from __future__ import division, print_function, absolute_import import os.path import tempfile import shutil import numpy as np import warnings import glob from numpy.testing import (assert_equal, dec, decorate_methods, TestCase, run_module_suite, assert_allclose, assert_array_equal) from scipy import misc try: import PIL.Image except ImportError: _have_PIL = False else: _have_PIL = True # Function / method decorator for skipping PIL tests on import failure _pilskip = dec.skipif(not _have_PIL, 'Need to import PIL for this test') datapath = os.path.dirname(__file__) class TestPILUtil(TestCase): def test_imresize(self): im = np.random.random((10, 20)) for T in np.sctypes['float'] + [float]: # 1.1 rounds to below 1.1 for float16, 1.101 works im1 = misc.imresize(im, T(1.101)) assert_equal(im1.shape, (11, 22)) def test_imresize2(self): im = np.random.random((20, 30)) im2 = misc.imresize(im, (30, 40), interp='bicubic') assert_equal(im2.shape, (30, 40)) def test_imresize3(self): im = np.random.random((15, 30)) im2 = misc.imresize(im, (30, 60), interp='nearest') assert_equal(im2.shape, (30, 60)) def test_imresize4(self): im = np.array([[1, 2], [3, 4]]) # Check that resizing by target size, float and int are the same im2 = misc.imresize(im, (4, 4), mode='F') # output size im3 = misc.imresize(im, 2., mode='F') # fraction im4 = misc.imresize(im, 200, mode='F') # percentage assert_equal(im2, im3) assert_equal(im2, im4) def test_imresize5(self): im = np.random.random((25, 15)) im2 = misc.imresize(im, (30, 60), interp='lanczos') assert_equal(im2.shape, (30, 60)) def test_bytescale(self): x = np.array([0, 1, 2], np.uint8) y = np.array([0, 1, 2]) assert_equal(misc.bytescale(x), x) assert_equal(misc.bytescale(y), [0, 127, 255]) def test_bytescale_keywords(self): x = np.array([40, 60, 120, 200, 300, 500]) res_lowhigh = misc.bytescale(x, low=10, high=143) assert_equal(res_lowhigh, [10, 16, 33, 56, 85, 143]) res_cmincmax = misc.bytescale(x, cmin=60, cmax=300) assert_equal(res_cmincmax, [0, 0, 64, 149, 255, 255]) assert_equal(misc.bytescale(np.array([3, 3, 3]), low=4), [4, 4, 4]) def test_imsave(self): picdir = os.path.join(datapath, "data") for png in glob.iglob(picdir + "/*.png"): with warnings.catch_warnings(record=True): # PIL ResourceWarning img = misc.imread(png) tmpdir = tempfile.mkdtemp() try: fn1 = os.path.join(tmpdir, 'test.png') fn2 = os.path.join(tmpdir, 'testimg') # PIL ResourceWarning with warnings.catch_warnings(record=True): misc.imsave(fn1, img) misc.imsave(fn2, img, 'PNG') # PIL ResourceWarning with warnings.catch_warnings(record=True): data1 = misc.imread(fn1) data2 = misc.imread(fn2) assert_allclose(data1, img) assert_allclose(data2, img) assert_equal(data1.shape, img.shape) assert_equal(data2.shape, img.shape) finally: shutil.rmtree(tmpdir) decorate_methods(TestPILUtil, _pilskip) def tst_fromimage(filename, irange, shape): fp = open(filename, "rb") img = misc.fromimage(PIL.Image.open(fp)) fp.close() imin, imax = irange assert_equal(img.min(), imin) assert_equal(img.max(), imax) assert_equal(img.shape, shape) @_pilskip def test_fromimage(): # Test generator for parametric tests # Tuples in the list are (filename, (datamin, datamax), shape). files = [('icon.png', (0, 255), (48, 48, 4)), ('icon_mono.png', (0, 255), (48, 48, 4)), ('icon_mono_flat.png', (0, 255), (48, 48, 3))] for fn, irange, shape in files: yield tst_fromimage, os.path.join(datapath, 'data', fn), irange, shape @_pilskip def test_imread_indexed_png(): # 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) filename = os.path.join(datapath, 'data', 'foo3x5x4indexed.png') im = misc.imread(filename) assert_array_equal(im, data) @_pilskip def test_imread_1bit(): # box1.png is a 48x48 grayscale image with bit depth 1. # The border pixels are 1 and the rest are 0. filename = os.path.join(datapath, 'data', 'box1.png') with open(filename, 'rb') as f: im = misc.imread(f) assert_equal(im.dtype, np.uint8) expected = np.zeros((48, 48), dtype=np.uint8) # When scaled up from 1 bit to 8 bits, 1 becomes 255. expected[:, 0] = 255 expected[:, -1] = 255 expected[0, :] = 255 expected[-1, :] = 255 assert_equal(im, expected) @_pilskip def test_imread_2bit(): # blocks2bit.png is a 12x12 grayscale image with bit depth 2. # The pattern is 4 square subblocks of size 6x6. Upper left # is all 0, upper right is all 1, lower left is all 2, lower # right is all 3. # When scaled up to 8 bits, the values become [0, 85, 170, 255]. filename = os.path.join(datapath, 'data', 'blocks2bit.png') with open(filename, 'rb') as f: im = misc.imread(f) assert_equal(im.dtype, np.uint8) expected = np.zeros((12, 12), dtype=np.uint8) expected[:6, 6:] = 85 expected[6:, :6] = 170 expected[6:, 6:] = 255 assert_equal(im, expected) @_pilskip def test_imread_4bit(): # pattern4bit.png is a 12(h) x 31(w) grayscale image with bit depth 4. # The value in row j and column i is maximum(j, i) % 16. # When scaled up to 8 bits, the values become [0, 17, 34, ..., 255]. filename = os.path.join(datapath, 'data', 'pattern4bit.png') with open(filename, 'rb') as f: im = misc.imread(f) assert_equal(im.dtype, np.uint8) # When the oldest supported version of numpy is 1.7, the following # line can be change to # j, i = np.meshgrid(np.arange(12), np.arange(31), indexing='ij') j, i = [k.T for k in np.meshgrid(np.arange(12), np.arange(31))] expected = 17*(np.maximum(j, i) % 16).astype(np.uint8) assert_equal(im, expected) if __name__ == "__main__": run_module_suite()