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import torch.utils.data as data
from PIL import Image
import os
import os.path
import numpy as np
IMG_EXTENSIONS = [
'.jpg', '.JPG', '.jpeg', '.JPEG',
'.png', '.PNG', '.ppm', '.PPM', '.bmp', '.BMP',
]
def is_image_file(filename):
return any(filename.endswith(extension) for extension in IMG_EXTENSIONS)
def dataloader(filepath):
left_fold = 'image_2/'
flow_noc = 'flow_occ/'
train = [img for img in os.listdir(filepath+left_fold) if img.find('_10') > -1]
# train = [i for i in train if int(i.split('_')[0])%5!=0]
with open('/data/gengshay/kitti_scene/devkit/mapping/train_mapping.txt','r') as f:
flags = [True if len(i)>1 else False for i in f.readlines()]
train = [fn for (it,fn) in enumerate(sorted(train)) if flags[it] ][100:]
l0_train = [filepath+left_fold+img for img in train]
l1_train = [filepath+left_fold+img.replace('_10','_11') for img in train]
flow_train = [filepath+flow_noc+img for img in train]
return sorted(l0_train), sorted(l1_train), sorted(flow_train)
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