def test_wrong_background_size(self):
pipeline_parameters = {
"camera_name": "simulation",
"image_background": "white_background"
}
simulated_camera = CameraSimulation(CameraConfig("simulation"))
image = simulated_camera.get_image()
x_axis, y_axis = simulated_camera.get_x_y_axis()
background_provider = MockBackgroundManager()
# Invalid background size.
background_provider.save_background("white_background", numpy.zeros(shape=(100, 100)),
append_timestamp=False)
parameters = PipelineConfig("test_pipeline", pipeline_parameters).get_configuration()
image_background_array = background_provider.get_background("white_background")
with self.assertRaisesRegex(RuntimeError, "Invalid background_image size "):
process_image(image=image,
timestamp=time.time(),
x_axis=x_axis,
y_axis=y_axis,
parameters=parameters,
image_background_array=image_background_array)
def test_image_background(self):
pipeline_parameters = {
"camera_name": "simulation",
"image_background": "white_background"
}
simulated_camera = CameraSimulation(CameraConfig("simulation"))
image = simulated_camera.get_image()
x_axis, y_axis = simulated_camera.get_x_y_axis()
background_provider = MockBackgroundManager()
x_size, y_size = simulated_camera.get_geometry()
background_provider.save_background("white_background", numpy.zeros(shape=(y_size, x_size)),
append_timestamp=False)
pipeline_config = PipelineConfig("test_pipeline", pipeline_parameters)
parameters = pipeline_config.get_configuration()
image_background_array = background_provider.get_background(parameters.get("image_background"))
result = process_image(image=image,
timestamp=time.time(),
x_axis=x_axis,
y_axis=y_axis,
parameters=parameters,
image_background_array=image_background_array)
self.assertTrue(numpy.array_equal(result["image"], image),
"A zero background should not change the image.")
max_value_in_image = result["max_value"]
pipeline_parameters = {
"camera_name": "simulation",
"image_background": "max_background",
"image_threshold": 0
}
max_background = numpy.zeros(shape=(y_size, x_size), dtype="uint16")
max_background.fill(max_value_in_image)
background_provider.save_background("max_background", max_background, append_timestamp=False)
pipeline_config = PipelineConfig("test_pipeline", pipeline_parameters)
parameters = pipeline_config.get_configuration()
image_background_array = background_provider.get_background(parameters.get("image_background"))
expected_image = numpy.zeros(shape=(y_size, x_size))
result = process_image(image=image,
timestamp=time.time(),
x_axis=x_axis,
y_axis=y_axis,
parameters=parameters,
image_background_array=image_background_array)
self.assertTrue(numpy.array_equal(result["image"], expected_image),
"The image should be all zeros - negative numbers are not allowed.")
def test_pipeline_background_manager(self):
manager = multiprocessing.Manager()
stop_event = multiprocessing.Event()
statistics = manager.Namespace()
parameter_queue = multiprocessing.Queue()
pipeline_config = PipelineConfig("test_pipeline",
parameters={
"camera_name": "simulation",
"image_background":
"full_background",
"image_background_enable": True,
"image_threshold": 0
})
background_manager = MockBackgroundManager()
with self.assertRaises(Exception):
processing_pipeline(stop_event, statistics, parameter_queue,
self.client, pipeline_config, 12000,
background_manager)
simulated_camera_shape = (960, 1280)
background_array = numpy.zeros(shape=simulated_camera_shape)
background_array.fill(99999)
background_manager.save_background("full_background",
background_array,
append_timestamp=False)
def send():
processing_pipeline(stop_event, statistics, parameter_queue,
self.client, pipeline_config, 12000,
background_manager)
thread = Thread(target=send)
thread.start()
with source(host="127.0.0.1", port=12000, mode=SUB) as stream:
data = stream.receive()
self.assertIsNotNone(data, "Received None message.")
self.assertTrue(
numpy.array_equal(data.data.data["image"].value,
numpy.zeros(shape=simulated_camera_shape)))
stop_event.set()
thread.join()