06e45fa266
i found it was producing better results, but providing both models makes it easy to switch back and forth
76 lines
2.5 KiB
Python
76 lines
2.5 KiB
Python
#
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# Copyright 2016 Google Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import magenta
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from magenta.models.melody_rnn import melody_rnn_config_flags
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from magenta.models.melody_rnn import melody_rnn_model
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from magenta.models.melody_rnn import melody_rnn_sequence_generator
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from magenta.protobuf import generator_pb2
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from magenta.protobuf import music_pb2
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import os
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import time
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import tempfile
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import pretty_midi
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BUNDLE_NAME = 'attention_rnn'
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config = magenta.models.melody_rnn.melody_rnn_model.default_configs[BUNDLE_NAME]
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bundle_file = magenta.music.read_bundle_file(os.path.abspath(BUNDLE_NAME+'.mag'))
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steps_per_quarter = 4
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generator = melody_rnn_sequence_generator.MelodyRnnSequenceGenerator(
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model=melody_rnn_model.MelodyRnnModel(config),
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details=config.details,
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steps_per_quarter=steps_per_quarter,
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bundle=bundle_file)
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def _steps_to_seconds(steps, qpm):
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return steps * 60.0 / qpm / steps_per_quarter
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def generate_midi(midi_data, total_seconds=10):
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primer_sequence = magenta.music.midi_io.midi_to_sequence_proto(midi_data)
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# predict the tempo
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if len(primer_sequence.notes) > 4:
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estimated_tempo = midi_data.estimate_tempo()
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if estimated_tempo > 240:
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qpm = estimated_tempo / 2
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else:
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qpm = estimated_tempo
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else:
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qpm = 120
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primer_sequence.tempos[0].qpm = qpm
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generator_options = generator_pb2.GeneratorOptions()
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# Set the start time to begin on the next step after the last note ends.
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last_end_time = (max(n.end_time for n in primer_sequence.notes)
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if primer_sequence.notes else 0)
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generator_options.generate_sections.add(
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start_time=last_end_time + _steps_to_seconds(1, qpm),
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end_time=total_seconds)
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# generate the output sequence
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generated_sequence = generator.generate(primer_sequence, generator_options)
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output = tempfile.NamedTemporaryFile()
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magenta.music.midi_io.sequence_proto_to_midi_file(generated_sequence, output.name)
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output.seek(0)
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return output
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