mirror of
https://github.com/santinic/audiblez.git
synced 2025-08-05 16:48:55 +00:00
258 lines
9.9 KiB
Python
Executable file
258 lines
9.9 KiB
Python
Executable file
#!/usr/bin/env python3
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# audiblez - A program to convert e-books into audiobooks using
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# Kokoro-82M model for high-quality text-to-speech synthesis.
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# by Claudio Santini 2025 - https://claudio.uk
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import argparse
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import sys
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import time
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import shutil
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import subprocess
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import numpy as np
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import soundfile
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import ebooklib
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import warnings
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import re
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import torch
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from pathlib import Path
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from string import Formatter
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from bs4 import BeautifulSoup
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from kokoro import KPipeline
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from ebooklib import epub
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from pydub import AudioSegment
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from pick import pick
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from tempfile import NamedTemporaryFile
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from voices import voices, available_voices_str
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sample_rate = 24000
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def main(file_path, voice, pick_manually, speed):
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filename = Path(file_path).name
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warnings.simplefilter("ignore")
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book = epub.read_epub(file_path)
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meta_title = book.get_metadata('DC', 'title')
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title = meta_title[0][0] if meta_title else ''
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meta_creator = book.get_metadata('DC', 'creator')
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by_creator = 'by ' + meta_creator[0][0] if meta_creator else ''
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cover_maybe = [c for c in book.get_items() if c.get_type() == ebooklib.ITEM_COVER]
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cover_image = cover_maybe[0].get_content() if cover_maybe else b""
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if cover_maybe:
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print(f'Found cover image {cover_maybe[0].file_name} in {cover_maybe[0].media_type} format')
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intro = f'{title} {by_creator}'
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print(intro)
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print('Found Chapters:', [c.get_name() for c in book.get_items() if c.get_type() == ebooklib.ITEM_DOCUMENT])
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if pick_manually:
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chapters = pick_chapters(book)
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else:
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chapters = find_chapters(book)
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print('Automatically selected chapters:', [c.get_name() for c in chapters])
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texts = extract_texts(chapters)
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has_ffmpeg = shutil.which('ffmpeg') is not None
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if not has_ffmpeg:
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print('\033[91m' + 'ffmpeg not found. Please install ffmpeg to create mp3 and m4b audiobook files.' + '\033[0m')
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total_chars, processed_chars = sum(map(len, texts)), 0
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print('Started at:', time.strftime('%H:%M:%S'))
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print(f'Total characters: {total_chars:,}')
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print('Total words:', len(' '.join(texts).split()))
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chars_per_sec = 500 if torch.cuda.is_available() else 50
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print(f'Estimated time remaining (assuming {chars_per_sec} chars/sec): {strfdelta((total_chars - processed_chars) / chars_per_sec)}')
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chapter_mp3_files = []
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for i, text in enumerate(texts, start=1):
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chapter_filename = filename.replace('.epub', f'_chapter_{i}.wav')
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chapter_mp3_files.append(chapter_filename)
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if Path(chapter_filename).exists():
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print(f'File for chapter {i} already exists. Skipping')
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continue
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if len(text.strip()) < 10:
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print(f'Skipping empty chapter {i}')
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chapter_mp3_files.remove(chapter_filename)
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continue
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print(f'Reading chapter {i} ({len(text):,} characters)...')
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if i == 1:
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text = intro + '.\n\n' + text
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start_time = time.time()
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audio_segments = gen_audio_segments(text, voice, speed)
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if audio_segments:
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final_audio = np.concatenate(audio_segments)
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soundfile.write(chapter_filename, final_audio, sample_rate)
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end_time = time.time()
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delta_seconds = end_time - start_time
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chars_per_sec = len(text) / delta_seconds
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processed_chars += len(text)
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print(f'Estimated time remaining: {strfdelta((total_chars - processed_chars) / chars_per_sec)}')
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print('Chapter written to', chapter_filename)
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print(f'Chapter {i} read in {delta_seconds:.2f} seconds ({chars_per_sec:.0f} characters per second)')
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progress = processed_chars * 100 // total_chars
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print('Progress:', f'{progress}%\n')
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else:
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print(f'Warning: No audio generated for chapter {i}')
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chapter_mp3_files.remove(chapter_filename)
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if has_ffmpeg:
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create_index_file(title, by_creator, chapter_mp3_files)
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create_m4b(chapter_mp3_files, filename, cover_image)
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def gen_audio_segments(text, voice, speed):
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pipeline = KPipeline(lang_code=voice[0]) # a for american or b for british etc.
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audio_segments = []
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for gs, ps, audio in pipeline(text, voice=voice, speed=speed, split_pattern=r'\n+'):
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audio_segments.append(audio)
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return audio_segments
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def extract_texts(chapters):
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texts = []
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for chapter in chapters:
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xml = chapter.get_body_content()
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soup = BeautifulSoup(xml, features='lxml')
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chapter_text = ''
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html_content_tags = ['title', 'p', 'h1', 'h2', 'h3', 'h4', 'li']
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for child in soup.find_all(html_content_tags):
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inner_text = child.text.strip() if child.text else ""
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if inner_text:
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chapter_text += inner_text + '\n'
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texts.append(chapter_text)
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return texts
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def is_chapter(c):
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name = c.get_name().lower()
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return bool(
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'chapter' in name.lower()
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or re.search(r'part\d{1,3}', name)
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or re.search(r'ch\d{1,3}', name)
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or re.search(r'chap\d{1,3}', name)
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)
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def find_chapters(book, verbose=False):
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chapters = [c for c in book.get_items() if c.get_type() == ebooklib.ITEM_DOCUMENT and is_chapter(c)]
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if verbose:
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for item in book.get_items():
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if item.get_type() == ebooklib.ITEM_DOCUMENT:
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print(f"'{item.get_name()}'" + ', #' + str(len(item.get_body_content())))
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if len(chapters) == 0:
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print('Not easy to find the chapters, defaulting to all available documents.')
