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[skip ci] doc(benchmark): adding microphones recording benchmark
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CarolinePascal
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#!/usr/bin/env python
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# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
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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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import argparse
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import time
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from pathlib import Path
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import matplotlib.pyplot as plt
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import numpy as np
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import soundfile as sf
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from lerobot.microphones.configs import MicrophoneConfig
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from lerobot.microphones.portaudio import PortAudioMicrophone, PortAudioMicrophoneConfig
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from lerobot.microphones.utils import (
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async_microphones_read,
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async_microphones_start_recording,
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async_microphones_stop_recording,
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make_microphones_from_configs,
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)
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def main(
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microphones_configs: dict[str, MicrophoneConfig],
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audio_chunks_number: int,
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audio_chunks_duration: float,
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repetitions: int,
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multiprocessing: bool = False,
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):
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recording_dir = Path("outputs/audio_benchmark")
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recording_dir.mkdir(parents=True, exist_ok=True)
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# Create microphones
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microphones = make_microphones_from_configs(microphones_configs)
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# Connect microphones
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for microphone in microphones.values():
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microphone.connect()
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all_audio_chunks = []
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for i in range(repetitions):
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# Create audio chunks
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audio_chunks = {}
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for microphone_key in microphones:
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audio_chunks.update({microphone_key: []})
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# Start recording
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async_microphones_start_recording(
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microphones,
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output_files=[
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recording_dir / f"{microphone_key}_recording_{i}.wav" for microphone_key in microphones
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],
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multiprocessing=True,
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)
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# Record audio chunks
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for j in range(audio_chunks_number):
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time.sleep(audio_chunks_duration)
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audio_readings = async_microphones_read(microphones)
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for microphone_index, reading in audio_readings.items():
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print(f"{microphone_index} - repetition {i} - chunk {j} - samples {reading.shape[0]}")
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audio_chunks[microphone_index].append(reading)
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# Stop recording
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async_microphones_stop_recording(microphones)
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for microphone_key in microphones:
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audio_chunks[microphone_key] = np.concatenate(audio_chunks[microphone_key], axis=0)
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all_audio_chunks.append(audio_chunks)
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# Disconnect microphones
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for microphone in microphones.values():
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microphone.disconnect()
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# Compute statistics
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cmap = plt.get_cmap("tab10")
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_, ax = plt.subplots(nrows=repetitions, ncols=len(microphones))
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chunk_length = np.zeros((repetitions, len(microphones)))
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record_length = np.zeros((repetitions, len(microphones)))
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for i in range(repetitions):
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for j, (microphone_key, microphone) in enumerate(microphones.items()):
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# Get recorded audio chunks
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recorded_audio_chunks = all_audio_chunks[i][microphone_key]
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# Load recorded file
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recorded_data, _ = sf.read(recording_dir / f"{microphone_key}_recording_{i}.wav")
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if len(recorded_data.shape) == 1:
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recorded_data = np.expand_dims(recorded_data, axis=1)
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record_length[i, j] = recorded_data.shape[0]
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chunk_length[i, j] = recorded_audio_chunks.shape[0]
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for k, (chunk_data, record_data) in enumerate(
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zip(recorded_audio_chunks.T, recorded_data.T, strict=False)
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):
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# Plot audio chunks and recorded data
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ax[i, j].plot(
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np.arange(0, len(chunk_data)) / microphone.sample_rate,
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chunk_data,
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label=f"audio chunks - channel {k}",
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color=cmap(2 * k),
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)
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ax[i, j].plot(
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np.arange(0, len(record_data)) / microphone.sample_rate,
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record_data,
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label=f"recorded data - channel {k}",
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linestyle="dashed",
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color=cmap(2 * k + 1),
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)
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# Plot absolute difference (errors should be located at the end of the recordings)
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if recorded_data.shape[0] - recorded_audio_chunks.shape[0] > 0:
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chunk_data = np.append(
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chunk_data, np.zeros(int(recorded_data.shape[0] - recorded_audio_chunks.shape[0]))
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)
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else:
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record_data = np.append(
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record_data, np.zeros(int(-recorded_data.shape[0] + recorded_audio_chunks.shape[0]))
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)
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ax[i, j].plot(
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np.arange(0, len(record_data)) / microphone.sample_rate,
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np.abs(chunk_data - record_data),
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label=f"differences - channel {k}",
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color="red",
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linestyle="dotted",
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)
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ax[i, j].set_title(f"{microphone_key} - repetition {i}")
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ax[i, j].legend()
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plt.show()
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# Print statistics
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differences = record_length - chunk_length
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for i, microphone in enumerate(microphones.values()):
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print(
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f"Average recorded duration for {microphone_key} : {np.mean(record_length[:, i]) / microphone.sample_rate:.3f} seconds"
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)
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print(
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f"Average chunk duration for {microphone_key} : {np.mean(chunk_length[:, i]) / microphone.sample_rate:.3f} seconds"
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)
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print(f"Average difference for {microphone_key} : {np.mean(differences[:, i]):.3f} samples")
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print(
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f"Average difference for {microphone_key} : {np.mean(differences[:, i]) / microphone.sample_rate:.3f} seconds"
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)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"--microphones_indices",
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type=int,
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nargs="+",
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default=[microphone["index"] for microphone in PortAudioMicrophone.find_microphones()],
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)
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parser.add_argument(
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"--microphones_sample_rate",
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type=float,
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nargs="+",
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default=[None] * len(PortAudioMicrophone.find_microphones()),
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)
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parser.add_argument(
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"--microphones_channels",
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type=int,
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nargs="+",
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default=[None] * len(PortAudioMicrophone.find_microphones()),
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)
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parser.add_argument("--audio_chunks_number", type=int, default=2)
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parser.add_argument(
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"--audio_chunks_duration",
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type=float,
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default=1.0,
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)
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parser.add_argument(
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"--repetitions",
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type=int,
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default=2,
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)
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parser.add_argument(
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"--multiprocessing",
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action="store_true",
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)
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args = vars(parser.parse_args())
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args["microphones_configs"] = {}
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for index, sample_rate, channels in zip(
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args["microphones_indices"],
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args["microphones_sample_rate"],
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args["microphones_channels"],
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strict=False,
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):
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microphone_config = PortAudioMicrophoneConfig(
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microphone_index=index,
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sample_rate=sample_rate,
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channels=channels,
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)
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args["microphones_configs"].update({f"microphone_{index}": microphone_config})
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args.pop("microphones_indices")
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args.pop("microphones_sample_rate")
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args.pop("microphones_channels")
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main(**args)
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