def __init__(self):
self.frame_count = 0
self.motion_frames = 0
self.mode = 'uncalibrated'
self._set_led = freenect.LED_BLINK_YELLOW
self._set_video = None
self._last_img = 0
self._snapshot = False
self._last_setting_check = 0
self.settings_delay = 10
self.snapshot_secs = 5
self.debug = True
self.nightvision = None
self.dsum_buffer = RingBuffer(100)
self.running_avg = AvgMatrix(15)
self.load_settings()
self.s3bucket = boto.connect_s3(settings.AWS_KEY,
settings.AWS_SECRET).create_bucket(
settings.AWS_BUCKET)
class Watcher(object):
def __init__(self):
self.frame_count = 0
self.motion_frames = 0
self.mode = 'uncalibrated'
self._set_led = freenect.LED_BLINK_YELLOW
self._set_video = None
self._last_img = 0
self._snapshot = False
self._last_setting_check = 0
self.settings_delay = 10
self.snapshot_secs = 5
self.debug = True
self.nightvision = None
self.dsum_buffer = RingBuffer(100)
self.running_avg = AvgMatrix(15)
self.load_settings()
self.s3bucket = boto.connect_s3(settings.AWS_KEY,
settings.AWS_SECRET).create_bucket(
settings.AWS_BUCKET)
def load_settings(self):
profile = UserProfile.objects.get()
if self.debug:
print 'load_settings', profile.motion_sensitivity, profile.nightvision_on
# low
if profile.motion_sensitivity < 10:
self.change_threshold = 1.5
self.min_report_event = 30
# high
elif profile.motion_sensitivity > 10:
self.change_threshold = 0.7
self.min_report_event = 15
# normal
else:
self.change_threshold = 1.0
self.min_report_event = 20
if profile.nightvision_on != self.nightvision:
self.nightvision = profile.nightvision_on
self._set_video = (freenect.VIDEO_IR_8BIT if self.nightvision
else freenect.VIDEO_RGB)
def set_mode(self, mode):
if mode == 'nomotion':
self._set_led = freenect.LED_GREEN
elif mode == 'motion':
self._set_led = freenect.LED_RED
else:
raise ValueError('unknown mode')
self.mode = mode
def depth_callback(self, dev, data, timestamp):
# add the data to our running average
self.running_avg.add(data)
if self.mode == 'uncalibrated':
self.frame_count += 1
if self.frame_count == self.dsum_buffer.size():
self.set_mode('nomotion')
else:
mean_array = self.running_avg.mean()
# difference from sum of buffer
dsum = mean_array.sum()
self.dsum_buffer.add(dsum)
delta = self.dsum_buffer.std_delta(dsum)
# frame will count as a motion frame
if delta > self.change_threshold:
self.motion_frames += 1
if (self.motion_frames == self.min_report_event and
self.mode == 'nomotion'):
self.set_mode('motion')
alert = Alert.objects.create(event_type='motion')
self._snapshot = alert.id
else:
# don't let motion_frames drop below 0
self.motion_frames = max(self.motion_frames-1, 0)
if self.motion_frames == 0 and self.mode == 'motion':
self.set_mode('nomotion')
# could log how long the event was and its intensity here
if self.debug:
cv.ShowImage('Depth', simplify_cv(mean_array.astype(numpy.uint16)))
cv.WaitKey(1)
def body_callback(self, dev, ctx):
# _set_led hackery is required because for some reason calling set_led
# from update loop hangs the process
if self._set_led:
freenect.set_led(dev, self._set_led)
self._set_led = None
if self._set_video is not None:
freenect.stop_video(dev)
freenect.set_video_mode(dev, freenect.RESOLUTION_MEDIUM,
self._set_video)
freenect.start_video(dev)
self._set_video = None
if self._last_setting_check + self.settings_delay < time.time():
self.load_settings()
self._last_setting_check = time.time()
def video_callback(self, dev, data, timestamp):
if self.nightvision:
cv_data = simplify_cv(data)
else:
cv_data = video_cv(data)
if self.debug:
cv.ShowImage('Video', cv_data)
if (self._last_img + self.snapshot_secs < time.time() or
self._snapshot):
cv.SaveImage('babby-current.jpg', cv_data)
k = boto.s3.key.Key(self.s3bucket)
if self._snapshot:
k.key = '/babby/snapshot-%s.jpg' % self._snapshot
self._snapshot = False
else:
k.key = '/babby/current.jpg'
k.set_contents_from_filename('babby-current.jpg')
k.set_acl('public-read')
self._last_img = time.time()
