stream

Module: stream.client

FuryStreamClient(showm[, max_window_size, ...])	This obj is responsible to create a StreamClient.
FuryStreamInteraction(showm[, ...])	This obj.
callback_stream_client(stream_client)	This callback is used to update the image inside of the ImageManager instance
interaction_callback(circular_queue, showm, ...)	This callback is used to invoke vtk interaction events reading those events from the provided circular_queue instance

Module: stream.constants

_CQUEUE_EVENT_IDs	CQUEUE_EVENT_IDS(mouse_weel, mouse_move, mouse_ids, left_btn_press, left_btn_release, middle_btn_press, middle_btn_release, right_btn_press, right_btn_release)
_CQUEUE_INDEX_INFO	CQUEUE_INDEX_INFO(weel, x, y, ctrl, shift, user_timestamp)
_CQUEUE	CQUEUE(dimension, event_ids, index_info)

Module: stream.server

Module: stream.server.async_app

pcs	set() -> new empty set object set(iterable) -> new set object
set_weel(data, circular_queue)
set_mouse(data, circular_queue)
set_mouse_click(data, circular_queue)	3 | LeftButtonPressEvent 4 | LeftButtonReleaseEvent 5 | MiddleButtonPressEvent 6 | MiddleButtonReleaseEvent 7 | RightButtonPressEvent 8 | RightButtonReleaseEvent
get_app([rtc_server, folder, ...])

Module: stream.server.main

RTCServer(image_buffer_manager)	This Obj it's responsible to create the VideoStream for the WebRTCServer
web_server_raw_array([image_buffers, ...])	This will create a streaming webserver running on the given port and host using RawArrays.
web_server([image_buffer_names, ...])	This will create a streaming webserver running on the given port and host using SharedMemory.

Module: stream.tools

GenericMultiDimensionalBuffer([max_size, ...])	This implements a abstract (generic) multidimensional buffer.
RawArrayMultiDimensionalBuffer(max_size[, ...])	This implements a multidimensional buffer with RawArray.
SharedMemMultiDimensionalBuffer(max_size[, ...])	This implements a generic multidimensional buffer with SharedMemory.
GenericCircularQueue([max_size, dimension, ...])	This implements a generic circular queue which works with shared memory resources.
ArrayCircularQueue([max_size, dimension, ...])	This implements a MultiDimensional Queue which works with Arrays and RawArrays.
SharedMemCircularQueue([max_size, ...])	This implements a MultiDimensional Queue which works with SharedMemory.
GenericImageBufferManager([max_window_size, ...])	This implements a abstract (generic) ImageBufferManager with the n-buffer technique.
RawArrayImageBufferManager([...])	This implements an ImageBufferManager using RawArrays.
SharedMemImageBufferManager([...])	This implements an ImageBufferManager using the SharedMemory approach.
IntervalTimerThreading(seconds, callback, ...)	Implements a object with the same behavior of setInterval from Js
IntervalTimer(seconds, callback, *args, **kwargs)	A object that creates a timer that calls a function periodically.
remove_shm_from_resource_tracker()	Monkey-patch multiprocessing.resource_tracker so SharedMemory won't be tracked

Module: stream.widget

Widget(showm[, ms_stream, ms_interaction, ...])	This Obj it's able execute the fury streaming system using the SharedMemory object from Python multiprocessing.
check_port_is_available(host, port)	Check if a given port it's available

FuryStreamClient

class fury.stream.client.FuryStreamClient(showm, max_window_size=None, use_raw_array=True, whithout_iren_start=False, num_buffers=2)

Bases: object

This obj is responsible to create a StreamClient.

__init__(showm, max_window_size=None, use_raw_array=True, whithout_iren_start=False, num_buffers=2)

A StreamClient extracts a framebuffer from the OpenGL context and writes into a shared memory resource.

Parameters:

• showm (ShowManager) –

• max_window_size (tuple of ints, optional) – This allows resize events inside of the FURY window instance. Should be greater than the window size.

• use_raw_array (bool, optional) – If False then FuryStreamClient will use SharedMemory instead of RawArrays. Notice that Python >=3.8 it’s a requirement to use SharedMemory)

• whithout_iren_start (bool, optional) – Sometimes you can’t initiate the vtkInteractor instance.

• num_buffers (int, optional) – Number of buffers to be used in the n-buffering technique.

cleanup()

Release the shared memory resources if necessary.

start(ms=0, use_asyncio=False)

Start the stream client.

