def run_recognition(filename, print_output=False):
db = SqliteDatabase()
abs_filename = os.path.abspath(filename)
filename = abs_filename.rsplit(os.sep)[-1]
r = FileReader(abs_filename)
data = r.parse_audio()
Fs = data["Fs"]
channel_amount = len(data["channels"])
matches = []
for channeln, channel in enumerate(data["channels"]):
# TODO: Remove prints or change them into optional logging.
#if print_output:
# msg = " fingerprinting channel %d/%d"
# print(
# logmsg(msg, attrs=["dark"], prefix=filename)
# % (channeln + 1, channel_amount)
# )
matches.extend(find_matches(db, channel, Fs, filename, print_output))
#if print_output:
# msg = " finished channel %d/%d, got %d hashes"
# print(
# logmsg(msg, attrs=["dark"], prefix=filename)
# % (channeln + 1, channel_amount, len(matches))
# )
#print_match_results(db, matches, filename)
return matches
def run_recognition(filename, logger):
db = SqliteDatabase()
abs_filename = os.path.abspath(filename)
filename = abs_filename.rsplit(os.sep)[-1]
r = FileReader(abs_filename)
data = r.parse_audio()
Fs = data["Fs"]
channel_amount = len(data["channels"])
matches = []
for channeln, channel in enumerate(data["channels"]):
msg = " fingerprinting channel %d/%d"
logger.info(
logmsg(msg, attrs=["dark"], prefix=filename),
channeln + 1,
channel_amount,
)
matches.extend(find_matches(db, channel, logger, Fs, filename))
msg = " finished channel %d/%d, got %d hashes"
logger.info(
logmsg(msg, attrs=["dark"], prefix=filename),
channeln + 1,
channel_amount,
len(matches),
)
print_match_results(db, matches, logger, filename)
def get_dict_for_file(file_name):
reader = FileReader(filename=file_name)
audio = reader.parse_audio()
data = audio['channels']
hashes = set()
for channel in data:
channel_hashes = fingerprint(channel)
hashes |= set(channel_hashes)
dict_song = {hash: offset for hash, offset in hashes}
return dict_song
from libs.reader_file import FileReader
from libs.db_sqlite import SqliteDatabase
from libs.config import get_config
if __name__ == '__main__':
config = get_config()
db = SqliteDatabase()
path = "mp3/"
# fingerprint all files in a directory
for filename in os.listdir(path):
if filename.endswith(".mp3"):
reader = FileReader(path + filename)
audio = reader.parse_audio()
song = db.get_song_by_filehash(audio['file_hash'])
song_id = db.add_song(filename, audio['file_hash'])
msg = ' * %s %s: %s' % (
colored('id=%s', 'white', attrs=['dark']), # id
colored('channels=%d', 'white', attrs=['dark']), # channels
colored('%s', 'white', attrs=['bold']) # filename
)
print(msg % (song_id, len(audio['channels']), filename))
if song:
hash_count = db.get_song_hashes_count(song_id)
if hash_count > 0:
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
song = '/home/blacksec21/hello.mp3'
#seconds = 5
r = FileReader(song) # only get filename
# get data,fs,file_hash,extension,songname,num_channels
data = r.parse_audio()
Fs = data['Fs']
num_channel = len(data['channels'])
result = set()
matches = []
db = SqliteDatabase()
#channel_amount = len(data)
def grouper(iterable, n, fillvalue=None):
args = [iter(iterable)] * n
return (filter(None, values)
for values in izip_longest(fillvalue=fillvalue, *args))
if not args.file:
parser.print_help()
sys.exit(0)
visualise_console = bool(config['mic.visualise_console'])
visualise_plot = bool(config['mic.visualise_plot'])
reader = FileReader(args.file)
def grouper(iterable, n, fillvalue=None):
args = [iter(iterable)] * n
return (filter(None, values)
for values in izip_longest(fillvalue=fillvalue, *args))
data = reader.parse_audio()
channel_amount = len(data['channels'])
print colored(' * found %d samples in %d channels', attrs=['dark']) % (len(
data['channels'][0]), channel_amount)
Fs = data['Fs']
result = set()
matches = []
def find_matches(samples, Fs=fingerprint.DEFAULT_FS):
hashes = fingerprint.fingerprint(samples, Fs=Fs, plots=False)
return return_matches(hashes)
def return_matches(hashes):
from libs.reader_file import FileReader
song = None
seconds = 5
r = FileReader(
'/home/kwok/projects/audio-fingerprint-identifying-python/mp3/beatles.mp3')
print(r.parse_audio())