Spaces:
Runtime error
Runtime error
from distutils.log import debug | |
import os, sys | |
import random | |
import datetime | |
import glob | |
# from xml.dom.minidom import Document | |
import markov | |
import pickle | |
import subprocess | |
import gradio as gr | |
import time | |
from MC.markov_chain import get_pngs | |
#TODO: convert these into inputs | |
# lengthofsong = 10 Should we control this? Setting it to random now | |
timesignature = ['3/4','4/4','1/8','6/8','2/4'] #Sometimes the letter “C” (meaning common time) will be used in place of 4/4. | |
#Both C and 4/4 indicate that there are four quarter note beats in each measure. | |
keysignature = ["C","G","D","No selection"] | |
difficulty = ["beginner","intermediate","expert"] | |
key_enforced = False | |
key_enforced = True #Set to true if user wants in specific key | |
# get the list of filenames (abc files downloaded from http://www.norbeck.nu/abc/) | |
# getdirs = [] | |
# dirs = ["hn201612/i/*.abc", "hn201612/s/*.abc"] | |
# dirs = ["data/*.abc"] | |
# dirs = ["data"] | |
# for dir1 in dirs: | |
# for filename in glob.iglob(dir1): | |
# getdirs += [filename] | |
selected_timeSign = '3/4' #Default values | |
selected_keySign = 'C' #Default Values | |
deployed = True | |
GlobalUIGallery = False | |
#Finds all absolute paths in directory | |
#https://stackoverflow.com/questions/9816816/get-absolute-paths-of-all-files-in-a-directory | |
def abs_paths(dir): | |
for dir_path,_,filenames in os.walk(dir): | |
for f in filenames: | |
yield os.path.abspath(os.path.join(dir_path, f)) | |
def time_sigFinder(time_Signature): | |
if time_Signature == "4/4": | |
return 'M:4/4',4 | |
elif time_Signature == "3/4": | |
return 'M:3/4',3 | |
elif time_Signature == "2/4": | |
return 'M:2/4',2 | |
elif time_Signature == "1/8": | |
pass | |
elif time_Signature == "2/4": | |
return 'M:2/4',2 | |
elif time_Signature == "2/2": | |
return 'M:2/2',2 | |
# def get_pngs(path): | |
# filelist=os.listdir(path) | |
# for fichier in filelist[:]: # filelist[:] makes a copy of filelist. | |
# if not(fichier.endswith(".png")): | |
# filelist.remove(fichier) | |
# newlist = [path+'/'+x for x in filelist] #making it cwd | |
# return newlist | |
def music_gen(difficulty,time_Signature, Key_Signature): | |
if deployed: | |
#delete all files stored in gen_songs_abc | |
command = "rm -r gen_songs_abc/*" | |
subprocess.Popen(command,shell=True,stdout=subprocess.PIPE,stderr=subprocess.PIPE).communicate() | |
corpus = [] | |
song = [] | |
selected_timeSign = time_Signature | |
selected_keySign = Key_Signature | |
data_path = "data/"+str(difficulty) | |
# ex_filename = "hn201612/i/hnsong1.abc" | |
# parsing on file to extract songs and add them to corpus | |
for filename in abs_paths(data_path): | |
with open(filename) as f: | |
lines = f.readlines() | |
last = len(lines) | |
accepted = False | |
for index, line in enumerate(lines): | |
if (line.find("|") < 0 and index - 1 == last): | |
# if the next line does not have pipes add song to corpus and then set song variable empty again | |
if accepted and key_enforced and key_accepted: | |
corpus.append(song) | |
accepted = False | |
key_accepted = False | |
if accepted: | |
corpus.append(song) | |
accepted = False | |
song = [] | |
else: | |
if line.find("|") > -1: | |
# a line should be split on "|" and copied to the corpus if it has pipes | |
sline = line.split("|") | |
# add the list of measures to the song | |
song += [x.strip("\r\n") for x in sline if len(x.strip("\r\n")) > 0] | |
last = index | |
elif "M:" in line: | |
#time signature | |
if selected_timeSign == "4/4": | |
if "4/4" in line or "C|" in line: | |
accepted = True | |
