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dataLoadess.py
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dataLoadess.py
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from torch.utils.data import Dataset
import os
import torch
import scipy.io as scio
class Imgdataset(Dataset):
def __init__(self, path):
super(Imgdataset, self).__init__()
self.data = []
if os.path.exists(path):
groung_truth_path = path + '/gt'
if os.path.exists(groung_truth_path):
groung_truth = os.listdir(groung_truth_path)
self.data = [{'groung_truth': groung_truth_path + '/' + groung_truth[i]} for i in
range(len(groung_truth))]
else:
raise FileNotFoundError('path doesnt exist!')
else:
raise FileNotFoundError('path doesnt exist!')
def __getitem__(self, index):
groung_truth = self.data[index]["groung_truth"]
gt = scio.loadmat(groung_truth)
if "patch_save" in gt:
gt = torch.from_numpy(gt['patch_save'] / 255)
elif "p1" in gt:
gt = torch.from_numpy(gt['p1'] / 255)
elif "p2" in gt:
gt = torch.from_numpy(gt['p2'] / 255)
elif "p3" in gt:
gt = torch.from_numpy(gt['p3'] / 255)
gt = gt.permute(2, 0, 1)
return gt
def __len__(self):
return len(self.data)