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preprocess-4band-atlantic-forest-data.py
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preprocess-4band-atlantic-forest-data.py
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import numpy as np
import os
import rioxarray as rxr
#
# Pre-Process GeoTIFF Atlantic Forest dataset
#
# Ingest images
base_dir3 = r"./ATLANTIC FOREST/"
## Training images
training_images_list3 = os.listdir(r"{}Training/image/".format(base_dir3))[0:250]
training_masks_list3 = []
training_images3 = []
for n in training_images_list3:
training_masks_list3.append(n)
a = (np.array(rxr.open_rasterio(r"{}Training/image/{}".format(base_dir3,n))))
a = (a-np.min(a)) / (np.max(a)-np.min(a))
training_images3.append(a)
## Training masks
training_masks3 = []
for n in training_masks_list3:
a = (np.array(rxr.open_rasterio(r"{}Training/label/{}".format(base_dir3,n))))
training_masks3.append(a)
## Test images
test_images_list3 = os.listdir(r"{}Test/image/".format(base_dir3))
test_masks_list3 = []
test_images3 = []
for n in test_images_list3:
test_masks_list3.append(n)
a = (np.array(rxr.open_rasterio(r"{}Test/image/{}".format(base_dir3,n))))
a = (a-np.min(a)) / (np.max(a)-np.min(a))
test_images3.append(a)
## Test masks
test_masks3 = []
for n in test_masks_list3:
a = (np.array(rxr.open_rasterio(r"{}Test/mask/{}".format(base_dir3,n))))
test_masks3.append(a)
## Validation images
validation_images_list3 = os.listdir(r"{}Validation/images/".format(base_dir3))
validation_masks_list3 = []
validation_images3 = []
for n in validation_images_list3:
validation_masks_list3.append(n)
a = (np.array(rxr.open_rasterio(r"{}Validation/images/{}".format(base_dir3,n))))
a = (a-np.min(a)) / (np.max(a)-np.min(a))
validation_images3.append(a)
## Validation masks
validation_masks3 = []
for n in validation_masks_list3:
a = (np.array(rxr.open_rasterio(r"{}Validation/masks/{}".format(base_dir3,n))))
validation_masks3.append(a)
# Pre-process data
for i in range(len(training_images3)):
#training_images3[i] = training_images3[i].reshape(1,512,512,4)
training_images3[i] = training_images3[i].astype('float32')
training_images3[i] = training_images3[i].T
for i in range(len(training_masks3)):
#training_masks3[i] = training_masks3[i][:512,:512]
training_masks3[i] = training_masks3[i].reshape(1,512,512,1)
training_masks3[i] = training_masks3[i].T
for i in range(len(validation_images3)):
#validation_images3[i] = validation_images3[i].reshape(1,512,512,4)
validation_images3[i] = validation_images3[i].astype('float32')
validation_images3[i] = validation_images3[i].T
for i in range(len(validation_masks3)):
#validation_masks3[i] = validation_masks3[i][:512,:512]
validation_masks3[i] = validation_masks3[i].reshape(1,512,512,1)
validation_masks3[i] = validation_masks3[i].T
for i in range(len(test_images3)):
#test_images3[i] = test_images3[i].reshape(1,512,512,4)
test_images3[i] = test_images3[i].astype('float32')
test_images3[i] = test_images3[i].T
for i in range(len(test_masks3)):
#test_masks3[i] = test_masks3[i][:512,:512]
test_masks3[i] = test_masks3[i].reshape(1,512,512,1)
test_masks3[i] = test_masks3[i].T
for i in range(len(training_images3)):
training_images3[i] = training_images3[i].reshape(-1,512,512,4)
for i in range(len(validation_images3)):
validation_images3[i] = validation_images3[i].reshape(-1,512,512,4)
for i in range(len(test_images3)):
test_images3[i] = test_images3[i].reshape(-1,512,512,4)
#
# Output as .npy files
#
os.mkdir('atlantic-processed-large')
os.chdir('atlantic-processed-large')
os.mkdir('training')
os.mkdir('test')
os.mkdir('validation')
os.chdir('training')
os.mkdir('images')
os.mkdir('masks')
os.chdir('images')
for i in range(len(training_images3)):
np.save(training_images_list3[i], training_images3[i])
os.chdir('../masks')
for i in range(len(training_masks3)):
np.save(training_masks_list3[i], training_masks3[i])
os.chdir('..')
os.chdir('../test')
os.mkdir('images')
os.mkdir('masks')
os.chdir('images')
for i in range(len(test_images3)):
np.save(test_images_list3[i], test_images3[i])
os.chdir('../masks')
for i in range(len(test_masks3)):
np.save(test_masks_list3[i], test_masks3[i])
os.chdir('..')
os.chdir('../validation')
os.mkdir('images')
os.mkdir('masks')
os.chdir('images')
for i in range(len(validation_images3)):
np.save(validation_images_list3[i], validation_images3[i])
os.chdir('../masks')
for i in range(len(validation_masks3)):
np.save(validation_masks_list3[i], validation_masks3[i])
os.chdir('..')