mirror of
https://github.com/denizsafak/abogen.git
synced 2026-07-18 13:40:27 +02:00
927 lines
40 KiB
Python
927 lines
40 KiB
Python
import os
|
|
import re
|
|
import tempfile
|
|
import time
|
|
import chardet
|
|
import charset_normalizer
|
|
from platformdirs import user_desktop_dir
|
|
from PyQt5.QtCore import QThread, pyqtSignal, Qt
|
|
from PyQt5.QtWidgets import QCheckBox, QVBoxLayout, QDialog, QLabel, QDialogButtonBox
|
|
import soundfile as sf
|
|
from utils import clean_text, create_process
|
|
from constants import PROGRAM_NAME, LANGUAGE_DESCRIPTIONS, SAMPLE_VOICE_TEXTS
|
|
from voice_formulas import get_new_voice
|
|
import static_ffmpeg
|
|
import threading # for efficient waiting
|
|
import subprocess
|
|
|
|
|
|
def get_sample_voice_text(lang_code):
|
|
return SAMPLE_VOICE_TEXTS.get(lang_code, SAMPLE_VOICE_TEXTS["a"])
|
|
|
|
|
|
def detect_encoding(file_path):
|
|
with open(file_path, "rb") as f:
|
|
raw_data = f.read()
|
|
detected_encoding = None
|
|
for detectors in (charset_normalizer, chardet):
|
|
try:
|
|
result = detectors.detect(raw_data)["encoding"]
|
|
except Exception:
|
|
continue
|
|
if result is not None:
|
|
detected_encoding = result
|
|
break
|
|
encoding = detected_encoding if detected_encoding else "utf-8"
|
|
return encoding.lower()
|
|
|
|
|
|
class ChapterOptionsDialog(QDialog):
|
|
def __init__(self, chapter_count, parent=None):
|
|
super().__init__(parent)
|
|
self.setWindowTitle("Chapter Options")
|
|
self.setMinimumWidth(350)
|
|
# Prevent closing with the X button and remove the help button
|
|
self.setWindowFlags(
|
|
self.windowFlags()
|
|
& ~Qt.WindowCloseButtonHint
|
|
& ~Qt.WindowContextHelpButtonHint
|
|
)
|
|
|
|
layout = QVBoxLayout(self)
|
|
|
|
# Add informational label
|
|
layout.addWidget(QLabel(f"Detected {chapter_count} chapters in the text file."))
|
|
layout.addWidget(QLabel("How would you like to process these chapters?"))
|
|
|
|
# Add checkboxes
|
|
self.save_separately_checkbox = QCheckBox("Save each chapter separately")
|
|
self.merge_at_end_checkbox = QCheckBox("Create a merged version at the end")
|
|
|
|
# Set default states
|
|
self.save_separately_checkbox.setChecked(True)
|
|
self.merge_at_end_checkbox.setChecked(True)
|
|
|
|
# Connect checkbox state change signal
|
|
self.save_separately_checkbox.stateChanged.connect(
|
|
self.update_merge_checkbox_state
|
|
)
|
|
|
|
layout.addWidget(self.save_separately_checkbox)
|
|
layout.addWidget(self.merge_at_end_checkbox)
|
|
|
|
# Add OK button
|
|
button_box = QDialogButtonBox(QDialogButtonBox.Ok)
|
|
button_box.accepted.connect(self.accept)
|
|
layout.addWidget(button_box)
|
|
|
|
# Initialize merge checkbox state
|
|
self.update_merge_checkbox_state()
|
|
|
|
def update_merge_checkbox_state(self):
|
|
# Enable merge checkbox only if save separately is checked
|
|
self.merge_at_end_checkbox.setEnabled(self.save_separately_checkbox.isChecked())
|
|
# Don't uncheck it, just leave it in its current state
|
|
|
|
def get_options(self):
|
|
save_separately = self.save_separately_checkbox.isChecked()
|
|
# Consider merge_at_end as false if the checkbox is disabled, regardless of its checked state
|
|
merge_at_end = (
|
|
self.merge_at_end_checkbox.isChecked()
|
|
and self.merge_at_end_checkbox.isEnabled()
|
|
)
|
|
return {
|
|
"save_chapters_separately": save_separately,
|
|
"merge_chapters_at_end": merge_at_end,
|
|
}
|
|
|
|
# Prevent closing by overriding the closeEvent
|
|
def closeEvent(self, event):
|
|
# Ignore all close events
|
|
event.ignore()
|
|
|
|
# Prevent escape key from closing the dialog
|
|
def keyPressEvent(self, event):
|
|
if event.key() == Qt.Key_Escape:
|
|
event.ignore()
|
|
else:
|
|
