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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
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 <ebook_file_path> [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)