def __init__(self, freq):
self.freq = freq
self.wav = None
self.histeresis = HISTERESIS_UP
self.old_histeresis = 0
self.is_recording = False
self.memory_up = []
self.insert_timestamp = False
# Energy (signal strength) estimation
self.dbfs_avg = None
self.dbfs_off = 0
self.display_count = 0
# Autocorrelation average
self.ac_avg = None
# IF
self.if_freq = freq - CENTER
# works because both if_freq and INPUT_RATE are multiples of STEP
self.carrier_table = [
cmath.exp((0 - 1j) * tau * t * (self.if_freq / INPUT_RATE))
for t in range(0, INGEST_SIZE * 2)
]
self.carrier_table = numpy.array(self.carrier_table)
self.if_period = INPUT_RATE // STEP
self.if_phase = 0
self.last_if_sample = numpy.array([])
# IF filtering
# complex samples, filter goes from -freq to +freq
self.if_filter = filters.low_pass(INPUT_RATE, IF_BANDWIDTH / 2, 48)
self.if_decimator = filters.decimator(INPUT_RATE // IF_RATE)
# Audio filter
self.audio_filter = filters.low_pass(IF_RATE, AUDIO_BANDWIDTH, 24)
self.audio_decimator = filters.decimator(IF_RATE // AUDIO_RATE)
self.dc_filter = filters.high_pass(AUDIO_RATE, 100, 6)
# Thread
def worker():
while True:
iqsamples = self.queue.get()
if iqsamples is None:
break
self._ingest(iqsamples)
self.queue.task_done()
self.queue = queue.Queue()
self.thread = threading.Thread(target=worker)
self.thread.start()
def prepare(image, show_image, logger):
# TODO comment
im_l = image.convert('L')
show_image(im_l, "ITU-R 601-2 luma transform")
logger("edge detection")
im_edges = filters.edge_detection(im_l)
show_image(im_edges, "edge detection")
im_h = filters.high_pass(im_edges, 100)
show_image(im_h, "high pass filters")
return im_h
def prepare(image, show_image, logger):
# TODO comment
im_l = image.convert('L')
show_image(im_l, "ITU-R 601-2 luma transform")
logger("edge detection")
im_edges = filters.edge_detection(im_l)
show_image(im_edges, "edge detection")
im_h = filters.high_pass(im_edges, 100)
show_image(im_h, "high pass filters")
return im_h
def transform(image, hough, show_image):
# TODO comment
im_hough = hough.transform(image)
show_image(im_hough, "hough transform")
# im_hough = filters.peaks(im_hough)
# show_image(im_hough, "peak extraction")
im_h2 = filters.high_pass(im_hough, 128)
show_image(im_h2, "second high pass filters")
im_h2 = filters.components(im_h2, 2)
show_image(im_h2, "components centers")
return im_h2
def transform(image, hough, show_image):
# TODO comment
im_hough = hough.transform(image)
show_image(im_hough, "hough transform")
# im_hough = filters.peaks(im_hough)
# show_image(im_hough, "peak extraction")
im_h2 = filters.high_pass(im_hough, 128)
show_image(im_h2, "second high pass filters")
im_h2 = filters.components(im_h2, 2)
show_image(im_h2, "components centers")
return im_h2
def transform(image, hough, show_image):
"""Produces a simplified Hough transformation of the input image."""
# TODO comment
im_hough = hough.transform(image)
show_image(im_hough, "hough transform")
# im_hough = filters.peaks(im_hough)
# show_image(im_hough, "peak extraction")
im_h2 = filters.high_pass(im_hough, 128)
show_image(im_h2, "second high pass filters")
im_h2 = filters.components(im_h2, 2)
show_image(im_h2, "components centers")
return im_h2