super().keyPressEvent(event)
|
|
|
|
|
|
class ConversionThread(QThread):
|
|
progress_updated = pyqtSignal(int, str) # Add str for ETR
|
|
conversion_finished = pyqtSignal(object, object) # Pass output path as second arg
|
|
log_updated = pyqtSignal(object) # Updated signal for log updates
|
|
chapters_detected = pyqtSignal(int) # Signal for chapter detection
|
|
|
|
def __init__(
|
|
self,
|
|
file_name,
|
|
lang_code,
|
|
speed,
|
|
voice,
|
|
save_option,
|
|
output_folder,
|
|
subtitle_mode,
|
|
output_format,
|
|
np_module,
|
|
kpipeline_class,
|
|
start_time,
|
|
total_char_count,
|
|
use_gpu=True,
|
|
): # Add use_gpu parameter
|
|
super().__init__()
|
|
self._chapter_options_event = threading.Event()
|
|
self.np = np_module
|
|
self.KPipeline = kpipeline_class
|
|
self.file_name = file_name
|
|
self.lang_code = lang_code
|
|
self.speed = speed
|
|
self.voice = voice
|
|
self.save_option = save_option
|
|
self.output_folder = output_folder
|
|
self.subtitle_mode = subtitle_mode
|
|
self.cancel_requested = False
|
|
self.output_format = output_format
|
|
self.start_time = start_time # Store start_time
|
|
self.total_char_count = total_char_count # Use passed total character count
|
|
self.processed_char_count = 0 # Initialize processed character count
|
|
self.display_path = None # Add variable for display path
|
|
self.is_direct_text = (
|
|
False # Flag to indicate if input is from textbox rather than file
|
|
)
|
|
self.chapter_options_set = False
|
|
self.waiting_for_user_input = False
|
|
self.use_gpu = use_gpu # Store the GPU setting
|
|
self.max_subtitle_words = 50 # Default value, will be overridden from GUI
|
|
|
|
def run(self):
|
|
print(
|
|
f"\nVoice: {self.voice}\nLanguage: {self.lang_code}\nSpeed: {self.speed}\nGPU: {self.use_gpu}\nFile: {self.file_name}\nSubtitle mode: {self.subtitle_mode}\nOutput format: {self.output_format}\nSave option: {self.save_option}\n"
|
|
)
|
|
try:
|
|
# Show configuration
|
|
self.log_updated.emit("Configuration:")
|
|
# Use display_path for logs if available, otherwise use the actual file name
|
|
display_file = self.display_path if self.display_path else self.file_name
|
|
self.log_updated.emit(f"- Input File: {display_file}")
|
|
|
|
# Use file size string passed from GUI
|
|
if hasattr(self, "file_size_str"):
|
|
self.log_updated.emit(f"- File size: {self.file_size_str}")
|
|
|
|
self.log_updated.emit(f"- Total characters: {self.total_char_count:,}")
|
|
|
|
self.log_updated.emit(
|
|
f"- Language: {self.lang_code} ({LANGUAGE_DESCRIPTIONS.get(self.lang_code, 'Unknown')})"
|
|
)
|
|
self.log_updated.emit(f"- Voice: {self.voice}")
|
|
self.log_updated.emit(f"- Speed: {self.speed}")
|
|
self.log_updated.emit(f"- Subtitle mode: {self.subtitle_mode}")
|
|
self.log_updated.emit(f"- Output format: {self.output_format}")
|
|
self.log_updated.emit(f"- Save option: {self.save_option}")
|
|
if self.replace_single_newlines:
|
|
self.log_updated.emit(f"- Replace single newlines: Yes")
|
|
|
|
# Display save_chapters_separately flag if it's set
|
|
if hasattr(self, "save_chapters_separately"):
|
|
self.log_updated.emit(
|
|
(
|
|
f"- Save chapters separately: {'Yes' if self.save_chapters_separately else 'No'}"
|
|
)
|
|
)
|
|
# Display merge_chapters_at_end flag if save_chapters_separately is True
|
|
if self.save_chapters_separately:
|
|
merge_at_end = getattr(self, "merge_chapters_at_end", True)
|
|
self.log_updated.emit(
|
|
f"- Merge chapters at the end: {'Yes' if merge_at_end else 'No'}"
|
|
)
|
|
|
|
if self.save_option == "Choose output folder":
|
|
self.log_updated.emit(
|
|
f" - Output folder: {self.output_folder or os.getcwd()}"
|
|
)
|
|
self.log_updated.emit("\nInitializing TTS pipeline...")
