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| import numpy | |
| def open_audio(filename=None, lib='auto'): | |
| if filename is None: | |
| from tkinter.filedialog import askopenfilename | |
| filename = askopenfilename(title='select song', filetypes=[("mp3", ".mp3"),("wav", ".wav"),("flac", ".flac"),("ogg", ".ogg"),("wma", ".wma")]) | |
| filename=filename.replace('\\', '/') | |
| if lib=='pedalboard.io': | |
| from pedalboard.io import AudioFile | |
| with AudioFile(filename) as f: | |
| audio = f.read(f.frames) | |
| samplerate = f.samplerate | |
| elif lib=='librosa': | |
| import librosa | |
| audio, samplerate = librosa.load(filename, sr=None, mono=False) | |
| elif lib=='soundfile': | |
| import soundfile | |
| audio, samplerate = soundfile.read(filename) | |
| audio=audio.T | |
| elif lib=='madmom': | |
| import madmom | |
| audio, samplerate = madmom.io.audio.load_audio_file(filename, dtype=float) | |
| audio=audio.T | |
| # elif lib=='pydub': | |
| # from pydub import AudioSegment | |
| # song=AudioSegment.from_file(filename) | |
| # audio = song.get_array_of_samples() | |
| # samplerate=song.frame_rate | |
| # print(audio) | |
| # print(filename) | |
| elif lib=='auto': | |
| for i in ('madmom', 'soundfile', 'librosa', 'pedalboard.io'): | |
| try: | |
| audio,samplerate=open_audio(filename, i) | |
| break | |
| except Exception as e: | |
| print(e) | |
| if len(audio)<2: audio=[audio,audio] | |
| return audio,samplerate | |
| def generate_sidechain(samplerate=44100, len=0.5, curve=2, vol0=0, vol1=1, smoothing=40): | |
| x=numpy.concaterate((numpy.linspace(1,0,smoothing),numpy.linspace(vol0,vol1,int(len*samplerate))**curve)) | |
| return(x,x) | |
| def outputfilename(output, filename, suffix='_beatswap'): | |
| return output+''.join(''.join(filename.split('/')[-1]).split('.')[:-1])+suffix+'.mp3' | |
| def generate_sine(len, freq, samplerate, volume=1): | |
| return numpy.sin(numpy.linspace(0, freq*3.1415926*2*len, int(len*samplerate)))*volume | |
| def generate_saw(len, freq, samplerate, volume=1): | |
| return (numpy.linspace(0, freq*2*len, int(len*samplerate))%2 - 1)*volume | |
| def generate_square(len, freq, samplerate, volume=1): | |
| return ((numpy.linspace(0, freq*2*len, int(len*samplerate)))//1%2 * 2 - 1)*volume | |
| class song: | |
| def __init__(self, filename=None, audio=None, samplerate=None, beatmap=None): | |
| if filename is None: | |
| from tkinter.filedialog import askopenfilename | |
| self.filename = askopenfilename(title='select song', filetypes=[("mp3", ".mp3"),("wav", ".wav"),("flac", ".flac"),("ogg", ".ogg"),("wma", ".wma")]) | |
| self.audio, self.samplerate=open_audio(self.filename) | |
| else: | |
| self.filename=filename | |
| if audio is None or samplerate is None: | |
| self.audio, self.samplerate=open_audio(self.filename) | |
| self.beatmap=beatmap | |
| self.filename=self.filename.replace('\\', '/') | |
| self.samplerate=int(self.samplerate) | |
| def write_audio(self, output:str, lib='auto'): | |
| if lib=='pedalboard.io': | |
| if not isinstance(self.audio,numpy.ndarray): self.audio=numpy.asarray(self.audio) | |
| #print(audio) | |
| from pedalboard.io import AudioFile | |
| with AudioFile(output, 'w', self.samplerate, self.audio.shape[0]) as f: | |
| f.write(self.audio) | |
| elif lib=='soundfile': | |
