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So2Sat-LCZ42 / v4 /read_file.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
# File : read_file.py
# Author : Jingliang Hu
# Date : 15.08.2018 14:05:08
# Last Modified Date: 15.08.2018 14:05:08
# Last Modified By : Yuanyuan Wang <[email protected]>
# Last modified: 15.08.2018 14:06:23 Yuanyuan Wang
# added visualization
# Last modified: 19.11.2025 Qi Zhang, Yi Wang
# added geolocation
import h5py
import numpy as np
import matplotlib.pyplot as plt
# select one of the given files
fileOfChoice = 'validation.h5'
# show the variables in selected file
fid = h5py.File(fileOfChoice,'r')
print('INFO: The names of variables in the file of \''+fileOfChoice+'\':')
print fid.keys()
# load the data into memory
print('INFO: Loading sentinel-1 data patches ...')
s1 = np.array(fid['sen1'])
print('INFO: Sentinel-1 data dimension:')
print(s1.shape)
print('INFO: Loading sentinel-2 data patches ...')
s2 = np.array(fid['sen2'])
print('INFO: Sentinel-2 data dimension:')
print(s2.shape)
print('INFO: Loading label ...')
lab = np.array(fid['label'])
print('INFO: Label dimension:')
print(lab.shape)
# visualization, plot the first pair of Sentinel-1 and Sentinel-2 patches of training.h5
plt.subplot(121)
plt.imshow(10*np.log10(s1[0,:,:,4]),cmap=plt.cm.get_cmap('gray'))
plt.colorbar()
plt.title('Sentinel-1')
plt.subplot(122)
plt.imshow(s2[0,:,:,1],cmap=plt.cm.get_cmap('gray'))
plt.colorbar()
plt.title('Sentinel-2')
plt.show()
#%%
# select one of the given files
fileOfChoice = 'validation_geo.h5'
# show the variables in selected file
fid = h5py.File(fileOfChoice,'r')
print('INFO: The names of variables in the file of \''+fileOfChoice+'\':')
# load the data into memory
print('INFO: Loading coordinate data ...')
coord = np.array(fid['coord'])
print('INFO: Coordinate data dimension:')
print(coord.shape)
# load the data into memory
print('INFO: Loading epsg data ...')
tfw = np.array(fid['tfw'])
print('INFO: tfw data dimension:')
print(tfw.shape)
# load the data into memory
print('INFO: Loading epsg data ...')
epsg = np.array(fid['epsg'])
print('INFO: epsg data dimension:')
print(epsg.shape)