# Copyright 2017 Google Inc.

#

# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

#

# http://www.apache.org/licenses/LICENSE-2.0

#

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.

"""Image generators test."""

from __future__ import absolute_import

from __future__ import division

from __future__ import print_function

# Dependency imports

import numpy as np

from tensor2tensor.data_generators import image

import tensorflow as tf

class ImageTest(tf.test.TestCase):

def testImageGenerator(self):

# 2 random images

np.random.seed(1111) # To avoid any flakiness.

image1 = np.random.randint(0, 255, size=(10, 12, 3))

image2 = np.random.randint(0, 255, size=(10, 12, 3))

# Call image generator on the 2 images with labels [1, 2].

encoded_imgs, labels = [], []

for dictionary in image.image_generator([image1, image2], [1, 2]):

self.assertEqual(

sorted(list(dictionary)), [

"image/class/label", "image/encoded", "image/format",

"image/height", "image/width"

])

self.assertEqual(dictionary["image/format"], ["png"])

self.assertEqual(dictionary["image/height"], [12])

self.assertEqual(dictionary["image/width"], [10])

encoded_imgs.append(dictionary["image/encoded"])

labels.append(dictionary["image/class/label"])

# Check that the result labels match the inputs.

self.assertEqual(len(labels), 2)

self.assertEqual(labels[0], [1])

self.assertEqual(labels[1], [2])

# Decode images and check that they match the inputs.

self.assertEqual(len(encoded_imgs), 2)

image_t = tf.placeholder(dtype=tf.string)

decoded_png_t = tf.image.decode_png(image_t)

with self.test_session() as sess:

encoded_img1 = encoded_imgs[0]

self.assertEqual(len(encoded_img1), 1)

decoded1 = sess.run(decoded_png_t, feed_dict={image_t: encoded_img1[0]})

self.assertAllClose(decoded1, image1)

encoded_img2 = encoded_imgs[1]

self.assertEqual(len(encoded_img2), 1)

decoded2 = sess.run(decoded_png_t, feed_dict={image_t: encoded_img2[0]})

self.assertAllClose(decoded2, image2)

if __name__ == "__main__":

tf.test.main()