| if not isinstance(self.audio,numpy.ndarray): self.audio=numpy.asarray(self.audio) | |
| audio=self.audio.T | |
| import soundfile | |
| soundfile.write(output, audio, self.samplerate) | |
| del audio | |
| elif lib=='auto': | |
| for i in ('soundfile', 'pedalboard.io'): | |
| try: | |
| song.write_audio(self, output, i) | |
| break | |
| except Exception as e: | |
| print(e) | |
| # elif lib=='pydub': | |
| # from pydub import AudioSegment | |
| # song = AudioSegment(self.audio.tobytes(), frame_rate=self.samplerate, sample_width=2, channels=2) | |
| # format = output.split('.')[-1] | |
| # if len(format) > 4: | |
| # format='mp3' | |
| # output = output + '.' + format | |
| # song.export(output, format=format) | |
| def beatmap_scale(self, scale:float): | |
| import math | |
| if scale!=1: | |
| a=0 | |
| b=numpy.array([]) | |
| while a <len( self.beatmap[:-math.ceil(scale)]): | |
| b=numpy.append(b, (1-(a%1))*self.beatmap[math.floor(a)]+(a%1)*self.beatmap[math.ceil(a)]) | |
| a+=scale | |
| self.beatmap=b | |
| def analyze_beats(self, lib='madmom.BeatDetectionProcessor', caching=True, split=None): | |
| #if audio is None and filename is None: (audio, samplerate) = open_audio() | |
| if caching is True: | |
| import hashlib | |
| with open(self.filename, "rb") as f: | |
| file_hash = hashlib.blake2b() | |
| while chunk := f.read(8192): | |
| file_hash.update(chunk) | |
| import os | |
| if not os.path.exists('SavedBeatmaps'): | |
| os.mkdir('SavedBeatmaps') | |
| cacheDir="SavedBeatmaps/" + ''.join(self.filename.split('/')[-1]) + lib+"_"+file_hash.hexdigest()[:5]+'.txt' | |
| try: | |
| self.beatmap=numpy.loadtxt(cacheDir, dtype=int) | |
| return numpy.loadtxt(cacheDir, dtype=int) | |
| except OSError: pass | |
| if lib.split('.')[0]=='madmom': | |
| from collections.abc import MutableMapping, MutableSequence | |
| import madmom | |
| if lib=='madmom.BeatTrackingProcessor': | |
| proc = madmom.features.beats.BeatTrackingProcessor(fps=100) | |
| act = madmom.features.beats.RNNBeatProcessor()(madmom.audio.signal.Signal(self.audio.T, self.samplerate)) | |
| self.beatmap= proc(act)*self.samplerate | |
| if lib=='madmom.BeatTrackingProcessor.constant': | |
| proc = madmom.features.beats.BeatTrackingProcessor(fps=100, look_ahead=None) | |
| act = madmom.features.beats.RNNBeatProcessor()(madmom.audio.signal.Signal(self.audio.T, self.samplerate)) | |
| self.beatmap= proc(act)*self.samplerate | |
| if lib=='madmom.BeatTrackingProcessor.consistent': | |
| proc = madmom.features.beats.BeatTrackingProcessor(fps=100, look_ahead=None, look_aside=0) | |
| act = madmom.features.beats.RNNBeatProcessor()(madmom.audio.signal.Signal(self.audio.T, self.samplerate)) | |
| self.beatmap= proc(act)*self.samplerate | |
| elif lib=='madmom.BeatDetectionProcessor': | |
| proc = madmom.features.beats.BeatDetectionProcessor(fps=100) | |
| act = madmom.features.beats.RNNBeatProcessor()(madmom.audio.signal.Signal(self.audio.T, self.samplerate)) | |
| self.beatmap= proc(act)*self.samplerate | |
| elif lib=='madmom.BeatDetectionProcessor.consistent': | |
| proc = madmom.features.beats.BeatDetectionProcessor(fps=100, look_aside=0) | |
| act = madmom.features.beats.RNNBeatProcessor()(madmom.audio.signal.Signal(self.audio.T, self.samplerate)) | |
| self.beatmap= proc(act)*self.samplerate | |
