import os.path import numpy as np from numpy.testing import ( assert_array_equal, assert_array_almost_equal, assert_raises, assert_allclose, run_module_suite) from tempfile import NamedTemporaryFile from ... import data_dir, img_as_float from .. import imread, imsave, use_plugin, reset_plugins from ..._shared.testing import mono_check, color_check from ..._shared._warnings import expected_warnings from ..._shared._tempfile import temporary_file from six import BytesIO from PIL import Image from .._plugins.pil_plugin import ( pil_to_ndarray, ndarray_to_pil, _palette_is_grayscale) from ...measure import compare_ssim as ssim from ...color import rgb2lab def setup(): use_plugin('pil') def teardown(): reset_plugins() def setup_module(self): """The effect of the `plugin.use` call may be overridden by later imports. Call `use_plugin` directly before the tests to ensure that PIL is used. """ try: use_plugin('pil') except ImportError: pass def test_png_round_trip(): f = NamedTemporaryFile(suffix='.png') fname = f.name f.close() I = np.eye(3) imsave(fname, I) Ip = img_as_float(imread(fname)) os.remove(fname) assert np.sum(np.abs(Ip-I)) < 1e-3 def test_imread_flatten(): # a color image is flattened img = imread(os.path.join(data_dir, 'color.png'), flatten=True) assert img.ndim == 2 assert img.dtype == np.float64 img = imread(os.path.join(data_dir, 'camera.png'), flatten=True) # check that flattening does not occur for an image that is grey already. assert np.sctype2char(img.dtype) in np.typecodes['AllInteger'] def test_imread_separate_channels(): # Test that imread returns RGBA values contiguously even when they are # stored in separate planes. x = np.random.rand(3, 16, 8) f = NamedTemporaryFile(suffix='.tif') fname = f.name f.close() imsave(fname, x) img = imread(fname) os.remove(fname) assert img.shape == (16, 8, 3), img.shape def test_imread_multipage_rgb_tif(): img = imread(os.path.join(data_dir, 'multipage_rgb.tif')) assert img.shape == (2, 10, 10, 3), img.shape def test_imread_palette(): img = imread(os.path.join(data_dir, 'palette_gray.png')) assert img.ndim == 2 img = imread(os.path.join(data_dir, 'palette_color.png')) assert img.ndim == 3 def test_imread_index_png_with_alpha(): # The file `foo3x5x4indexed.png` was created with this array # (3x5 is (height)x(width)): data = np.array([[[127, 0, 255, 255], [127, 0, 255, 255], [127, 0, 255, 255], [127, 0, 255, 255], [127, 0, 255, 255]], [[192, 192, 255, 0], [192, 192, 255, 0], [0, 0, 255, 0], [0, 0, 255, 0], [0, 0, 255, 0]], [[0, 31, 255, 255], [0, 31, 255, 255], [0, 31, 255, 255], [0, 31, 255, 255], [0, 31, 255, 255]]], dtype=np.uint8) img = imread(os.path.join(data_dir, 'foo3x5x4indexed.png')) assert_array_equal(img, data) def test_palette_is_gray(): gray = Image.open(os.path.join(data_dir, 'palette_gray.png')) assert _palette_is_grayscale(gray) color = Image.open(os.path.join(data_dir, 'palette_color.png')) assert not _palette_is_grayscale(color) def test_bilevel(): expected = np.zeros((10, 10)) expected[::2] = 255 img = imread(os.path.join(data_dir, 'checker_bilevel.png')) assert_array_equal(img, expected) def test_imread_uint16(): expected = np.load(os.path.join(data_dir, 'chessboard_GRAY_U8.npy')) img = imread(os.path.join(data_dir, 'chessboard_GRAY_U16.tif')) assert np.issubdtype(img.dtype, np.uint16) assert_array_almost_equal(img, expected) def test_imread_truncated_jpg(): assert_raises((IOError, ValueError), imread, os.path.join(data_dir, 'truncated.jpg')) def test_jpg_quality_arg(): chessboard = np.load(os.path.join(data_dir, 'chessboard_GRAY_U8.npy')) with temporary_file(suffix='.jpg') as jpg: imsave(jpg, chessboard, quality=95) im = imread(jpg) sim = ssim(chessboard, im, dynamic_range=chessboard.max() - chessboard.min()) assert sim > 0.99 def test_imread_uint16_big_endian(): expected = np.load(os.path.join(data_dir, 'chessboard_GRAY_U8.npy')) img = imread(os.path.join(data_dir, 'chessboard_GRAY_U16B.tif')) assert img.dtype == np.uint16 assert_array_almost_equal(img, expected) class TestSave: def roundtrip_file(self, x): with temporary_file(suffix='.png') as fname: imsave(fname, x) y = imread(fname) return y def roundtrip_pil_image(self, x): pil_image = ndarray_to_pil(x) y = pil_to_ndarray(pil_image) return y def verify_roundtrip(self, dtype, x, y, scaling=1): assert_array_almost_equal((x * scaling).astype(np.int32), y) def verify_imsave_roundtrip(self, roundtrip_function): for shape in [(10, 10), (10, 10, 3), (10, 10, 4)]: for dtype in (np.uint8, np.uint16, np.float32, np.float64): x = np.ones(shape, dtype=dtype) * np.random.rand(*shape) if np.issubdtype(dtype, float): yield (self.verify_roundtrip, dtype, x, roundtrip_function(x), 255) else: x = (x * 255).astype(dtype) yield (self.verify_roundtrip, dtype, x, roundtrip_function(x)) def test_imsave_roundtrip_file(self): self.verify_imsave_roundtrip(self.roundtrip_file) def test_imsave_roundtrip_pil_image(self): self.verify_imsave_roundtrip(self.roundtrip_pil_image) def test_imsave_filelike(): shape = (2, 2) image = np.zeros(shape) s = BytesIO() # save to file-like object with expected_warnings(['precision loss', 'is a low contrast image']): imsave(s, image) # read from file-like object s.seek(0) out = imread(s) assert out.shape == shape assert_allclose(out, image) def test_imexport_imimport(): shape = (2, 2) image = np.zeros(shape) with expected_warnings(['precision loss']): pil_image = ndarray_to_pil(image) out = pil_to_ndarray(pil_image) assert out.shape == shape def test_all_color(): color_check('pil') color_check('pil', 'bmp') def test_all_mono(): mono_check('pil') def test_multi_page_gif(): img = imread(os.path.join(data_dir, 'no_time_for_that_tiny.gif')) assert img.shape == (24, 25, 14, 3), img.shape img2 = imread(os.path.join(data_dir, 'no_time_for_that_tiny.gif'), img_num=5) assert img2.shape == (25, 14, 3) assert_allclose(img[5], img2) def test_cmyk(): ref = imread(os.path.join(data_dir, 'color.png')) img = Image.open(os.path.join(data_dir, 'color.png')) img = img.convert('CMYK') f = NamedTemporaryFile(suffix='.jpg') fname = f.name f.close() img.save(fname) try: img.close() except AttributeError: # `close` not available on PIL pass new = imread(fname) ref_lab = rgb2lab(ref) new_lab = rgb2lab(new) for i in range(3): newi = np.ascontiguousarray(new_lab[:, :, i]) refi = np.ascontiguousarray(ref_lab[:, :, i]) sim = ssim(refi, newi, dynamic_range=refi.max() - refi.min()) assert sim > 0.99 if __name__ == "__main__": run_module_suite()