| import os |
| import textwrap |
| from pathlib import Path |
| import logging |
| import numpy as np |
| from scipy.io.wavfile import write |
| import config |
| import csv |
| import av |
| def log_block(key: str, value, unit=''): |
| if config.DEBUG: |
| return |
| """格式化输出日志内容""" |
| key_fmt = f"[ {key.ljust(25)}]" |
| val_fmt = f"{value} {unit}".strip() |
| logging.info(f"{key_fmt}: {val_fmt}") |
|
|
|
|
| def clear_screen(): |
| """Clears the console screen.""" |
| os.system("cls" if os.name == "nt" else "clear") |
|
|
|
|
| def print_transcript(text): |
| """Prints formatted transcript text.""" |
| wrapper = textwrap.TextWrapper(width=60) |
| for line in wrapper.wrap(text="".join(text)): |
| print(line) |
|
|
|
|
| def format_time(s): |
| """Convert seconds (float) to SRT time format.""" |
| hours = int(s // 3600) |
| minutes = int((s % 3600) // 60) |
| seconds = int(s % 60) |
| milliseconds = int((s - int(s)) * 1000) |
| return f"{hours:02}:{minutes:02}:{seconds:02},{milliseconds:03}" |
|
|
|
|
| def create_srt_file(segments, resampled_file): |
| with open(resampled_file, 'w', encoding='utf-8') as srt_file: |
| segment_number = 1 |
| for segment in segments: |
| start_time = format_time(float(segment['start'])) |
| end_time = format_time(float(segment['end'])) |
| text = segment['text'] |
|
|
| srt_file.write(f"{segment_number}\n") |
| srt_file.write(f"{start_time} --> {end_time}\n") |
| srt_file.write(f"{text}\n\n") |
|
|
| segment_number += 1 |
|
|
|
|
| def resample(file: str, sr: int = 16000): |
| """ |
| Resample the audio file to 16kHz. |
| |
| Args: |
| file (str): The audio file to open |
| sr (int): The sample rate to resample the audio if necessary |
| |
| Returns: |
| resampled_file (str): The resampled audio file |
| """ |
| container = av.open(file) |
| stream = next(s for s in container.streams if s.type == 'audio') |
|
|
| resampler = av.AudioResampler( |
| format='s16', |
| layout='mono', |
| rate=sr, |
| ) |
|
|
| resampled_file = Path(file).stem + "_resampled.wav" |
| output_container = av.open(resampled_file, mode='w') |
| output_stream = output_container.add_stream('pcm_s16le', rate=sr) |
| output_stream.layout = 'mono' |
|
|
| for frame in container.decode(audio=0): |
| frame.pts = None |
| resampled_frames = resampler.resample(frame) |
| if resampled_frames is not None: |
| for resampled_frame in resampled_frames: |
| for packet in output_stream.encode(resampled_frame): |
| output_container.mux(packet) |
|
|
| for packet in output_stream.encode(None): |
| output_container.mux(packet) |
|
|
| output_container.close() |
| return resampled_file |
|
|
|
|
| def save_to_wave(filename, data:np.ndarray, sample_rate=16000): |
| data = (data * 32767).astype(np.int16) |
| write(filename, sample_rate, data) |
|
|
|
|
| def pcm_bytes_to_np_array(pcm_bytes: bytes, dtype=np.float32, channels=1): |
| |
| audio_np = np.frombuffer(pcm_bytes, dtype=np.int16) |
| audio_np = audio_np.astype(dtype=dtype) |
| if dtype == np.float32: |
| audio_np /= 32768.0 |
| |
| if channels > 1: |
| audio_np = audio_np.reshape(-1, channels) |
| return audio_np |
|
|
| class TestDataWriter: |
| def __init__(self, file_path='test_data.csv'): |
| self.file_path = file_path |
| self.fieldnames = [ |
| 'seg_id', 'transcrible_time', 'translate_time', |
| 'transcribleContent', 'from', 'to', 'translateContent', 'partial' |
| ] |
| self._ensure_file_has_header() |
|
|
| def _ensure_file_has_header(self): |
| if not os.path.exists(self.file_path) or os.path.getsize(self.file_path) == 0: |
| with open(self.file_path, mode='w', newline='') as file: |
| writer = csv.DictWriter(file, fieldnames=self.fieldnames) |
| writer.writeheader() |
|
|
| def write(self, result: 'DebugResult'): |
| with open(self.file_path, mode='a', newline='') as file: |
| writer = csv.DictWriter(file, fieldnames=self.fieldnames) |
| writer.writerow(result.model_dump(by_alias=True)) |
