print("starting...") import os import shutil import subprocess import re from pydub import AudioSegment import tempfile from pydub import AudioSegment import os import nltk from nltk.tokenize import sent_tokenize from .. import import_all_files #nltk.download('punkt') # Make sure to download the necessary models def is_folder_empty(folder_path): if os.path.exists(folder_path) and os.path.isdir(folder_path): # List directory contents if not os.listdir(folder_path): return True # The folder is empty else: return False # The folder is not empty else: print(f"The path {folder_path} is not a valid folder.") return None # The path is not a valid folder def remove_folder_with_contents(folder_path): try: shutil.rmtree(folder_path) print(f"Successfully removed {folder_path} and all of its contents.") except Exception as e: print(f"Error removing {folder_path}: {e}") def wipe_folder(folder_path): # Check if the folder exists if not os.path.exists(folder_path): print(f"The folder {folder_path} does not exist.") return # Iterate over all the items in the given folder for item in os.listdir(folder_path): item_path = os.path.join(folder_path, item) # If it's a file, remove it and print a message if os.path.isfile(item_path): os.remove(item_path) print(f"Removed file: {item_path}") # If it's a directory, remove it recursively and print a message elif os.path.isdir(item_path): shutil.rmtree(item_path) print(f"Removed directory and its contents: {item_path}") print(f"All contents wiped from {folder_path}.") # Example usage # folder_to_wipe = 'path_to_your_folder' # wipe_folder(folder_to_wipe) def create_m4b_from_chapters(input_dir, ebook_file, output_dir): # Function to sort chapters based on their numeric order def sort_key(chapter_file): numbers = re.findall(r'\d+', chapter_file) return int(numbers[0]) if numbers else 0 # Extract metadata and cover image from the eBook file def extract_metadata_and_cover(ebook_path): try: cover_path = ebook_path.rsplit('.', 1)[0] + '.jpg' subprocess.run(['ebook-meta', ebook_path, '--get-cover', cover_path], check=True) if os.path.exists(cover_path): return cover_path except Exception as e: print(f"Error extracting eBook metadata or cover: {e}") return None # Combine WAV files into a single file def combine_wav_files(chapter_files, output_path): # Initialize an empty audio segment combined_audio = AudioSegment.empty() # Sequentially append each file to the combined_audio for chapter_file in chapter_files: audio_segment = AudioSegment.from_wav(chapter_file) combined_audio += audio_segment # Export the combined audio to the output file path combined_audio.export(output_path, format='wav') print(f"Combined audio saved to {output_path}") # Function to generate metadata for M4B chapters def generate_ffmpeg_metadata(chapter_files, metadata_file): with open(metadata_file, 'w') as file: file.write(';FFMETADATA1\n') start_time = 0 for index, chapter_file in enumerate(chapter_files): duration_ms = len(AudioSegment.from_wav(chapter_file)) file.write(f'[CHAPTER]\nTIMEBASE=1/1000\nSTART={start_time}\n') file.write(f'END={start_time + duration_ms}\ntitle=Chapter {index + 1}\n') start_time += duration_ms # Generate the final M4B file using ffmpeg def create_m4b(combined_wav, metadata_file, cover_image, output_m4b): # Ensure the output directory exists os.makedirs(os.path.dirname(output_m4b), exist_ok=True) ffmpeg_cmd = ['ffmpeg', '-i', combined_wav, '-i', metadata_file] if cover_image: ffmpeg_cmd += ['-i', cover_image, '-map', '0:a', '-map', '2:v'] else: ffmpeg_cmd += ['-map', '0:a'] ffmpeg_cmd += ['-map_metadata', '1', '-c:a', 'aac', '-b:a', '192k'] if cover_image: ffmpeg_cmd += ['-c:v', 'png', '-disposition:v', 'attached_pic'] ffmpeg_cmd += [output_m4b] subprocess.run(ffmpeg_cmd, check=True) # Main logic chapter_files = sorted([os.path.join(input_dir, f) for f in os.listdir(input_dir) if f.endswith('.wav')], key=sort_key) temp_dir = tempfile.gettempdir() temp_combined_wav = os.path.join(temp_dir, 'combined.wav') metadata_file = os.path.join(temp_dir, 'metadata.txt') cover_image = extract_metadata_and_cover(ebook_file) output_m4b = os.path.join(output_dir, os.path.splitext(os.path.basename(ebook_file))[0] + '.m4b') combine_wav_files(chapter_files, temp_combined_wav) generate_ffmpeg_metadata(chapter_files, metadata_file) create_m4b(temp_combined_wav, metadata_file, cover_image, output_m4b) # Cleanup if os.path.exists(temp_combined_wav): os.remove(temp_combined_wav) if os.path.exists(metadata_file): os.remove(metadata_file) if cover_image and os.path.exists(cover_image): os.remove(cover_image) # Example usage # create_m4b_from_chapters('path_to_chapter_wavs', 'path_to_ebook_file', 'path_to_output_dir') #this code right here isnt the book grabbing thing but its before to refrence in ordero to create the sepecial chapter labeled book thing with calibre idk some systems cant seem to get it so just in case but the next bit of code after this is the book grabbing code with booknlp import os import subprocess import ebooklib from ebooklib import epub from bs4 import BeautifulSoup import re import csv import nltk # Only run the main script if Value is True def create_chapter_labeled_book(ebook_file_path): # Function to ensure the existence of a directory def ensure_directory(directory_path): if not os.path.exists(directory_path): os.makedirs(directory_path) print(f"Created directory: {directory_path}") ensure_directory(os.path.join(".", 'Working_files', 'Book')) def convert_to_epub(input_path, output_path): # Convert the ebook to EPUB format using Calibre's ebook-convert try: subprocess.run(['ebook-convert', input_path, output_path], check=True) except subprocess.CalledProcessError as e: print(f"An error occurred while converting the eBook: {e}") return False return True def save_chapters_as_text(epub_path): # Create the directory if it doesn't exist directory = os.path.join(".", "Working_files", "temp_ebook") ensure_directory(directory) # Open the EPUB file book = epub.read_epub(epub_path) previous_chapter_text = '' previous_filename = '' chapter_counter = 0 # Iterate through the items in the EPUB file for item in book.get_items(): if item.get_type() == ebooklib.ITEM_DOCUMENT: # Use BeautifulSoup to parse HTML content soup = BeautifulSoup(item.get_content(), 'html.parser') text = soup.get_text() # Check if the text is not empty if text.strip(): if len(text) < 2300 and previous_filename: # Append text to the previous chapter if it's short with open(previous_filename, 'a', encoding='utf-8') as file: file.write('\n' + text) else: # Create a new chapter file and increment the counter previous_filename = os.path.join(directory, f"chapter_{chapter_counter}.txt") chapter_counter += 1 with open(previous_filename, 'w', encoding='utf-8') as file: file.write(text) print(f"Saved chapter: {previous_filename}") # Example usage input_ebook = ebook_file_path # Replace with your eBook file path output_epub = os.path.join(".", "Working_files", "temp.epub") if os.path.exists(output_epub): os.remove(output_epub) print(f"File {output_epub} has been removed.") else: print(f"The file {output_epub} does not exist.") if convert_to_epub(input_ebook, output_epub): save_chapters_as_text(output_epub) # Download the necessary NLTK data (if not already present) #nltk.download('punkt') def process_chapter_files(folder_path, output_csv): with open(output_csv, 'w', newline='', encoding='utf-8') as csvfile: writer = csv.writer(csvfile) # Write the header row writer.writerow(['Text', 'Start Location', 'End Location', 'Is Quote', 'Speaker', 'Chapter']) # Process each chapter file chapter_files = sorted(os.listdir(folder_path), key=lambda x: int(x.split('_')[1].split('.')[0])) for filename in chapter_files: if filename.startswith('chapter_') and filename.endswith('.txt'): chapter_number = int(filename.split('_')[1].split('.')