Parameters:

• ms (float, optional) – positive number. This update the image buffer using a interval of ms milliseconds. If ms is 0 then the stream client will update the buffer after every Render event.

• use_asyncio (bool, optional) – If False then the stream client will update the image using a threading technique.

stop()

Stop the stream client.

FuryStreamInteraction

class fury.stream.client.FuryStreamInteraction(showm, max_queue_size=50, use_raw_array=True, whithout_iren_start=False)

Bases: object

This obj. is responsible to manage the user interaction

__init__(showm, max_queue_size=50, use_raw_array=True, whithout_iren_start=False)

Parameters:

• showm (ShowmManager) –

• max_queue_size (int, optional) – maximum number of events to be stored.

• use_raw_array (bool, optional) – If False then a CircularQueue will be created using SharedMemory instead of RawArrays. Notice that Python >=3.8 it’s requirement to use SharedMemory.

• whithout_iren_start (bool, optional) – Set that to True if you can’t initiate the vtkInteractor instance.

cleanup()

Release the shared memory resources if necessary.

start(ms=3, use_asyncio=False)

Start the stream interaction client.

Parameters:

• ms (float, optional) – positive number greater than zero.

• use_asyncio (bool, optional) – If False then the interaction will be performed in a separate thread.

stop()

Stop the stream interaction client.

callback_stream_client

fury.stream.client.callback_stream_client(stream_client)

This callback is used to update the image inside of the ImageManager instance

Parameters:

stream_client (StreamClient) –

interaction_callback

fury.stream.client.interaction_callback(circular_queue, showm, iren, render_after)

This callback is used to invoke vtk interaction events reading those events from the provided circular_queue instance

Parameters:

• circular_queue (CircularQueue) –

• showm (ShowmManager) –

• iren (vtkInteractor) –

• render_after (bool, optional) – If the render method should be called after an dequeue

_CQUEUE_EVENT_IDs

fury.stream.constants._CQUEUE_EVENT_IDs()

CQUEUE_EVENT_IDS(mouse_weel, mouse_move, mouse_ids, left_btn_press, left_btn_release, middle_btn_press, middle_btn_release, right_btn_press, right_btn_release)

_CQUEUE_INDEX_INFO

fury.stream.constants._CQUEUE_INDEX_INFO()

CQUEUE_INDEX_INFO(weel, x, y, ctrl, shift, user_timestamp)

_CQUEUE

fury.stream.constants._CQUEUE()

CQUEUE(dimension, event_ids, index_info)

pcs

fury.stream.server.async_app.pcs()

set() -> new empty set object set(iterable) -> new set object

Build an unordered collection of unique elements.

set_weel

fury.stream.server.async_app.set_weel(data, circular_queue)

set_mouse

fury.stream.server.async_app.set_mouse(data, circular_queue)

set_mouse_click

fury.stream.server.async_app.set_mouse_click(data, circular_queue)

3 | LeftButtonPressEvent 4 | LeftButtonReleaseEvent 5 | MiddleButtonPressEvent 6 | MiddleButtonReleaseEvent 7 | RightButtonPressEvent 8 | RightButtonReleaseEvent

get_app

fury.stream.server.async_app.get_app(rtc_server=None, folder=None, circular_queue=None, image_buffer_manager=None, provides_mjpeg=False, broadcast=True)

RTCServer

class fury.stream.server.main.RTCServer(image_buffer_manager)

Bases: object

This Obj it’s responsible to create the VideoStream for the WebRTCServer

__init__(image_buffer_manager)

Parameters:

image_buffer_manager (ImageBufferManager) –

async recv()

Return a VideoFrame to be used in the WebRTC Server

The frame will be created using the image stored in the shared memory

Returns:

frame

Return type:

VideoFrame

release()

Release the RTCServer

web_server_raw_array

fury.stream.server.main.web_server_raw_array(image_buffers=None, info_buffer=None, queue_head_tail_buffer=None, queue_buffer=None, port=8000, host='localhost', provides_mjpeg=True, provides_webrtc=True, ms_jpeg=16, run_app=True)

This will create a streaming webserver running on the given port and host using RawArrays.

Parameters:

• image_buffers (list of buffers) – A list of buffers with each one containing a frame.

• info_buffer (buffer) – A buffer with the information about the current frame to be streamed and the respective sizes

• queue_head_tail_buffer (buffer) – If buffer is passed than this Obj will read a a already created RawArray.

• queue_buffer (buffer) – If queue_buffer is passed than this Obj will read a a already created RawArray containing the user interactions events stored in the queue_buffer.