|
|
|
|
# Set device based on use_gpu setting
|
|
device = "cuda" if self.use_gpu else "cpu"
|
|
tts = self.KPipeline(
|
|
lang_code=self.lang_code, repo_id="hexgrad/Kokoro-82M", device=device
|
|
)
|
|
|
|
if self.is_direct_text:
|
|
text = self.file_name # Treat file_name as direct text input
|
|
else:
|
|
encoding = detect_encoding(self.file_name)
|
|
with open(
|
|
self.file_name, "r", encoding=encoding, errors="replace"
|
|
) as file:
|
|
text = file.read()
|
|
|
|
# Clean up text using utility function
|
|
text = clean_text(text)
|
|
|
|
# --- Chapter splitting logic ---
|
|
chapter_pattern = r"<<CHAPTER_MARKER:(.*?)>>"
|
|
chapter_splits = list(re.finditer(chapter_pattern, text))
|
|
chapters = []
|
|
if chapter_splits:
|
|
# prepend Introduction for content before first marker
|
|
first_start = chapter_splits[0].start()
|
|
if first_start > 0:
|
|
intro_text = text[:first_start].strip()
|
|
if intro_text:
|
|
chapters.append(("Introduction", intro_text))
|
|
for idx, match in enumerate(chapter_splits):
|
|
start = match.end()
|
|
end = (
|
|
chapter_splits[idx + 1].start()
|
|
if idx + 1 < len(chapter_splits)
|
|
else len(text)
|
|
)
|
|
chapter_name = match.group(1).strip()
|
|
chapter_text = text[start:end].strip()
|
|
chapters.append((chapter_name, chapter_text))
|
|
else:
|
|
chapters = [("text", text)]
|
|
total_chapters = len(chapters)
|
|
|
|
# For text files with chapters, prompt user for options if not already set
|
|
is_txt_file = not self.is_direct_text and (
|
|
self.file_name.lower().endswith(".txt")
|
|
or (self.display_path and self.display_path.lower().endswith(".txt"))
|
|
)
|
|
|
|
if (
|
|
is_txt_file
|
|
and total_chapters > 1
|
|
and (
|
|
not hasattr(self, "save_chapters_separately")
|
|
or not hasattr(self, "merge_chapters_at_end")
|
|
)
|
|
and not self.chapter_options_set
|
|
):
|
|
|
|
# Emit signal to main thread and wait
|
|
self.chapters_detected.emit(total_chapters)
|
|
self._chapter_options_event.wait()
|
|
if self.cancel_requested:
|
|
self.conversion_finished.emit("Cancelled", None)
|
|
return
|
|
self.chapter_options_set = True
|
|
|
|
# Log all detected chapters at the beginning
|
|
if total_chapters > 1:
|
|
chapter_list = "\n".join(
|
|
[f"{i+1}) {c[0]}" for i, c in enumerate(chapters)]
|
|
)
|
|
self.log_updated.emit(
|
|
(f"\nDetected chapters ({total_chapters}):\n" + chapter_list)
|
|
)
|
|
else:
|
|
self.log_updated.emit((f"\nProcessing {chapters[0][0]}..."))