| elif lib=='madmom.CRFBeatDetectionProcessor': | |
| proc = madmom.features.beats.CRFBeatDetectionProcessor(fps=100) | |
| act = madmom.features.beats.RNNBeatProcessor()(madmom.audio.signal.Signal(self.audio.T, self.samplerate)) | |
| self.beatmap= proc(act)*self.samplerate | |
| elif lib=='madmom.CRFBeatDetectionProcessor.constant': | |
| proc = madmom.features.beats.CRFBeatDetectionProcessor(fps=100, use_factors=True, factors=[0.5, 1, 2]) | |
| act = madmom.features.beats.RNNBeatProcessor()(madmom.audio.signal.Signal(self.audio.T, self.samplerate)) | |
| self.beatmap= proc(act)*self.samplerate | |
| elif lib=='madmom.DBNBeatTrackingProcessor': | |
| proc = madmom.features.beats.DBNBeatTrackingProcessor(fps=100) | |
| act = madmom.features.beats.RNNBeatProcessor()(madmom.audio.signal.Signal(self.audio.T, self.samplerate)) | |
| self.beatmap= proc(act)*self.samplerate | |
| elif lib=='madmom.DBNBeatTrackingProcessor.1000': | |
| proc = madmom.features.beats.DBNBeatTrackingProcessor(fps=100, transition_lambda=1000) | |
| act = madmom.features.beats.RNNBeatProcessor()(madmom.audio.signal.Signal(self.audio.T, self.samplerate)) | |
| self.beatmap= proc(act)*self.samplerate | |
| elif lib=='madmom.MultiModelSelectionProcessor': #broken | |
| proc = madmom.features.beats.RNNBeatProcessor(post_processor=None) | |
| predictions = proc(madmom.audio.signal.Signal(self.audio.T, self.samplerate)) | |
| mm_proc = madmom.features.beats.MultiModelSelectionProcessor(num_ref_predictions=None) | |
| self.beatmap= numpy.sort(mm_proc(predictions)*self.samplerate) | |
| elif lib=='madmom.DBNDownBeatTrackingProcessor': | |
| proc = madmom.features.downbeats.DBNDownBeatTrackingProcessor(beats_per_bar=[4], fps=100) | |
| act = madmom.features.downbeats.RNNDownBeatProcessor()(madmom.audio.signal.Signal(self.audio.T, self.samplerate)) | |
| self.beatmap= proc(act)*self.samplerate | |
| self.beatmap=self.beatmap[:,0] | |
| elif lib=='madmom.PatternTrackingProcessor': #broken | |
| from madmom.models import PATTERNS_BALLROOM | |
| proc = madmom.features.downbeats.PatternTrackingProcessor(PATTERNS_BALLROOM, fps=50) | |
| from madmom.audio.spectrogram import LogarithmicSpectrogramProcessor, SpectrogramDifferenceProcessor, MultiBandSpectrogramProcessor | |
| from madmom.processors import SequentialProcessor | |
| log = LogarithmicSpectrogramProcessor() | |
| diff = SpectrogramDifferenceProcessor(positive_diffs=True) | |
| mb = MultiBandSpectrogramProcessor(crossover_frequencies=[270]) | |
| pre_proc = SequentialProcessor([log, diff, mb]) | |
| act = pre_proc(madmom.audio.signal.Signal(self.audio.T, self.samplerate)) | |
| self.beatmap= proc(act)*self.samplerate | |
| self.beatmap=self.beatmap[:,0] | |
| elif lib=='madmom.DBNBarTrackingProcessor': #broken | |
| beats = song.analyze_beats(self,lib='madmom.DBNBeatTrackingProcessor', caching = caching) | |
| proc = madmom.features.downbeats.DBNBarTrackingProcessor(beats_per_bar=[4], fps=100) | |
| act = madmom.features.downbeats.RNNBarProcessor()(((madmom.audio.signal.Signal(self.audio.T, self.samplerate)), beats)) | |
| self.beatmap= proc(act)*self.samplerate | |
| elif lib=='librosa': #broken in 3.9, works in 3.8 | |
| import librosa | |
| beat_frames = librosa.beat.beat_track(y=self.audio[0], sr=self.samplerate,hop_length=512) | |
| self.beatmap = librosa.frames_to_samples(beat_frames[1]) | |
