1 | #! /usr/bin/env python |
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2 | |
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3 | import sys |
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4 | from aubio import source, pitch, freqtomidi |
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5 | |
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6 | if len(sys.argv) < 2: |
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7 | print "Usage: %s <filename> [samplerate]" % sys.argv[0] |
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8 | sys.exit(1) |
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9 | |
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10 | filename = sys.argv[1] |
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11 | |
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12 | downsample = 1 |
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13 | samplerate = 44100 / downsample |
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14 | if len( sys.argv ) > 2: samplerate = int(sys.argv[2]) |
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15 | |
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16 | win_s = 4096 / downsample # fft size |
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17 | hop_s = 512 / downsample # hop size |
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18 | |
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19 | s = source(filename, samplerate, hop_s) |
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20 | samplerate = s.samplerate |
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21 | |
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22 | tolerance = 0.8 |
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23 | |
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24 | pitch_o = pitch("yin", win_s, hop_s, samplerate) |
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25 | pitch_o.set_unit("midi") |
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26 | pitch_o.set_tolerance(tolerance) |
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27 | |
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28 | pitches = [] |
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29 | confidences = [] |
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30 | |
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31 | # total number of frames read |
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32 | total_frames = 0 |
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33 | while True: |
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34 | samples, read = s() |
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35 | pitch = pitch_o(samples)[0] |
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36 | #pitch = int(round(pitch)) |
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37 | confidence = pitch_o.get_confidence() |
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38 | #if confidence < 0.8: pitch = 0. |
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39 | #print "%f %f %f" % (total_frames / float(samplerate), pitch, confidence) |
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40 | pitches += [pitch] |
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41 | confidences += [confidence] |
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42 | total_frames += read |
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43 | if read < hop_s: break |
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44 | |
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45 | if 0: sys.exit(0) |
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46 | |
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47 | #print pitches |
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48 | from numpy import array, ma |
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49 | import matplotlib.pyplot as plt |
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50 | from demo_waveform_plot import get_waveform_plot, set_xlabels_sample2time |
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51 | |
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52 | skip = 1 |
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53 | |
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54 | pitches = array(pitches[skip:]) |
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55 | confidences = array(confidences[skip:]) |
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56 | times = [t * hop_s for t in range(len(pitches))] |
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57 | |
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58 | fig = plt.figure() |
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59 | |
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60 | ax1 = fig.add_subplot(311) |
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61 | ax1 = get_waveform_plot(filename, samplerate = samplerate, block_size = hop_s, ax = ax1) |
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62 | plt.setp(ax1.get_xticklabels(), visible = False) |
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63 | ax1.set_xlabel('') |
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64 | |
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65 | def array_from_text_file(filename, dtype = 'float'): |
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66 | import os.path |
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67 | from numpy import array |
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68 | filename = os.path.join(os.path.dirname(__file__), filename) |
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69 | return array([line.split() for line in open(filename).readlines()], |
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70 | dtype = dtype) |
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71 | |
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72 | ax2 = fig.add_subplot(312, sharex = ax1) |
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73 | import sys, os.path |
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74 | ground_truth = os.path.splitext(filename)[0] + '.f0.Corrected' |
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75 | if os.path.isfile(ground_truth): |
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76 | ground_truth = array_from_text_file(ground_truth) |
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77 | true_freqs = ground_truth[:,2] |
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78 | true_freqs = ma.masked_where(true_freqs < 2, true_freqs) |
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79 | true_times = float(samplerate) * ground_truth[:,0] |
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80 | ax2.plot(true_times, true_freqs, 'r') |
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81 | ax2.axis( ymin = 0.9 * true_freqs.min(), ymax = 1.1 * true_freqs.max() ) |
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82 | # plot raw pitches |
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83 | ax2.plot(times, pitches, '.g') |
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84 | # plot cleaned up pitches |
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85 | cleaned_pitches = pitches |
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86 | #cleaned_pitches = ma.masked_where(cleaned_pitches < 0, cleaned_pitches) |
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87 | #cleaned_pitches = ma.masked_where(cleaned_pitches > 120, cleaned_pitches) |
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88 | cleaned_pitches = ma.masked_where(confidences < tolerance, cleaned_pitches) |
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89 | ax2.plot(times, cleaned_pitches, '.-') |
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90 | #ax2.axis( ymin = 0.9 * cleaned_pitches.min(), ymax = 1.1 * cleaned_pitches.max() ) |
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91 | #ax2.axis( ymin = 55, ymax = 70 ) |
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92 | plt.setp(ax2.get_xticklabels(), visible = False) |
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93 | ax2.set_ylabel('f0 (midi)') |
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94 | |
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95 | # plot confidence |
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96 | ax3 = fig.add_subplot(313, sharex = ax1) |
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97 | # plot the confidence |
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98 | ax3.plot(times, confidences) |
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99 | # draw a line at tolerance |
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100 | ax3.plot(times, [tolerance]*len(confidences)) |
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101 | ax3.axis( xmin = times[0], xmax = times[-1]) |
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102 | ax3.set_ylabel('condidence') |
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103 | set_xlabels_sample2time(ax3, times[-1], samplerate) |
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104 | plt.show() |
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105 | #plt.savefig(os.path.basename(filename) + '.svg') |
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