[0]) file_path = os.path.join(folder_path, filename) try: with open(file_path, 'r', encoding='utf-8') as file: text = file.read() # Insert "NEWCHAPTERABC" at the beginning of each chapter's text if text: text = "NEWCHAPTERABC" + text sentences = nltk.tokenize.sent_tokenize(text) for sentence in sentences: start_location = text.find(sentence) end_location = start_location + len(sentence) writer.writerow([sentence, start_location, end_location, 'True', 'Narrator', chapter_number]) except Exception as e: print(f"Error processing file {filename}: {e}") # Example usage folder_path = os.path.join(".", "Working_files", "temp_ebook") output_csv = os.path.join(".", "Working_files", "Book", "Other_book.csv") process_chapter_files(folder_path, output_csv) def sort_key(filename): """Extract chapter number for sorting.""" match = re.search(r'chapter_(\d+)\.txt', filename) return int(match.group(1)) if match else 0 def combine_chapters(input_folder, output_file): # Create the output folder if it doesn't exist os.makedirs(os.path.dirname(output_file), exist_ok=True) # List all txt files and sort them by chapter number files = [f for f in os.listdir(input_folder) if f.endswith('.txt')] sorted_files = sorted(files, key=sort_key) with open(output_file, 'w', encoding='utf-8') as outfile: # Specify UTF-8 encoding here for i, filename in enumerate(sorted_files): with open(os.path.join(input_folder, filename), 'r', encoding='utf-8') as infile: # And here outfile.write(infile.read()) # Add the marker unless it's the last file if i < len(sorted_files) - 1: outfile.write("\nNEWCHAPTERABC\n") # Paths input_folder = os.path.join(".", 'Working_files', 'temp_ebook') output_file = os.path.join(".", 'Working_files', 'Book', 'Chapter_Book.txt') # Combine the chapters combine_chapters(input_folder, output_file) ensure_directory(os.path.join(".", "Working_files", "Book")) #create_chapter_labeled_book() import os import subprocess import sys import torchaudio # Check if Calibre's ebook-convert tool is installed def calibre_installed(): try: subprocess.run(['ebook-convert', '--version'], stdout=subprocess.PIPE, stderr=subprocess.PIPE) return True except FileNotFoundError: print("Calibre is not installed. Please install Calibre for this functionality.") return False import os import torch from TTS.api import TTS from nltk.tokenize import sent_tokenize from pydub import AudioSegment # Assuming split_long_sentence and wipe_folder are defined elsewhere in your code default_target_voice_path = "default_voice.wav" # Ensure this is a valid path default_language_code = "en" device = torch.device("cuda" if torch.cuda.is_available() else "cpu") def combine_wav_files(input_directory, output_directory, file_name): # Ensure that the output directory exists, create it if necessary os.makedirs(output_directory, exist_ok=True) # Specify the output file path output_file_path = os.path.join(output_directory, file_name) # Initialize an empty audio segment combined_audio = AudioSegment.empty() # Get a list of all .wav files in the specified input directory and sort them input_file_paths = sorted( [os.path.join(input_directory, f) for f in os.listdir(input_directory) if f.endswith(".wav")], key=lambda f: int(''.join(filter(str.isdigit, f))) ) # Sequentially append each file to the combined_audio for input_file_path in input_file_paths: audio_segment = AudioSegment.from_wav(input_file_path) combined_audio += audio_segment # Export the combined audio to the output file path combined_audio.export(output_file_path, format='wav') print(f"Combined audio saved to {output_file_path}") # Function to split long strings into parts def split_long_sentence(sentence, max_length=249, max_pauses=10): """ Splits a sentence into parts based on length or number of pauses without recursion. :param sentence: The sentence to split. :param max_length: Maximum allowed length of a sentence. :param max_pauses: Maximum allowed number of pauses in a sentence. :return: A list of sentence parts that meet the criteria. """ parts = [] while len(sentence) > max_length or sentence.count(',') + sentence.count(';') + sentence.count('.') > max_pauses: possible_splits = [i for i, char