• port (int, optional) – Port to be used by the aiohttp server

• host (str, optional, default localhost) – host to be used by the aiohttp server

• provides_mjpeg (bool, default True) – If a MJPEG streaming should be available. If True you can consume that through host:port/video/mjpeg or if you want to interact you can consume that through your browser http://host:port?encoding=mjpeg

• provides_webrtc (bool, default True) – If a WebRTC streaming should be available. http://host:port

• ms_jpeg (float, optional) – This it’s used only if the MJPEG will be used. The ms_jpeg represents the amount of milliseconds between to consecutive calls of the jpeg encoding.

• run_app (bool, default True) – This will run the aiohttp application. The False condition is used just to be able to test the server.

web_server

fury.stream.server.main.web_server(image_buffer_names=None, info_buffer_name=None, queue_head_tail_buffer_name=None, queue_buffer_name=None, port=8000, host='localhost', provides_mjpeg=True, provides_webrtc=True, avoid_unlink_shared_mem=True, ms_jpeg=16, run_app=True)

This will create a streaming webserver running on the given port and host using SharedMemory.

Parameters:

• image_buffers_name (list of str) – A list of buffers with each one containing a frame.

• info_buffer_name (str) – A buffer with the information about the current frame to be streamed and the respective sizes

• queue_head_tail_buffer_name (str, optional) – If buffer is passed than this Obj will read a a already created RawArray.

• buffer_name (str, optional) – If queue_buffer is passed than this Obj will read a a already created RawArray containing the user interactions events stored in the queue_buffer.

• port (int, optional) – Port to be used by the aiohttp server

• host (str, optional, default localhost) – host to be used by the aiohttp server

• provides_mjpeg (bool, default True) – If a MJPEG streaming should be available. If True you can consume that through host:port/video/mjpeg or if you want to interact you can consume that through your browser http://host:port?encoding=mjpeg

• provides_webrtc (bool, default True) – If a WebRTC streaming should be available. http://host:port

• avoid_unlink_shared_mem (bool, default False) – If True, then this will apply a monkey-patch solution to a python>=3.8 core bug

• ms_jpeg (float, optional) – This it’s used only if the MJPEG will be used. The ms_jpeg represents the amount of milliseconds between to consecutive calls of the jpeg encoding.

• run_app (bool, default True) – This will run the aiohttp application. The False condition is used just to be able to test the server.

GenericMultiDimensionalBuffer

class fury.stream.tools.GenericMultiDimensionalBuffer(max_size=None, dimension=8)

Bases: ABC

This implements a abstract (generic) multidimensional buffer.

__init__(max_size=None, dimension=8)

Parameters:

• max_size (int, optional) – If buffer_name or buffer was not passed then max_size it’s mandatory

• dimension (int, default 8) –

property buffer

abstract cleanup()

abstract create_mem_resource()

get_start_end(idx)

abstract load_mem_resource()

RawArrayMultiDimensionalBuffer

class fury.stream.tools.RawArrayMultiDimensionalBuffer(max_size, dimension=4, buffer=None)

Bases: GenericMultiDimensionalBuffer

This implements a multidimensional buffer with RawArray.

__init__(max_size, dimension=4, buffer=None)

Stream system uses that to implement the CircularQueue with shared memory resources.

Parameters:

• max_size (int, optional) – If buffer_name or buffer was not passed then max_size it’s mandatory

• dimension (int, default 8) –

• buffer (buffer, optional) – If buffer is not passed to __init__ then the multidimensional buffer obj will create a new RawArray object to store the data If buffer is passed than this Obj will read a a already created RawArray

cleanup()

create_mem_resource()

load_mem_resource()

SharedMemMultiDimensionalBuffer

class fury.stream.tools.SharedMemMultiDimensionalBuffer(max_size, dimension=4, buffer_name=None)

Bases: GenericMultiDimensionalBuffer

This implements a generic multidimensional buffer with SharedMemory.

__init__(max_size, dimension=4, buffer_name=None)

Stream system uses that to implement the CircularQueue with shared memory resources.

Parameters:

• max_size (int, optional) – If buffer_name or buffer was not passed then max_size it’s mandatory

• dimension (int, default 8) –

• buffer_name (str, optional) – if buffer_name is passed than this Obj will read a a already created SharedMemory

cleanup()

create_mem_resource()

load_mem_resource()

GenericCircularQueue

class fury.stream.tools.GenericCircularQueue(max_size=None, dimension=8, use_shared_mem=False, buffer=None, buffer_name=None)

Bases: ABC

This implements a generic circular queue which works with shared memory resources.

