mjsynth.py 文件源码

def _read_word_record(data_queue):

    reader = tf.TFRecordReader() # Construct a general reader
    key, example_serialized = reader.read(data_queue) 

    feature_map = {
        'image/encoded':  tf.FixedLenFeature( [], dtype=tf.string, 
                                              default_value='' ),
        'image/labels':   tf.VarLenFeature( dtype=tf.int64 ), 
        'image/width':    tf.FixedLenFeature( [1], dtype=tf.int64,
                                              default_value=1 ),
        'image/filename': tf.FixedLenFeature([], dtype=tf.string,
                                             default_value='' ),
        'text/string':     tf.FixedLenFeature([], dtype=tf.string,
                                             default_value='' ),
        'text/length':    tf.FixedLenFeature( [1], dtype=tf.int64,
                                              default_value=1 )
    }
    features = tf.parse_single_example( example_serialized, feature_map )

    image = tf.image.decode_jpeg( features['image/encoded'], channels=1 ) #gray
    width = tf.cast( features['image/width'], tf.int32) # for ctc_loss
    label = tf.serialize_sparse( features['image/labels'] ) # for batching
    length = features['text/length']
    text = features['text/string']
    filename = features['image/filename']
    return image,width,label,length,text,filename