def test_03_01_non_contiguous(self):
'''make sure MeasureObjectAreaShape doesn't crash if fed non-contiguous objects'''
module = cpmoas.MeasureObjectAreaShape()
module.object_groups[0].name.value = "SomeObjects"
module.calculate_zernikes.value = True
object_set = cpo.ObjectSet()
labels = np.zeros((10, 20), int)
labels[1:9, 1:5] = 1
labels[4:6, 6:19] = 1
objects = cpo.Objects()
objects.segmented = labels
object_set.add_objects(objects, "SomeObjects")
module.module_num = 1
image_set_list = cpi.ImageSetList()
measurements = cpmeas.Measurements()
pipeline = cpp.Pipeline()
pipeline.add_module(module)
def callback(caller, event):
self.assertFalse(isinstance(event, cpp.RunExceptionEvent))
pipeline.add_listener(callback)
workspace = cpw.Workspace(pipeline, module,
image_set_list.get_image_set(0),
object_set, measurements, image_set_list)
module.run(workspace)
values = measurements.get_current_measurement("SomeObjects",
"AreaShape_Perimeter")
self.assertEqual(len(values), 1)
self.assertEqual(values[0], 54)
def test_01_00_zeros(self):
"""Run on an empty labels matrix"""
object_set = cpo.ObjectSet()
labels = np.zeros((10, 20), int)
objects = cpo.Objects()
objects.segmented = labels
object_set.add_objects(objects, "SomeObjects")
module = cpmoas.MeasureObjectAreaShape()
settings = ["SomeObjects", "Yes"]
module.set_settings_from_values(settings, 1, module.module_class())
module.module_num = 1
image_set_list = cpi.ImageSetList()
measurements = cpmeas.Measurements()
pipeline = cpp.Pipeline()
pipeline.add_module(module)
workspace = cpw.Workspace(pipeline, module,
image_set_list.get_image_set(0),
object_set, measurements, image_set_list)
module.run(workspace)
for f in (cpmoas.F_AREA, cpmoas.F_CENTER_X, cpmoas.F_CENTER_Y,
cpmoas.F_ECCENTRICITY, cpmoas.F_EULER_NUMBER,
cpmoas.F_EXTENT, cpmoas.F_FORM_FACTOR,
cpmoas.F_MAJOR_AXIS_LENGTH, cpmoas.F_MINOR_AXIS_LENGTH,
cpmoas.F_ORIENTATION, cpmoas.F_PERIMETER,
cpmoas.F_SOLIDITY, cpmoas.F_COMPACTNESS,
cpmoas.F_MAXIMUM_RADIUS, cpmoas.F_MEAN_RADIUS,
cpmoas.F_MEDIAN_RADIUS,
cpmoas.F_MIN_FERET_DIAMETER, cpmoas.F_MAX_FERET_DIAMETER):
m = cpmoas.AREA_SHAPE + "_" + f
a = measurements.get_current_measurement('SomeObjects', m)
self.assertEqual(len(a), 0)
def test_04_01_extent(self):
module = cpmoas.MeasureObjectAreaShape()
module.object_groups[0].name.value = "SomeObjects"
module.calculate_zernikes.value = True
object_set = cpo.ObjectSet()
labels = np.zeros((10, 20), int)
# 3/4 of a square is covered
labels[5:7, 5:10] = 1
labels[7:9, 5:15] = 1
objects = cpo.Objects()
objects.segmented = labels
object_set.add_objects(objects, "SomeObjects")
module.module_num = 1
image_set_list = cpi.ImageSetList()
measurements = cpmeas.Measurements()
pipeline = cpp.Pipeline()
pipeline.add_module(module)
def callback(caller, event):
self.assertFalse(isinstance(event, cpp.RunExceptionEvent))
pipeline.add_listener(callback)
workspace = cpw.Workspace(pipeline, module,
image_set_list.get_image_set(0),
object_set, measurements, image_set_list)
module.run(workspace)
values = measurements.get_current_measurement(
"SomeObjects", "_".join((cpmoas.AREA_SHAPE, cpmoas.F_EXTENT)))
self.assertEqual(len(values), 1)
self.assertAlmostEqual(values[0], .75)
def test_05_01_overlapping(self):
'''Test object measurement with two overlapping objects in ijv format'''
i, j = np.mgrid[0:10, 0:20]
m = (i > 1) & (i < 9) & (j > 1) & (j < 19)
