def test_02_03_clean_pipeline(self):
pipeline = cpp.Pipeline()
load_images = LoadImages()
load_images.module_num = 1
load_images.add_imagecb()
load_images.images[0].channels[0].image_name.value = "Foo"
load_images.images[1].channels[0].image_name.value = "Bar"
pipeline.add_module(load_images)
identify = IdentifyPrimaryObjects()
identify.module_num = 2
identify.x_name.value = "Foo"
identify.y_name.value = "dizzy"
pipeline.add_module(identify)
saveimages = SaveImages()
saveimages.module_num = 3
saveimages.image_name.value = "Foo"
pipeline.add_module(saveimages)
measureobjectsizeshape = MeasureObjectSizeShape()
measureobjectsizeshape.module_num = 4
measureobjectsizeshape.object_groups[0].name.value = "dizzy"
pipeline.add_module(measureobjectsizeshape)
pipeline_txt = StringIO()
pipeline.savetxt(pipeline_txt)
module_names = json.dumps([SaveImages.module_name])
message = [
zmq.Frame(self.session_id),
zmq.Frame(),
zmq.Frame(CLEAN_PIPELINE_REQ_1),
zmq.Frame(pipeline_txt.getvalue()),
zmq.Frame(module_names)
]
self.socket.send_multipart(message)
message = self.socket.recv_multipart()
self.assertEqual(message.pop(0), self.session_id)
self.assertEqual(message.pop(0), "")
self.assertEqual(message.pop(0), CLEAN_PIPELINE_REPLY_1)
pipeline_txt = message.pop(0)
pipeline = cpp.Pipeline()
pipeline.loadtxt(StringIO(pipeline_txt))
self.assertEqual(len(pipeline.modules()), 3)
self.assertIsInstance(pipeline.modules()[0], LoadImages)
self.assertIsInstance(pipeline.modules()[1], IdentifyPrimaryObjects)
self.assertIsInstance(pipeline.modules()[2], MeasureObjectSizeShape)
def test_02_03_clean_pipeline(self):
pipeline = cpp.Pipeline()
load_images = LoadImages()
load_images.module_num = 1
load_images.add_imagecb()
load_images.images[0].channels[0].image_name.value = "Foo"
load_images.images[1].channels[0].image_name.value = "Bar"
pipeline.add_module(load_images)
identify = IdentifyPrimaryObjects()
identify.module_num = 2
identify.image_name.value = "Foo"
identify.object_name.value = "dizzy"
pipeline.add_module(identify)
saveimages = SaveImages()
saveimages.module_num = 3
saveimages.image_name.value = "Foo"
pipeline.add_module(saveimages)
measureobjectsizeshape = MeasureObjectSizeShape()
measureobjectsizeshape.module_num = 4
measureobjectsizeshape.object_groups[0].name.value = "dizzy"
pipeline.add_module(measureobjectsizeshape)
pipeline_txt = StringIO()
pipeline.savetxt(pipeline_txt)
module_names = json.dumps([SaveImages.module_name])
message = [
zmq.Frame(self.session_id),
zmq.Frame(),
zmq.Frame(CLEAN_PIPELINE_REQ_1),
zmq.Frame(pipeline_txt.getvalue()),
zmq.Frame(module_names),
]
self.socket.send_multipart(message)
message = self.socket.recv_multipart()
self.assertEqual(message.pop(0), self.session_id)
self.assertEqual(message.pop(0), "")
self.assertEqual(message.pop(0), CLEAN_PIPELINE_REPLY_1)
pipeline_txt = message.pop(0)
pipeline = cpp.Pipeline()
pipeline.loadtxt(StringIO(pipeline_txt))
self.assertEqual(len(pipeline.modules()), 3)
self.assertIsInstance(pipeline.modules()[0], LoadImages)
self.assertIsInstance(pipeline.modules()[1], IdentifyPrimaryObjects)
self.assertIsInstance(pipeline.modules()[2], MeasureObjectSizeShape)
def test_03_03_run_missing_measurement(self):
# Regression test of knime-bridge issue #6
#
# Missing measurement causes exception
#
pipeline = cpp.Pipeline()
load_images = LoadImages()
load_images.module_num = 1
load_images.images[0].channels[0].image_name.value = "Foo"
pipeline.add_module(load_images)
identify = IdentifyPrimaryObjects()
identify.module_num = 2
identify.use_advanced.value = True
identify.x_name.value = "Foo"
identify.y_name.value = "dizzy"
identify.threshold.threshold_scope.value = TS_GLOBAL
identify.threshold.global_operation.value = TM_MANUAL