| # elif lib=='BeatNet': | |
| # from BeatNet.BeatNet import BeatNet # doesn't seem to work well for some reason | |
| # estimator = BeatNet(1, mode='offline', inference_model='DBN', plot=[], thread=False) | |
| # beatmap = estimator.process(filename) | |
| # beatmap=beatmap[:,0]*samplerate | |
| # elif lib=='jump-reward-inference': # doesn't seem to work well for some reason | |
| # from jump_reward_inference.joint_tracker import joint_inference | |
| # estimator = joint_inference(1, plot=False) | |
| # beatmap = estimator.process(filename) | |
| # beatmap=beatmap[:,0]*samplerate | |
| elif lib=='split': | |
| self.beatmap= list(range(0, len(self.audio), len(self.audio)//split)) | |
| if lib.split('.')[0]=='madmom': | |
| self.beatmap=numpy.absolute(self.beatmap-500) | |
| if caching is True: numpy.savetxt(cacheDir, self.beatmap.astype(int)) | |
| def audio_autotrim(self): | |
| n=0 | |
| for i in self.audio[0]: | |
| if i>=0.0001:break | |
| n+=1 | |
| self.audio = numpy.asarray([self.audio[0,n:], self.audio[1,n:]]) | |
| #print(beatmap) | |
| if self.beatmap is not None: | |
| self.beatmap=numpy.absolute(self.beatmap-n) | |
| else: | |
| print('It is recommended to only use autotrim after computing the beatmap') | |
| def beatmap_autoscale(self): | |
| bpm=(self.beatmap[-1]-self.beatmap[0])/(len(self.beatmap)-1) | |
| #print('BPM =', (bpm/samplerate) * 240, bpm) | |
| if bpm>=160000: scale=1/8 | |
| elif (bpm)>=80000: scale=1/4 | |
| elif (bpm)>=40000: scale=1/2 | |
| elif (bpm)<=20000: scale=2 | |
| elif (bpm)<=10000: scale=4 | |
| elif (bpm)<=5000: scale=8 | |
| song.beatmap_scale(self,scale) | |
| def beatmap_autoinsert(self): | |
| diff=(self.beatmap[1]-self.beatmap[0]) | |
| while diff<self.beatmap[0]: | |
| self.beatmap=numpy.insert(self.beatmap, 0, self.beatmap[0]-diff) | |
| def beatmap_shift(self, shift: float): | |
| if shift>0: | |
| for i in range(len(self.beatmap)-1): | |
| self.beatmap[i] = self.beatmap[i] + shift * (self.beatmap[i+1] - self.beatmap[i]) | |
| elif shift<0: | |
| for i in reversed(range(len(self.beatmap)-1)): | |
| self.beatmap[i+1] = self.beatmap[i+1] - shift * (self.beatmap[i] - self.beatmap[i+1]) | |
| def beatmap_trim(self, start=0, end=None): | |
| start*=self.samplerate | |
| self.beatmap=self.beatmap[self.beatmap>=start].astype(int) | |
| if end is not None: self.beatmap=self.beatmap[self.beatmap<=end].astype(int) | |
| def beatswap(self, pattern: str, sep=',', smoothing=40, smoothing_mode='replace'): | |
| import math, numpy | |
| # get pattern size | |
| size=0 | |
| #cut processing??? not worth it, it is really fast anyways | |
| pattern=pattern.replace(' ', '').split(sep) | |
| for j in pattern: | |
| s='' | |
| if '?' not in j: | |
| for i in j: | |
| if i.isdigit() or i=='.' or i=='-' or i=='/' or i=='+' or i=='%': s=str(s)+str(i) | |
| elif i==':': | |
| if s=='': s='0' | |
| size=max(math.ceil(float(eval(s))), size) | |
| s='' | |
| elif s!='': break | |
| if s=='': s='0' | |
| if s=='': s='0' | |
| size=max(size, eval(s)) | |
| if isinstance(self.audio,numpy.ndarray): self.audio=numpy.ndarray.tolist(self.audio) | |
| if self.beatmap.dtype!='int32': self.beatmap=self.beatmap.astype(int) | |
| #beat=[] | |
| #start=audio[:beatmap[0]] | |
| #end=audio[beatmap[-1]:audio[-1]] | |
| #for i in range(len(beatmap)-1): | |
