makaveli10
321 lines
11 KiB
Python
321 lines
11 KiB
Python
import io
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import os
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import argparse
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import wave
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import uuid
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import hashlib
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import base64
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import time
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import numpy as np
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import scipy
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import ffmpeg
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import torch
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import socket, pickle, pyaudio, struct
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import threading
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import textwrap
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import json
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import torchaudio
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from dataclasses import dataclass
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CHUNK = 1024
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FORMAT = pyaudio.paInt16
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CHANNELS = 1
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RATE = 16000
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RECORD_SECONDS = 60000
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all_segments = []
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@dataclass(frozen=True)
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class Constants:
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ACK = b"acknowledged"
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RECORDING_OVER = b"audio_data_over"
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RECEIVED_AUDIO_FILE = b"audio_file_sent"
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RECEIVING_AUDIO_FILE = b"sending_audio_file"
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class Client:
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def __init__(self, topic=None, host=None, port=None):
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self.timestamp_offset = 0.0
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self.audio_bytes = None
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self.p = pyaudio.PyAudio()
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self.payload_size = struct.calcsize("Q")
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self.stream = self.p.open(format=FORMAT,
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channels=CHANNELS,
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rate=RATE,
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input=True,
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frames_per_buffer=CHUNK)
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print(self.p.get_sample_size(FORMAT))
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self.client_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
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host_ip = 'localhost' if host is None else host
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port = 5901 if port is None else port
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socket_address = (host_ip, port)
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self.client_socket.connect(socket_address)
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print("CLIENT CONNECTED TO", socket_address)
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# voice activity detection model
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self.vad_model, _ = torch.hub.load(repo_or_dir='snakers4/silero-vad',
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model='silero_vad',
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force_reload=True,
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onnx=True)
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self.window_size = 1024
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self.vad_threshold = 0.4
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# subscribing to the correct topic
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if topic is not None:
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self.topic = topic
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else:
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self.topic = self.get_mac_address().decode()
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self.frames = b""
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data = b""
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while True:
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while len(data) < self.payload_size:
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packet = self.client_socket.recv(4*1024) #4K
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if not packet: break
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data+=packet
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packed_msg_size = data[:self.payload_size]
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data = data[self.payload_size:]
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try:
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msg_size = struct.unpack("Q",packed_msg_size)[0]
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except struct.error:
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break
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while len(data) < msg_size:
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data += self.client_socket.recv(4*1024)
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frame_data = data[:msg_size]
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frame_data = pickle.loads(frame_data)
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if Constants.ACK in frame_data:
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print("Server is ready. Sending audio ...")
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break
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print("* recording")
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def send_packet_to_server(self, message):
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a = pickle.dumps(message)
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message = struct.pack("Q",len(a))+a
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self.client_socket.sendall(message)
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def get_mac_address(self):
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mac = hex(uuid.getnode())
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hasher = hashlib.sha1(mac.encode())
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return base64.urlsafe_b64encode(hasher.digest()[:5])
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@staticmethod
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def bytes_to_audio_tensor(audio_bytes):
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bytes_io = io.BytesIO()
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raw_data = np.frombuffer(
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buffer=audio_bytes, dtype=np.int16
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)
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scipy.io.wavfile.write(bytes_io, RATE, raw_data)
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audio, _ = torchaudio.load(bytes_io)
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return audio.squeeze(0)
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def play_file(self, filename):
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# read audio and create pyaudio stream
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self.wf = wave.open(filename, 'rb')
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self.stream = self.p.open(format=self.p.get_format_from_width(self.wf.getsampwidth()),
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channels=self.wf.getnchannels(),
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rate=self.wf.getframerate(),
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input=True,
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output=True,
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frames_per_buffer=CHUNK)
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try:
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while True:
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data = self.wf.readframes(CHUNK)
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if data==b'': break
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# voice activity detection
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chunk_tensor = Client.bytes_to_audio_tensor(data)
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try:
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speech_prob = self.vad_model(chunk_tensor, RATE).item()
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except ValueError:
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break # input audio chunk is too short
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if speech_prob > self.vad_threshold:
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data_dict = {
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"topic": self.topic,
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"audio": data
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}
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self.send_packet_to_server(data_dict)
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self.stream.write(data)
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self.wf.close()
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self.stream.close()
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# let the server know that we're done
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data = Constants.RECORDING_OVER
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self.send_packet_to_server(data)
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with open("results.json", "w") as f:
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json_dict = json.dumps(all_segments, indent=2)
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f.write(json_dict)
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except KeyboardInterrupt:
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# write all segments to a file
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with open("results.json", "w") as f:
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json_dict = json.dumps(all_segments, indent=2)
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f.write(json_dict)
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def get_client_socket(self):
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return self.client_socket
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def write_audio_frames_to_file(self, frames, file_name):
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wf = wave.open(file_name, 'wb')
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wf.setnchannels(CHANNELS)
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wf.setsampwidth(2)
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wf.setframerate(RATE)
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wf.writeframes(frames)
