def test_combine(self): img1_array = scipy.misc.lena() img2_array = scipy.misc.lena() sub_result = analyse.combine('img1 - img2', img1_array, img2_array) self.assertEqual(0, sub_result.sum()) add_result = analyse.combine('img1 + img2', img1_array, img2_array) add_testval = img1_array.ravel()[0] + img2_array.ravel()[0] self.assertEqual(add_testval, add_result.ravel()[0])
def test_combine_unequal_dimensions(self): """Check if smaller image is casted to bigger one.""" img1_array = scipy.misc.lena() smaller_array = np.ones(shape=(100, 100, 3), dtype=np.uint8) # rgb img result = analyse.combine('img1 - img2', img1_array, smaller_array) self.assertEqual(result.shape, img1_array.shape) bigger_array = np.ones(shape=(1000, 100, 3), dtype=np.uint8) # rgb img result = analyse.combine('img1 - img2', img1_array, bigger_array) self.assertEqual(result.shape, bigger_array.shape) testval = img1_array.ravel()[0] - 1 self.assertEqual(testval, result.ravel()[0])
def test_combine_output(self): img1_array = scipy.misc.lena() img2_array = scipy.misc.lena() with imgs.TempFile() as tmp_path: analyse.combine('img1 ^ img2', img1_array, img2_array, tmp_path) self.assertTrue(os.path.isfile(tmp_path))