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Update 228_training_aerial_imagery.py #38

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Update 228_training_aerial_imagery.py #38

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8 changes: 4 additions & 4 deletions 228_semantic_segmentation_of_aerial_imagery_using_unet/228_training_aerial_imagery.py
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Original file line number Diff line number Diff line change
Expand Up @@ -177,8 +177,8 @@
label = single_patch_mask

# Now replace RGB to integer values to be used as labels.
#Find pixels with combination of RGB for the above defined arrays...
#if matches then replace all values in that pixel with a specific integer
# Find pixels with combination of RGB for the above defined arrays...
# if matches then replace all values in that pixel with a specific integer
def rgb_to_2D_label(label):
"""
Suply our labale masks as input in RGB format.
Expand Down Expand Up @@ -207,7 +207,7 @@ def rgb_to_2D_label(label):

print("Unique labels in label dataset are: ", np.unique(labels))

#Another Sanity check, view few mages
#Another Sanity check, view few images
import random
import numpy as np
image_number = random.randint(0, len(image_dataset))
Expand Down Expand Up @@ -287,7 +287,7 @@ def get_model():

#model.save('models/satellite_standard_unet_100epochs_7May2021.hdf5')
############################################################
#TRY ANOTHE MODEL - WITH PRETRINED WEIGHTS
#TRY ANOTHER MODEL - WITH PRETRAINED WEIGHTS
#Resnet backbone
BACKBONE = 'resnet34'
preprocess_input = sm.get_preprocessing(BACKBONE)
Expand Down