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import numpy as np
import pytest
from keras_preprocessing.image import utils
def test_validate_filename(tmpdir):
valid_extensions = ('png', 'jpg')
filename = tmpdir.ensure('test.png')
assert utils.validate_filename(str(filename), valid_extensions)
filename = tmpdir.ensure('test.PnG')
assert utils.validate_filename(str(filename), valid_extensions)
filename = tmpdir.ensure('test.some_extension')
assert not utils.validate_filename(str(filename), valid_extensions)
assert not utils.validate_filename('some_test_file.png', valid_extensions)
def test_load_img(tmpdir):
filename_rgb = str(tmpdir / 'rgb_utils.png')
filename_rgba = str(tmpdir / 'rgba_utils.png')
original_rgb_array = np.array(255 * np.random.rand(100, 100, 3),
dtype=np.uint8)
original_rgb = utils.array_to_img(original_rgb_array, scale=False)
original_rgb.save(filename_rgb)
original_rgba_array = np.array(255 * np.random.rand(100, 100, 4),
dtype=np.uint8)
original_rgba = utils.array_to_img(original_rgba_array, scale=False)
original_rgba.save(filename_rgba)
# Test that loaded image is exactly equal to original.
loaded_im = utils.load_img(filename_rgb)
loaded_im_array = utils.img_to_array(loaded_im)
assert loaded_im_array.shape == original_rgb_array.shape
assert np.all(loaded_im_array == original_rgb_array)
loaded_im = utils.load_img(filename_rgba, color_mode='rgba')
loaded_im_array = utils.img_to_array(loaded_im)
assert loaded_im_array.shape == original_rgba_array.shape
assert np.all(loaded_im_array == original_rgba_array)
loaded_im = utils.load_img(filename_rgb, color_mode='grayscale')
loaded_im_array = utils.img_to_array(loaded_im)
assert loaded_im_array.shape == (original_rgb_array.shape[0],
original_rgb_array.shape[1], 1)
# Test that nothing is changed when target size is equal to original.
loaded_im = utils.load_img(filename_rgb, target_size=(100, 100))
loaded_im_array = utils.img_to_array(loaded_im)
assert loaded_im_array.shape == original_rgb_array.shape
assert np.all(loaded_im_array == original_rgb_array)
loaded_im = utils.load_img(filename_rgba, color_mode='rgba',
target_size=(100, 100))
loaded_im_array = utils.img_to_array(loaded_im)
assert loaded_im_array.shape == original_rgba_array.shape
assert np.all(loaded_im_array == original_rgba_array)
loaded_im = utils.load_img(filename_rgb, color_mode='grayscale',
target_size=(100, 100))
loaded_im_array = utils.img_to_array(loaded_im)
assert loaded_im_array.shape == (original_rgba_array.shape[0],
original_rgba_array.shape[1], 1)
# Test down-sampling with bilinear interpolation.
loaded_im = utils.load_img(filename_rgb, target_size=(25, 25))
loaded_im_array = utils.img_to_array(loaded_im)
assert loaded_im_array.shape == (25, 25, 3)
loaded_im = utils.load_img(filename_rgba, color_mode='rgba',
target_size=(25, 25))
loaded_im_array = utils.img_to_array(loaded_im)
assert loaded_im_array.shape == (25, 25, 4)
loaded_im = utils.load_img(filename_rgb, color_mode='grayscale',
target_size=(25, 25))
loaded_im_array = utils.img_to_array(loaded_im)
assert loaded_im_array.shape == (25, 25, 1)
# Test down-sampling with nearest neighbor interpolation.
loaded_im_nearest = utils.load_img(filename_rgb, target_size=(25, 25),
interpolation="nearest")
loaded_im_array_nearest = utils.img_to_array(loaded_im_nearest)
assert loaded_im_array_nearest.shape == (25, 25, 3)
assert np.any(loaded_im_array_nearest != loaded_im_array)
loaded_im_nearest = utils.load_img(filename_rgba, color_mode='rgba',
target_size=(25, 25),
interpolation="nearest")
loaded_im_array_nearest = utils.img_to_array(loaded_im_nearest)
assert loaded_im_array_nearest.shape == (25, 25, 4)
assert np.any(loaded_im_array_nearest != loaded_im_array)
# Check that exception is raised if interpolation not supported.
loaded_im = utils.load_img(filename_rgb, interpolation="unsupported")
with pytest.raises(ValueError):
loaded_im = utils.load_img(filename_rgb, target_size=(25, 25),
interpolation="unsupported")
def test_list_pictures(tmpdir):
filenames = ['test.png', 'test0.jpg', 'test-1.jpeg', '2test.bmp',
'2-test.ppm', '3.png', '1.jpeg', 'test.bmp', 'test0.ppm',
'test4.tiff', '5-test.tif', 'test.txt', 'foo.csv',
'face.gif', 'bar.txt']
subdirs = ['', 'subdir1', 'subdir2']
filenames = [tmpdir.ensure(subdir, f) for subdir in subdirs
for f in filenames]
found_images = utils.list_pictures(str(tmpdir))
assert len(found_images) == 33
found_images = utils.list_pictures(str(tmpdir), ext='png')
assert len(found_images) == 6
def test_array_to_img_and_img_to_array():
height, width = 10, 8
# Test the data format
# Test RGB 3D
x = np.random.random((3, height, width))
img = utils.array_to_img(x, data_format='channels_first')
assert img.size == (width, height)
x = utils.img_to_array(img, data_format='channels_first')
assert x.shape == (3, height, width)
# Test RGBA 3D
x = np.random.random((4, height, width))
img = utils.array_to_img(x, data_format='channels_first')
assert img.size == (width, height)
x = utils.img_to_array(img, data_format='channels_first')
assert x.shape == (4, height, width)
# Test 2D
x = np.random.random((1, height, width))
img = utils.array_to_img(x, data_format='channels_first')
assert img.size == (width, height)
x = utils.img_to_array(img, data_format='channels_first')
assert x.shape == (1, height, width)
# Test tf data format
# Test RGB 3D
x = np.random.random((height, width, 3))
img = utils.array_to_img(x, data_format='channels_last')
assert img.size == (width, height)
x = utils.img_to_array(img, data_format='channels_last')
assert x.shape == (height, width, 3)
# Test RGBA 3D
x = np.random.random((height, width, 4))
img = utils.array_to_img(x, data_format='channels_last')
assert img.size == (width, height)
x = utils.img_to_array(img, data_format='channels_last')
assert x.shape == (height, width, 4)
# Test 2D
x = np.random.random((height, width, 1))
img = utils.array_to_img(x, data_format='channels_last')
assert img.size == (width, height)
x = utils.img_to_array(img, data_format='channels_last')
assert x.shape == (height, width, 1)
# Test invalid use case
with pytest.raises(ValueError):
x = np.random.random((height, width)) # not 3D
img = utils.array_to_img(x, data_format='channels_first')
with pytest.raises(ValueError):
x = np.random.random((height, width, 3))
# unknown data_format
img = utils.array_to_img(x, data_format='channels')
with pytest.raises(ValueError):
# neither RGB, RGBA, or gray-scale
x = np.random.random((height, width, 5))
img = utils.array_to_img(x, data_format='channels_last')
with pytest.raises(ValueError):
x = np.random.random((height, width, 3))
# unknown data_format
img = utils.img_to_array(x, data_format='channels')
with pytest.raises(ValueError):
# neither RGB, RGBA, or gray-scale
x = np.random.random((height, width, 5, 3))
img = utils.img_to_array(x, data_format='channels_last')
if __name__ == '__main__':
pytest.main([__file__])
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