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2017/04/20 01:00

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@@ -244,356 +244,34 @@
 inference.py以外のコードは
-model.py
-```ここに言語を入力
-# coding: utf-8
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-import tensorflow as tf
-NUM_CLASSES = 10
-def _get_weights(shape,stddev=1.0):
-  var = tf.get_variable(
-      'weights',
-      shape,
-      initializer=tf.truncated_normal_initializer(stddev=stddev)
-  )
-  return var
-def _get_biases(shape,value=0.0):
-  var = tf.get_variable(
-      'biases',
-      shape,
-      initializer=tf.constant_initializer(value)
-  )
-  return var
-def inference(image_node):
-   #  conv1
-   with tf.variable_scope('conv1') as scope:
-     weights = _get_weights(shape=[5,5,3,64],stddev=1e-4)
-     conv = tf.nn.conv2d(image_node,weights,[1,1,1,1],padding='SAME')
-     biases = _get_biases([64],value=0.1)
-     bias = tf.nn.bias_add(conv,biases)
-     conv1 = tf.nn.relu(bias,name=scope.name)
-   #  pool
-   pool1 = tf.nn.max_pool(conv1,ksize=[1,3,3,1],strides=[1,2,2,1],padding='SAME',name='pool1')
-   #  conv2
-   with tf.variable_scope('conv2') as scope:
-     weights = _get_weights(shape=[5,5,64,64],stddev=1e-4)
-     conv = tf.nn.conv2d(pool1,weights,[1,1,1,1],padding='SAME')
-     biases = _get_biases([64],value=0.1)
-     bias = tf.nn.bias_add(conv,biases)
-     conv2 = tf.nn.relu(bias,name=scope.name)
-   #  pool2
-   pool2 = tf.nn.max_pool(conv2,ksize=[1,3,3,1],strides=[1,2,2,1],padding='SAME',name='pool2')
-   reshape = tf.reshape(pool2,[1,-1])
-   dim = reshape.get_shape()[1].value
-   #  fc3
-   with tf.variable_scope('fc3') as scope:
-       weights = _get_weights(shape=[dim,384],stddev=0.04)
-       biases = _get_biases([384],value=0.1)
-       fc3 = tf.nn.relu(
-           tf.matmul(reshape,weights) + biases,
-           name=scope.name
-       )
-   #  fc4
-   with tf.variable_scope('fc4') as scope:
-       weights = _get_weights(shape=[384,192],stddev=0.04)
-       biases = _get_biases([192],value=0.1)
-       fc4 = tf.nn.relu(tf.matmul(fc3,weights) + biases,name=scope.name)
-   #   output
-   with tf.variable_scope('output') as scope:
-       weights = _get_weights(shape=[192,NUM_CLASSES],stddev=1/192.0)
-       biases = _get_biases([NUM_CLASSES],value=0.0)
-       logits = tf.add(tf.matmul(fc4,weights),biases,name='logits')
-   return logits
-```
-reader.py
-```ここに言語を入力
-# -*- coding: utf-8 -*-
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-import os
-import numpy as np
-class Cifar10Record(object):
-    width = 32
-    height = 32
-    depth = 3
-    def set_label(self,label_byte):
-        #self.label = np.frombuffer(label_byte,dtype=np.unit8)
-        self.label = np.frombuffer(label_byte,dtype=np.uint8) # unit8 -> uint8に修正
-    def set_image(self,image_bytes):
-        byte_buffer = np.frombuffer(image_bytes,dtype=np.int8)
-        reshaped_array = np.reshape(byte_buffer,[self.depth,self.height,self.width])
-        self.byte_array = np.transpose(reshaped_array,[1,2,0])
-        self.byte_array = self.byte_array.astype(np.float32)
-class Cifar10Reader(object):
- def __init__(self,filename):
-     if not os.path.exists(filename):
-         print(filename + ' is not exist')
-         return
-     self.bytestream = open(filename,mode="rb")
- def close(self):
-     if not self.bytestream:
-         self.bytestream.close()
- def read(self,index):
-     result = Cifar10Record()
-     label_bytes = 1
-     image_bytes = result.height * result.width * result.depth
-     record_bytes = label_bytes + image_bytes
-     self.bytestream.seek(record_bytes * index,0)
-     result.set_label(self.bytestream.read(label_bytes))
-     result.set_image(self.bytestream.read(image_bytes))
-     return result
-     print(self.bytestream)
-# 追加
-reader = Cifar10Reader("lena_std.tif")
-ret = reader.read(0)
-print(ret)
-```
-png10.py
-```ここに言語を入力
-# coding: utf-8
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-import os
-import numpy as np
-import tensorflow as tf
-from PIL import Image
-from reader import Cifar10Reader
-FLAGS = tf.app.flags.FLAGS
-tf.app.flags.DEFINE_string('file',None,"処理するファイルのパス")
-tf.app.flags.DEFINE_integer('offset',0,"読み飛ばすレコード数")
-tf.app.flags.DEFINE_integer('length',16,"読み込んで変換するレコード数")
-basename = os.path.basename(FLAGS.file)
-path = os.path.dirname(FLAGS.file)
-reader = Cifar10Reader(FLAGS.file)
-stop = FLAGS.offset + FLAGS.length
-for index in range(FLAGS.offset,stop):
+前回に記載した通りになっています。
+https://teratail.com/questions/71848?whotofollow=
+ちなみにエラーの全体は
+Traceback (most recent call last):
+  File "inference.py", line 72, in <module>
+    tf.app.run()
+  File "/Users/XXX/anaconda/envs/py36/lib/python3.6/site-packages/tensorflow/python/platform/app.py", line 44, in run
+    _sys.exit(main(_sys.argv[:1] + flags_passthrough))
+  File "inference.py", line 49, in main
     image = reader.read(index)
+  File "/Users/XXX/Desktop/cifar/reader.py", line 42, in read
-    print('label: %d' % image.label)
+    self.bytestream.seek(record_bytes * index,0)
-    imageshow = Image.fromarray(image.byte_array.astype(np.unit8))
-    file_name = '%s-%02d-%d.png' % (basename,index,image.label)
+AttributeError: 'Cifar10Reader' object has no attribute 'bytestream'
-    file = os.path.join(path,file_name)
-    with open(file,mode='wb') as out:
-        imageshow.save(out,format='png')
-reader.close()
-```
 のようになっています。