In the data_provider.py, in the class HSIDataLoader->def prepare_data(self):
base_img, labels, train_index2pos, test_index2pos, all_index2pos, margin, patch_size
= self.get_train_test_patches(norm_data, self.labels, self.TR, self.TE)
print('------[data] split data to train, test------')
print("train len: %s" % len(train_index2pos ))
print("test len : %s" % len(test_index2pos ))
print("all len: %s" % len(all_index2pos ))
trainset = DataSetIter(base_img, labels, train_index2pos, margin, patch_size, self.append_dim)
unlabelset=DataSetIter(base_img,labels,test_index2pos,margin, patch_size, self.append_dim)
testset = DataSetIter(base_img, labels, test_index2pos , margin, patch_size, self.append_dim)
allset = DataSetIter(base_img, labels, all_index2pos, margin, patch_size, self.append_dim)
why the unlabelset and testset used the same param "test_index2pos" to create the dataset? Is this a problem?
In the data_provider.py, in the class HSIDataLoader->def prepare_data(self):
base_img, labels, train_index2pos, test_index2pos, all_index2pos, margin, patch_size
= self.get_train_test_patches(norm_data, self.labels, self.TR, self.TE)