def compare_fingerprint_to_database(filename):
'''
Takes the mono .wav file and creates a fingerprint of it, which it then compares
to the existing database of fingerprints, returning information of most likely match.
'''
user_audio = fingerprint.location_fingerprint(filename)
fingerprints = model.Fingerprint.query.all()
database_iteration = []
max_offset = 0
for row in fingerprints:
db_audio = cPickle.loads(row.fingerprint)
ranked_matches = align(user_audio, db_audio)
current_song = {}
song_match = {}
current_song["title"] = row.title
current_song["artist"] = row.artist
current_song["offset"] = ranked_matches[0][1]
current_song["high_match"] = False
database_iteration.append(current_song)
for current_song in database_iteration:
if current_song["offset"] > max_offset:
max_offset = current_song["offset"]
for current_song in database_iteration:
if current_song["offset"] == max_offset:
current_song["high_match"] = True
return database_iteration
def compare_fingerprint_to_database(filename):
file1 = fingerprint.location_fingerprint(filename)
fingerprints = session.query(model.Fingerprint)
database_iteration = []
max_offset = 0
for row in fingerprints:
file2 = pickle.loads(row.fingerprint)
ranked_matches = align.align(file1, file2)
current_song = {}
song_match = {}
#assorted song information
current_song["title"] = row.title
current_song["artist"] = row.artist
current_song["album"] = row.album
current_song["offset"] = ranked_matches[0][1]
database_iteration.append(current_song)
for current_song in database_iteration:
if current_song["offset"] > max_offset:
max_offset = current_song["offset"]
#information for most likely match
for current_song in database_iteration:
if current_song["offset"] == max_offset:
song_match["title"] = current_song["title"]
song_match["artist"] = current_song["artist"]
song_match["album"] = current_song["album"]
return song_match
def add_fingerprint():
'''Add individual music data (including fingerprint) to database.'''
title = request.form.get('title')
artist = request.form.get('artist')
music_file = request.files['music_file']
filename = secure_filename("user_input.wav")
music_file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename))
comparison.change_stereo_to_mono(filename)
time.sleep(1)
music_fingerprint = fingerprint.location_fingerprint(filename)
pickled_song_fingerprint = cPickle.dumps(music_fingerprint)
new_fingerprint = Fingerprint(title = title,
artist = artist,
fingerprint = pickled_song_fingerprint)
db.session.add(new_fingerprint)
db.session.commit()
return redirect("/database")
def load_test_data(wav_file): song_fingerprint = fingerprint.location_fingerprint(wav_file) pickled_song_fingerprint = pickle.dumps(song_fingerprint) song = model.Fingerprint(fingerprint = pickled_song_fingerprint) session.add(song) session.commit()