|
|
|
|
# If save_chapters_separately is enabled, find a unique suffix ONCE and use for both folder and merged file
|
|
save_chapters_separately = getattr(self, "save_chapters_separately", False)
|
|
chapters_out_dir = None
|
|
suffix = ""
|
|
base_path = self.display_path if self.display_path else self.file_name
|
|
base_name = os.path.splitext(os.path.basename(base_path))[0]
|
|
if self.save_option == "Save to Desktop":
|
|
parent_dir = user_desktop_dir()
|
|
elif self.save_option == "Save next to input file":
|
|
parent_dir = os.path.dirname(base_path)
|
|
else:
|
|
parent_dir = self.output_folder or os.getcwd()
|
|
# Ensure the output folder exists, error if it doesn't
|
|
if not os.path.exists(parent_dir):
|
|
self.log_updated.emit(
|
|
(
|
|
f"Output folder does not exist: {parent_dir}",
|
|
"red",
|
|
)
|
|
)
|
|
# Find a unique suffix for both folder and merged file, always
|
|
counter = 1
|
|
while True:
|
|
suffix = f"_{counter}" if counter > 1 else ""
|
|
chapters_out_dir_candidate = os.path.join(
|
|
parent_dir, f"{base_name}{suffix}_chapters"
|
|
)
|
|
merged_file_candidate = os.path.join(
|
|
parent_dir, f"{base_name}{suffix}.{self.output_format}"
|
|
)
|
|
merged_srt_candidate = (
|
|
os.path.splitext(merged_file_candidate)[0] + ".srt"
|
|
)
|
|
if (
|
|
not os.path.exists(chapters_out_dir_candidate)
|
|
and not os.path.exists(merged_file_candidate)
|
|
and (
|
|
self.subtitle_mode == "Disabled"
|
|
or not os.path.exists(merged_srt_candidate)
|
|
)
|
|
):
|
|
break
|
|
counter += 1
|
|
if save_chapters_separately and total_chapters > 1:
|
|
chapters_out_dir = chapters_out_dir_candidate
|
|
os.makedirs(chapters_out_dir, exist_ok=True)
|
|
self.log_updated.emit(f"\nChapters output folder: {chapters_out_dir}")
|
|
|
|
audio_segments = []
|
|
subtitle_entries = []
|
|
current_time = 0.0
|
|
rate = 24000
|
|
subtitle_mode = self.subtitle_mode
|
|
raw_tts_results = [] # Collect all raw tts Result objects
|
|
|
|
# ETR timing starts here, after model loading but before processing
|
|
self.etr_start_time = time.time()
|
|
self.processed_char_count = 0 # Initialize processed character count
|
|
|
|
# Initialize current segment counter
|
|
current_segment = 0
|
|
|
|
# Initialize chapter times
|
|
chapters_time = [
|
|
{"chapter": chapter[0], "start": 0.0, "end": 0.0}
|
|
for chapter in chapters
|
|
]
|
|
|
|
# Instead of processing the whole text, process by chapter
|
|
for chapter_idx, (chapter_name, chapter_text) in enumerate(chapters, 1):
|
|
if total_chapters > 1:
|
|
self.log_updated.emit(
|
|
(
|
|
f"\nChapter {chapter_idx}/{total_chapters}: {chapter_name}",
|
|
"green",
|
|
)
|
|
)
|
|
|
|
# Variables for per-chapter processing when save_chapters_separately is enabled
|
|
chapter_audio_segments = []
|
|
chapter_subtitle_entries = []
|
|
chapter_current_time = 0.0
|
|
|
|
# chapter start time
|
|
chapter_time = chapters_time[chapter_idx - 1]
|
|
chapter_time["start"] = current_time
|
|
|
|
# Set split_pattern to \n+ which will split on one or more newlines
|
|
split_pattern = r"\n+"
|
|
|
|
# Check if the voice is a formula and load it if necessary
|
|
if "*" in self.voice:
|
|
loaded_voice = get_new_voice(tts, self.voice, self.use_gpu)
|
|
else:
|
|
loaded_voice = self.voice
|
|
|
|
for result in tts(
|
|
chapter_text,
|
|
voice=loaded_voice,
|
|
speed=self.speed,
|
|
split_pattern=split_pattern,
|
|
):
|
|
# Print the result for debugging
|
|
# print(f"Result: {result}")
|
|
if self.cancel_requested:
|
|
self.conversion_finished.emit("Cancelled", None)
|
|
return
|
|
current_segment += 1
|
|
grapheme_len = len(result.graphemes)
|
|
self.processed_char_count += grapheme_len
|
|
