def test_draw_bounding_box(self):
"""Test case for draw_bounding_box."""
width = 560
height = 320
channels = 4
with open(
os.path.join(os.path.dirname(os.path.abspath(__file__)),
"test_image", "small-00.png"), 'rb') as f:
png_contents = f.read()
with open(
os.path.join(os.path.dirname(os.path.abspath(__file__)),
"test_image", "small-bb.png"), 'rb') as f:
ex_png_contents = f.read()
with self.cached_session():
ex_image_p = image.decode_png(ex_png_contents, channels=channels)
ex_image_p = tf.expand_dims(ex_image_p, 0)
# TODO: Travis seems to have issues with different rendering. Skip for now.
# ex_image_v = ex_image_p.eval()
_ = ex_image_p.eval()
bb = [[[0.1, 0.2, 0.5, 0.9]]]
with self.cached_session():
image_p = image.decode_png(png_contents, channels=channels)
image_v = image_p.eval()
self.assertEqual(image_v.shape, (height, width, channels))
image_p = image.convert_image_dtype(image_p, tf.float32)
image_p = tf.expand_dims(image_p, 0)
bb_image_p = image_io.draw_bounding_boxes(image_p, bb,
["hello world!"])
bb_image_p = image.convert_image_dtype(bb_image_p, tf.uint8)
# TODO: Travis seems to have issues with different rendering. Skip for now.
# bb_image_v = bb_image_p.eval()
# self.assertAllEqual(bb_image_v, ex_image_v)
_ = bb_image_p.eval()
def test_tiff_file_dataset(self):
"""Test case for TIFFDataset.
"""
width = 560
height = 320
channels = 4
images = []
for filename in ["small-00.png", "small-01.png", "small-02.png", "small-03.png", "small-04.png"]:
with open(os.path.join(os.path.dirname(os.path.abspath(__file__)), "test_image", filename), 'rb') as f:
png_contents = f.read()
with self.cached_session():
image_p = image.decode_png(png_contents, channels=channels)
image_v = image_p.eval()
self.assertEqual(image_v.shape, (height, width, channels))
images.append(image_v)
filename = os.path.join(os.path.dirname(os.path.abspath(__file__)), "test_image", "small.tiff")
filename = "file://" + filename
num_repeats = 2
dataset = image_io.TIFFDataset([filename]).repeat(num_repeats)
iterator = dataset.make_initializable_iterator()
init_op = iterator.initializer
get_next = iterator.get_next()
with self.cached_session() as sess:
sess.run(init_op)
for _ in range(num_repeats):
for i in range(5):
v = sess.run(get_next)
self.assertAllEqual(images[i], v)
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
def test_webp_file_dataset(self):
"""Test case for WebPDataset.
"""
width = 400
height = 301
channel = 4
png_file = os.path.join(os.path.dirname(os.path.abspath(__file__)), "test_image", "sample.png")
with open(png_file, 'rb') as f:
png_contents = f.read()
with self.cached_session():
image_p = image.decode_png(png_contents, channels=channel)
image_v = image_p.eval()
self.assertEqual(image_v.shape, (height, width, channel))
filename = os.path.join(os.path.dirname(os.path.abspath(__file__)), "test_image", "sample.webp")
num_repeats = 2
dataset = image_io.WebPDataset([filename]).repeat(
num_repeats)
iterator = dataset.make_initializable_iterator()
init_op = iterator.initializer
get_next = iterator.get_next()
with self.cached_session() as sess:
sess.run(init_op)
for _ in range(num_repeats): # Dataset is repeated.
v = sess.run(get_next)
self.assertAllEqual(image_v, v)
with self.assertRaises(errors.OutOfRangeError):
sess.run(get_next)
def test_decode_webp(self):
"""Test case for decode_webp.
"""
width = 400
height = 301
channel = 4
png_file = os.path.join(os.path.dirname(os.path.abspath(__file__)),
"test_image", "sample.png")
with open(png_file, 'rb') as f:
png_contents = f.read()
filename = os.path.join(os.path.dirname(os.path.abspath(__file__)),
"test_image", "sample.webp")
with open(filename, 'rb') as f:
webp_contents = f.read()
with self.cached_session():
png_op = image.decode_png(png_contents, channels=channel)
png = png_op.eval()
self.assertEqual(png.shape, (height, width, channel))
webp_p = image_io.decode_webp(webp_contents)
webp_v = webp_p.eval()
self.assertEqual(webp_v.shape, (height, width, channel))
self.assertAllEqual(webp_v, png)
def image_generator(test_size=0.2, testing=False):
path = '/content/drive/My Drive/Flickr_Faces'
no_of_images = len(os.listdir(path))
if testing:
list_of_images = os.listdir(path)[int(no_of_images * test_size):]
else:
list_of_images = os.listdir(path)[:int(no_of_images * test_size)]
for filename in list_of_images:
img = os.path.join(path, filename)
img = read_file(img)
img = decode_png(img, channels=3)
yield img / 255
def load_image(file_path):
img = read_file(file_path)
# decode and resize image
img = decode_png(img, channels=3)
img = resize(img, [32, 32])
return img
def plotImages(figure):
buf = BytesIO()
plt.savefig(buf, format='png')
plt.close(figure)
buf.seek(0)
return expand_dims(_image.decode_png(buf.getvalue(), channels=4), 0)
