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print("starting...") |
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import os |
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import shutil |
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import subprocess |
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import re |
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from pydub import AudioSegment |
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import tempfile |
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from pydub import AudioSegment |
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import os |
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import nltk |
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from nltk.tokenize import sent_tokenize |
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nltk.download('punkt') |
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def is_folder_empty(folder_path): |
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if os.path.exists(folder_path) and os.path.isdir(folder_path): |
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if not os.listdir(folder_path): |
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return True |
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else: |
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return False |
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else: |
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print(f"The path {folder_path} is not a valid folder.") |
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return None |
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def remove_folder_with_contents(folder_path): |
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try: |
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shutil.rmtree(folder_path) |
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print(f"Successfully removed {folder_path} and all of its contents.") |
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except Exception as e: |
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print(f"Error removing {folder_path}: {e}") |
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def wipe_folder(folder_path): |
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if not os.path.exists(folder_path): |
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print(f"The folder {folder_path} does not exist.") |
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return |
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for item in os.listdir(folder_path): |
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item_path = os.path.join(folder_path, item) |
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if os.path.isfile(item_path): |
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os.remove(item_path) |
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print(f"Removed file: {item_path}") |
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elif os.path.isdir(item_path): |
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shutil.rmtree(item_path) |
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print(f"Removed directory and its contents: {item_path}") |
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print(f"All contents wiped from {folder_path}.") |
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def create_m4b_from_chapters(input_dir, ebook_file, output_dir): |
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def sort_key(chapter_file): |
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numbers = re.findall(r'\d+', chapter_file) |
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return int(numbers[0]) if numbers else 0 |
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def extract_metadata_and_cover(ebook_path): |
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try: |
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cover_path = ebook_path.rsplit('.', 1)[0] + '.jpg' |
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subprocess.run(['ebook-meta', ebook_path, '--get-cover', cover_path], check=True) |
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if os.path.exists(cover_path): |
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return cover_path |
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except Exception as e: |
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print(f"Error extracting eBook metadata or cover: {e}") |
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return None |
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def combine_wav_files(chapter_files, output_path): |
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combined_audio = AudioSegment.empty() |
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for chapter_file in chapter_files: |
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audio_segment = AudioSegment.from_wav(chapter_file) |
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combined_audio += audio_segment |
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combined_audio.export(output_path, format='wav') |
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print(f"Combined audio saved to {output_path}") |
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def generate_ffmpeg_metadata(chapter_files, metadata_file): |
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with open(metadata_file, 'w') as file: |
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file.write(';FFMETADATA1\n') |
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start_time = 0 |
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for index, chapter_file in enumerate(chapter_files): |
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duration_ms = len(AudioSegment.from_wav(chapter_file)) |
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file.write(f'[CHAPTER]\nTIMEBASE=1/1000\nSTART={start_time}\n') |
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file.write(f'END={start_time + duration_ms}\ntitle=Chapter {index + 1}\n') |
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start_time += duration_ms |
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def create_m4b(combined_wav, metadata_file, cover_image, output_m4b): |
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os.makedirs(os.path.dirname(output_m4b), exist_ok=True) |
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ffmpeg_cmd = ['ffmpeg', '-i', combined_wav, '-i', metadata_file] |
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if cover_image: |
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ffmpeg_cmd += ['-i', cover_image, '-map', '0:a', '-map', '2:v'] |
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else: |
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ffmpeg_cmd += ['-map', '0:a'] |
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ffmpeg_cmd += ['-map_metadata', '1', '-c:a', 'aac', '-b:a', '192k'] |
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if cover_image: |
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ffmpeg_cmd += ['-c:v', 'png', '-disposition:v', 'attached_pic'] |
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ffmpeg_cmd += [output_m4b] |
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subprocess.run(ffmpeg_cmd, check=True) |