in enumerate(sentence) if char in ',;.' and i < max_length] if possible_splits: # Find the best place to split the sentence, preferring the last possible split to keep parts longer split_at = possible_splits[-1] + 1 else: # If no punctuation to split on within max_length, split at max_length split_at = max_length # Split the sentence and add the first part to the list parts.append(sentence[:split_at].strip()) sentence = sentence[split_at:].strip() # Add the remaining part of the sentence parts.append(sentence) return parts """ if 'tts' not in locals(): tts = TTS(selected_tts_model, progress_bar=True).to(device) """ from tqdm import tqdm # Convert chapters to audio using XTTS def convert_chapters_to_audio(chapters_dir, output_audio_dir, target_voice_path=None, language=None): selected_tts_model = "tts_models/multilingual/multi-dataset/xtts_v2" tts = TTS(selected_tts_model, progress_bar=False).to(device) # Set progress_bar to False to avoid nested progress bars if not os.path.exists(output_audio_dir): os.makedirs(output_audio_dir) for chapter_file in sorted(os.listdir(chapters_dir)): if chapter_file.endswith('.txt'): # Extract chapter number from the filename match = re.search(r"chapter_(\d+).txt", chapter_file) if match: chapter_num = int(match.group(1)) else: print(f"Skipping file {chapter_file} as it does not match the expected format.") continue chapter_path = os.path.join(chapters_dir, chapter_file) output_file_name = f"audio_chapter_{chapter_num}.wav" output_file_path = os.path.join(output_audio_dir, output_file_name) temp_audio_directory = os.path.join(".", "Working_files", "temp") os.makedirs(temp_audio_directory, exist_ok=True) temp_count = 0 with open(chapter_path, 'r', encoding='utf-8') as file: chapter_text = file.read() # Use the specified language model for sentence tokenization sentences = sent_tokenize(chapter_text, language='italian' if language == 'it' else 'english') for sentence in tqdm(sentences, desc=f"Chapter {chapter_num}"): fragments = [] if language == "en": fragments = split_long_sentence(sentence, max_length=249, max_pauses=10) if language == "it": fragments = split_long_sentence(sentence, max_length=213, max_pauses=10) for fragment in fragments: if fragment != "": #a hot fix to avoid blank fragments print(f"Generating fragment: {fragment}...") fragment_file_path = os.path.join(temp_audio_directory, f"{temp_count}.wav") speaker_wav_path = target_voice_path if target_voice_path else default_target_voice_path language_code = language if language else default_language_code tts.tts_to_file(text=fragment, file_path=fragment_file_path, speaker_wav=speaker_wav_path, language=language_code) temp_count += 1 combine_wav_files(temp_audio_directory, output_audio_dir, output_file_name) wipe_folder(temp_audio_directory) print(f"Converted chapter {chapter_num} to audio.") # Main execution flow if __name__ == "__main__": if len(sys.argv) < 2: print("Usage: python script.py [target_voice_file_path]") sys.exit(1) ebook_file_path = sys.argv[1] target_voice = sys.argv[2] if len(sys.argv) > 2 else None language = sys.argv[3] if len(sys.argv) > 3 else None if not calibre_installed(): sys.exit(1) working_files = os.path.join(".","Working_files", "temp_ebook") full_folder_working_files =os.path.join(".","Working_files") chapters_directory = os.path.join(".","Working_files", "temp_ebook") output_audio_directory = os.path.join(".", 'Chapter_wav_files') print("Wiping and removeing Working_files folder...") remove_folder_with_contents(full_folder_working_files) print("Wiping and and removeing chapter_wav_files folder...") remove_folder_with_contents(output_audio_directory) create_chapter_labeled_book(ebook_file_path) audiobook_output_path = os.path.join(".", "Audiobooks") print(f"{chapters_directory}||||{output_audio_directory}|||||{target_voice}") convert_chapters_to_audio(chapters_directory, output_audio_directory, target_voice, language) create_m4b_from_chapters(output_audio_directory, ebook_file_path, audiobook_output_path)