# Log progress with both character counts and the graphemes content
|
|
self.log_updated.emit(
|
|
f"\n{self.processed_char_count:,}/{self.total_char_count:,}: {result.graphemes}"
|
|
)
|
|
raw_tts_results.append(result)
|
|
|
|
chunk_dur = len(result.audio) / rate
|
|
chunk_start = current_time
|
|
audio_segments.append(result.audio)
|
|
|
|
# For per-chapter output
|
|
if save_chapters_separately and total_chapters > 1:
|
|
chapter_audio_segments.append(result.audio)
|
|
chapter_chunk_start = chapter_current_time
|
|
|
|
# Process token timestamps for subtitle generation
|
|
if self.subtitle_mode != "Disabled":
|
|
tokens_list = getattr(result, "tokens", [])
|
|
tokens_with_timestamps = []
|
|
chapter_tokens_with_timestamps = []
|
|
|
|
# Process every token, regardless of text or timestamps
|
|
for tok in tokens_list:
|
|
tokens_with_timestamps.append(
|
|
{
|
|
"start": chunk_start + (tok.start_ts or 0),
|
|
"end": chunk_start + (tok.end_ts or 0),
|
|
"text": tok.text,
|
|
"whitespace": tok.whitespace,
|
|
}
|
|
)
|
|
if save_chapters_separately and total_chapters > 1:
|
|
chapter_tokens_with_timestamps.append(
|
|
{
|
|
"start": chapter_chunk_start
|
|
+ (tok.start_ts or 0),
|
|
"end": chapter_chunk_start + (tok.end_ts or 0),
|
|
"text": tok.text,
|
|
"whitespace": tok.whitespace,
|
|
}
|
|
)
|
|
|
|
# Process tokens according to subtitle mode
|
|
# Global subtitle processing
|
|
self._process_subtitle_tokens(
|
|
tokens_with_timestamps,
|
|
subtitle_entries,
|
|
self.max_subtitle_words,
|
|
)
|
|
|
|
# Per-chapter subtitle processing if enabled
|
|
if save_chapters_separately and total_chapters > 1:
|
|
self._process_subtitle_tokens(
|
|
chapter_tokens_with_timestamps,
|
|
chapter_subtitle_entries,
|
|
self.max_subtitle_words,
|
|
)
|
|
|
|
current_time += chunk_dur
|
|
|
|
# Update chapter_current_time for per-chapter output
|
|
if save_chapters_separately and total_chapters > 1:
|
|
chapter_current_time += chunk_dur
|
|
|
|
# Calculate percentage based on characters processed
|
|
percent = min(
|
|
int(self.processed_char_count / self.total_char_count * 100), 99
|
|
)
|
|
|
|
# Calculate ETR based on characters processed
|
|
etr_str = "Estimating..."
|
|
chars_done = self.processed_char_count
|
|
elapsed = time.time() - self.etr_start_time
|
|
|
|
# Calculate ETR if enough data is available
|
|
if (
|
|
chars_done > 0 and elapsed > 0.5
|
|
): # Check elapsed > 0.5 to avoid instability
|
|
avg_time_per_char = elapsed / chars_done
|
|
remaining = self.total_char_count - self.processed_char_count
|
|
if remaining > 0:
|
|
secs = avg_time_per_char * remaining
|
|
h = int(secs // 3600)
|
|
m = int((secs % 3600) // 60)
|
|
s = int(secs % 60)
|
|
etr_str = f"{h:02d}:{m:02d}:{s:02d}"
|
|
|
|
# Update progress more frequently (after each result)
|
|
self.progress_updated.emit(percent, etr_str)
|
|
|
|
# Update chapter end time
|
|
chapter_time["end"] = current_time
|
|
|
|
# Save the individual chapter output if save_chapters_separately is enabled
|
|
if (
|
|
save_chapters_separately
|
|
and total_chapters > 1
|
|
and chapters_out_dir
|
|
and chapter_audio_segments
|
|
):
|
|
# Sanitize chapter name for use in filenames
|
|
sanitized_chapter_name = re.sub(r"[^\w\-\. ]", "_", chapter_name)
|
|
sanitized_chapter_name = re.sub(
|
|
r"_+", "_", sanitized_chapter_name
|
|
) # Replace multiple underscores with one
|
|
chapter_filename = f"{chapter_idx:02d}_{sanitized_chapter_name}"
|
|
|
|
# Concatenate chapter audio and save
|
|
chapter_audio = self.np.concatenate(chapter_audio_segments)
|
|
# Determine chapter extension (.wav for m4b output)
|
|
chapter_ext = 'wav' if self.output_format == 'm4b' else self.output_format
|
|
chapter_out_path = os.path.join(
