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# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# 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.
# ==============================================================================
"""Tests for decode_image."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os.path
import numpy as np
from tensorflow.python.framework import errors_impl
from tensorflow.python.ops import image_ops
from tensorflow.python.ops import io_ops
import tensorflow.python.ops.nn_grad # pylint: disable=unused-import
from tensorflow.python.platform import test
prefix_path = "tensorflow/core/lib"
class DecodeImageOpTest(test.TestCase):
def testBmp(self):
# Read a real bmp and verify shape
path = os.path.join(prefix_path, "bmp", "testdata", "lena.bmp")
with self.test_session(use_gpu=True) as sess:
bmp0 = io_ops.read_file(path)
image0 = image_ops.decode_image(bmp0)
image1 = image_ops.decode_bmp(bmp0)
bmp0, image0, image1 = sess.run([bmp0, image0, image1])
self.assertEqual(len(bmp0), 4194)
self.assertAllEqual(image0, image1)
def testGif(self):
# Read some real GIFs
path = os.path.join(prefix_path, "gif", "testdata", "scan.gif")
width = 20
height = 40
stride = 5
shape = (12, height, width, 3)
with self.test_session(use_gpu=True) as sess:
gif0 = io_ops.read_file(path)
image0 = image_ops.decode_image(gif0)
image1 = image_ops.decode_gif(gif0)
gif0, image0, image1 = sess.run([gif0, image0, image1])
self.assertEqual(image0.shape, shape)
self.assertAllEqual(image0, image1)
for frame_idx, frame in enumerate(image0):
gt = np.zeros(shape[1:], dtype=np.uint8)
start = frame_idx * stride
end = (frame_idx + 1) * stride
if end <= width:
gt[:, start:end, :] = 255
else:
start -= width
end -= width
gt[start:end, :, :] = 255
self.assertAllClose(frame, gt)
bad_channels = image_ops.decode_image(gif0, channels=1)
with self.assertRaises(errors_impl.InvalidArgumentError):
bad_channels.eval()
def testJpeg(self):
# Read a real jpeg and verify shape
path = os.path.join(prefix_path, "jpeg", "testdata", "jpeg_merge_test1.jpg")
with self.test_session(use_gpu=True) as sess:
jpeg0 = io_ops.read_file(path)
image0 = image_ops.decode_image(jpeg0)
image1 = image_ops.decode_jpeg(jpeg0)
jpeg0, image0, image1 = sess.run([jpeg0, image0, image1])
self.assertEqual(len(jpeg0), 3771)
self.assertEqual(image0.shape, (256, 128, 3))
self.assertAllEqual(image0, image1)
bad_channels = image_ops.decode_image(jpeg0, channels=4)
with self.assertRaises(errors_impl.InvalidArgumentError):
bad_channels.eval()
def testPng(self):
# Read some real PNGs, converting to different channel numbers
inputs = [(1, "lena_gray.png")]
for channels_in, filename in inputs:
for channels in 0, 1, 3, 4:
with self.test_session(use_gpu=True) as sess:
path = os.path.join(prefix_path, "png", "testdata", filename)
png0 = io_ops.read_file(path)
image0 = image_ops.decode_image(png0, channels=channels)
image1 = image_ops.decode_png(png0, channels=channels)
png0, image0, image1 = sess.run([png0, image0, image1])
self.assertEqual(image0.shape, (26, 51, channels or channels_in))
self.assertAllEqual(image0, image1)
def testInvalidBytes(self):
image_bytes = b"ThisIsNotAnImage!"
decode = image_ops.decode_image(image_bytes)
with self.cached_session():
with self.assertRaises(errors_impl.InvalidArgumentError):
decode.eval()
if __name__ == "__main__":
test.main()
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