identify.threshold.manual_threshold.value = .5
identify.exclude_size.value = False
pipeline.add_module(identify)
flag_module = FlagImage()
flag_module.module_num = 3
flag = flag_module.flags[0]
flag.wants_skip.value = True
criterion = flag.measurement_settings[0]
criterion.source_choice.value = S_IMAGE
criterion.measurement.value = "Count_dizzy"
criterion.wants_minimum.value = True
criterion.minimum_value.value = 1000
pipeline.add_module(flag_module)
measureobjectsizeshape = MeasureObjectSizeShape()
measureobjectsizeshape.module_num = 4
measureobjectsizeshape.object_groups[0].name.value = "dizzy"
pipeline.add_module(measureobjectsizeshape)
pipeline_txt = StringIO()
pipeline.savetxt(pipeline_txt)
image = np.zeros((11, 17))
image[2:-2, 2:-2] = 1
image_metadata = [[
"Foo",
[["Y", image.shape[0], image.strides[0] / 8],
["X", image.shape[1], image.strides[1] / 8]]
]]
message = [
zmq.Frame(self.session_id),
zmq.Frame(),
zmq.Frame(RUN_REQ_1),
zmq.Frame(pipeline_txt.getvalue()),
zmq.Frame(json.dumps(image_metadata)),
zmq.Frame(image)
]
self.socket.send_multipart(message)
response = self.socket.recv_multipart()
self.assertEqual(response.pop(0), self.session_id)
self.assertEqual(response.pop(0), "")
self.assertEqual(response.pop(0), RUN_REPLY_1)
metadata = json.loads(response.pop(0))
data = response.pop(0)
measurements = self.decode_measurements(metadata, data)
self.assertEqual(measurements[cpmeas.IMAGE]["Count_dizzy"][0], 1)
self.assertEqual(measurements["dizzy"]["Location_Center_Y"][0], 5)
self.assertEqual(len(measurements["dizzy"]["AreaShape_Area"]), 0)
def test_03_03_run_missing_measurement(self):
# Regression test of knime-bridge issue #6
#
# Missing measurement causes exception
#
pipeline = cpp.Pipeline()
load_images = LoadImages()
load_images.module_num = 1
load_images.images[0].channels[0].image_name.value = "Foo"
pipeline.add_module(load_images)
identify = IdentifyPrimaryObjects()
identify.module_num = 2
identify.use_advanced.value = True
identify.x_name.value = "Foo"
identify.y_name.value = "dizzy"
identify.threshold.threshold_scope.value = TS_GLOBAL
identify.threshold.global_operation.value = TM_MANUAL
identify.threshold.manual_threshold.value = .5
identify.exclude_size.value = False
pipeline.add_module(identify)
flag_module = FlagImage()
flag_module.module_num = 3
flag = flag_module.flags[0]
flag.wants_skip.value = True
criterion = flag.measurement_settings[0]
criterion.source_choice.value = S_IMAGE
criterion.measurement.value = "Count_dizzy"
criterion.wants_minimum.value = True
criterion.minimum_value.value = 1000
pipeline.add_module(flag_module)
measureobjectsizeshape = MeasureObjectSizeShape()
measureobjectsizeshape.module_num = 4
measureobjectsizeshape.object_groups[0].name.value = "dizzy"
pipeline.add_module(measureobjectsizeshape)
pipeline_txt = StringIO()
pipeline.savetxt(pipeline_txt)
image = np.zeros((11, 17))
image[2:-2, 2:-2] = 1
image_metadata = [
["Foo",
[["Y", image.shape[0], image.strides[0] / 8],
["X", image.shape[1], image.strides[1] / 8]]]]
message = [
zmq.Frame(self.session_id),
zmq.Frame(),
zmq.Frame(RUN_REQ_1),
zmq.Frame(pipeline_txt.getvalue()),
zmq.Frame(json.dumps(image_metadata)),
zmq.Frame(image)]
self.socket.send_multipart(message)
response = self.socket.recv_multipart()
self.assertEqual(response.pop(0), self.session_id)
self.assertEqual(response.pop(0), "")
self.assertEqual(response.pop(0), RUN_REPLY_1)
metadata = json.loads(response.pop(0))
data = response.pop(0)
measurements = self.decode_measurements(metadata, data)
self.assertEqual(measurements[cpmeas.IMAGE]["Count_dizzy"][0], 1)
self.assertEqual(measurements["dizzy"]["Location_Center_Y"][0], 5)
self.assertEqual(len(measurements["dizzy"]["AreaShape_Area"]), 0)
