mp2i-vms.fr
small refactoring of main function
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64a2a96628
commit
05b642bdcc
200
cleaned_sp.py
200
cleaned_sp.py
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@ -1,3 +1,13 @@
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from math import *
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import numpy as np
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import scipy as scp
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from scipy.io import wavfile
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import matplotlib.pyplot as plt
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import subprocess
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import heapq
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from pathlib import Path
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from time import sleep
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def is_data_stereo(raw_global_data:list) -> bool:
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"""
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self-explainatory
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@ -11,14 +21,17 @@ def is_data_stereo(raw_global_data:list) -> bool:
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return True
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def dist_to_integer(x):
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ent = np.floor(x+0.5)
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return np.abs(x - ent)
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ent = np.floor(x)
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if(ent < 0.5):
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return ent
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else:
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return (1-ent)
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def is_note_within(fr1, fr2):
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if(fr1 > fr2):
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return (fr1/fr2 <= NOTE_DIST and dist_to_integer(fr1/fr2) >= OCTAVE_DIST)
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return (fr1/fr2 <= NOTE_DIST or dist_to_integer(fr1/fr2) >= OCTAVE_DIST) # same tone or octave
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else:
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return (fr2/fr1 <= NOTE_DIST and dist_to_integer(fr2/fr1) >= OCTAVE_DIST)
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return (fr2/fr1 <= NOTE_DIST or dist_to_integer(fr2/fr1) >= OCTAVE_DIST)
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def keep_highest(song_name, offset, songlen, segsize, count, output_name, minfreq=110, maxfreq=5000, ampthr=250):
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# extracting data from cropped song
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@ -114,7 +127,7 @@ def keep_highest(song_name, offset, songlen, segsize, count, output_name, minfre
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amp_ct = 0
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incr_a = segsize*4
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len_seg_a = int(sample_rate*incr_a)
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count_a = len_seg_a//1250
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count_a = len_seg_a//1000
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left_0 = int(sample_rate*(amp_ct+offset))
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while(amp_ct < songlen-segsize):
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left = int(sample_rate*(amp_ct+offset))
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@ -139,8 +152,10 @@ def keep_highest(song_name, offset, songlen, segsize, count, output_name, minfre
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time_d = 0.035
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cur_t = 0
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locs = []
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loct = []
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last_t = -10.0
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locs = [] # amplitudes
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loct = [] # times
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for i in range(len(new_new_amps)):
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if(new_new_amps[i] > 100):
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if(not in_seg):
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@ -153,109 +168,80 @@ def keep_highest(song_name, offset, songlen, segsize, count, output_name, minfre
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cur_t += 1/sample_rate
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if(in_seg and cur_t >= time_d):
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in_seg = False
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locs.append(a_ampl)
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loct.append((left_id + right_id)/(2*sample_rate) + offset)
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delta_t = (right_id - left_id)/sample_rate
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if(np.abs(left_id/sample_rate - last_t) >= 0.01): # these notes are less than 10ms apart !
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last_t = right_id/sample_rate
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if(delta_t < segsize*1.1):
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locs.append(a_ampl)
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loct.append((left_id + right_id)/(2*sample_rate) + offset)
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else:
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locs.append(a_ampl)
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loct.append([left_id/sample_rate, right_id/sample_rate])
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a_ampl = 0
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# detect sliders
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sl_a = []
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sl_t = []
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in_slider = False
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slider_dtct = segsize
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for i in range(1, len(loct)-1):
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delta = loct[i] - loct[i-1]
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delta2 = loct[i+1] - loct[i]
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if(delta < slider_dtct and delta2 < slider_dtct):
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if(in_slider):
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sl_t.append(loct[i])
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sl_a.append(locs[i])
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else:
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in_slider = True
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sl_t.append(loct[i-1])
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sl_a.append(locs[i-1])
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sl_t.append(loct[i])
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sl_a.append(locs[i])
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# -------------------------------------------- Clean with freq -------------------------------------------- #
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ssize_0 = segsize/3
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locf = [] # frequencies
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for k in range(len(locs)):
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ktime = 0
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ssize = ssize_0
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if(type(loct[k]) == float): # circle
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ktime = loct[k]
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else: # slider
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ktime = (loct[k][1]+loct[k][0])/2
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ssize = max((loct[k][1]-loct[k][0])/2, ssize_0)
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left_id = max(0, int((ktime-ssize/2)*sample_rate))
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right_id = min(int((ktime+ssize/2)*sample_rate), len(song_data))
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# calculate the fft
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pff = scp.fft.rfft(song_data[left_id:right_id])
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fmax = pfreq[0]
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fampmax = 0
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for i in range(1, len(pff)):
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if(pfreq[i] > minfreq and pfreq[i] < maxfreq and fampmax < np.abs(pff[i])):
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fmax = pfreq[i]
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fampmax = np.abs(pff[i])
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locf.append(fmax)
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# -------------------------------------------- Plot -------------------------------------------- #
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plt_loct_all = []
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plt_loct = []
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plt_locs = []
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plt_slidt = []
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plt_slids = []
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for i in range(len(loct)):
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if(type(loct[i]) == float):
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plt_loct_all.append(loct[i])
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plt_loct.append(loct[i])
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plt_locs.append(locs[i])
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else:
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in_slider = False
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plt_loct_all.append(loct[i][0])
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plt_slidt.append(loct[i][0])
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plt_slidt.append(loct[i][1])
