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import tempfile
import collections
import note_seq
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
from PIL import Image
class AudioIOReadError(BaseException): # pylint:disable=g-bad-exception-name
pass
def upload_audio(audio, sample_rate):
return note_seq.audio_io.wav_data_to_samples_librosa(audio, sample_rate=sample_rate)
# Generate piano_roll
def sequence_to_pandas_dataframe(sequence):
pd_dict = collections.defaultdict(list)
for note in sequence.notes:
pd_dict["start_time"].append(note.start_time)
pd_dict["end_time"].append(note.end_time)
pd_dict["duration"].append(note.end_time - note.start_time)
pd_dict["pitch"].append(note.pitch)
pd_dict['instrument'].append(note.instrument)
return pd.DataFrame(pd_dict)
def dataframe_to_pianoroll_img(df):
fig = plt.figure(figsize=(8, 5))
ax = fig.add_subplot(111)
ax.scatter(df.start_time, df.pitch, c="white")
for _, row in df.iterrows():
ax.add_patch(Rectangle((row["start_time"], row["pitch"]-0.4), row["duration"], 0.4, color="black"))
plt.xlabel('time (sec.)', fontsize=18)
plt.ylabel('pitch (MIDI)', fontsize=16)
return fig
def fig2img(fig):
"""Convert a Matplotlib figure to a PIL Image and return it"""
import io
buf = io.BytesIO()
fig.savefig(buf, format="png")
buf.seek(0)
img = Image.open(buf)
return img
def create_image_from_note_sequence(sequence):
df_sequence = sequence_to_pandas_dataframe(sequence)
fig = dataframe_to_pianoroll_img(df_sequence)
img = fig2img(fig)
return img |