elif selected_timeSign in line: | |
accepted = True | |
elif line.find("K:") and key_enforced: | |
#key signature | |
if selected_keySign in line: | |
key_accepted = True | |
# print("Training on {} songs...".format(len(corpus))) | |
# MARKOV PART | |
# n-gram length for markov model | |
n = 1 | |
model = markov.generate_model_from_token_lists(corpus, n) | |
# save pickle | |
# with open('markov_chain.pickle', 'wb') as handle: | |
# pickle.dump(model, handle) | |
def nextword(word): | |
return markov.generate(model, 3, seed=word, max_iterations=1) | |
def writesong(songlength, first): | |
song = [first] | |
for i in range(songlength): | |
song += nextword(str(song[-1])) | |
return song | |
# choose a random song length from list of song lengths in corpus | |
lengthofsong = random.choice([len(x) for x in corpus if len(x) > 10]) | |
song_len = [len(x) for x in corpus if len(x)>10] | |
song_len.sort() | |
firstnote = markov.generate(model, n, max_iterations=3)[0] | |
# print "first note: {}".format(firstnote) | |
print("Here is the song in abc format:") | |
song = writesong(lengthofsong, firstnote) | |
dob = datetime.datetime.now().strftime('%H%M%S') | |
modifier = format(dob) | |
path = "gen_songs_abc/song_"+modifier | |
# make song file | |
# songname = "./gen_songs_abc/gen_song_{}.abc".modifier | |
song_path = path+"/gen_song_"+modifier #without extension | |
songname = path+"/gen_song_"+modifier+".abc" | |
print("\n\nYou can find the song in {}".format(songname)) | |
lastpart = lengthofsong - lengthofsong%4 | |
# hack to include dictionary at the beginning of every abc file | |
# will add a more sophisticated way to generate the values in the future | |
title = "Markov Song {}".format(dob) | |
final_timeS,numOfnotes = time_sigFinder(time_Signature) | |
songbeginning = ['X:1','T:' + title, 'R:song', 'C:Visakh Ajith', 'Z:id:hn-song-111', final_timeS, 'L:1/8', 'Q:1/4=120', 'K:G' | |
] | |
songbeginning = [x+"\n" for x in songbeginning] | |
# convert song to abc format and write to file | |
if not os.path.exists(path): | |
os.makedirs("gen_songs_abc/song_"+modifier) | |
newsong = open(os.path.abspath(songname), 'w') | |
newsong.writelines(songbeginning) | |
for i in range(lastpart): | |
newsong.write(" | ".join(song[i:i+numOfnotes]) + "\n") | |
newsong.write(" | ".join(song[lastpart:lengthofsong])) | |
newsong.close() | |
#abc2ly markov.abc | |
# lilypond -fpng markov.ly | |
#convert abc to markov | |
#create folder with that name and push .ly, midi and abc there? | |
f = open(song_path+".ly","w") | |
# subprocess.Popen(['/usr/bin/abc2midi',songname],stdout=subprocess.PIPE).communicate() | |
command = "abc2ly "+"-o "+song_path+".ly"+" "+songname | |
# cmd1 = subprocess.Popen(['/usr/bin/abc2ly','-o',song_path+".ly",songname],stdout=subprocess.PIPE,stderr=subprocess.PIPE) | |
# cmd1 = subprocess.Popen(command,shell=True,stdout=subprocess.PIPE,stderr=subprocess.PIPE) | |
subprocess.Popen(command,shell=True,stdout=subprocess.PIPE,stderr=subprocess.PIPE).communicate() | |
# os.system(command) | |
f.close() | |
# out, err = cmd1.communicate() | |
# # time.sleep(2) | |
cmd2 = subprocess.Popen(['lilypond','-fpng','-o',path,song_path+".ly"]).communicate() | |
# cmd2.wait() | |
#fluidsynth() dependency | |
# subprocess.Popen(['midi2audio',song_path+'.midi',song_path+'.wav']).communicate() | |
subprocess.Popen(['timidity',song_path+'.midi','-Ow','-o',song_path+'.wav']).communicate() | |
# output = str(temp.communicate()) | |
#Introduces this wait time as we were returning file path even before lilypond converted the abc file | |
# final_path = os.path.abspath(song_path+".png") | |
png_list = get_pngs(path) | |
return png_list,song_path+".wav" | |