367 lines
14 KiB
Python
367 lines
14 KiB
Python
# Copyright 2024 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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"""
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This file contains utilities for recording audio from a microhone.
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"""
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import argparse
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import soundfile as sf
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import numpy as np
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import logging
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from threading import Thread, Event
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from multiprocessing import Process
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from queue import Empty
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from queue import Queue as thread_Queue
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from threading import Event as thread_Event
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from multiprocessing import JoinableQueue as process_Queue
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from multiprocessing import Event as process_Event
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from os import getcwd
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from pathlib import Path
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import shutil
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import time
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from lerobot.common.utils.utils import capture_timestamp_utc
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from lerobot.common.robot_devices.microphones.configs import MicrophoneConfig
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from lerobot.common.robot_devices.utils import (
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RobotDeviceAlreadyConnectedError,
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RobotDeviceNotConnectedError,
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RobotDeviceNotRecordingError,
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RobotDeviceAlreadyRecordingError,
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)
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def find_microphones(raise_when_empty=False, mock=False) -> list[dict]:
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microphones = []
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if mock:
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import tests.microphones.mock_sounddevice as sd
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else:
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import sounddevice as sd
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devices = sd.query_devices()
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for device in devices:
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if device["max_input_channels"] > 0:
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microphones.append(
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{
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"index": device["index"],
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"name": device["name"],
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}
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)
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if raise_when_empty and len(microphones) == 0:
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raise OSError(
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"Not a single microphone was detected. Try re-plugging the microphone or check the microphone settings."
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)
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return microphones
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def record_audio_from_microphones(
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output_dir: Path,
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microphone_ids: list[int] | None = None,
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record_time_s: float = 2.0):
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if microphone_ids is None or len(microphone_ids) == 0:
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microphones = find_microphones()
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microphone_ids = [m["index"] for m in microphones]
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microphones = []
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for microphone_id in microphone_ids:
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config = MicrophoneConfig(microphone_index=microphone_id)
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microphone = Microphone(config)
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microphone.connect()
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print(
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f"Recording audio from microphone {microphone_id} for {record_time_s} seconds at {microphone.sample_rate} Hz."
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)
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microphones.append(microphone)
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output_dir = Path(output_dir)
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if output_dir.exists():
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shutil.rmtree(
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output_dir,
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)
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output_dir.mkdir(parents=True, exist_ok=True)
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print(f"Saving audio to {output_dir}")
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for microphone in microphones:
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microphone.start_recording(getcwd() / output_dir / f"microphone_{microphone.microphone_index}.wav")
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time.sleep(record_time_s)
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for microphone in microphones:
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microphone.stop_recording()
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#Remark : recording may be resumed here if needed
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for microphone in microphones:
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microphone.disconnect()
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print(f"Images have been saved to {output_dir}")
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class Microphone:
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"""
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The Microphone class handles all microphones compatible with sounddevice (and the underlying PortAudio library). Most microphones and sound cards are compatible, accross all OS (Linux, Mac, Windows).
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A Microphone instance requires the sounddevice index of the microphone, which may be obtained using `python -m sounddevice`. It also requires the recording sample rate as well as the list of recorded channels.
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Example of usage:
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```python
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from lerobot.common.robot_devices.microphones.configs import MicrophoneConfig
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config = MicrophoneConfig(microphone_index=0, sample_rate=16000, channels=[1])
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microphone = Microphone(config)
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microphone.connect()
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microphone.start_recording("some/output/file.wav")
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...
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audio_readings = microphone.read() #Gets all recorded audio data since the last read or since the beginning of the recording
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...
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microphone.stop_recording()
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microphone.disconnect()
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```
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"""
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def __init__(self, config: MicrophoneConfig):
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self.config = config
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self.microphone_index = config.microphone_index
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#Store the recording sample rate and channels
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self.sample_rate = config.sample_rate
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self.channels = config.channels
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self.mock = config.mock
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#Input audio stream
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self.stream = None
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#Thread-safe concurrent queue to store the recorded/read audio
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self.record_queue = None
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self.read_queue = None
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#Thread to handle data reading and file writing in a separate thread (safely)
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self.record_thread = None
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self.record_stop_event = None
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self.logs = {}
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self.is_connected = False
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self.is_recording = False
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def connect(self) -> None:
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if self.is_connected:
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raise RobotDeviceAlreadyConnectedError(f"Microphone {self.microphone_index} is already connected.")
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if self.mock:
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import tests.microphones.mock_sounddevice as sd
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else:
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import sounddevice as sd
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#Check if the provided microphone index does match an input device
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is_index_input = sd.query_devices(self.microphone_index)["max_input_channels"] > 0
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if not is_index_input:
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microphones_info = find_microphones()
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available_microphones = [m["index"] for m in microphones_info]
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raise OSError(
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f"Microphone index {self.microphone_index} does not match an input device (microphone). Available input devices : {available_microphones}"
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)
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#Check if provided recording parameters are compatible with the microphone
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actual_microphone = sd.query_devices(self.microphone_index)
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if self.sample_rate is not None :
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if self.sample_rate > actual_microphone["default_samplerate"]:
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raise OSError(
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f"Provided sample rate {self.sample_rate} is higher than the sample rate of the microphone {actual_microphone['default_samplerate']}."
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)
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elif self.sample_rate < actual_microphone["default_samplerate"]:
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logging.warning("Provided sample rate is lower than the sample rate of the microphone. Performance may be impacted.")
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else:
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self.sample_rate = int(actual_microphone["default_samplerate"])
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if self.channels is not None:
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if any(c > actual_microphone["max_input_channels"] for c in self.channels):
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raise OSError(
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f"Some of the provided channels {self.channels} are outside the maximum channel range of the microphone {actual_microphone['max_input_channels']}."
