Spaces:
Sleeping
Sleeping
| import numpy as np | |
| import streamlit as st | |
| import streamlit_pianoroll | |
| from fortepyan import MidiPiece | |
| st.set_page_config( | |
| page_title="PianoRoll Demo", | |
| page_icon=":musical_keyboard:", | |
| ) | |
| def main(): | |
| piano_music_demo() | |
| def piano_music_demo(): | |
| piece = MidiPiece.from_file("haydn.mid") | |
| # TODO Improve fortepyan to make this cleaner | |
| piece.time_shift(-piece.df.start.min()) | |
| st.write("## Display a PianoRoll player") | |
| st.write(""" | |
| The core functionality of pianorolls includes music playback and visualization. | |
| If you have a MIDI file with piano music, see here for instructions on interacting with it using Streamlit components. | |
| """) | |
| code = """ | |
| import streamlit_pianoroll | |
| from fortepyan import MidiPiece | |
| piece = MidiPiece.from_file("haydn.mid") | |
| streamlit_pianoroll.from_fortepyan(piece) | |
| """ | |
| st.code(code, language="python") | |
| streamlit_pianoroll.from_fortepyan(piece) | |
| st.info( | |
| body="This component is dedicated to piano music, there's no way to interract with multiple instruments.", | |
| icon="🎹", | |
| ) | |
| st.write("## Conditional coloring") | |
| st.write(""" | |
| To create a pianoroll with different notes in separate colors, | |
| create two `MidiPiece` objects, each containing the notes for one color. | |
| """) | |
| st.write("#### Absolute pitch value condition") | |
| st.write(""" | |
| Here's how to highlight notes with pitch above or below a certain threshold. | |
| Value of pitch 60 corresponds to the middle C (C4) on a piano keyboard | |
| ([refrence table](https://inspiredacoustics.com/en/MIDI_note_numbers_and_center_frequencies)). | |
| """) | |
| code = """ | |
| df = piece.df | |
| ids = df.pitch > pitch_threshold | |
| part_a = df[ids] | |
| part_b = df[~ids] | |
| piece_a = MidiPiece(df=part_a) | |
| piece_b = MidiPiece(df=part_b) | |
| streamlit_pianoroll.from_fortepyan( | |
| piece=piece_a, | |
| secondary_piece=piece_b, | |
| ) | |
| """ | |
| st.code(code, language="python") | |
| df = piece.df.copy() | |
| pitch_threshold = st.number_input( | |
| label="pitch_threshold", | |
| min_value=df.pitch.min(), | |
| max_value=df.pitch.max(), | |
| value=60, | |
| ) | |
| ids = df.pitch > pitch_threshold | |
| part_a = df[ids].copy() | |
| part_b = df[~ids].copy() | |
| piece_a = MidiPiece(df=part_a) | |
| piece_b = MidiPiece(df=part_b) | |
| streamlit_pianoroll.from_fortepyan( | |
| piece=piece_a, | |
| secondary_piece=piece_b, | |
| ) | |
| st.write("#### Note duration condition") | |
| st.write(""" | |
| Here's how to highlight notes based on their absolute duration, which can differentiate between fast and slow notes. | |
| """) | |
| code = """ | |
| df = piece.df | |
| ids = df.duration > duration_threshold | |
| part_a = df[ids] | |
| part_b = df[~ids] | |
| piece_a = MidiPiece(df=part_a) | |
| piece_b = MidiPiece(df=part_b) | |
| streamlit_pianoroll.from_fortepyan( | |
| piece=piece_a, | |
| secondary_piece=piece_b, | |
| ) | |
| """ | |
| st.code(code, language="python") | |
| df = piece.df.copy() | |
| duration_threshold = st.number_input( | |
| label="duration threshold [s]", | |
| min_value=0.05, | |
| max_value=5., | |
| value=0.25, | |
| ) | |
| ids = df.duration > duration_threshold | |
| part_a = df[ids].copy() | |
| part_b = df[~ids].copy() | |
| piece_a = MidiPiece(df=part_a) | |
| piece_b = MidiPiece(df=part_b) | |
| streamlit_pianoroll.from_fortepyan( | |
| piece=piece_a, | |
| secondary_piece=piece_b, | |
| ) | |
| st.write("#### Music generation prompting") | |
| st.write(""" | |
| Here's how to highlight show results of a generative algorithm that is supposed to work musically with an input from. | |
| We can take the notes with pitch below 72 (C5) as a prompt, and display it together with the generation. | |
| This sample performs random shuffle of the note pitch values, so the results are not muscially great (your algorithms should be better). | |
| """) | |
| df = piece.df.copy() | |
| ids = df.pitch < 72 | |
| part_a = df[ids].copy() | |
| piece_a = MidiPiece(df=part_a) | |
| # Fake random algorithm | |
| part_b = df[~ids].copy() | |
| part_b.pitch = np.random.permutation(part_b.pitch) | |
| part_b.velocity = np.random.permutation(part_b.velocity) | |
| piece_b = MidiPiece(df=part_b) | |
| streamlit_pianoroll.from_fortepyan( | |
| piece=piece_a, | |
| secondary_piece=piece_b, | |
| ) | |
| if __name__ == "__main__": | |
| main() | |