__init__(max_size=None, dimension=8, use_shared_mem=False, buffer=None, buffer_name=None)

Parameters:

• max_size (int, optional) – If buffer_name or buffer was not passed then max_size it’s mandatory. This will be used to construct the multidimensional buffer

• dimension (int, default 8) – This will be used to construct the multidimensional buffer

• use_shared_mem (bool, default False) – If the multidimensional memory resource should create or read using SharedMemory or RawArrays

• buffer (RawArray, optional) –

• buffer_name (str, optional) –

abstract cleanup()

abstract create_mem_resource()

abstract dequeue()

abstract enqueue(data)

property head

abstract load_mem_resource()

set_head_tail(head, tail, lock=1)

property tail

ArrayCircularQueue

class fury.stream.tools.ArrayCircularQueue(max_size=10, dimension=6, head_tail_buffer=None, buffer=None)

Bases: GenericCircularQueue

This implements a MultiDimensional Queue which works with Arrays and RawArrays.

__init__(max_size=10, dimension=6, head_tail_buffer=None, buffer=None)

Stream system uses that to implement user interactions

Parameters:

• max_size (int, optional) – If buffer_name or buffer was not passed then max_size it’s mandatory. This will be used to construct the multidimensional buffer

• dimension (int, default 8) – This will be used to construct the multidimensional buffer

• head_tail_buffer (buffer, optional) – If buffer is not passed to __init__ then this obj will create a new RawArray to store head and tail position.

• buffer (buffer, optional) – If buffer is not passed to __init__ then the multidimensional buffer obj will create a new RawArray to store the data

cleanup()

create_mem_resource()

dequeue()

enqueue(data)

load_mem_resource()

SharedMemCircularQueue

class fury.stream.tools.SharedMemCircularQueue(max_size=10, dimension=6, head_tail_buffer_name=None, buffer_name=None)

Bases: GenericCircularQueue

This implements a MultiDimensional Queue which works with SharedMemory.

__init__(max_size=10, dimension=6, head_tail_buffer_name=None, buffer_name=None)

Stream system uses that to implement user interactions

Parameters:

• max_size (int, optional) – If buffer_name or buffer was not passed then max_size it’s mandatory. This will be used to construct the multidimensional buffer

• dimension (int, default 8) – This will be used to construct the multidimensional buffer

• head_tail_buffer_name (str, optional) – if buffer_name is passed than this Obj will read a a already created SharedMemory with the head and tail information

• buffer_name (str, optional) – if buffer_name is passed than this Obj will read a a already created SharedMemory to create the MultiDimensionalBuffer

cleanup()

create_mem_resource()

dequeue()

enqueue(data)

is_unlocked()

load_mem_resource()

lock()

unlock()

GenericImageBufferManager

class fury.stream.tools.GenericImageBufferManager(max_window_size=None, num_buffers=2, use_shared_mem=False)

Bases: ABC

This implements a abstract (generic) ImageBufferManager with the n-buffer technique.

__init__(max_window_size=None, num_buffers=2, use_shared_mem=False)

Parameters:

• max_window_size (tuple of ints, optional) – This allows resize events inside of the FURY window instance. Should be greater than the window size.

• num_buffers (int, optional) – Number of buffers to be used in the n-buffering technique.

• use_shared_mem (bool, default False) –

async async_get_jpeg(ms=33)

property buffer_index

abstract cleanup()

abstract create_mem_resource()

get_current_frame()

Get the current frame from the buffer.

get_jpeg()

Returns a jpeg image from the buffer.

Returns:

jpeg image.

Return type:

bytes

abstract load_mem_resource()

property next_buffer_index

write_into(w, h, np_arr)

RawArrayImageBufferManager

class fury.stream.tools.RawArrayImageBufferManager(max_window_size=(100, 100), num_buffers=2, image_buffers=None, info_buffer=None)

Bases: GenericImageBufferManager

This implements an ImageBufferManager using RawArrays.

__init__(max_window_size=(100, 100), num_buffers=2, image_buffers=None, info_buffer=None)

Parameters:

• max_window_size (tuple of ints, optional) – This allows resize events inside of the FURY window instance. Should be greater than the window size.

• num_buffers (int, optional) – Number of buffers to be used in the n-buffering technique.

