import os

code_root = "/home/cristi/PycharmProjects/heart-chamber-identification"
data_root = "/home/cristi/PycharmProjects/segmentation/datasets/HVSMR2016/Training short-axis cropped"
train_path = os.path.join(data_root, "Training dataset")
label_path = os.path.join(data_root, "Ground truth")
test_path = "/home/cristi/PycharmProjects/segmentation/datasets/HVSMR2016/Test short-axis cropped/Test dataset"

nr_patients = 10
crop_size = 192
batch_size = 24
seed = 2019
classes = 3
weights = [0.1, 0.45, 0.45]
epochs = 150
MODEL_CHECKPOINT = 'model-hvsmr.h5'

### TRAINING ###
# optimizer options
optimizer = "adam"
learning_rate = 0.001
momentum = None  # Used only by SGD optimizer
decay = 0.

# augmentation
validation_split = 0.1
rotation_range = 180
width_shift_range = 0.1
height_shift_range = 0.1
shear_range = 0.1
zoom_range = 0.05
fill_mode = 'nearest'
vertical_flip = True
horizontal_flip = True
alpha = 500
sigma = 20

9658816690f95da9789f0c6230ef68ebc1afa4e8
<mask token>

<mask token>
code_root = '/home/cristi/PycharmProjects/heart-chamber-identification'
data_root = (
    '/home/cristi/PycharmProjects/segmentation/datasets/HVSMR2016/Training short-axis cropped'
    )
train_path = os.path.join(data_root, 'Training dataset')
label_path = os.path.join(data_root, 'Ground truth')
test_path = (
    '/home/cristi/PycharmProjects/segmentation/datasets/HVSMR2016/Test short-axis cropped/Test dataset'
    )
nr_patients = 10
crop_size = 192
batch_size = 24
seed = 2019
classes = 3
weights = [0.1, 0.45, 0.45]
epochs = 150
MODEL_CHECKPOINT = 'model-hvsmr.h5'
optimizer = 'adam'
learning_rate = 0.001
momentum = None
decay = 0.0
validation_split = 0.1
rotation_range = 180
width_shift_range = 0.1
height_shift_range = 0.1
shear_range = 0.1
zoom_range = 0.05
fill_mode = 'nearest'
vertical_flip = True
horizontal_flip = True
alpha = 500
sigma = 20

import os
code_root = '/home/cristi/PycharmProjects/heart-chamber-identification'
data_root = (
    '/home/cristi/PycharmProjects/segmentation/datasets/HVSMR2016/Training short-axis cropped'
    )
train_path = os.path.join(data_root, 'Training dataset')
label_path = os.path.join(data_root, 'Ground truth')
test_path = (
    '/home/cristi/PycharmProjects/segmentation/datasets/HVSMR2016/Test short-axis cropped/Test dataset'
    )
nr_patients = 10
crop_size = 192
batch_size = 24
seed = 2019
classes = 3
weights = [0.1, 0.45, 0.45]
epochs = 150
MODEL_CHECKPOINT = 'model-hvsmr.h5'
optimizer = 'adam'
learning_rate = 0.001
momentum = None
decay = 0.0
validation_split = 0.1
rotation_range = 180
width_shift_range = 0.1
height_shift_range = 0.1
shear_range = 0.1
zoom_range = 0.05
fill_mode = 'nearest'
vertical_flip = True
horizontal_flip = True
alpha = 500
sigma = 20

import os

code_root = "/home/cristi/PycharmProjects/heart-chamber-identification"
data_root = "/home/cristi/PycharmProjects/segmentation/datasets/HVSMR2016/Training short-axis cropped"
train_path = os.path.join(data_root, "Training dataset")
label_path = os.path.join(data_root, "Ground truth")
test_path = "/home/cristi/PycharmProjects/segmentation/datasets/HVSMR2016/Test short-axis cropped/Test dataset"

nr_patients = 10
crop_size = 192
batch_size = 24
seed = 2019
classes = 3
weights = [0.1, 0.45, 0.45]
epochs = 150
MODEL_CHECKPOINT = 'model-hvsmr.h5'

### TRAINING ###
# optimizer options
optimizer = "adam"
learning_rate = 0.001
momentum = None  # Used only by SGD optimizer
decay = 0.

# augmentation
validation_split = 0.1
rotation_range = 180
width_shift_range = 0.1
height_shift_range = 0.1
shear_range = 0.1
zoom_range = 0.05
fill_mode = 'nearest'
vertical_flip = True
horizontal_flip = True
alpha = 500
sigma = 20