m1 = m & (i < j)
m2 = m & (i < 9 - j)
mlist = []
olist = []
for m in (m1, m2):
objects = cpo.Objects()
objects.segmented = m.astype(int)
olist.append(objects)
ijv = np.column_stack((
np.hstack([np.argwhere(m)[:, 0] for m in (m1, m2)]),
np.hstack([np.argwhere(m)[:, 1] for m in (m1, m2)]),
np.array([1] * np.sum(m1) + [2] * np.sum(m2))))
objects = cpo.Objects()
objects.ijv = ijv
olist.append(objects)
for objects in olist:
module = cpmoas.MeasureObjectAreaShape()
module.object_groups[0].name.value = "SomeObjects"
module.calculate_zernikes.value = True
object_set = cpo.ObjectSet()
object_set.add_objects(objects, "SomeObjects")
module.module_num = 1
image_set_list = cpi.ImageSetList()
measurements = cpmeas.Measurements()
mlist.append(measurements)
pipeline = cpp.Pipeline()
pipeline.add_module(module)
def callback(caller, event):
self.assertFalse(isinstance(event, cpp.RunExceptionEvent))
pipeline.add_listener(callback)
workspace = cpw.Workspace(pipeline, module,
image_set_list.get_image_set(0),
object_set, measurements, image_set_list)
module.run(workspace)
for c in module.get_measurement_columns(None):
oname, feature = c[:2]
if oname != "SomeObjects":
continue
measurements = mlist[0]
self.assertTrue(isinstance(measurements, cpmeas.Measurements))
v1 = measurements.get_current_measurement(oname, feature)
self.assertEqual(len(v1), 1)
v1 = v1[0]
measurements = mlist[1]
v2 = measurements.get_current_measurement(oname, feature)
self.assertEqual(len(v2), 1)
v2 = v2[0]
expected = (v1, v2)
v = mlist[2].get_current_measurement(oname, feature)
self.assertEqual(tuple(v), expected)
def test_02_03_measurements_no_zernike(self):
module = cpmoas.MeasureObjectAreaShape()
settings = ["SomeObjects", "OtherObjects", "No"]
module.set_settings_from_values(settings, 1, module.module_class())
for object_name in settings[:-1]:
measurements = module.get_measurements(None, object_name, 'AreaShape')
for measurement in cpmoas.F_STANDARD:
self.assertTrue(measurement in measurements)
self.assertFalse('Zernike_3_1' in measurements)
def test_02_01_categories(self):
module = cpmoas.MeasureObjectAreaShape()
settings = ["SomeObjects", "OtherObjects", "Yes"]
module.set_settings_from_values(settings, 1, module.module_class())
for object_name in settings[:-1]:
categories = module.get_categories(None, object_name)
self.assertEqual(len(categories), 1)
self.assertEqual(categories[0], "AreaShape")
self.assertEqual(len(module.get_categories(None, "Bogus")), 0)
def make_workspace(self, labels):
image_set_list = cpi.ImageSetList()
image_set = image_set_list.get_image_set(0)
object_set = cpo.ObjectSet()
objects = cpo.Objects()
objects.segmented = labels
object_set.add_objects(objects, OBJECTS_NAME)
m = cpmeas.Measurements()
module = cpmoas.MeasureObjectAreaShape()
module.module_num = 1
module.object_groups[0].name.value = OBJECTS_NAME
pipeline = cpp.Pipeline()
def callback(caller, event):
self.assertFalse(isinstance(event, cpp.RunExceptionEvent))
pipeline.add_listener(callback)
pipeline.add_module(module)
workspace = cpw.Workspace(pipeline, module, image_set, object_set,
m, image_set_list)
return workspace, module
def test_03_02_zernikes_are_different(self):
'''Regression test of IMG-773'''
np.random.seed(32)
labels = np.zeros((40, 20), int)
#
# Make two "objects" composed of random foreground/background
#
labels[1:19,
1:19] = (np.random.uniform(size=(18, 18)) > .5).astype(int)