| # beat[i]=audio[beatmap[i]:beatmap[i+1]] | |
| # audio is a tuple with l and r channels | |
| #print(len(audio)) | |
| self.audio=(self.audio[0], self.audio[1]) | |
| #print(beatmap[0], audio[0][100]) | |
| result=(self.audio[0][:self.beatmap[0]],self.audio[1][:self.beatmap[0]]) | |
| beat=numpy.asarray([[],[]]) | |
| # size, iterations are integers | |
| size=int(max(size//1, 1)) | |
| iterations=int(len(self.beatmap)//size) | |
| # add beat to the end | |
| self.beatmap=numpy.append(self.beatmap, len(self.audio[0])) | |
| def beatswap_getnum(i: str, c: str): | |
| if c in i: | |
| try: | |
| x=i.index(c)+1 | |
| z='' | |
| try: | |
| while i[x].isdigit() or i[x]=='.' or i[x]=='-' or i[x]=='/' or i[x]=='+' or i[x]=='%': | |
| z+=i[x] | |
| x+=1 | |
| return z | |
| except IndexError: | |
| return z | |
| except ValueError: return None | |
| #print(size, iterations) | |
| # processing | |
| for j in range(iterations): | |
| for i in pattern: | |
| if '!' not in i: | |
| n,s,st,reverse,z=0,'',None,False,None | |
| for c in i: | |
| n+=1 | |
| #print('c =', s, ', st =', st, ', s =', s, ', n =,',n) | |
| # Get the character | |
| if c.isdigit() or c=='.' or c=='-' or c=='/' or c=='+' or c=='%': | |
| s=str(s)+str(c) | |
| # If character is : - get start | |
| elif s!='' and c==':': | |
| #print ('Beat start:',s,'=', eval(s),'=',int(eval(s)//1), '+',j,'*',size,' =',int(eval(s)//1)+j*size, ', mod=',eval(s)%1) | |
| try: st=self.beatmap[int(eval(s)//1)+j*size ] + eval(s)%1* (self.beatmap[int(eval(s)//1)+j*size +1] - self.beatmap[int(eval(s)//1)+j*size]) | |
| except IndexError: break | |
| s='' | |
| # create a beat | |
| if s!='' and (n==len(i) or not(c.isdigit() or c=='.' or c=='-' or c=='/' or c=='+' or c=='%')): | |
| # start already exists | |
| if st is not None: | |
| #print ('Beat end: ',s,'=', eval(s),'=',int(eval(s)//1), '+',j,'*',size,' =',int(eval(s)//1)+j*size, ', mod=',eval(s)%1) | |
| try: | |
| s=self.beatmap[int(eval(s)//1)+j*size ] + eval(s)%1* (self.beatmap[int(eval(s)//1)+j*size +1] - self.beatmap[int(eval(s)//1)+j*size]) | |
| #print(s) | |
| except IndexError: break | |
| else: | |
| # start doesn't exist | |
| #print ('Beat start:',s,'=', eval(s),'=',int(eval(s)//1), '+',j,'*',size,'- 1 =',int(eval(s)//1)+j*size, ', mod=',eval(s)%1) | |
| #print ('Beat end: ',s,'=', eval(s),'=',int(eval(s)//1), '+',j,'*',size,' =',int(eval(s)//1)+j*size+1, ', mod=',eval(s)%1) | |
| try: | |
| st=self.beatmap[int(eval(s)//1)+j*size-1 ] + eval(s)%1* (self.beatmap[int(eval(s)//1)+j*size +1] - self.beatmap[int(eval(s)//1)+j*size]) | |
| s=self.beatmap[int(eval(s)//1)+j*size ] + eval(s)%1* (self.beatmap[int(eval(s)//1)+j*size +1] - self.beatmap[int(eval(s)//1)+j*size]) | |
| except IndexError: break | |
| if st>s: | |
| s, st=st, s | |
| reverse=True | |
| # create the beat | |
| if len(self.audio)>1: | |
| if smoothing_mode=='add': beat=numpy.asarray([self.audio[0][int(st):int(s)],self.audio[1][int(st):int(s)]]) | |
| else: beat=numpy.asarray([self.audio[0][int(st):int(s)-smoothing],self.audio[1][int(st):int(s)-smoothing]]) | |
| else: | |
| if smoothing_mode=='add': beat=numpy.asarray([self.audio[0][int(st):int(s)]]) | |
| else: beat=numpy.asarray([self.audio[0][int(st):int(s)-smoothing]]) | |
| # process the beat | |
| # channels | |
| z=beatswap_getnum(i,'c') | |
