import tensorflow as tf

from datetime import datetime
from sklearn.metrics import confusion_matrix
from sklearn.metrics import classification_report

slim = tf.contrib.slim

global first
first = True

classnum=12
testnum = tf.placeholder(tf.int32)
trainnum = tf.placeholder(tf.int32)
validnum = tf.placeholder(tf.int32)
learnrate = tf.placeholder(tf.float32)

def getinputs(path):
    filename_queue=tf.train.string_input_producer([path])
    reader=tf.TFRecordReader()
    _,serialized_example=reader.read(filename_queue)
    features=tf.parse_single_example(serialized_example,
                                     features={
                                        'label':tf.FixedLenFeature([], tf.int64),
                                        'img_raw' : tf.FixedLenFeature([], tf.string),
                                     })