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plt_slids.append(locs[i])
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plt_slids.append(locs[i])
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plt.plot(new_new_t, new_new_amps, "b-")
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plt.plot(loct, locs, "ro")
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plt.plot(sl_t, sl_a, "go")
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plt.grid()
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plt.show()
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# -------------------------------------------- Localize -------------------------------------------- #
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timing_points = []
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last_freq = new_freqs[0]
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for i in range(len(new_times)):
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if(np.abs(new_ampls[i]) > ampthr and (i == 0 or not is_note_within(new_freqs[i], last_freq))):
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last_freq = new_freqs[i]
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timing_points.append(new_times[i])
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new_kept.append(new_freqs[i])
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else:
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new_kept.append(0)
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mx = max(new_ampls)
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plt.plot(new_new_t, new_new_amps, "y-")
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plt.plot(plt_loct, plt_locs, "ro")
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plt.plot(plt_slidt, plt_slids, "go")
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plt.plot(plt_loct_all, locf, "mo")
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plt.plot(new_times, new_freqs)
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'''plt.plot(new_times, new_freqs)
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plt.plot(new_times, [elt*1000/mx for elt in new_ampls])
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plt.plot(new_times, new_kept, "ro")
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plt.plot(new_times, new_kept, "bo")'''
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plt.grid()
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plt.show()
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# -------------------------------------------- Write -------------------------------------------- #
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i0 = 0
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timing_points.append(999999)
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write_freq = 880
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write_cur = 0
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write_id = -1
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while(write_cur <= write_freq): # shouldnt seg fault
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write_id += 1
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write_cur = pfreq[write_id]
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# remove
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# i = time, j = freq
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for i in range(len(fft_list)):
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# retrieve dominant freq
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if(segsize*i >= timing_points[i0]-offset):
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i0 += 1
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maxfreq = 0
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maxfreqid = 0
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maxamp = 0
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for j in range(len(fft_list[0])):
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if(np.abs(fft_list[i][j]) > maxamp):
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maxamp = np.abs(fft_list[i][j])
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maxfreq = pfreq[j]
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maxfreqid = j
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fft_list_untouched[i][write_id] = max(maxamp*2, 32767)
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fft_list_untouched[i][write_id-1] = max(maxamp*2, 32767)
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fft_list_untouched[i][write_id+1] = max(maxamp*2, 32767)
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res = []
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print("Converting...")
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for i in range(len(fft_list_untouched)):
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ift = scp.fft.irfft(fft_list_untouched[i], n=blit)
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for k in ift:
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res.append(k)
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#print(type(res[0]))
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mx = 0
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for j in range(len(res)):
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if(res[j] > mx):
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mx = res[j]
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for i in range(len(res)):
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res[i] = np.int16(32767*res[i]/mx)
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res = np.array(res)
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wavfile.write(output_name, sample_rate, res)
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return (loct, sl_t, timing_points) # amplitude result, sliders and frequency result
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return (loct, locs) # amplitude result, sliders and frequency result
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def convert_to_wav(song_name:str, output_file="audio.wav") -> str:
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"""
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@ -312,22 +298,22 @@ def retrieve_all_from_song(filename, t0, t1, bpm, dta=0.001, dtf=0.01, threshold
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plt.show()
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# free()
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'''
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# c-type
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SONG_LEN = 7
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OFFSET = 0.042
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BPM = 149.3
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SEGSIZE = 1/(BPM/60)
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wavved_song = convert_to_wav("ctype.mp3")
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wavved_song = convert_to_wav("songs/ctype.mp3")
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'''
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# tetris_2
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SONG_LEN = 10
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OFFSET = 0
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BPM = 157
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SEGSIZE = 1/(BPM/60)
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wavved_song = convert_to_wav("tetris_2.wav")
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'''
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wavved_song = convert_to_wav("songs/tetris_2.wav")
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'''
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# test
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SONG_LEN = 1
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@ -341,7 +327,7 @@ SONG_LEN = 5
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OFFSET = 1.652
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BPM = 155
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SEGSIZE = 1/(BPM/60)
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wavved_song = convert_to_wav("furioso melodia.mp3")
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wavved_song = convert_to_wav("songs/furioso melodia.mp3")
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'''
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'''
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# E
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@ -349,7 +335,7 @@ SONG_LEN = 30
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OFFSET = 2.641
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BPM = 155
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SEGSIZE = 1/(BPM/60)
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wavved_song = convert_to_wav("rushe.mp3")
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wavved_song = convert_to_wav("songs/rushe.mp3")
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'''
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'''
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# Tsubaki
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@ -357,7 +343,7 @@ SONG_LEN = 10
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OFFSET = 35.659
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BPM = 199
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SEGSIZE = 1/(BPM/60)
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wavved_song = convert_to_wav("TSUBAKI.mp3")
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wavved_song = convert_to_wav("songs/TSUBAKI.mp3")
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'''
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'''
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# death
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@ -368,7 +354,7 @@ SEGSIZE = 1/(BPM/60)
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wavved_song = convert_to_wav("songs/Night of Knights.mp3")
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'''
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#wavved_song = convert_to_wav("tetris_2.wav")
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#wavved_song = convert_to_wav("songs/tetris_2.wav")
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NOTE_DIST = (2**(1/4))
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OCTAVE_DIST = 0.05
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