def populate(self, directory):
'''
Analyzes all audio files in a directory and add their fingerprint
to the database. Writes result to disk when done.
Args:
directory: directory containing audio files.
'''
audio_files = sorted(soundfiles.find_files(directory + '/*'))
c.notice("Reading {} files...".format(len(audio_files)))
i = 0
for filename in audio_files:
i += 1
c.write('\r\t-file ' + str(i) + ' of ' + str(len(audio_files)))
signal = soundfiles.load_signal(filename)
self.add(fingerprint.get_tokens(signal))
c.write("\n")
c.notice("Writing database to disk...")
self.save()
c.succes("Database written")
def populate(self, directory):
'''
Analyzes all audio files in a directory and add their fingerprint
to the database. Writes result to disk when done.
Args:
directory: directory containing audio files.
'''
audio_files = sorted(soundfiles.find_files(directory + '/*'))
c.notice("Reading {} files...".format(len(audio_files)))
i = 0
for filename in audio_files:
i += 1
c.write('\r\t-file ' + str(i) + ' of ' + str(len(audio_files)))
signal = soundfiles.load_signal(filename)
self.add(fingerprint.get_tokens(signal))
c.write("\n")
c.notice("Writing database to disk...")
self.save()
c.succes("Database written")
This program generates random testcases from the pokemon sounds.
'''
import soundfiles
import random
import matplotlib.pyplot as plt
import wave
import numpy as np
import os
if not os.path.exists("audio/pokemon"):
os.makedirs("audio/pokemon")
directory = "training/pokemon/*.wav"
files = soundfiles.find_files(directory)
for f in files:
signal = soundfiles.load_signal(f)
'''
initialize the suffix of the new file and the new samples
'''
suffix = ""
new_samples = signal.samples
if random.random() < 0.5:
'''
add noise
'''
new_samples += 0.05 - 0.1 * np.random.rand(len(new_samples))
This program generates random testcases from the pokemon sounds.
'''
import soundfiles
import random
import matplotlib.pyplot as plt
import wave
import numpy as np
import os
if not os.path.exists("audio/pokemon"):
os.makedirs("audio/pokemon")
directory = "training/pokemon/*.wav"
files = soundfiles.find_files(directory)
for f in files:
signal = soundfiles.load_signal(f)
'''
initialize the suffix of the new file and the new samples
'''
suffix = ""
new_samples = signal.samples
if random.random() < 0.5:
'''
add noise
'''
new_samples += 0.05 - 0.1 * np.random.rand(len(new_samples))
suffix += "-noise"
'''
This file tests the classifier. It uses the generates testcases from
generate_samples.py.
'''
from database import Database
from soundfiles import load_signal, find_files
from fingerprint import get_tokens
import matplotlib.pyplot as plt
from random import shuffle
from sys import exit
database = Database("pokemon", replace=False)
classifier = database.as_classifier()
filenames = find_files("audio/pokemon/*.wav")
if not filenames:
print "No files found"
exit()
print "Start testing classifier with {} files\n".format(len(filenames))
shuffle(filenames)
correct_match = 0
wrong_match = 0
no_match = 0
wrong_matches = ""
correct_matches = ""
'''
This file tests the classifier. It uses the generates testcases from
generate_samples.py.
'''
from database import Database
from soundfiles import load_signal, find_files
from fingerprint import get_tokens
import matplotlib.pyplot as plt
from random import shuffle
from sys import exit
database = Database("pokemon", replace=False)
classifier = database.as_classifier()
filenames = find_files("audio/pokemon/*.wav")
if not filenames:
print "No files found"
exit()
print "Start testing classifier with {} files\n".format(len(filenames))
shuffle(filenames)
correct_match = 0
wrong_match = 0
no_match = 0
wrong_matches = ""
correct_matches = ""