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wf.close()
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def record(self, out_file="output_recording.wav"):
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n_audio_file = 0
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# create dir for saving audio chunks
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if not os.path.exists("chunks"):
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os.makedirs("chunks", exist_ok=True)
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try:
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for _ in range(0, int(RATE / CHUNK * RECORD_SECONDS)):
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data = self.stream.read(CHUNK)
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self.frames += data
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# voice activity detection
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chunk_tensor = Client.bytes_to_audio_tensor(data)
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speech_prob = self.vad_model(chunk_tensor, RATE).item()
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if speech_prob > self.vad_threshold:
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data_dict = {
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"topic": self.topic,
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"audio": data
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}
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self.send_packet_to_server(data_dict)
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# save frames if more than a minute
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if len(self.frames) > 60*RATE:
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t = threading.Thread(
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target=self.write_audio_frames_to_file,
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args=(self.frames[:], f"chunks/{n_audio_file}.wav", )
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)
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t.start()
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n_audio_file += 1
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self.frames = b""
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except KeyboardInterrupt:
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if len(self.frames):
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self.write_audio_frames_to_file(
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self.frames[:], f"chunks/{n_audio_file}.wav")
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n_audio_file += 1
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self.stream.stop_stream()
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self.stream.close()
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self.p.terminate()
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# let the server know that we're done
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data = Constants.RECORDING_OVER
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self.send_packet_to_server(data)
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# combine all the audio files
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self.write_output_recording(n_audio_file, out_file)
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# write all segments to a file
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with open("results.json", "w") as f:
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json_dict = json.dumps(all_segments, indent=2)
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f.write(json_dict)
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def write_output_recording(self, n_audio_file, out_file):
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input_files = [f"chunks/{i}.wav" for i in range(n_audio_file) if os.path.exists(f"chunks/{i}.wav")]
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wf = wave.open(out_file, 'wb')
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wf.setnchannels(CHANNELS)
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wf.setsampwidth(2)
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wf.setframerate(RATE)
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for in_file in input_files:
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w = wave.open(in_file, 'rb')
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while True:
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data = w.readframes(CHUNK)
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if data==b'': break
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wf.writeframes(data)
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w.close()
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# remove this file
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os.remove(in_file)
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wf.close()
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def recieve_response(client_socket):
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data = b""
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payload_size = struct.calcsize("Q")
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while True:
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while len(data) < payload_size:
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packet = client_socket.recv(4*1024) # 4K
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if not packet: break
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data+=packet
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packed_msg_size = data[:payload_size]
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data = data[payload_size:]
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try:
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msg_size = struct.unpack("Q",packed_msg_size)[0]
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except struct.error:
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break
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while len(data) < msg_size:
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data += client_socket.recv(4*1024)
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frame_data = data[:msg_size]
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data = data[msg_size:]
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response = pickle.loads(frame_data)
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if response is not None and isinstance(response, dict):
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os.system('clear')
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text = response['text']
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segments = response['segments']
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if len(segments):
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for seg in segments:
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all_segments.append(seg)
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wrapper = textwrap.TextWrapper(width=50)
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word_list = wrapper.wrap(text=text)
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# Print each line.
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for element in word_list:
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print(element)
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def resample(file: str, sr: int = 16000):
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"""
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# https://github.com/openai/whisper/blob/7858aa9c08d98f75575035ecd6481f462d66ca27/whisper/audio.py#L22
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Open an audio file and read as mono waveform, resampling as necessary,
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save the resampled audio
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Parameters
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----------
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file: str
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The audio file to open
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sr: int
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The sample rate to resample the audio if necessary
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"""
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try:
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# This launches a subprocess to decode audio while down-mixing and resampling as necessary.
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# Requires the ffmpeg CLI and `ffmpeg-python` package to be installed.
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out, _ = (
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ffmpeg.input(file, threads=0)
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.output("-", format="s16le", acodec="pcm_s16le", ac=1, ar=sr)
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.run(cmd=["ffmpeg", "-nostdin"], capture_stdout=True, capture_stderr=True)
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)
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except ffmpeg.Error as e:
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raise RuntimeError(f"Failed to load audio: {e.stderr.decode()}") from e
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np_buffer = np.frombuffer(out, dtype=np.int16)
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resampled_file = f"{file.split('.')[0]}_resampled.wav"
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scipy.io.wavfile.write(resampled_file, sr, np_buffer.astype(np.int16))
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return resampled_file
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if __name__=="__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument('--audio', type=str, help='audio file to transcribe')
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parser.add_argument('--topic', default=None, type=str, help='topic to subscribe for results')
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parser.add_argument('--host', default=None, type=str, help='server address to connect to')
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parser.add_argument('--port', default=None, type=str, help='server port to connect to')
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opt = parser.parse_args()
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c = Client(topic=opt.topic, host=opt.host, port=opt.port)
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while True:
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if c.get_client_socket() is not None:
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break
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client_socket = c.get_client_socket()
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t2 = threading.Thread(target=recieve_response, args=(client_socket, ))
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t2.start()
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if opt.audio is not None:
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resampled_file = resample(opt.audio)
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c.play_file(resampled_file)
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else:
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c.record()
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t2.join()
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