|
|
chapters_out_dir, f"{chapter_filename}.{chapter_ext}"
|
|
)
|
|
if self.output_format == "opus":
|
|
static_ffmpeg.add_paths()
|
|
proc = create_process(
|
|
[
|
|
"ffmpeg",
|
|
"-y",
|
|
"-thread_queue_size", "1024", # Increased thread_queue_size for chapter opus
|
|
"-f",
|
|
"f32le",
|
|
"-ar",
|
|
"24000",
|
|
"-ac",
|
|
"1",
|
|
"-i",
|
|
"pipe:0",
|
|
"-c:a",
|
|
"libopus",
|
|
"-b:a",
|
|
"24000",
|
|
chapter_out_path,
|
|
],
|
|
stdin=subprocess.PIPE,
|
|
text=False # Ensure binary stdin for audio data
|
|
)
|
|
proc.stdin.write(chapter_audio.astype("float32").tobytes())
|
|
proc.stdin.close()
|
|
proc.wait()
|
|
else:
|
|
sf.write(
|
|
chapter_out_path,
|
|
chapter_audio,
|
|
24000,
|
|
format='wav' if self.output_format == 'm4b' else self.output_format,
|
|
)
|
|
|
|
# Generate .srt subtitle file for chapter if not Disabled
|
|
if self.subtitle_mode != "Disabled" and chapter_subtitle_entries:
|
|
chapter_srt_path = os.path.join(
|
|
chapters_out_dir, f"{chapter_filename}.srt"
|
|
)
|
|
with open(
|
|
chapter_srt_path, "w", encoding="utf-8", errors="replace"
|
|
) as srt_file:
|
|
for i, (start, end, text) in enumerate(
|
|
chapter_subtitle_entries, 1
|
|
):
|
|
srt_file.write(
|
|
f"{i}\n{self._srt_time(start)} --> {self._srt_time(end)}\n{text}\n\n"
|
|
)
|
|
|
|
self.log_updated.emit(
|
|
(
|
|
f"\nChapter {chapter_idx} saved to: {chapter_out_path}\n\nSubtitle saved to: {chapter_srt_path}",
|
|
"green",
|
|
)
|
|
)
|
|
else:
|
|
self.log_updated.emit(
|
|
(
|
|
f"\nChapter {chapter_idx} saved to: {chapter_out_path}",
|
|
"green",
|
|
)
|
|
)
|
|
|
|
# Set progress to 100% when processing is complete
|
|
self.progress_updated.emit(100, "00:00:00")
|
|
|
|
# Only generate the merged output file if merge_chapters_at_end is True or save_chapters_separately is False
|
|
merge_chapters = (
|
|
not hasattr(self, "save_chapters_separately")
|
|
or not self.save_chapters_separately
|
|
or getattr(self, "merge_chapters_at_end", True)
|
|
)
|
|
|
|
intended_output_format = self.output_format # Store the original choice
|
|
|
|
if audio_segments and merge_chapters:
|
|
self.log_updated.emit("\nFinalizing audio file...\n")
|
|
audio_data_np = self.np.concatenate(audio_segments)
|
|
|
|
out_dir = parent_dir
|
|
base_filepath_no_ext = os.path.join(out_dir, f"{base_name}{suffix}")
|
|
|
|
final_out_path = None
|
|
|
|
if intended_output_format == "m4b":
|
|
final_out_path = self._generate_m4b_with_chapters(audio_data_np, chapters_time, base_filepath_no_ext)
|
|
elif intended_output_format == "opus":
|
|
static_ffmpeg.add_paths()
|
|
opus_out_path = f"{base_filepath_no_ext}.opus"
|
|
ffmpeg_cmd_opus = [
|
|
"ffmpeg", "-y",
|
|
"-thread_queue_size", "1024", # Increased thread_queue_size
|
|
"-f", "f32le", "-ar", "24000", "-ac", "1", "-i", "pipe:0",
|
|
"-c:a", "libopus", "-b:a", "24000", # Original bitrate
|
|
opus_out_path,
|
|
]
|
|
try:
|
|
process = create_process(ffmpeg_cmd_opus, stdin=subprocess.PIPE, text=False) # Ensure binary stdin
|
|
process.stdin.write(audio_data_np.astype("float32").tobytes())
|
|
process.stdin.close()
|
|
if process.wait() == 0:
|
|
final_out_path = opus_out_path
|
|
else:
|
|
self.log_updated.emit(("Opus conversion failed.", "red"))
|
|
final_out_path = None
|
|
except Exception as e_opus:
|
|
self.log_updated.emit((f"Error during Opus conversion: {str(e_opus)}", "red"))
|
|
final_out_path = None
|
|
else: # For other formats like wav
|
|
standard_out_path = f"{base_filepath_no_ext}.{intended_output_format}"
|
|
try:
|
|
sf.write(standard_out_path, audio_data_np, 24000, format=intended_output_format)
|
|
final_out_path = standard_out_path
|
|
except Exception as e_sf:
|
|
