File size: 1,972 Bytes
6107278 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 | from torch.utils.data import Dataset
import pandas as pd
import cv2 as cv
import os
class myDataset(Dataset):
def __init__(self, filelist, cxr_dir, bs_dir,
transform=None):
self.cxr_dir = cxr_dir
self.bs_dir = bs_dir
self.transform = transform
self.filelist = pd.read_csv(filelist, sep="\t", header=None)
def __len__(self):
return len(self.filelist)
def __getitem__(self, idx):
file = self.filelist.iloc[idx, 0]
cxr = cv.imread(os.path.join(self.cxr_dir, file))
bs = cv.imread(os.path.join(self.bs_dir, file))
if self.transform:
cxr = self.transform(cxr)
bs = self.transform(bs)
return cxr, bs, file
class myDiTDataset(Dataset):
def __init__(self, filelist, cxr_dir, bs_dir,
transform=None):
self.cxr_dir = cxr_dir
self.bs_dir = bs_dir
self.transform = transform
self.filelist = pd.read_csv(filelist, sep="\t", header=None)
def __len__(self):
return len(self.filelist)
def __getitem__(self, idx):
file = self.filelist.iloc[idx, 0]
cxr = cv.imread(os.path.join(self.cxr_dir, file))
bs = cv.imread(os.path.join(self.bs_dir, file))
if self.transform:
cxr, bs = self.transform(cxr, bs)
return cxr, bs, file
class mySingleDataset(Dataset):
def __init__(self, filelist, cxr_dir,
transform=None):
self.cxr_dir = cxr_dir
self.transform = transform
self.filelist = pd.read_csv(filelist, sep="\t", header=None)
def __len__(self):
return len(self.filelist)
def __getitem__(self, idx):
file = self.filelist.iloc[idx, 0]
cxr = cv.imread(os.path.join(self.cxr_dir, file))
if self.transform:
cxr = self.transform(cxr)
return cxr, file
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