def get_loops(fileobj, output_temp, inter=8.0, trans=2.0):
track = LocalAudioFile(fileobj.name)
tracks = [track, track, track] # 3 of em!
valid = []
# compute resampled and normalized matrices
for track in tracks:
track.resampled = resample_features(track, rate='beats')
track.resampled['matrix'] = timbre_whiten(track.resampled['matrix'])
# remove tracks that are too small
if is_valid(track, inter, trans):
valid.append(track)
# for compatibility, we make mono tracks stereo
track = make_stereo(track)
tracks = valid
if len(tracks) < 1: return []
# Initial transition. Should contain 2 instructions: fadein, and playback.
start = initialize(tracks[0], inter, trans)
# Middle transitions. Should each contain 2 instructions: crossmatch, playback.
middle = []
[middle.extend(make_transition(t1, t2, inter, trans)) for (t1, t2) in tuples(tracks)]
# Last chunk. Should contain 1 instruction: fadeout.
end = terminate(tracks[-1], FADE_OUT)
actions = start + middle + end
# output_temp = tempfile.NamedTemporaryFile(mode="w+b", suffix=".mp3")
render(actions, output_temp.name, False)
# Do it again
new_one = audio.LocalAudioFile(output_temp.name)
analysis = json.loads(urllib.urlopen(new_one.analysis.pyechonest_track.analysis_url).read())
return (output_temp.name, analysis)
def do_work(audio_files, options):
inter = float(options.inter)
trans = float(options.transition)
order = bool(options.order)
equal = bool(options.equalize)
verbose = bool(options.verbose)
# Get pyechonest/remix objects
analyze = lambda x: LocalAudioFile(
x, verbose=verbose, sampleRate=44100, numChannels=2)
tracks = map(analyze, audio_files)
# decide on an initial order for those tracks
if order == True:
if verbose: print "Ordering tracks..."
tracks = order_tracks(tracks)
if equal == True:
equalize_tracks(tracks)
if verbose:
print
for track in tracks:
print "Vol = %.0f%%\t%s" % (
track.gain * 100.0, track.analysis.pyechonest_track.title)
print
valid = []
# compute resampled and normalized matrices
for track in tracks:
if verbose:
print "Resampling features for", track.analysis.pyechonest_track.title
track.resampled = resample_features(track, rate='beats')
track.resampled['matrix'] = timbre_whiten(track.resampled['matrix'])
# remove tracks that are too small
if is_valid(track, inter, trans):
valid.append(track)
# for compatibility, we make mono tracks stereo
track = make_stereo(track)
tracks = valid
if len(tracks) < 1: return []
# Initial transition. Should contain 2 instructions: fadein, and playback.
if verbose: print "Computing transitions..."
start = initialize(tracks[0], inter, trans)
# Middle transitions. Should each contain 2 instructions: crossmatch, playback.
middle = []
[
middle.extend(make_transition(t1, t2, inter, trans))
for (t1, t2) in tuples(tracks)
]
# Last chunk. Should contain 1 instruction: fadeout.
end = terminate(tracks[-1], FADE_OUT)
return start + middle + end
def do_work(audio_files, options):
inter = float(options.inter)
trans = float(options.transition)
order = bool(options.order)
equal = bool(options.equalize)
verbose = bool(options.verbose)
# Get pyechonest/remix objects
analyze = lambda x : LocalAudioFile(x, verbose=verbose, sampleRate = 44100, numChannels = 2)
tracks = map(analyze, audio_files)
# decide on an initial order for those tracks
if order == True:
if verbose: print "Ordering tracks..."
tracks = order_tracks(tracks)
if equal == True:
equalize_tracks(tracks)
if verbose:
print
for track in tracks:
print "Vol = %.0f%%\t%s" % (track.gain*100.0, track.analysis.pyechonest_track.title)
print
valid = []
# compute resampled and normalized matrices
for track in tracks:
if verbose: print "Resampling features for", track.analysis.pyechonest_track.title
track.resampled = resample_features(track, rate='beats')
track.resampled['matrix'] = timbre_whiten(track.resampled['matrix'])
# remove tracks that are too small
if is_valid(track, inter, trans):
valid.append(track)
# for compatibility, we make mono tracks stereo
track = make_stereo(track)
tracks = valid
if len(tracks) < 1: return []
# Initial transition. Should contain 2 instructions: fadein, and playback.
if verbose: print "Computing transitions..."
start = initialize(tracks[0], inter, trans)
# Middle transitions. Should each contain 2 instructions: crossmatch, playback.
middle = []
[middle.extend(make_transition(t1, t2, inter, trans)) for (t1, t2) in tuples(tracks)]
# Last chunk. Should contain 1 instruction: fadeout.
end = terminate(tracks[-1], FADE_OUT)
return start + middle + end
def process(self, track):
if not hasattr(track.analysis.pyechonest_track, "title"):
setattr(track.analysis.pyechonest_track, "title", track._metadata.title)
log.info("Resampling features...", uid=track._metadata.id)
track.resampled = resample_features(track, rate='beats')
track.resampled['matrix'] = timbre_whiten(track.resampled['matrix'])
if not is_valid(track, self.transition_time):
raise ValueError("Track too short!")
track.gain = self.__db_2_volume(track.analysis.loudness)
log.info("Done processing.", uid=track._metadata.id)
return track
def process(self, track):
if not hasattr(track.analysis.pyechonest_track, "title"):
setattr(track.analysis.pyechonest_track, "title", track._metadata.track_details['title'])
log.info("Resampling features [%r]...", track._metadata.id)
if len(track.analysis.beats):
track.resampled = resample_features(track, rate='beats')
track.resampled['matrix'] = timbre_whiten(track.resampled['matrix'])
else:
log.info("no beats returned for this track.")
track.resampled = {"rate":'beats', "matrix": []}
track.gain = self.__db_2_volume(track.analysis.loudness)
log.info("Done processing [%r].", track._metadata.id)
return track
def get_loops(fileobj, output_temp, inter=8.0, trans=2.0):
track = LocalAudioFile(fileobj.name)
tracks = [track, track, track] # 3 of em!
valid = []
# compute resampled and normalized matrices
for track in tracks:
track.resampled = resample_features(track, rate='beats')
track.resampled['matrix'] = timbre_whiten(track.resampled['matrix'])
# remove tracks that are too small
if is_valid(track, inter, trans):
valid.append(track)
# for compatibility, we make mono tracks stereo
track = make_stereo(track)
tracks = valid
if len(tracks) < 1: return []
# Initial transition. Should contain 2 instructions: fadein, and playback.
start = initialize(tracks[0], inter, trans)
# Middle transitions. Should each contain 2 instructions: crossmatch, playback.
middle = []
[
middle.extend(make_transition(t1, t2, inter, trans))
for (t1, t2) in tuples(tracks)
]
# Last chunk. Should contain 1 instruction: fadeout.
end = terminate(tracks[-1], FADE_OUT)
actions = start + middle + end
# output_temp = tempfile.NamedTemporaryFile(mode="w+b", suffix=".mp3")
render(actions, output_temp.name, False)
# Do it again
new_one = audio.LocalAudioFile(output_temp.name)
analysis = json.loads(
urllib.urlopen(new_one.analysis.pyechonest_track.analysis_url).read())
return (output_temp.name, analysis)