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Two tiny improvements. #4

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Two tiny improvements. #4

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25034b6
Example_Classification: Fix default model path.
maximumspatium Jul 19, 2019
5475a29
Add an argument for specifying number of training steps.
maximumspatium Jul 20, 2019
986aa07
Classification_BatchDataset: replace scipy.misc.imread with imageio.i…
maximumspatium Jul 26, 2019
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4 changes: 2 additions & 2 deletions Classification_BatchDataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@
"""
from past.builtins import xrange
import numpy as np
import scipy.misc as misc
import imageio
import pandas as pa
import re
import os
Expand Down Expand Up @@ -121,7 +121,7 @@ def load_class(self, folder, class_index):
return None

def load_image(self,folder,image, class_index):
image = misc.imread(self.path + "/" + folder + "/" + image)
image = imageio.imread(self.path + "/" + folder + "/" + image)
nr_y = image.shape[0] // self.tile_size[0]
nr_x = image.shape[1] // self.tile_size[1]

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10 changes: 7 additions & 3 deletions Example_Classification.py
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Original file line number Diff line number Diff line change
Expand Up @@ -103,7 +103,10 @@ def main(unused_argv):

with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
for i in range(5):

print("Training the network with %d training steps..." % FLAGS.num_steps)

for i in range(FLAGS.num_steps):
batch = data_reader.next_batch(FLAGS.batch_size)
if i % 1000 == 0:
train_accuracy = accuracy.eval(feed_dict={
Expand Down Expand Up @@ -139,8 +142,9 @@ def main(unused_argv):
help='Directory for storing input data')
parser.add_argument("--batch_size", type=int, default=2, help="batch size for training")
parser.add_argument("--test_batch_size", type=int, default=200, help="batch size for training")
parser.add_argument("--model_path", type=str, default="Models/deepscores_class.ckpt",
parser.add_argument("--num_steps", type=int, default=5, help="Number of training steps")
parser.add_argument("--model_path", type=str, default="./Models/deepscores_class.ckpt",
help="where to store the trained model")

FLAGS, unparsed = parser.parse_known_args()
tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)