import tensorflow as tf
from tensorflow.python.framework import ops
import math
import time
import matplotlib.pyplot as plt
from generate_input import load_STONE_data
# Load training data, cropped and resized from MATLAB
tic1 = time.time()
# Folder with images
dir_train = "/home/chongduan/Documents/Automap-MRI/Datasett"
n_cases = (0,3) # load 70 cases
X_train, Y_train = load_STONE_data( # Load images for training
dir_train,
n_cases,
normalize=True,
imrotate=True,
motion=True)
toc1 = time.time()
print('Time to load data = ', (toc1 - tic1))
print('X_train.shape at input = ', X_train.shape)
print('Y_train.shape at input = ', Y_train.shape)
def create_placeholders(n_H0, n_W0):
""" Creates placeholders for x and y for tf.session
:param n_H0: image height
:param n_W0: image width
:return: x and y - tf placeholders
"""
#n_cases = (0,1) # load image data from 0 to 2
#X_dev, Y_dev = load_images_from_folder( # Load images for training
# dir_dev,
# n_cases,
# normalize=False,
# imrotate=False)
#print('X_dev.shape at input = ', X_dev.shape)
#print('Y_dev.shape at input = ', Y_dev.shape)
# Load training data, cropped and resized from MATLAB
# Folder with images
dir_train = "/home/chongduan/Documents/11_AUTOMAP/Dataset"
n_cases = 3 # load 3 cases
X_dev, Y_dev = load_STONE_data( # Load images for training
dir_train,
n_cases,
normalize=False,
imrotate=False)
print('X_train.shape at input = ', X_dev.shape)
print('Y_train.shape at input = ', Y_dev.shape)
def create_placeholders(n_H0, n_W0):
""" Creates placeholders for x and y for tf.session
:param n_H0: image height
:param n_W0: image width
:return: x and y - tf placeholders
"""
x = tf.placeholder(tf.float32, shape=[None, n_H0, n_W0, 2], name='x')
y = tf.placeholder(tf.float32, shape=[None, n_H0, n_W0], name='y')
import numpy as np
import tensorflow as tf
from tensorflow.python.framework import ops
import math
import time
import matplotlib.pyplot as plt
from generate_input import load_STONE_data
# Load training data, cropped and resized from MATLAB
tic1 = time.time()
dir_train = "/home/chongduan/Documents/Automap-MRI/Dataset"
n_cases = (0,1)
X_train, Y_train = load_STONE_data(
dir_train,
n_cases,
normalize=False,
imrotate=False,
motion=True)
toc1 = time.time()
print('Time to load data = ', (toc1 - tic1))
print('X_train.shape at input = ', X_train.shape)
print('Y_train.shape at input = ', Y_train.shape)
def create_placeholders(n_H0, n_W0):
""" Creates placeholders for x and y for tf.session
:param n_H0: image height
:param n_W0: image width
:return: x and y - tf placeholders
"""