self.log_updated.emit((f"Failed to write audio file {standard_out_path}: {str(e_sf)}", "red"))
|
|
final_out_path = None
|
|
|
|
# Subtitle and final message logic
|
|
if final_out_path:
|
|
if self.subtitle_mode != "Disabled":
|
|
srt_path = os.path.splitext(final_out_path)[0] + ".srt"
|
|
with open(srt_path, "w", encoding="utf-8", errors="replace") as srt_file:
|
|
for i, (start, end, text) in enumerate(subtitle_entries, 1):
|
|
srt_file.write(
|
|
f"{i}\n{self._srt_time(start)} --> {self._srt_time(end)}\n{text}\n\n"
|
|
)
|
|
self.conversion_finished.emit(
|
|
(
|
|
f"Audiobook saved to: {final_out_path}\n\nSubtitle saved to: {srt_path}",
|
|
"green",
|
|
),
|
|
final_out_path,
|
|
)
|
|
else:
|
|
self.conversion_finished.emit(
|
|
(f"Audiobook saved to: {final_out_path}", "green"), final_out_path
|
|
)
|
|
else:
|
|
self.log_updated.emit(("Audio generation failed (final_out_path was not set).", "red"))
|
|
self.conversion_finished.emit(("Audio generation failed.", "red"), None)
|
|
elif audio_segments and not merge_chapters:
|
|
self.conversion_finished.emit(
|
|
(
|
|
f"\nAll chapters processed successfully and saved to: {chapters_out_dir}",
|
|
"green",
|
|
),
|
|
chapters_out_dir,
|
|
)
|
|
else:
|
|
self.log_updated.emit(("No audio segments were generated.", "red"))
|
|
self.conversion_finished.emit(("Audio generation failed.", "red"), None)
|
|
except Exception as e:
|
|
self.log_updated.emit((f"Error occurred: {str(e)}", "red"))
|
|
self.conversion_finished.emit(("Audio generation failed.", "red"), None)
|
|
|
|
def set_chapter_options(self, options):
|
|
"""Set chapter options from the dialog and resume processing"""
|
|
self.save_chapters_separately = options["save_chapters_separately"]
|
|
self.merge_chapters_at_end = options["merge_chapters_at_end"]
|
|
self.waiting_for_user_input = False
|
|
self._chapter_options_event.set()
|
|
|
|
def _generate_m4b_with_chapters(self, audio_data_np, chapters_time, base_filepath_no_ext):
|
|
final_wav_path = f"{base_filepath_no_ext}.wav"
|
|
|
|
if not chapters_time or len(chapters_time) <= 1:
|
|
self.log_updated.emit(
|
|
(
|
|
"File contains only one chapter or no chapters were detected. Audio will be saved as a standard .wav file instead.\n",
|
|
"red",
|
|
)
|
|
)
|
|
try:
|
|
sf.write(final_wav_path, audio_data_np, 24000, format="wav")
|
|
return final_wav_path
|
|
except Exception as e_wav_single:
|
|
self.log_updated.emit((f"Failed to save single/no chapter audio as WAV: {str(e_wav_single)}", "red"))
|
|
return None
|
|
|
|
output_m4b_path = f"{base_filepath_no_ext}.m4b"
|
|
chapters_info_path = f"{base_filepath_no_ext}_chapters.txt"
|
|
|
|
try:
|
|
with open(chapters_info_path, "w", encoding="utf-8") as f:
|
|
f.write(";FFMETADATA1\n")
|
|
for chapter in chapters_time:
|
|
f.write(f"[CHAPTER]\n")
|
|
f.write(f"TIMEBASE=1/1000\n") # Using milliseconds for precision
|
|
f.write(f"START={int(chapter['start']*1000)}\n")
|
|
f.write(f"END={int(chapter['end']*1000)}\n")
|
|
f.write(f"title={chapter['chapter']}\n\n")
|
|
|
|
static_ffmpeg.add_paths()
|
|
ffmpeg_cmd = [
|
|
"ffmpeg", "-y",
|
|
"-thread_queue_size", "1024", # Increased thread_queue_size
|
|
"-f", "f32le", "-ar", "24000", "-ac", "1", "-i", "pipe:0",
|
|
"-i", chapters_info_path,
|
|
"-map", "0:a",
|
|
"-map_metadata", "1",
|
|
"-map_chapters", "1",
|
|
"-c:a", "aac", "-b:a", "128k", # Explicitly AAC with a common bitrate
|
|
output_m4b_path,
|
|
]
|
|
|
|
self.log_updated.emit(f"Generating audio with chapters...\n")
|
|
|
|
process = create_process(ffmpeg_cmd, stdin=subprocess.PIPE, text=False) # Ensure binary stdin
|
|
process.stdin.write(audio_data_np.astype("float32").tobytes())
|
|
process.stdin.close()
|
|
return_code = process.wait()