• info_buffer (buffer, optional) – A buffer with the information about the current frame to be streamed and the respective sizes

• image_buffers (list of buffers, optional) – A list of buffers with each one containing a frame.

cleanup()

create_mem_resource()

load_mem_resource()

SharedMemImageBufferManager

class fury.stream.tools.SharedMemImageBufferManager(max_window_size=(100, 100), num_buffers=2, image_buffer_names=None, info_buffer_name=None)

Bases: GenericImageBufferManager

This implements an ImageBufferManager using the SharedMemory approach.

__init__(max_window_size=(100, 100), num_buffers=2, image_buffer_names=None, info_buffer_name=None)

Note

Python >=3.8 is a requirement to use this object.

Parameters:

• max_window_size (tuple of ints, optional) – This allows resize events inside of the FURY window instance. Should be greater than the window size.

• num_buffers (int, optional) – Number of buffers to be used in the n-buffering technique.

• info_buffer_name (str) – The name of a buffer with the information about the current frame to be streamed and the respective sizes

• image_buffer_names (list of str, optional) – a list of buffer names. Each buffer contains a frame

cleanup()

Release the resources used by the Shared Memory Manager

create_mem_resource()

load_mem_resource()

IntervalTimerThreading

class fury.stream.tools.IntervalTimerThreading(seconds, callback, *args, **kwargs)

Bases: object

Implements a object with the same behavior of setInterval from Js

__init__(seconds, callback, *args, **kwargs)

Parameters:

• seconds (float) – A positive float number. Represents the total amount of seconds between each call

• callback (function) – The function to be called

• *args (args) – args to be passed to callback

• **kwargs (kwargs) – kwargs to be passed to callback

Examples

def callback(arr):
    arr += [len(arr)]
arr = []
interval_timer = tools.IntervalTimer(1, callback, arr)
interval_timer.start()
time.sleep(5)
interval_timer.stop()
# len(arr) == 5

References

[1] https://stackoverflow.com/questions/3393612/run-certain-code-every-n-seconds

start()

Start the timer

stop()

Stop the timer

IntervalTimer

class fury.stream.tools.IntervalTimer(seconds, callback, *args, **kwargs)

Bases: object

A object that creates a timer that calls a function periodically.

__init__(seconds, callback, *args, **kwargs)

Parameters:

• seconds (float) – A positive float number. Represents the total amount of seconds between each call

• callback (function) – The function to be called

• *args (args) – args to be passed to callback

• **kwargs (kwargs) – kwargs to be passed to callback

start()

Start the timer

stop()

Stop the timer

remove_shm_from_resource_tracker

fury.stream.tools.remove_shm_from_resource_tracker()

Monkey-patch multiprocessing.resource_tracker so SharedMemory won’t be tracked

Notes

More details at: https://bugs.python.org/issue38119

Widget

class fury.stream.widget.Widget(showm, ms_stream=33, ms_interaction=33, host='localhost', port=None, encoding='mjpeg', ms_jpeg=33, queue_size=20)

Bases: object

This Obj it’s able execute the fury streaming system using the SharedMemory object from Python multiprocessing.

__init__(showm, ms_stream=33, ms_interaction=33, host='localhost', port=None, encoding='mjpeg', ms_jpeg=33, queue_size=20)

Parameters:

• showm (ShowmManager) –

• ms_stream (float, optional) – time in mileseconds between each frame buffer update.

• ms_interaction (float, optional) – time in mileseconds between each user interaction update.

• host (str, optional) –

• port (int, optional) –

• encoding (str, optional) – If should use MJPEG streaming or WebRTC.

• ms_jpeg (float, optional) – This it’s used only if the MJPEG will be used. The ms_jpeg represents the amount of milliseconds between to consecutive calls of the jpeg encoding.

• queue_size (int, optional) – maximum number of user interactions to be stored

cleanup()

Release the shared memory

property command_string

Return the command string to start the server

Returns:

command_string

Return type:

str

display(height=150)

Start the server and display the url in an iframe

return_iframe(height=200)

Return the jupyter div iframe used to show the stream

run_command()

Evaluate the command string to start the server

start(use_asyncio=False)

Start the fury client and the interaction client and return the url

Parameters:

use_asyncio (bool, optional) – If should use the asyncio version of the server. Default is False.

stop()

Stop the streaming server and release the shared memory

property url

Return the url to access the server

check_port_is_available

fury.stream.widget.check_port_is_available(host, port)

Check if a given port it’s available

Parameters:

• host (str) –

• port (int) –

Returns:

available

Return type:

bool