elif visualisation_type == 'Value':
update_dpg_gui()
elif visualisation_type == 'Single Pane Plot':
update_dpg_gui()
elif visualisation_type == 'Multi Pane Plot':
update_dpg_gui()
elif visualisation_type == 'Histogram':
pass
except Exception as e:
print(e)
return [data]
def on_end_of_life():
global visualisation_checking_thread_is_on
visualisation_checking_thread_is_on = False
if __name__ == "__main__":
worker_object = gu.start_the_transform_worker_process(
initialisation_function=get_vis_type_parameter,
work_function=visualise,
end_of_life_function=on_end_of_life)
worker_object.start_ioloop()
# Now do stuff
# Whatever data the Node must visualise should be put in the vis.visualised_data variable
vis.visualised_data = image
# For Operations with multiple outputs the work_function must return a list of numpy arrays with length the number
# of outputs. Each array from left to right in the list gets passed to each output from top to bottom on the Node.
# So in this example the data would go out of the 'Something Out 1' output and the np.array([ct.IGNORE]) would go
# out of the 'Something Out 2' output. If you want to stop one or more outputs from sending out any data on the
# current pass then put as an array the np.array([ct.IGNORE]) array. The com process knows to ignore this array.
result = [vis.visualised_data, np.array([ct.IGNORE])]
return result
# The on_end_of_life function must exist even if it is just a pass
def on_end_of_life():
global vis
# If using in Node visualisation then the vis object must be cleared here like this
vis.kill()
if __name__ == "__main__":
worker_object = gu.start_the_transform_worker_process(
work_function=work_function,
end_of_life_function=on_end_of_life,
initialisation_function=initialise)
worker_object.start_ioloop()
global vis
try:
vis.visualisation_on = parameters[0]
min_val = parameters[1]
max_val = parameters[2]
except:
vis.visualisation_on = canny_com.ParametersDefaultValues[0]
min_val = canny_com.ParametersDefaultValues[1]
max_val = canny_com.ParametersDefaultValues[2]
message = data[1:] # data[0] is the topic
image = Socket.reconstruct_array_from_bytes_message_cv2correction(message)
try:
vis.visualised_data = cv2.Canny(image, min_val, max_val)
except:
vis.visualised_data = np.array((10, 10))
print('Canny operation failed')
return [vis.visualised_data]
def on_end_of_life():
global vis
vis.kill()
if __name__ == "__main__":
worker_object = gu.start_the_transform_worker_process(canny, on_end_of_life, initialise)
worker_object.start_ioloop()
'Shapes of two arrays are not the same. Input 1 shape = {}, input 2 shape = {}. Passing through 1st input'
.format(
np.shape(
worker_object.recv_topics_buffer[all_topics[0]]),
np.shape(
worker_object.recv_topics_buffer[all_topics[1]])))
worker_object.worker_result = worker_object.recv_topics_buffer[
all_topics[0]]
if frame2_minus_frame1:
worker_object.worker_result = worker_object.recv_topics_buffer[all_topics[1]] -\
worker_object.recv_topics_buffer[all_topics[0]]
else:
worker_object.worker_result = np.random.random((100, 100))
print('Differencing {} failed. The frame buffer is empty.'.format(
worker_object.node_index))
vis.visualised_data = worker_object.worker_result
return [worker_object.worker_result]
def on_end_of_life():
pass
if __name__ == "__main__":
worker_object = gu.start_the_transform_worker_process(
differencing, on_end_of_life, initialise)
worker_object.start_ioloop()
