from helper import unittest, PillowTestCase, lena from PIL import Image try: import site import numpy except ImportError: # Skip via setUp() pass class TestNumpy(PillowTestCase): def setUp(self): try: import site import numpy except ImportError: self.skipTest("ImportError") def test_numpy_to_image(self): def to_image(dtype, bands=1, bool=0): if bands == 1: if bool: data = [0, 1] * 50 else: data = list(range(100)) a = numpy.array(data, dtype=dtype) a.shape = 10, 10 i = Image.fromarray(a) if list(i.getdata()) != data: print("data mismatch for", dtype) else: data = list(range(100)) a = numpy.array([[x]*bands for x in data], dtype=dtype) a.shape = 10, 10, bands i = Image.fromarray(a) if list(i.split()[0].getdata()) != list(range(100)): print("data mismatch for", dtype) # print dtype, list(i.getdata()) return i # self.assert_image(to_image(numpy.bool, bool=1), "1", (10, 10)) # self.assert_image(to_image(numpy.bool8, bool=1), "1", (10, 10)) self.assertRaises(TypeError, lambda: to_image(numpy.uint)) self.assert_image(to_image(numpy.uint8), "L", (10, 10)) self.assertRaises(TypeError, lambda: to_image(numpy.uint16)) self.assertRaises(TypeError, lambda: to_image(numpy.uint32)) self.assertRaises(TypeError, lambda: to_image(numpy.uint64)) self.assert_image(to_image(numpy.int8), "I", (10, 10)) if Image._ENDIAN == '<': # Little endian self.assert_image(to_image(numpy.int16), "I;16", (10, 10)) else: self.assert_image(to_image(numpy.int16), "I;16B", (10, 10)) self.assert_image(to_image(numpy.int32), "I", (10, 10)) self.assertRaises(TypeError, lambda: to_image(numpy.int64)) self.assert_image(to_image(numpy.float), "F", (10, 10)) self.assert_image(to_image(numpy.float32), "F", (10, 10)) self.assert_image(to_image(numpy.float64), "F", (10, 10)) self.assert_image(to_image(numpy.uint8, 3), "RGB", (10, 10)) self.assert_image(to_image(numpy.uint8, 4), "RGBA", (10, 10)) # based on an erring example at http://is.gd/6F0esS (which resolves to) # http://stackoverflow.com/questions/10854903/what-is-causing-dimension-dependent-attributeerror-in-pil-fromarray-function def test_3d_array(self): a = numpy.ones((10, 10, 10), dtype=numpy.uint8) self.assert_image(Image.fromarray(a[1, :, :]), "L", (10, 10)) self.assert_image(Image.fromarray(a[:, 1, :]), "L", (10, 10)) self.assert_image(Image.fromarray(a[:, :, 1]), "L", (10, 10)) def _test_img_equals_nparray(self, img, np): self.assertEqual(img.size, np.shape[0:2]) px = img.load() for x in range(0, img.size[0], int(img.size[0]/10)): for y in range(0, img.size[1], int(img.size[1]/10)): self.assert_deep_equal(px[x, y], np[y, x]) def test_16bit(self): img = Image.open('Tests/images/16bit.cropped.tif') np_img = numpy.array(img) self._test_img_equals_nparray(img, np_img) self.assertEqual(np_img.dtype, numpy.dtype('u2'), ("I;16L", '