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import torch.utils.data as data
from PIL import Image
import os
import os.path
import numpy as np
import glob
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):
l0_train = []
l1_train = []
flow_train = []
for flow_map in sorted(glob.glob('%s/flow/*.pfm'%filepath)):
img1 = flow_map.replace('flow','t0').replace('.pfm','.png')
img2 = flow_map.replace('flow','t1').replace('.pfm','.png')
l0_train.append(img1)
l1_train.append(img2)
flow_train.append(flow_map)
return l0_train, l1_train, flow_train
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