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chapters = [c for c in book.get_items() if c.get_type() == ebooklib.ITEM_DOCUMENT]
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return chapters
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def pick_chapters(book):
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all_chapters_names = [c.get_name() for c in book.get_items() if c.get_type() == ebooklib.ITEM_DOCUMENT]
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title = 'Select which chapters to read in the audiobook'
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selected_chapters_names = pick(all_chapters_names, title, multiselect=True, min_selection_count=1)
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selected_chapters_names = [c[0] for c in selected_chapters_names]
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selected_chapters = [c for c in book.get_items() if c.get_name() in selected_chapters_names]
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return selected_chapters
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def strfdelta(tdelta, fmt='{D:02}d {H:02}h {M:02}m {S:02}s'):
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remainder = int(tdelta)
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f = Formatter()
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desired_fields = [field_tuple[1] for field_tuple in f.parse(fmt)]
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possible_fields = ('W', 'D', 'H', 'M', 'S')
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constants = {'W': 604800, 'D': 86400, 'H': 3600, 'M': 60, 'S': 1}
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values = {}
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for field in possible_fields:
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if field in desired_fields and field in constants:
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values[field], remainder = divmod(remainder, constants[field])
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return f.format(fmt, **values)
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def create_m4b(chapter_files, filename, cover_image):
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tmp_filename = filename.replace('.epub', '.tmp.mp4')
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if not Path(tmp_filename).exists():
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combined_audio = AudioSegment.empty()
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for wav_file in chapter_files:
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audio = AudioSegment.from_wav(wav_file)
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combined_audio += audio
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print('Converting to Mp4...')
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combined_audio.export(tmp_filename, format="mp4", codec="aac", bitrate="64k")
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final_filename = filename.replace('.epub', '.m4b')
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print('Creating M4B file...')
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if cover_image:
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cover_image_file = NamedTemporaryFile("wb")
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cover_image_file.write(cover_image)
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cover_image_args = ["-i", cover_image_file.name, "-map", "0:a", "-map", "2:v"]
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else:
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cover_image_args = []
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proc = subprocess.run([
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'ffmpeg',
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'-i', f'{tmp_filename}',
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'-i', 'chapters.txt',
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*cover_image_args,
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'-map', '0',
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'-map_metadata', '1',
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'-c:a', 'copy',
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'-c:v', 'copy',
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'-disposition:v', 'attached_pic',
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'-c', 'copy',
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'-f', 'mp4',
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f'{final_filename}'
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])
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Path(tmp_filename).unlink()
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if proc.returncode == 0:
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print(f'{final_filename} created. Enjoy your audiobook.')
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print('Feel free to delete the intermediary .wav chapter files, the .m4b is all you need.')
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def probe_duration(file_name):
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args = ['ffprobe', '-i', file_name, '-show_entries', 'format=duration', '-v', 'quiet', '-of', 'default=noprint_wrappers=1:nokey=1']
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proc = subprocess.run(args, capture_output=True, text=True, check=True)
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return float(proc.stdout.strip())
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def create_index_file(title, creator, chapter_mp3_files):
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with open("chapters.txt", "w") as f:
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f.write(f";FFMETADATA1\ntitle={title}\nartist={creator}\n\n")
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start = 0
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i = 0
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for c in chapter_mp3_files:
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duration = probe_duration(c)
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end = start + (int)(duration * 1000)
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f.write(f"[CHAPTER]\nTIMEBASE=1/1000\nSTART={start}\nEND={end}\ntitle=Chapter {i}\n\n")
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i += 1
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start = end
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def cli_main():
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voices_str = ', '.join(voices)
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epilog = ('example:\n' +
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' audiblez book.epub -l en-us -v af_sky\n\n' +
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'available voices:\n' +
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available_voices_str)
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default_voice = 'af_sky'
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parser = argparse.ArgumentParser(epilog=epilog, formatter_class=argparse.RawDescriptionHelpFormatter)
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parser.add_argument('epub_file_path', help='Path to the epub file')
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parser.add_argument('-v', '--voice', default=default_voice, help=f'Choose narrating voice: {voices_str}')
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parser.add_argument('-p', '--pick', default=False, help=f'Interactively select which chapters to read in the audiobook', action='store_true')
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parser.add_argument('-s', '--speed', default=1.0, help=f'Set speed from 0.5 to 2.0', type=float)
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parser.add_argument('-c', '--cuda', default=False, help=f'Use GPU via Cuda in Torch if available', action='store_true')
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if len(sys.argv) == 1:
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parser.print_help(sys.stderr)
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sys.exit(1)
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args = parser.parse_args()
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if args.cuda:
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if torch.cuda.is_available():
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print('CUDA GPU available')
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torch.set_default_device('cuda')
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else:
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print('CUDA GPU not available. Defaulting to CPU')
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main(args.epub_file_path, args.voice, args.pick, args.speed)
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if __name__ == '__main__':
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cli_main()
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