labels[21:39,
1:19] = (np.random.uniform(size=(18, 18)) > .5).astype(int) * 2
objects = cpo.Objects()
objects.segmented = labels
object_set = cpo.ObjectSet()
object_set.add_objects(objects, "SomeObjects")
module = cpmoas.MeasureObjectAreaShape()
module.object_groups[0].name.value = "SomeObjects"
module.calculate_zernikes.value = True
module.module_num = 1
image_set_list = cpi.ImageSetList()
measurements = cpmeas.Measurements()
pipeline = cpp.Pipeline()
pipeline.add_module(module)
def callback(caller, event):
self.assertFalse(isinstance(event, cpp.RunExceptionEvent))
pipeline.add_listener(callback)
workspace = cpw.Workspace(pipeline, module,
image_set_list.get_image_set(0), object_set,
measurements, image_set_list)
module.run(workspace)
features = [
x[1] for x in module.get_measurement_columns(pipeline)
if x[0] == "SomeObjects" and x[1].startswith("AreaShape_Zernike")
]
for feature in features:
values = measurements.get_current_measurement(
"SomeObjects", feature)
self.assertEqual(len(values), 2)
self.assertNotEqual(values[0], values[1])
def test_01_02_run(self):
"""Run with a rectangle, cross and circle"""
object_set = cpo.ObjectSet()
labels = np.zeros((10, 20), int)
labels[1:9, 1:5] = 1
labels[1:9, 11] = 2
labels[4, 6:19] = 2
objects = cpo.Objects()
objects.segmented = labels
object_set.add_objects(objects, "SomeObjects")
labels = np.zeros((115, 115), int)
x, y = np.mgrid[-50:51, -50:51]
labels[:101, :101][x ** 2 + y ** 2 <= 2500] = 1
objects = cpo.Objects()
objects.segmented = labels
object_set.add_objects(objects, "OtherObjects")
module = cpmoas.MeasureObjectAreaShape()
settings = ["SomeObjects", "OtherObjects", "Yes"]
module.set_settings_from_values(settings, 1, module.module_class())
module.module_num = 1
image_set_list = cpi.ImageSetList()
measurements = cpmeas.Measurements()
pipeline = cpp.Pipeline()
pipeline.add_module(module)
workspace = cpw.Workspace(pipeline, module,
image_set_list.get_image_set(0),
object_set, measurements, image_set_list)
module.run(workspace)
self.features_and_columns_match(measurements, module)
a = measurements.get_current_measurement('SomeObjects', 'AreaShape_Area')
self.assertEqual(len(a), 2)
self.assertEqual(a[0], 32)
self.assertEqual(a[1], 20)
#
# Mini-test of the form factor of a circle
#
ff = measurements.get_current_measurement('OtherObjects',
'AreaShape_FormFactor')
self.assertEqual(len(ff), 1)
perim = measurements.get_current_measurement('OtherObjects',
'AreaShape_Perimeter')
area = measurements.get_current_measurement('OtherObjects',
'AreaShape_Area')
# The perimeter is obtained geometrically and is overestimated.
expected = 100 * np.pi
diff = abs((perim[0] - expected) / (perim[0] + expected))
self.assertTrue(diff < .05, "perimeter off by %f" % diff)
wrongness = (perim[0] / expected) ** 2
# It's an approximate circle...
expected = np.pi * 50.0 ** 2
diff = abs((area[0] - expected) / (area[0] + expected))
self.assertTrue(diff < .05, "area off by %f" % diff)
wrongness *= expected / area[0]
self.assertAlmostEqual(ff[0] * wrongness, 1.0)
for object_name, object_count in (('SomeObjects', 2),
('OtherObjects', 1)):
for measurement in module.get_measurements(pipeline, object_name,
'AreaShape'):
feature_name = 'AreaShape_%s' % measurement
m = measurements.get_current_measurement(object_name,
feature_name)
self.assertEqual(len(m), object_count)
