def input_pipeline(self, batch_size, num_epochs=None, aug=False):
images_tensor = tf.convert_to_tensor(self.image_names, dtype=tf.string)
labels_tensor = tf.convert_to_tensor(self.labels, dtype=tf.int64)
input_queue = tf.train.slice_input_producer([images_tensor, labels_tensor], num_epochs=num_epochs)
labels = input_queue[1]
images_content = tf.read_file(input_queue[0])
images = tf.image.convert_image_dtype(tf.image.decode_png(images_content, channels=1), tf.float32)
if aug:
images = self.data_augmentation(images)
new_size = tf.constant([FLAGS.image_size, FLAGS.image_size], dtype=tf.int32)
images = tf.image.resize_images(images, new_size)
image_batch, label_batch = tf.train.shuffle_batch([images, labels], batch_size=batch_size, capacity=50000,
min_after_dequeue=10000)
# print 'image_batch', image_batch.get_shape()
return image_batch, label_batch
chinese_character_recognition_bn.py 文件源码
python
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