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chapter_files = sorted([os.path.join(input_dir, f) for f in os.listdir(input_dir) if f.endswith('.wav')], key=sort_key) |
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temp_dir = tempfile.gettempdir() |
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temp_combined_wav = os.path.join(temp_dir, 'combined.wav') |
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metadata_file = os.path.join(temp_dir, 'metadata.txt') |
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cover_image = extract_metadata_and_cover(ebook_file) |
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output_m4b = os.path.join(output_dir, os.path.splitext(os.path.basename(ebook_file))[0] + '.m4b') |
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combine_wav_files(chapter_files, temp_combined_wav) |
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generate_ffmpeg_metadata(chapter_files, metadata_file) |
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create_m4b(temp_combined_wav, metadata_file, cover_image, output_m4b) |
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if os.path.exists(temp_combined_wav): |
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os.remove(temp_combined_wav) |
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if os.path.exists(metadata_file): |
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os.remove(metadata_file) |
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if cover_image and os.path.exists(cover_image): |
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os.remove(cover_image) |
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import os |
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import subprocess |
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import ebooklib |
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from ebooklib import epub |
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from bs4 import BeautifulSoup |
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import re |
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import csv |
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import nltk |
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def create_chapter_labeled_book(ebook_file_path): |
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def ensure_directory(directory_path): |
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if not os.path.exists(directory_path): |
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os.makedirs(directory_path) |
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print(f"Created directory: {directory_path}") |
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ensure_directory(os.path.join(".", 'Working_files', 'Book')) |
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def convert_to_epub(input_path, output_path): |
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try: |
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subprocess.run(['ebook-convert', input_path, output_path], check=True) |
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except subprocess.CalledProcessError as e: |
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print(f"An error occurred while converting the eBook: {e}") |
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return False |
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return True |
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def save_chapters_as_text(epub_path): |
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directory = os.path.join(".", "Working_files", "temp_ebook") |
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ensure_directory(directory) |
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book = epub.read_epub(epub_path) |
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previous_chapter_text = '' |
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previous_filename = '' |
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chapter_counter = 0 |
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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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soup = BeautifulSoup(item.get_content(), 'html.parser') |
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text = soup.get_text() |
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if text.strip(): |
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if len(text) < 2300 and previous_filename: |
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with open(previous_filename, 'a', encoding='utf-8') as file: |
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file.write('\n' + text) |
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else: |
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previous_filename = os.path.join(directory, f"chapter_{chapter_counter}.txt") |
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chapter_counter += 1 |
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with open(previous_filename, 'w', encoding='utf-8') as file: |
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file.write(text) |
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print(f"Saved chapter: {previous_filename}") |
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input_ebook = ebook_file_path |
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output_epub = os.path.join(".", "Working_files", "temp.epub") |
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if os.path.exists(output_epub): |
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os.remove(output_epub) |
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print(f"File {output_epub} has been removed.") |
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else: |
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print(f"The file {output_epub} does not exist.") |
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if convert_to_epub(input_ebook, output_epub): |
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save_chapters_as_text(output_epub) |
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nltk.download('punkt') |
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def process_chapter_files(folder_path, output_csv): |
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with open(output_csv, 'w', newline='', encoding='utf-8') as csvfile: |
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writer = csv.writer(csvfile) |
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writer.writerow(['Text', 'Start Location', 'End Location', 'Is Quote', 'Speaker', 'Chapter']) |
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chapter_files = sorted(os.listdir(folder_path), key=lambda x: int(x.split('_')[1].split('.')[0])) |
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for filename in chapter_files: |
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if filename.startswith('chapter_') and filename.endswith('.txt'): |
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chapter_number = int(filename.split('_')[1].split('.')[0]) |
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file_path = os.path.join(folder_path, filename) |
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try: |
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with open(file_path, 'r', encoding='utf-8') as file: |
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text = file.read() |
