forked from platypush/platypush
- Added frames throttling support on Leap Motion backend
- Moved the Leap listener to another process to prevent it from hanging the other backends - Added support for sound and mix frequency analysis
This commit is contained in:
Fabio Manganiello
parent
2e82651dbf
commit
54c3381ae3
3 changed files with 153 additions and 22 deletions
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@ -1,5 +1,8 @@
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import time
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from threading import Timer
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from multiprocessing import Process
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import Leap
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from platypush.backend import Backend
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@ -21,6 +24,12 @@ class SensorLeapBackend(Backend):
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instructions at https://www.leapmotion.com/setup/) and the `leapd` daemon
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running to recognize your controller.
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Requires:
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* The Redis backend enabled
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* The Leap Motion SDK compiled with Python 3 support, see my port at https://github.com:BlackLight/leap-sdk-python3.git
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* The `leapd` daemon to be running and your Leap Motion connected
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Triggers:
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* :class:`platypush.message.event.sensor.leap.LeapFrameEvent` when a new frame is received
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@ -30,6 +39,8 @@ class SensorLeapBackend(Backend):
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* :class:`platypush.message.event.sensor.leap.LeapDisconnectEvent` when a Leap Motion device disconnects
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"""
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_listener_proc = None
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def __init__(self,
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position_ranges=[
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[-300.0, 300.0], # x axis
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@ -37,6 +48,7 @@ class SensorLeapBackend(Backend):
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[-300.0, 300.0], # z axis
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],
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position_tolerance=0.0, # Position variation tolerance in %
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frames_throttle_secs=None,
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*args, **kwargs):
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"""
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:param position_ranges: It specifies how wide the hand space (x, y and z axes) should be in millimiters.
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@ -53,19 +65,30 @@ class SensorLeapBackend(Backend):
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:param position_tolerance: % of change between a frame and the next to really consider the next frame as a new one (default: 0)
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:type position_tolerance: float
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:param frames_throttle_secs: If set, the frame events will be throttled
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and pushed to the main queue at the specified rate. Good to set if
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you want to connect Leap Motion events to actions that have a lower
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throughput (the Leap Motion can send a lot of frames per second).
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Default: None (no throttling)
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:type frames_throttle_secs: float
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"""
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super().__init__(*args, **kwargs)
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self.position_ranges = position_ranges
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self.position_tolerance = position_tolerance
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self.frames_throttle_secs = frames_throttle_secs
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def run(self):
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super().run()
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def _listener_process():
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listener = LeapListener(position_ranges=self.position_ranges,
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position_tolerance=self.position_tolerance)
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position_tolerance=self.position_tolerance,
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frames_throttle_secs=self.frames_throttle_secs,
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logger=self.logger)
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controller = Leap.Controller()
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@ -76,23 +99,42 @@ class SensorLeapBackend(Backend):
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controller.add_listener(listener)
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self.logger.info('Leap Motion backend initialized')
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try:
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while not self.should_stop():
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time.sleep(0.1)
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finally:
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controller.remove_listener(listener)
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time.sleep(1)
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self._listener_proc = Process(target=_listener_process)
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self._listener_proc.start()
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self._listener_proc.join()
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class LeapFuture(Timer):
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def __init__(self, seconds, listener, event):
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self.listener = listener
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self.event = event
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super().__init__(seconds, self._callback_wrapper())
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def _callback_wrapper(self):
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def _callback():
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self.listener._send_event(self.event)
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return _callback
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class LeapListener(Leap.Listener):
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def __init__(self, position_ranges, position_tolerance, *args, **kwargs):
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def __init__(self, position_ranges, position_tolerance, logger,
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frames_throttle_secs=None, *args, **kwargs):
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super().__init__(*args, **kwargs)
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self.prev_frame = None
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self.position_ranges = position_ranges
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self.position_tolerance = position_tolerance
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self.frames_throttle_secs = frames_throttle_secs
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self.logger = logger
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self.running_future = None
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def send_event(self, event):
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def _send_event(self, event):
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backend = get_backend('redis')
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if not backend:
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self.logger.warning('Redis backend not configured, I cannot propagate the following event: {}'.format(event))
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@ -101,6 +143,16 @@ class LeapListener(Leap.Listener):
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backend.send_message(event)
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def send_event(self, event):
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if self.frames_throttle_secs:
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if not self.running_future or not self.running_future.is_alive():
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self.running_future = LeapFuture(seconds=self.frames_throttle_secs,
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listener=self, event=event)
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self.running_future.start()
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else:
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self._send_event(event)
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def on_init(self, controller):
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self.prev_frame = None
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self.logger.info('Leap controller listener initialized')
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@ -155,7 +155,7 @@ class SoundPlugin(Plugin):
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data = q.get_nowait()
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except queue.Empty:
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self.logger.warning('Buffer is empty: increase buffersize?')