| if z is not None: | |
| if z=='': beat[0],beat[1]=beat[1],beat[0] | |
| elif eval(z)==0:beat[0]*=0 | |
| else:beat[1]*=0 | |
| # volume | |
| z=beatswap_getnum(i,'v') | |
| if z is not None: | |
| if z=='': z='0' | |
| beat*=eval(z) | |
| z=beatswap_getnum(i,'t') | |
| if z is not None: | |
| if z=='': z='2' | |
| beat**=1/eval(z) | |
| # speed | |
| z=beatswap_getnum(i,'s') | |
| if z is not None: | |
| if z=='': z='2' | |
| z=eval(z) | |
| if z<1: | |
| beat=numpy.asarray((numpy.repeat(beat[0],int(1//z)),numpy.repeat(beat[1],int(1//z)))) | |
| else: | |
| beat=numpy.asarray((beat[0,::int(z)],beat[1,::int(z)])) | |
| # bitcrush | |
| z=beatswap_getnum(i,'b') | |
| if z is not None: | |
| if z=='': z='3' | |
| z=1/eval(z) | |
| if z<1: beat=beat*z | |
| beat=numpy.around(beat, max(int(z), 1)) | |
| if z<1: beat=beat/z | |
| # downsample | |
| z=beatswap_getnum(i,'d') | |
| if z is not None: | |
| if z=='': z='3' | |
| z=int(eval(z)) | |
| beat=numpy.asarray((numpy.repeat(beat[0,::z],z),numpy.repeat(beat[1,::z],z))) | |
| # convert to list | |
| beat=beat.tolist() | |
| # effects with list | |
| # reverse | |
| if ('r' in i and reverse is False) or (reverse is True and 'r' not in i): | |
| beat=(beat[0][::-1],beat[1][::-1] ) | |
| # add beat to the result | |
| for a in range(len(self.audio)): | |
| #print('Adding beat... a, s, st:', a, s, st, sep=', ') | |
| #print(result[a][-1]) | |
| #print(beat[a][0]) | |
| if smoothing>0: result[a].extend(numpy.linspace(result[a][-1],beat[a][0],smoothing)) | |
| result[a].extend(beat[a]) | |
| #print(len(result[0])) | |
| # | |
| break | |
| #print(time.process_time() - benchmark) | |
| self.audio = result | |
| def beatsample(self, audio2, shift=0): | |
| try: l=len(audio2[0]) | |
| except (TypeError, IndexError): | |
| l=len(audio2) | |
| audio2=numpy.vstack((audio2,audio2)) | |
| for i in range(len(self.beatmap)): | |
| try: self.audio[:,int(self.beatmap[i]) + int(float(shift) * (int(self.beatmap[i+1])-int(self.beatmap[i]))) : int(self.beatmap[i])+int(float(shift) * (int(self.beatmap[i+1])-int(self.beatmap[i])))+int(l)]+=audio2 | |
| except (IndexError, ValueError): pass | |
| def sidechain(self, audio2, shift=0, smoothing=40): | |
| try: l=len(audio2[0]) | |
| except (TypeError, IndexError): | |
| l=len(audio2) | |
| audio2=numpy.vstack((audio2,audio2)) | |
| for i in range(len(self.beatmap)): | |
| try: self.audio[:,int(self.beatmap[i])-smoothing + int(float(shift) * (int(self.beatmap[i+1])-int(self.beatmap[i]))) : int(self.beatmap[i])-smoothing+int(float(shift) * (int(self.beatmap[i+1])-int(self.beatmap[i])))+int(l)]*=audio2 | |
| except (IndexError, ValueError): break | |
| def quick_beatswap(self, output='', pattern=None, scale=1, shift=0, start=0, end=None, autotrim=True, autoscale=False, autoinsert=False, suffix='_BeatSwap', lib='madmom.BeatDetectionProcessor'): | |
| if self.beatmap is None: song.analyze_beats(self,lib=lib) | |
| if autotrim is True: song.audio_autotrim(self) | |
| save=self.beatmap | |
| if autoscale is True: song.beatmap_autoscale(self) | |
| if shift!=0: song.beatmap_shift(self,shift) | |
| if scale!=1: song.beatmap_scale(self,scale) | |
| if autoinsert is True: song.beatmap_autoinsert(self) | |
| if start!=0 or end is not None: song.beatmap_trim(self,start, end) | |
| song.beatswap(self,pattern) | |