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)
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else:
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self.channels = np.arange(1, actual_microphone["max_input_channels"]+1)
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# Get channels index instead of number for slicing
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self.channels = np.array(self.channels) - 1
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#Create the audio stream
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self.stream = sd.InputStream(
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device=self.microphone_index,
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samplerate=self.sample_rate,
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channels=max(self.channels)+1,
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dtype="float32",
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callback=self._audio_callback,
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)
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#Remark : the blocksize parameter could be passed to the stream to ensure that audio_callback always recieve same length buffers.
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#However, this may lead to additionnal latency. We thus stick to blocksize=0 which means that audio_callback will recieve varying length buffers, but with no addtional latency.
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self.is_connected = True
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def _audio_callback(self, indata, frames, time, status) -> None :
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if status:
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logging.warning(status)
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# Slicing makes copy unecessary
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# Two separate queues are necessary because .get() also pops the data from the queue
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self.record_queue.put(indata[:,self.channels])
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self.read_queue.put(indata[:,self.channels])
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@staticmethod
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def _record_loop(queue, event: Event, sample_rate: int, channels: list[int], output_file: Path) -> None:
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#Can only be run on a single process/thread for file writing safety
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with sf.SoundFile(output_file, mode='x', samplerate=sample_rate,
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channels=max(channels)+1, subtype=sf.default_subtype(output_file.suffix[1:])) as file:
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while not event.is_set():
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try:
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file.write(queue.get(timeout=0.02)) #Timeout set as twice the usual sounddevice buffer size
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queue.task_done()
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except Empty:
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continue
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def _read(self) -> np.ndarray:
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"""
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Gets audio data from the queue and coverts it to a numpy array.
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-> PROS : Inherently thread safe, no need to lock the queue, lightweight CPU usage
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-> CONS : Reading duration does not scale well with the number of channels and reading duration
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"""
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audio_readings = np.empty((0, len(self.channels)))
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while True:
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try:
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audio_readings = np.concatenate((audio_readings, self.read_queue.get_nowait()), axis=0)
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except Empty:
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break
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self.read_queue = thread_Queue()
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return audio_readings
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def read(self) -> np.ndarray:
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if not self.is_connected:
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raise RobotDeviceNotConnectedError(f"Microphone {self.microphone_index} is not connected.")
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if not self.is_recording:
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raise RobotDeviceNotRecordingError(f"Microphone {self.microphone_index} is not recording.")
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start_time = time.perf_counter()
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audio_readings = self._read()
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# log the number of seconds it took to read the audio chunk
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self.logs["delta_timestamp_s"] = time.perf_counter() - start_time
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# log the utc time at which the audio chunk was received
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self.logs["timestamp_utc"] = capture_timestamp_utc()
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return audio_readings
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def start_recording(self, output_file : str | None = None, multiprocessing : bool | None = False) -> None:
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if not self.is_connected:
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raise RobotDeviceNotConnectedError(f"Microphone {self.microphone_index} is not connected.")
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if self.is_recording:
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raise RobotDeviceAlreadyRecordingError(f"Microphone {self.microphone_index} is already recording.")
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#Reset queues
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self.read_queue = thread_Queue()
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if multiprocessing:
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self.record_queue = process_Queue()
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else:
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self.record_queue = thread_Queue()
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#Write recordings into a file if output_file is provided
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if output_file is not None:
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output_file = Path(output_file)
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if output_file.exists():
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output_file.unlink()
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if multiprocessing:
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self.record_stop_event = process_Event()
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self.record_thread = Process(target=Microphone._record_loop, args=(self.record_queue, self.record_stop_event, self.sample_rate, self.channels, output_file, ))
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else:
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self.record_stop_event = thread_Event()
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self.record_thread = Thread(target=Microphone._record_loop, args=(self.record_queue, self.record_stop_event, self.sample_rate, self.channels, output_file, ))
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self.record_thread.daemon = True
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self.record_thread.start()
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self.is_recording = True
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self.stream.start()
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def stop_recording(self) -> None:
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if not self.is_connected:
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raise RobotDeviceNotConnectedError(f"Microphone {self.microphone_index} is not connected.")
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if not self.is_recording:
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raise RobotDeviceNotRecordingError(f"Microphone {self.microphone_index} is not recording.")
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if self.stream.active:
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self.stream.stop() #Wait for all buffers to be processed
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#Remark : stream.abort() flushes the buffers !
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self.is_recording = False
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if self.record_thread is not None:
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self.record_queue.join()
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self.record_stop_event.set()
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self.record_thread.join()
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self.record_thread = None
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self.record_stop_event = None
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self.is_writing = False
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def disconnect(self) -> None:
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if not self.is_connected:
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raise RobotDeviceNotConnectedError(f"Microphone {self.microphone_index} is not connected.")
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if self.is_recording:
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self.stop_recording()
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self.stream.close()
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self.is_connected = False
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def __del__(self):
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if getattr(self, "is_connected", False):
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self.disconnect()
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(
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description="Records audio using `Microphone` for all microphones connected to the computer, or a selected subset."
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)
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parser.add_argument(
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"--microphone-ids",
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type=int,
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nargs="*",
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default=None,
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help="List of microphones indices used to instantiate the `Microphone`. If not provided, find and use all available microphones indices.",
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)
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parser.add_argument(
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"--output-dir",
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type=Path,
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default="outputs/audio_from_microphones",
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help="Set directory to save an audio snipet for each microphone.",
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)
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parser.add_argument(
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"--record-time-s",
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type=float,
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default=4.0,
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help="Set the number of seconds used to record the audio. By default, 4 seconds.",
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)
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args = parser.parse_args()
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record_audio_from_microphones(**vars(args))
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