def test_laplacian_has_correct_size(self):
# gaussian pyramid
p_collection = PyramidManager(self._images, self._config).laplacian_pyramid(self._depth)
# number of layers in the collection
self.assertEqual(p_collection.get_number_of_layers(), 2)
collection_layer_0 = p_collection.get_pyramid(0)
# high of the pyramid in the collection
self.assertEqual(collection_layer_0.get_depth(), self._depth)
# sieze of first level is half of level zero
self.assertEqual(collection_layer_0.get_level(1).get_array().shape, (2, 2))
def test_that_the_top_of_pyramids_has_the_lowest_resolution(self):
l = PyramidManager(self._images, self._config).laplacian_pyramid(self._depth).get_pyramid(0)
p = PyramidManager(self._images, self._config)._gaussian_pyramid(self._depth).get_pyramid(0)
# top level has lowest resolution
self.assertLess(l.get_top_level().array.shape[0], l.get_level(0).array.shape[0])
# top level has lowest resolution
self.assertLess(p.get_top_level().array.shape[0], p.get_level(0).array.shape[0])
def test_top_level_of_laplacian_and_gaussian_pyramids_are_the_same(self):
l = PyramidManager(self._images, self._config).laplacian_pyramid(
self._depth).get_pyramid(0)
p = PyramidManager(self._images, self._config)._gaussian_pyramid(
self._depth).get_pyramid(0)
#top level
self.assertIn(l.get_top_level().get_array(),
p.get_top_level().get_array())
def composite(self):
log = logging.getLogger(".".join([__name__, self.__class__.__name__]))
log.addFilter(logconfig.ThreadContextFilter())
extra = self._config.all_to_json()
log = logging.LoggerAdapter(log, extra)
log.info("Focusstack Started, first image, " +
self._image_file_list[0].name)
log.debug(extra)
start_t = time.time()
t1 = time.time()
man = ImageFFTManager(self._image_file_list)
man.read_ftt_images()
sd = SharpnessDetector(man.get_fft_images(), self._config)
images = sd.images_to_stack()
self.fft_images = sd.get_fft_images_to_stack()
t2 = time.time() - t1
#add extra field to the log
extra = {'FTT_time': t2}
log = logging.LoggerAdapter(log, extra)
log.info("FFT calculation finished")
log.debug(extra)
images = np.array(images, dtype=images[0].dtype)
#TODO:Implement alignment algo
#aligned_images, gray_images = self.align(images)
#stacked_image = pyramid(aligned_images, self._config).get_pyramid_fusion()
stacked_image = PyramidManager(images,
self._config).get_pyramid_fusion()
stacked_image = cv2.convertScaleAbs(stacked_image)
backtorgb = cv2.cvtColor(stacked_image, cv2.COLOR_GRAY2RGB)
calculation_time = time.time() - start_t
extra = {'stack_time': calculation_time}
log = logging.LoggerAdapter(log, extra)
log.info("Stacking Finished")
log.debug(extra)
return Image(backtorgb)
def test_get_pyramid_fusion_calls_laplacian_pyramid_once(self):
self._config.pyramid_min_size.value.return_value = 1
p = PyramidManager(self._images, self._config)
p.laplacian_pyramid = MagicMock(return_value = MagicMock())
p.get_pyramid_fusion()
p.laplacian_pyramid.assert_called_once()