def test_01_01_combine(self):
img = self.get_my_image()
inj = cpm_inject.InjectImage("my_image", img)
inj.module_num = 1
ctg = cpm_ctg.ColorToGray()
ctg.module_num = 2
ctg.image_name.value = "my_image"
ctg.combine_or_split.value = cpm_ctg.COMBINE
ctg.red_contribution.value = 1
ctg.green_contribution.value = 2
ctg.blue_contribution.value = 3
ctg.grayscale_name.value = "my_grayscale"
pipeline = cpp.Pipeline()
pipeline.add_module(inj)
pipeline.add_module(ctg)
pipeline.test_valid()
measurements = cpm.Measurements()
object_set = cpo.ObjectSet()
image_set_list = cpi.ImageSetList()
workspace = Workspace(pipeline, inj, None, None, measurements,
image_set_list, None)
inj.prepare_run(workspace)
inj.prepare_group(workspace, {}, [1])
image_set = image_set_list.get_image_set(0)
inj.run(Workspace(pipeline, inj, image_set, object_set, measurements, None))
ctg.run(Workspace(pipeline, ctg, image_set, object_set, measurements, None))
grayscale = image_set.get_image("my_grayscale")
self.assertTrue(grayscale)
img = grayscale.image
self.assertAlmostEqual(img[0, 0], 1.0 / 6.0)
self.assertAlmostEqual(img[0, 25], 1.0 / 3.0)
self.assertAlmostEqual(img[25, 0], 1.0 / 2.0)
self.assertAlmostEqual(img[25, 25], 0)
def test_01_04_split_channels(self):
np.random.seed(13)
image = np.random.uniform(size=(20, 10, 5))
image_set_list = cpi.ImageSetList()
image_set = image_set_list.get_image_set(0)
image_set.add(IMAGE_NAME, cpi.Image(image))
module = cpm_ctg.ColorToGray()
module.module_num = 1
module.image_name.value = IMAGE_NAME
module.combine_or_split.value = cpm_ctg.SPLIT
module.rgb_or_channels.value = cpm_ctg.CH_CHANNELS
module.add_channel()
module.add_channel()
channel_indexes = np.array([1, 4, 2])
for i, channel_index in enumerate(channel_indexes):
module.channels[i].channel_choice.value = module.channel_names[channel_index]
module.channels[i].image_name.value = OUTPUT_IMAGE_F % i
pipeline = cpp.Pipeline()
def callback(caller, event):
self.assertFalse(isinstance(event, cpp.RunExceptionEvent))
pipeline.add_listener(callback)
pipeline.add_module(module)
workspace = Workspace(pipeline, module, image_set, cpo.ObjectSet(),
cpm.Measurements(), image_set_list)
module.run(workspace)
for i, channel_index in enumerate(channel_indexes):
pixels = image_set.get_image(module.channels[i].image_name.value).pixel_data
self.assertEqual(pixels.ndim, 2)
self.assertEqual(tuple(pixels.shape), (20, 10))
np.testing.assert_almost_equal(image[:, :, channel_index], pixels)
def test_01_02_split_all(self):
img = self.get_my_image()
inj = cpm_inject.InjectImage("my_image", img)
inj.module_num = 1
ctg = cpm_ctg.ColorToGray()
ctg.module_num = 2
ctg.image_name.value = "my_image"
ctg.combine_or_split.value = cpm_ctg.SPLIT
ctg.use_red.value = True
ctg.use_blue.value = True
ctg.use_green.value = True
ctg.red_name.value = "my_red"
ctg.green_name.value = "my_green"
ctg.blue_name.value = "my_blue"
pipeline = cpp.Pipeline()
pipeline.add_module(inj)
pipeline.add_module(ctg)
pipeline.test_valid()
measurements = cpm.Measurements()
object_set = cpo.ObjectSet()
image_set_list = cpi.ImageSetList()
workspace = Workspace(pipeline, inj, None, None, measurements,
image_set_list, None)
inj.prepare_run(workspace)
inj.prepare_group(workspace, {}, [1])
image_set = image_set_list.get_image_set(0)
inj.run(
Workspace(pipeline, inj, image_set, object_set, measurements,
None))
ctg.run(
Workspace(pipeline, ctg, image_set, object_set, measurements,
None))
red = image_set.get_image("my_red")
self.assertTrue(red)
img = red.image
self.assertAlmostEqual(img[0, 0], 1)
self.assertAlmostEqual(img[0, 25], 0)
self.assertAlmostEqual(img[25, 0], 0)
self.assertAlmostEqual(img[25, 25], 0)
green = image_set.get_image("my_green")
self.assertTrue(green)
img = green.image
self.assertAlmostEqual(img[0, 0], 0)
self.assertAlmostEqual(img[0, 25], 1)
self.assertAlmostEqual(img[25, 0], 0)
self.assertAlmostEqual(img[25, 25], 0)
blue = image_set.get_image("my_blue")
self.assertTrue(blue)
img = blue.image
self.assertAlmostEqual(img[0, 0], 0)
self.assertAlmostEqual(img[0, 25], 0)
self.assertAlmostEqual(img[25, 0], 1)
self.assertAlmostEqual(img[25, 25], 0)
def test_01_03_combine_channels(self):
np.random.seed(13)
image = np.random.uniform(size=(20, 10, 5))
image_set_list = cpi.ImageSetList()
image_set = image_set_list.get_image_set(0)
image_set.add(IMAGE_NAME, cpi.Image(image))
module = cpm_ctg.ColorToGray()
module.module_num = 1
module.image_name.value = IMAGE_NAME
module.combine_or_split.value = cpm_ctg.COMBINE
module.grayscale_name.value = OUTPUT_IMAGE_F % 1
module.rgb_or_channels.value = cpm_ctg.CH_CHANNELS
module.add_channel()
module.add_channel()
channel_indexes = np.array([2, 0, 3])
factors = np.random.uniform(size=3)
divisor = np.sum(factors)
expected = np.zeros((20, 10))
for i, channel_index in enumerate(channel_indexes):
module.channels[i].channel_choice.value = module.channel_names[
channel_index]
module.channels[i].contribution.value_text = "%.10f" % factors[i]
expected += image[:, :, channel_index] * factors[i] / divisor
pipeline = cpp.Pipeline()
def callback(caller, event):
self.assertFalse(isinstance(event, cpp.RunExceptionEvent))
pipeline.add_listener(callback)
pipeline.add_module(module)
workspace = Workspace(pipeline, module, image_set, cpo.ObjectSet(),
cpm.Measurements(), image_set_list)
module.run(workspace)
pixels = image_set.get_image(module.grayscale_name.value).pixel_data
self.assertEqual(pixels.ndim, 2)
self.assertEqual(tuple(pixels.shape), (20, 10))
np.testing.assert_almost_equal(expected, pixels)
def test_00_00_init(self):
x = cpm_ctg.ColorToGray()