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return
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raise sd.CallbackAbort
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if len(data) < len(outdata):
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outdata[:len(data)] = data
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@ -647,8 +647,11 @@ class SoundPlugin(Plugin):
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for i, event in completed_callback_events.items():
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event.wait()
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if i in self.completed_callback_events:
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del self.completed_callback_events[i]
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if i in self.active_streams:
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del self.active_streams[i]
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if i in self.stream_mixes:
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del self.stream_mixes[i]
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self.logger.info('Playback stopped on streams [{}]'.format(
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@ -730,10 +733,6 @@ class SoundPlugin(Plugin):
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:type frequency: float
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"""
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if sound_index is None and midi_note is None and frequency is None:
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raise RuntimeError('Please specify either a sound index, ' +
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'midi_note or frequency to release')
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mixes = {
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i: mix for i, mix in self.stream_mixes.items()
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} if stream_index is None else {
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@ -131,7 +131,8 @@ class Sound(object):
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:param samplerate: Audio sample rate. Default: 44100 Hz
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:type samplerate: int
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:returns: A numpy.ndarray[n,1] with the raw float values
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:returns: A ``numpy.ndarray[(t_end-t_start)*samplerate, 1]``
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with the raw float values
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"""
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import numpy as np
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@ -156,6 +157,45 @@ class Sound(object):
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return self.gain * wave
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def fft(self, t_start=0., t_end=0., samplerate=_DEFAULT_SAMPLERATE,
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freq_range=None, freq_buckets=None):
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"""
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Get the Fourier transform associated to a time-bounded sample of this
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sound
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:param t_start: Start offset for the wave in seconds. Default: 0
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:type t_start: float
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:param t_end: End offset for the wave in seconds. Default: 0
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:type t_end: float
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:param samplerate: Audio sample rate. Default: 44100 Hz
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:type samplerate: int
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:param freq_range: FFT frequency range. Default: ``(0, samplerate/2)``
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(see `Nyquist-Shannon sampling theorem <https://en.wikipedia.org/wiki/Nyquist%E2%80%93Shannon_sampling_theorem>`_)
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:type freq_range: list or tuple with 2 int elements (range)
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:param freq_buckets: Number of buckets to subdivide the frequency range.
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Default: None
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:type freq_buckets: int
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:returns: A numpy.ndarray[freq_range,1] with the raw float values
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"""
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import numpy as np
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if not freq_range:
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freq_range = (0, int(samplerate/2))
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wave = self.get_wave(t_start=t_start, t_end=t_end, samplerate=samplerate)
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fft = np.fft.fft(wave.reshape(len(wave)))[freq_range[0]:freq_range[1]]
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if freq_buckets is not None:
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fft = np.histogram(fft, bins=freq_buckets)
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return fft
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def __iter__(self):
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for attr in ['midi_note', 'frequency', 'gain', 'duration']:
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yield (attr, getattr(self, attr))
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@ -278,6 +318,46 @@ class Mix(object):
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return wave
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def fft(self, t_start=0., t_end=0., samplerate=Sound._DEFAULT_SAMPLERATE,
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freq_range=None, freq_buckets=None):
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"""
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Get the Fourier transform associated to a time-bounded sample of this
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mix
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:param t_start: Start offset for the wave in seconds. Default: 0
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:type t_start: float
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:param t_end: End offset for the wave in seconds. Default: 0
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:type t_end: float
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:param samplerate: Audio sample rate. Default: 44100 Hz
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:type samplerate: int
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:param freq_range: FFT frequency range. Default: ``(0, samplerate/2)``
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(see `Nyquist-Shannon sampling theorem <https://en.wikipedia.org/wiki/Nyquist%E2%80%93Shannon_sampling_theorem>`_)
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:type freq_range: list or tuple with 2 int elements (range)
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:param freq_buckets: Number of buckets to subdivide the frequency range.
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Default: None
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:type freq_buckets: int
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:returns: A numpy.ndarray[freq_range,1] with the raw float values
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"""
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import numpy as np
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if not freq_range:
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freq_range = (0, int(samplerate/2))
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wave = self.get_wave(t_start=t_start, t_end=t_end, samplerate=samplerate)
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fft = np.fft.fft(wave.reshape(len(wave)))[freq_range[0]:freq_range[1]]
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if freq_buckets is not None:
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fft = np.histogram(fft, bins=freq_buckets)
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return fft
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def duration(self):
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"""
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:returns: The duration of the mix in seconds as duration of its longest
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