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if text: |
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text = "NEWCHAPTERABC" + text |
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sentences = nltk.tokenize.sent_tokenize(text) |
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for sentence in sentences: |
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start_location = text.find(sentence) |
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end_location = start_location + len(sentence) |
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writer.writerow([sentence, start_location, end_location, 'True', 'Narrator', chapter_number]) |
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except Exception as e: |
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print(f"Error processing file {filename}: {e}") |
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folder_path = os.path.join(".", "Working_files", "temp_ebook") |
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output_csv = os.path.join(".", "Working_files", "Book", "Other_book.csv") |
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process_chapter_files(folder_path, output_csv) |
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def sort_key(filename): |
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"""Extract chapter number for sorting.""" |
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match = re.search(r'chapter_(\d+)\.txt', filename) |
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return int(match.group(1)) if match else 0 |
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def combine_chapters(input_folder, output_file): |
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os.makedirs(os.path.dirname(output_file), exist_ok=True) |
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files = [f for f in os.listdir(input_folder) if f.endswith('.txt')] |
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sorted_files = sorted(files, key=sort_key) |
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with open(output_file, 'w', encoding='utf-8') as outfile: |
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for i, filename in enumerate(sorted_files): |
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with open(os.path.join(input_folder, filename), 'r', encoding='utf-8') as infile: |
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outfile.write(infile.read()) |
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if i < len(sorted_files) - 1: |
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outfile.write("\nNEWCHAPTERABC\n") |
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input_folder = os.path.join(".", 'Working_files', 'temp_ebook') |
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output_file = os.path.join(".", 'Working_files', 'Book', 'Chapter_Book.txt') |
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combine_chapters(input_folder, output_file) |
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ensure_directory(os.path.join(".", "Working_files", "Book")) |
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import os |
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import subprocess |
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import sys |
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import torchaudio |
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def calibre_installed(): |
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try: |
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subprocess.run(['ebook-convert', '--version'], stdout=subprocess.PIPE, stderr=subprocess.PIPE) |
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return True |
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except FileNotFoundError: |
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print("Calibre is not installed. Please install Calibre for this functionality.") |
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return False |
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import os |
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import torch |
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from TTS.api import TTS |
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from nltk.tokenize import sent_tokenize |
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from pydub import AudioSegment |
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default_target_voice_path = "default_voice.wav" |
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default_language_code = "en" |
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
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def combine_wav_files(input_directory, output_directory, file_name): |
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os.makedirs(output_directory, exist_ok=True) |
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output_file_path = os.path.join(output_directory, file_name) |
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combined_audio = AudioSegment.empty() |
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input_file_paths = sorted( |
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[os.path.join(input_directory, f) for f in os.listdir(input_directory) if f.endswith(".wav")], |
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key=lambda f: int(''.join(filter(str.isdigit, f))) |
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) |
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for input_file_path in input_file_paths: |
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audio_segment = AudioSegment.from_wav(input_file_path) |
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combined_audio += audio_segment |
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combined_audio.export(output_file_path, format='wav') |
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print(f"Combined audio saved to {output_file_path}") |
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def split_long_sentence(sentence, max_length=249, max_pauses=10): |
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""" |
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Splits a sentence into parts based on length or number of pauses without recursion. |
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:param sentence: The sentence to split. |
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:param max_length: Maximum allowed length of a sentence. |
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:param max_pauses: Maximum allowed number of pauses in a sentence. |
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:return: A list of sentence parts that meet the criteria. |
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""" |
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parts = [] |
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while len(sentence) > max_length or sentence.count(',') + sentence.count(';') + sentence.count('.') > max_pauses: |
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possible_splits = [i for i, char in enumerate(sentence) if char in ',;.' and i < max_length] |
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if possible_splits: |
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split_at = possible_splits[-1] + 1 |
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else: |
