Version 1.0. Added piano-roll. Limited number of generation attempts.

Adjusted default settings.

Examples/markovify_piano.py

@@ -6,7 +6,7 @@
 Original file is located at
     https://colab.research.google.com/drive/17SGUaA8r6nZyHHH3huOmgcsVUDH6HBWE
 
-# Markovify Piano
+# Markovify Piano (ver 1.0)
 
 ***
 
@@ -31,6 +31,12 @@
 !apt install fluidsynth #Pip does not work for some reason. Only apt works
 !pip install midi2audio
 
+# packages below are for plotting pianoroll only
+# they are not needed for anything else
+!pip install pretty_midi
+!pip install librosa
+!pip install matplotlib
+
 #@title Load needed modules
 print('Loading needed modules. Please wait...')
 
@@ -50,6 +56,11 @@
 from midi2audio import FluidSynth
 from IPython.display import display, Javascript, HTML, Audio
 
+# only for plotting pianoroll
+import pretty_midi
+import librosa.display
+import matplotlib.pyplot as plt
+
 from google.colab import output, drive
 
 print('Creating Dataset dir...')
@@ -227,7 +238,7 @@
 """# Train TXT Markov chain/model"""
 
 #@title Train Markov-chain/model
-markov_chain_state_size = 4 #@param {type:"slider", min:1, max:10, step:1}
+markov_chain_state_size = 5 #@param {type:"slider", min:1, max:10, step:1}
 
 print('Training Markov chain/model. Please wait...')
 markov_text_model = markovify.NewlineText(text, well_formed=False, state_size=markov_chain_state_size)
@@ -263,9 +274,12 @@
 #@title Generate Music
 
 #@markdown HINT: Each note = 3-5 characters depending on the MIDI processing settings above
-minimum_number_of_characters_to_generate = 5000 #@param {type:"slider", min:100, max:10000, step:100}
-number_of_cycles_to_try_to_generate_desired_result = 5000 #@param {type:"slider", min:10, max:10000, step:10}
-minimum_notes_to_generate = 210 #@param {type:"slider", min:10, max:1000, step:10}
+
+#@markdown NOTE: If nothing is being generated after 10+ attempts, try again with different model state # and generation settings
+
+minimum_number_of_characters_to_generate = 600 #@param {type:"slider", min:100, max:1500, step:100}
+number_of_cycles_to_try_to_generate_desired_result = 9000 #@param {type:"slider", min:10, max:10000, step:10}
+minimum_notes_to_generate = 100 #@param {type:"slider", min:10, max:1000, step:10}
 print_generated_song = False #@param {type:"boolean"}
 
 Output_TXT_String = ''
@@ -281,6 +295,8 @@
   Output_TXT_String = ''.join(out)
   print('Attempt #', attempt)
   attempt += 1
+  if attempt > 15:
+    break
 
 print('Generation complete!')
 print('=' * 70)
@@ -317,8 +333,21 @@
   print('Detailed MIDI stats:')
   pprint(detailed_stats)
 
-#@title Listen to the last generated composition
+#@title Plot and listen to the last generated composition
 #@markdown NOTE: May be very slow with the long compositions
+fn = os.path.basename(fname + '.mid')
+fn1 = fn.split('.')[0]
+print('Playing and plotting composition...')
+
+pm = pretty_midi.PrettyMIDI(fname + '.mid')
+
+# Retrieve piano roll of the MIDI file
+piano_roll = pm.get_piano_roll()
+
+plt.figure(figsize=(14, 5))
+librosa.display.specshow(piano_roll, x_axis='time', y_axis='cqt_note', sr=64000, cmap=plt.cm.hot)
+plt.title('Composition: ' + fn1)
+
 print('Synthesizing the last output MIDI. Please stand-by... ')
 FluidSynth("/usr/share/sounds/sf2/FluidR3_GM.sf2", 16000).midi_to_audio(str(fname + '.mid'), str(fname + '.wav'))
 Audio(str(fname + '.wav'), rate=16000)