def test_put_probmap_data_dimorder_zxyc(self): img_path = os.path.join( base_path, '../test_data/ilastik/dimensionstest/images/*') label_path = os.path.join( base_path, '../test_data/ilastik/dimensionstest/x15_y10_z2_c4_classes2.ilp') with tempfile.TemporaryDirectory() as tmpdirname: c = TiffConnector(img_path, 'some/path', savepath=tmpdirname) d = Dataset(c) size = (2, 3, 5) # zxy batch_size = 1 # shape: 1 batch, 4 channels, 2 z, 3 x, 5 y p = PredictionBatch(d, batch_size, size) self.assertEqual((1, 4, 2, 3, 5), p[0].pixels().shape) self.assertEqual((1, 4, 2, 3, 5), p[1].pixels().shape) p.set_pixel_dimension_order('bzxyc') self.assertEqual((1, 2, 3, 5, 4), p[0].pixels().shape) self.assertEqual((1, 2, 3, 5, 4), p[1].pixels().shape) pixels = p[0].pixels() for tile in p: tile.put_probmap_data(pixels)
def test_pixel_dimensions(self): img_path = os.path.abspath( os.path.join(base_path, '../test_data/tiffconnector_1/im/*')) c = io_connector(img_path, '', savepath=self.tmpdir) d = Dataset(c) size = (1, 5, 4) batch_size = 2 p = PredictionBatch(d, batch_size, size)[0] print(p.pixels().shape) self.assertEqual((2, 3, 1, 5, 4), p.pixels().shape) p.set_pixel_dimension_order('bzxyc') self.assertEqual((2, 1, 5, 4, 3), p.pixels().shape)