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split_at = max_length |
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parts.append(sentence[:split_at].strip()) |
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sentence = sentence[split_at:].strip() |
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parts.append(sentence) |
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return parts |
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""" |
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if 'tts' not in locals(): |
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tts = TTS(selected_tts_model, progress_bar=True).to(device) |
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""" |
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from tqdm import tqdm |
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def convert_chapters_to_audio(chapters_dir, output_audio_dir, target_voice_path=None, language=None): |
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selected_tts_model = "tts_models/multilingual/multi-dataset/xtts_v2" |
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tts = TTS(selected_tts_model, progress_bar=False).to(device) |
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if not os.path.exists(output_audio_dir): |
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os.makedirs(output_audio_dir) |
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for chapter_file in sorted(os.listdir(chapters_dir)): |
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if chapter_file.endswith('.txt'): |
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match = re.search(r"chapter_(\d+).txt", chapter_file) |
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if match: |
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chapter_num = int(match.group(1)) |
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else: |
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print(f"Skipping file {chapter_file} as it does not match the expected format.") |
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continue |
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chapter_path = os.path.join(chapters_dir, chapter_file) |
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output_file_name = f"audio_chapter_{chapter_num}.wav" |
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output_file_path = os.path.join(output_audio_dir, output_file_name) |
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temp_audio_directory = os.path.join(".", "Working_files", "temp") |
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os.makedirs(temp_audio_directory, exist_ok=True) |
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temp_count = 0 |
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with open(chapter_path, 'r', encoding='utf-8') as file: |
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chapter_text = file.read() |
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sentences = sent_tokenize(chapter_text, language='italian' if language == 'it' else 'english') |
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for sentence in tqdm(sentences, desc=f"Chapter {chapter_num}"): |
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fragments = [] |
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if language == "en": |
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fragments = split_long_sentence(sentence, max_length=249, max_pauses=10) |
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if language == "it": |
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fragments = split_long_sentence(sentence, max_length=213, max_pauses=10) |
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for fragment in fragments: |
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if fragment != "": |
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print(f"Generating fragment: {fragment}...") |
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fragment_file_path = os.path.join(temp_audio_directory, f"{temp_count}.wav") |
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speaker_wav_path = target_voice_path if target_voice_path else default_target_voice_path |
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language_code = language if language else default_language_code |
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tts.tts_to_file(text=fragment, file_path=fragment_file_path, speaker_wav=speaker_wav_path, language=language_code) |
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temp_count += 1 |
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combine_wav_files(temp_audio_directory, output_audio_dir, output_file_name) |
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wipe_folder(temp_audio_directory) |
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print(f"Converted chapter {chapter_num} to audio.") |
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if __name__ == "__main__": |
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if len(sys.argv) < 2: |
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print("Usage: python script.py <ebook_file_path> [target_voice_file_path]") |
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sys.exit(1) |
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ebook_file_path = sys.argv[1] |
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target_voice = sys.argv[2] if len(sys.argv) > 2 else None |
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language = sys.argv[3] if len(sys.argv) > 3 else None |
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|
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if not calibre_installed(): |
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sys.exit(1) |
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working_files = os.path.join(".","Working_files", "temp_ebook") |
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full_folder_working_files =os.path.join(".","Working_files") |
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chapters_directory = os.path.join(".","Working_files", "temp_ebook") |
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output_audio_directory = os.path.join(".", 'Chapter_wav_files') |
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print("Wiping and removeing Working_files folder...") |
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remove_folder_with_contents(full_folder_working_files) |
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print("Wiping and and removeing chapter_wav_files folder...") |
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remove_folder_with_contents(output_audio_directory) |
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create_chapter_labeled_book(ebook_file_path) |
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audiobook_output_path = os.path.join(".", "Audiobooks") |
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print(f"{chapters_directory}||||{output_audio_directory}|||||{target_voice}") |
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convert_chapters_to_audio(chapters_directory, output_audio_directory, target_voice, language) |
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create_m4b_from_chapters(output_audio_directory, ebook_file_path, audiobook_output_path) |
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