From 0c76788ed637741a720b9ad313074a1371cfbe1f Mon Sep 17 00:00:00 2001
From: Tiago Freitas Pereira <tiagofrepereira@gmail.com>
Date: Tue, 31 Oct 2017 09:30:43 +0100
Subject: [PATCH] Created a function that batches a tf-record in order and
apply data augmentation
---
bob/learn/tensorflow/dataset/tfrecords.py | 51 +++++++++++++++++++++++
1 file changed, 51 insertions(+)
diff --git a/bob/learn/tensorflow/dataset/tfrecords.py b/bob/learn/tensorflow/dataset/tfrecords.py
index 84c21ab9..faa0938a 100644
--- a/bob/learn/tensorflow/dataset/tfrecords.py
+++ b/bob/learn/tensorflow/dataset/tfrecords.py
@@ -291,4 +291,55 @@ def batch_data_and_labels(tfrecord_filenames, data_shape, data_type,
features['key'] = key
return features, labels
+
+
+def batch_data_and_labels_image_augmentation(tfrecord_filenames, data_shape, data_type,
+ batch_size, epochs=1,
+ gray_scale=False,
+ output_shape=None,
+ random_flip=False,
+ random_brightness=False,
+ random_contrast=False,
+ random_saturation=False,
+ per_image_normalization=True):
+ """
+ Dump in order batches from a list of tf-record files
+
+ **Parameters**
+
+ tfrecord_filenames:
+ List containing the tf-record paths
+
+ data_shape:
+ Samples shape saved in the tf-record
+
+ data_type:
+ tf data type(https://www.tensorflow.org/versions/r0.12/resources/dims_types#data_types)
+
+ batch_size:
+ Size of the batch
+
+ epochs:
+ Number of epochs to be batched
+
+ """
+
+ dataset = create_dataset_from_records_with_augmentation(tfrecord_filenames, data_shape,
+ data_type,
+ gray_scale=gray_scale,
+ output_shape=output_shape,
+ random_flip=random_flip,
+ random_brightness=random_brightness,
+ random_contrast=random_contrast,
+ random_saturation=random_saturation,
+ per_image_normalization=per_image_normalization)
+
+ dataset = dataset.batch(batch_size).repeat(epochs)
+
+ data, labels, key = dataset.make_one_shot_iterator().get_next()
+ features = dict()
+ features['data'] = data
+ features['key'] = key
+
+ return features, labels
--
GitLab