| if output is not None: | |
| if not (output.lower().endswith('.mp3') or output.lower().endswith('.wav') or output.lower().endswith('.flac') or output.lower().endswith('.ogg') or | |
| output.lower().endswith('.aac') or output.lower().endswith('.ac3') or output.lower().endswith('.aiff') or output.lower().endswith('.wma')): | |
| output=output+''.join(''.join(self.filename.split('/')[-1]).split('.')[:-1])+suffix+'.mp3' | |
| song.write_audio(self,output) | |
| self.beatmap=save | |
| def quick_sidechain(self, output='', audio2=None, scale=1, shift=0, start=0, end=None, autotrim=True, autoscale=False, autoinsert=False, filename2=None, suffix='_Sidechain', lib='madmom.BeatDetectionProcessor'): | |
| if filename2 is None and audio2 is None: | |
| audio2=generate_sidechain() | |
| if audio2 is None: | |
| audio2, samplerate2=open_audio(filename2) | |
| if self.beatmap is None: song.analyze_beats(self,lib=lib) | |
| if autotrim is True: song.audio_autotrim(self) | |
| save=self.beatmap | |
| if autoscale is True: song.beatmap_autoscale(self) | |
| if shift!=0: song.beatmap_shift(self,shift) | |
| if scale!=1: song.beatmap_scale(self,scale) | |
| if autoinsert is True: song.beatmap_autoinsert(self) | |
| if start!=0 or end is not None: song.beatmap_trim(self,start, end) | |
| song.sidechain(self,audio2) | |
| if output is not None: | |
| if not (output.lower().endswith('.mp3') or output.lower().endswith('.wav') or output.lower().endswith('.flac') or output.lower().endswith('.ogg') or | |
| output.lower().endswith('.aac') or output.lower().endswith('.ac3') or output.lower().endswith('.aiff') or output.lower().endswith('.wma')): | |
| output=output+''.join(''.join(self.filename.split('/')[-1]).split('.')[:-1])+suffix+'.mp3' | |
| song.write_audio(self,output) | |
| self.beatmap=save | |
| def quick_beatsample(self, output='', filename2=None, scale=1, shift=0, start=0, end=None, autotrim=True, autoscale=False, autoinsert=False, audio2=None, suffix='_BeatSample', lib='madmom.BeatDetectionProcessor'): | |
| if filename2 is None and audio2 is None: | |
| from tkinter.filedialog import askopenfilename | |
| filename2 = askopenfilename(title='select sidechain impulse', filetypes=[("mp3", ".mp3"),("wav", ".wav"),("flac", ".flac"),("ogg", ".ogg"),("wma", ".wma")]) | |
| if audio2 is None: | |
| audio2, samplerate2=open_audio(filename2) | |
| if self.beatmap is None: song.analyze_beats(self,lib=lib) | |
| if autotrim is True: song.audio_autotrim(self) | |
| save=numpy.copy(self.beatmap) | |
| if autoscale is True: song.beatmap_autoscale(self) | |
| if shift!=0: song.beatmap_shift(self,shift) | |
| if scale!=1: song.beatmap_scale(self,scale) | |
| if autoinsert is True: song.beatmap_autoinsert(self) | |
| if start!=0 or end is not None: song.beatmap_trim(self,start, end) | |
| song.beatsample(self,audio2) | |
| if output is not None: | |
| if not (output.lower().endswith('.mp3') or output.lower().endswith('.wav') or output.lower().endswith('.flac') or output.lower().endswith('.ogg') or | |
| output.lower().endswith('.aac') or output.lower().endswith('.ac3') or output.lower().endswith('.aiff') or output.lower().endswith('.wma')): | |
| output=output+''.join(''.join(self.filename.split('/')[-1]).split('.')[:-1])+suffix+'.mp3' | |
| song.write_audio(self,output) | |
| self.beatmap=save | |