diff --git a/Linked Horizon - Shinzou o Sasageyo! [TV Size] (Monstrata) [Insane].osu b/Linked Horizon - Shinzou o Sasageyo! [TV Size] (Monstrata) [Insane].osu deleted file mode 100644 index 947700c..0000000 --- a/Linked Horizon - Shinzou o Sasageyo! [TV Size] (Monstrata) [Insane].osu +++ /dev/null @@ -1,503 +0,0 @@ -osu file format v14 - -[General] -AudioFilename: audio.wav -AudioLeadIn: 0 -PreviewTime: 63278 -Countdown: 0 -SampleSet: Normal -StackLeniency: 0.5 -Mode: 0 -LetterboxInBreaks: 0 -WidescreenStoryboard: 1 - -[Editor] -DistanceSpacing: 1.2 -BeatDivisor: 4 -GridSize: 32 -TimelineZoom: 1.8 - -[Metadata] -Title:Shinzou o Sasageyo! [TV Size] -TitleUnicode:心臓を捧げよ! 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-309,133,84747,2,0,P|255:112|202:134,1,116.875002229214,10|0,0:2|0:0,0:0:0:0: -392,294,85122,2,0,P|439:326|495:318,1,116.875002229214,14|0,0:2|0:0,0:0:0:0: -257,187,85497,1,10,0:3:0:0: -249,205,85590,1,0,0:0:0:0: -249,224,85684,1,0,0:0:0:0: -255,242,85778,1,0,0:0:0:0: -262,260,85872,1,8,0:3:0:0: -263,280,85965,1,0,0:0:0:0: -256,298,86059,5,12,1:2:0:0: diff --git a/audio.mp3 b/audio.mp3 deleted file mode 100644 index db16921..0000000 Binary files a/audio.mp3 and /dev/null differ diff --git a/audio.wav b/audio.wav deleted file mode 100644 index e12b9b6..0000000 Binary files a/audio.wav and /dev/null differ diff --git a/cleaned_sp.py b/cleaned_sp.py index 487d973..ab19ec3 100644 --- a/cleaned_sp.py +++ b/cleaned_sp.py @@ -71,7 +71,7 @@ def retrieve_dominant_freqs(song_name, offset, songlen, segsize): print("Retrieving freqs from", offset, "to", songlen+offset, "...") print("amplitudes are from", minfreq, "to", maxfreq) - while(current_time < songlen-segsize): + while(current_time < songlen+offset-segsize): # index corresponding to left boundary left_id = int(current_time*sample_rate) @@ -136,8 +136,8 @@ def void_freq_clean(song_name, offset, songlen, segsize, minfreq, maxfreq, ampth else: song_data = raw_song_data - # remove the copy of the song - subprocess.run(["rm", "crop.wav"], shell=False) + print("\nSampleRate : ", sample_rate) + print("SegSize : ", blit) # calculate the frequencies associated to the FFTs pfreq = scp.fft.rfftfreq(blit, 1/sample_rate) @@ -152,8 +152,8 @@ def void_freq_clean(song_name, offset, songlen, segsize, minfreq, maxfreq, ampth k = 0 print("Retrieving freqs from", offset, "to", songlen+offset, "...") - print("amplitudes are from", minfreq, "to", maxfreq) - while(current_time < songlen-segsize): + print("Freqs are from", minfreq, "to", maxfreq) + while(current_time < songlen+offset-segsize): # index corresponding to left boundary left_id = int(current_time*sample_rate) @@ -172,20 +172,138 @@ def void_freq_clean(song_name, offset, songlen, segsize, minfreq, maxfreq, ampth print("\n\nSegSize :", segsize, "\nFFT :", len(fft_list), "\nFFT[0] :", len(fft_list[0]), "\npfreq :", len(pfreq), "\n\n") # remove + # i = time, j = freq for i in range(len(fft_list)): # get the local max freq lmax = 0 for j in range(len(fft_list[i])): + if(np.abs(fft_list[i][j]) > lmax): lmax = np.abs(fft_list[i][j]) # remove freqs + amps for j in range(len(fft_list[i])): - if(pfreq[j] <= minfreq or pfreq[j] >= maxfreq): - fft_list[i][j] = 0+0j + if(j < len(pfreq)): + if(pfreq[j] <= minfreq or pfreq[j] >= maxfreq): + fft_list[i][j] = 0+0j - if(np.abs(fft_list[i][j]) <= lmax*ampthr): - fft_list[i][j] = 0+0j + if(np.abs(fft_list[i][j]) <= lmax*ampthr): + fft_list[i][j] = 0+0j + + # writing new .wav + res = [] + print("Converting...") + for i in range(len(fft_list)): + ift = scp.fft.irfft(fft_list[i], n=blit) + for k in ift: + res.append(k) + #print(type(res[0])) + mx = 0 + for j in range(len(res)): + if(res[j] > mx): + mx = res[j] + + for i in range(len(res)): + res[i] = np.int16(32767*res[i]/mx) + + res = np.array(res) + wavfile.write(output_name, sample_rate, res) + +def is_within_reach(xref, x, error): + return(np.abs(xref - x) <= error) + +def localize_frequencies(song_name, offset, songlen, segsize, output_name): + # removes unnecessary frequencies/amps from a song + # ampthr is in [0, 1] + + # extracting data from cropped song + sample_rate, raw_song_data = wavfile.read(song_name) + blit = int(sample_rate*segsize) # Te + + song_data = [0 for i in range(len(raw_song_data))] + + a = 0 + if(is_data_stereo(raw_song_data)): + print("Converting to mono...") + for x in range(len(raw_song_data)): + song_data[x] = raw_song_data[x][0]/2 + raw_song_data[x][1]/2 + + if(x % (int(len(raw_song_data)/100)) == 0): + print(a, "/ 100") + a += 1 + else: + song_data = raw_song_data + + print("\nSampleRate : ", sample_rate) + print("SegSize : ", blit) + + # calculate the frequencies associated to the FFTs + pfreq = scp.fft.rfftfreq(blit, 1/sample_rate) + + # left boundary of segment to crop + current_time = offset + + # list of FFTs + fft_list = [] + + # number of samples + k = 0 + + print("Retrieving freqs from", offset, "to", songlen+offset, "...") + while(current_time < songlen+offset-segsize): + # index corresponding to left boundary + left_id = int(current_time*sample_rate) + + # index corresponding to right boundary + right_id = int((current_time+segsize)*sample_rate) + + # calculate the fft, append it to fft_list + pff = scp.fft.rfft(song_data[int(current_time*sample_rate):int(sample_rate*(current_time+segsize))]) + fft_list.append(pff) + + # just to avoid what causes 0.1 + 0.1 == 0.2 to be False + k += 1 + current_time = offset + k*segsize + #print(current_time) + + print("\n\nSegSize :", segsize, "\nFFT :", len(fft_list), "\nFFT[0] :", len(fft_list[0]), "\npfreq :", len(pfreq), "\n\n") + + let_ring_currentLength = 0 + let_ring_freq = -200 + + let_ring_freqLeniency = 37 + + let_ring_leniencySecond = 0.07 + let_ring_lengthLeniency = 2 + + # remove + # i = time, j = freq + for i in range(len(fft_list)): + # retrieve dominant freq + maxfreq = 0 + maxfreqid = 0 + maxamp = 0 + for j in range(len(fft_list[i])): + if(np.abs(fft_list[i][j]) > maxamp): + maxamp = np.abs(fft_list[i][j]) + maxfreq = pfreq[j] + maxfreqid = j + + if(is_within_reach(maxfreq, let_ring_freq, let_ring_freqLeniency)): + let_ring_freq = maxfreq + let_ring_currentLength += 1 + + if(let_ring_currentLength > let_ring_lengthLeniency): + for j in range(len(fft_list[i])): + #if(j < len(pfreq) and is_within_reach(pfreq[j], maxfreq, 75)): + fft_list[i][j] = 0+0j + print("here") + + else: + let_ring_freq = maxfreq + let_ring_currentLength = 0 + + print("(at time", i, ") maxfreq and length are", let_ring_freq, let_ring_currentLength) # writing new .wav res = [] @@ -267,7 +385,7 @@ def retrieve_dominant_amps(song_name, offset, songlen, segsize, percent, divlen) k = 0 current_time = offset - while(current_time < songlen-segsize): + while(current_time < songlen+offset-segsize): # index corresponding to left boundary left_id = int(current_time*sample_rate) @@ -315,13 +433,15 @@ def retrieve_all_from_song(filename, t0, t1, bpm, dta=0.001, dtf=0.01, threshold new_fn = convert_to_wav(filename) print("Filtering song...") - #void_freq_clean(new_fn, t0, t1-t0, dt, 200, 2500, 0.05, "crop1.wav") + #void_freq_clean(new_fn, t0, t1, dtf, 20, 20000, 0.05, "crop1.wav") + #def void_freq_clean(song_name, offset, songlen, segsize, minfreq, maxfreq, ampthr, output_name): print("Now retrieving the frequencies") (maxlist, maxamps) = retrieve_dominant_freqs(new_fn, t0, t1, dtf) + #def retrieve_dominant_freqs(song_name, offset, songlen, segsize): print("Now retrieving the amplitudes") - amps = retrieve_dominant_amps(new_fn, t0, t1, dta, threshold, 4/(bpm/60)) + amps = retrieve_dominant_amps(new_fn, t0, t1, dta, threshold, (4/(bpm/60))/4) print("Len of freqs : ", len(maxlist), "|", len(maxamps)) print("Len of amps : ", len(maxlist), "|", len(amps)) @@ -344,7 +464,14 @@ def retrieve_all_from_song(filename, t0, t1, bpm, dta=0.001, dtf=0.01, threshold # free() -retrieve_all_from_song("ctype.mp3", 0, 5, 149.3, dtf=1/(149.3/60)/8) +''' +void_freq_clean(convert_to_wav("ctype.mp3"), 0.042, 5, 1/(149.3/60)/8, 100, 3000, 0.05, "ctype_void.mp3") +localize_frequencies(convert_to_wav("ctype_void.mp3"), 0, 5, 1/(149.3/60)/12, "ctype_filtered.mp3") +retrieve_all_from_song("ctype_filtered.mp3", 0, 5, 149.3, dta=1/(149.3/60)/128, dtf=1/(149.3/60)/8) +''' +void_freq_clean(convert_to_wav("tetris_2.wav"), 0.042, 5, 1/(149.3/60)/8, 100, 3000, 0.05, "tetris_2_void.wav") +localize_frequencies(convert_to_wav("tetris_2_void.wav"), 0, 5, 1/(149.3/60)/12, "tetris_2_f.wav") +retrieve_all_from_song("tetris_2_f.wav", 0, 5, 149.3, dtf=1/(149.3/60)/8) print("yipee") diff --git a/crop.wav b/crop.wav deleted file mode 100644 index e3ef10d..0000000 Binary files a/crop.wav and /dev/null differ diff --git a/crop1.wav b/crop1.wav deleted file mode 100644 index 530107d..0000000 Binary files a/crop1.wav and /dev/null differ