py')
dataset_i = ApolloscapeDataset(cfg['Apolloscape'], 'train', **cfg.data_basic)
print(dataset_i)
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