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recognize-from-microphone.py
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recognize-from-microphone.py
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#!/usr/bin/python
import os
import sys
import libs
import libs.fingerprint as fingerprint
import argparse
from argparse import RawTextHelpFormatter
from itertools import izip_longest
from termcolor import colored
from libs.config import get_config
from libs.reader_microphone import MicrophoneReader
from libs.visualiser_console import VisualiserConsole as visual_peak
from libs.visualiser_plot import VisualiserPlot as visual_plot
from libs.db_sqlite import SqliteDatabase
# from libs.db_mongo import MongoDatabase
if __name__ == '__main__':
config = get_config()
db = SqliteDatabase()
parser = argparse.ArgumentParser(formatter_class=RawTextHelpFormatter)
parser.add_argument('-s', '--seconds', nargs='?')
args = parser.parse_args()
if not args.seconds:
parser.print_help()
sys.exit(0)
seconds = int(args.seconds)
chunksize = 2**12 # 4096
channels = 2#int(config['channels']) # 1=mono, 2=stereo
record_forever = False
visualise_console = bool(config['mic.visualise_console'])
visualise_plot = bool(config['mic.visualise_plot'])
reader = MicrophoneReader(None)
reader.start_recording(seconds=seconds,
chunksize=chunksize,
channels=channels)
msg = ' * started recording..'
print colored(msg, attrs=['dark'])
while True:
bufferSize = int(reader.rate / reader.chunksize * seconds)
for i in range(0, bufferSize):
nums = reader.process_recording()
if visualise_console:
msg = colored(' %05d', attrs=['dark']) + colored(' %s', 'green')
print msg % visual_peak.calc(nums)
else:
msg = ' processing %d of %d..' % (i, bufferSize)
print colored(msg, attrs=['dark'])
if not record_forever: break
if visualise_plot:
data = reader.get_recorded_data()[0]
visual_plot.show(data)
reader.stop_recording()
msg = ' * recording has been stopped'
print colored(msg, attrs=['dark'])
def grouper(iterable, n, fillvalue=None):
args = [iter(iterable)] * n
return (filter(None, values) for values
in izip_longest(fillvalue=fillvalue, *args))
data = reader.get_recorded_data()
msg = ' * recorded %d samples'
print colored(msg, attrs=['dark']) % len(data[0])
# reader.save_recorded('test.wav')
Fs = fingerprint.DEFAULT_FS
channel_amount = len(data)
result = set()
matches = []
def find_matches(samples, Fs=fingerprint.DEFAULT_FS):
hashes = fingerprint.fingerprint(samples, Fs=Fs)
return return_matches(hashes)
def return_matches(hashes):
mapper = {}
for hash, offset in hashes:
mapper[hash.upper()] = offset
values = mapper.keys()
for split_values in grouper(values, 1000):
# @todo move to db related files
query = """
SELECT upper(hash), song_fk, offset
FROM fingerprints
WHERE upper(hash) IN (%s)
"""
query = query % ', '.join('?' * len(split_values))
x = db.executeAll(query, split_values)
matches_found = len(x)
if matches_found > 0:
msg = ' ** found %d hash matches (step %d/%d)'
print colored(msg, 'green') % (
matches_found,
len(split_values),
len(values)
)
else:
msg = ' ** not matches found (step %d/%d)'
print colored(msg, 'red') % (
len(split_values),
len(values)
)
for hash, sid, offset in x:
# (sid, db_offset - song_sampled_offset)
yield (sid, offset - mapper[hash])
for channeln, channel in enumerate(data):
# TODO: Remove prints or change them into optional logging.
msg = ' fingerprinting channel %d/%d'
print colored(msg, attrs=['dark']) % (channeln+1, channel_amount)
matches.extend(find_matches(channel))
msg = ' finished channel %d/%d, got %d hashes'
print colored(msg, attrs=['dark']) % (
channeln+1, channel_amount, len(matches)
)
def align_matches(matches):
diff_counter = {}
largest = 0
largest_count = 0
song_id = -1
for tup in matches:
sid, diff = tup
if diff not in diff_counter:
diff_counter[diff] = {}
if sid not in diff_counter[diff]:
diff_counter[diff][sid] = 0
diff_counter[diff][sid] += 1
if diff_counter[diff][sid] > largest_count:
largest = diff
largest_count = diff_counter[diff][sid]
song_id = sid
songM = db.get_song_by_id(song_id)
nseconds = round(float(largest) / fingerprint.DEFAULT_FS *
fingerprint.DEFAULT_WINDOW_SIZE *
fingerprint.DEFAULT_OVERLAP_RATIO, 5)
return {
"SONG_ID" : song_id,
"SONG_NAME" : songM[1],
"CONFIDENCE" : largest_count,
"OFFSET" : int(largest),
"OFFSET_SECS" : nseconds
}
total_matches_found = len(matches)
print ''
if total_matches_found > 0:
msg = ' ** totally found %d hash matches'
print colored(msg, 'green') % total_matches_found
song = align_matches(matches)
msg = ' => song: %s (id=%d)\n'
msg += ' offset: %d (%d secs)\n'
msg += ' confidence: %d'
print colored(msg, 'green') % (
song['SONG_NAME'], song['SONG_ID'],
song['OFFSET'], song['OFFSET_SECS'],
song['CONFIDENCE']
)
else:
msg = ' ** not matches found at all'
print colored(msg, 'red')