|
|
|
|
if return_code == 0:
|
|
return output_m4b_path
|
|
else:
|
|
self.log_updated.emit(
|
|
(f"FFmpeg failed to create M4B (return code {return_code}).\n\nFalling back to WAV.\n", "red")
|
|
)
|
|
sf.write(final_wav_path, audio_data_np, 24000, format="wav")
|
|
return final_wav_path
|
|
|
|
except Exception as e:
|
|
self.log_updated.emit((f"Error during M4B generation: {str(e)}.\n\nFalling back to WAV.\n", "red"))
|
|
try:
|
|
sf.write(final_wav_path, audio_data_np, 24000, format="wav")
|
|
return final_wav_path
|
|
except Exception as e_wav_fallback:
|
|
self.log_updated.emit((f"Critical error: Failed to save fallback WAV: {str(e_wav_fallback)}\n", "red"))
|
|
return None
|
|
finally:
|
|
if os.path.exists(chapters_info_path):
|
|
try:
|
|
os.remove(chapters_info_path)
|
|
except Exception as e_clean:
|
|
self.log_updated.emit((f"Warning: Could not delete temporary chapter file {chapters_info_path}: {e_clean}", "orange"))
|
|
|
|
def _srt_time(self, t):
|
|
"""Helper function to format time for SRT files"""
|
|
h = int(t // 3600)
|
|
m = int((t % 3600) // 60)
|
|
s = int(t % 60)
|
|
ms = int((t - int(t)) * 1000)
|
|
return f"{h:02}:{m:02}:{s:02},{ms:03}"
|
|
|
|
def _process_subtitle_tokens(
|
|
self, tokens_with_timestamps, subtitle_entries, max_subtitle_words
|
|
):
|
|
"""Helper function to process subtitle tokens according to the subtitle mode"""
|
|
if not tokens_with_timestamps:
|
|
return
|
|
|
|
if self.subtitle_mode == "Sentence" or self.subtitle_mode == "Sentence + Comma":
|
|
# Define separator pattern based on mode
|
|
separator = r"[.!?]" if self.subtitle_mode == "Sentence" else r"[.!?,]"
|
|
current_sentence = []
|
|
word_count = 0
|
|
|
|
for token in tokens_with_timestamps:
|
|
current_sentence.append(token)
|
|
word_count += 1
|
|
|
|
# Split sentences based on separator or word count
|
|
if (
|
|
re.search(separator, token["text"]) and token["whitespace"] == " "
|
|
) or word_count >= max_subtitle_words:
|
|
if current_sentence:
|
|
# Create subtitle entry for this sentence
|
|
start_time = current_sentence[0]["start"]
|
|
end_time = current_sentence[-1]["end"]
|
|
|
|
# Simplified text joining logic
|
|
sentence_text = ""
|
|
for t in current_sentence:
|
|
sentence_text += t["text"] + (t.get("whitespace", "") or "")
|
|
|
|
subtitle_entries.append(
|
|
(start_time, end_time, sentence_text.strip())
|
|
)
|
|
current_sentence = []
|
|
word_count = 0
|
|
|
|
# Add any remaining tokens as a sentence
|
|
if current_sentence:
|
|
start_time = current_sentence[0]["start"]
|
|
end_time = current_sentence[-1]["end"]
|
|
|
|
# Simplified text joining logic
|
|
sentence_text = ""
|
|
for t in current_sentence:
|
|
sentence_text += t["text"] + (t.get("whitespace", "") or "")
|
|
|
|
subtitle_entries.append((start_time, end_time, sentence_text.strip()))
|
|
|
|
else:
|
|
# Word count-based grouping
|
|
try:
|
|
word_count = int(self.subtitle_mode.split()[0])
|
|
word_count = min(word_count, max_subtitle_words)
|
|
except (ValueError, IndexError):
|
|
word_count = 1
|
|
|
|
# Combine punctuation with preceding words
|
|
processed_tokens = []
|
|
i = 0
|
|
while i < len(tokens_with_timestamps):
|
|
token = tokens_with_timestamps[i].copy()
|
|
|
|
# Look ahead for punctuation
|
|
while i + 1 < len(tokens_with_timestamps) and re.match(
|
|
r"^[^\w\s]+$", tokens_with_timestamps[i + 1]["text"]
|
|
):
|
|
token["text"] += tokens_with_timestamps[i + 1]["text"]
|
|
token["end"] = tokens_with_timestamps[i + 1]["end"]
|
|
token["whitespace"] = tokens_with_timestamps[i + 1]["whitespace"]
|
|
i += 1
|
|
|
|
processed_tokens.append(token)
|
|
i += 1
|
|
|
|
# Group words into subtitle entries
|
|
for i in range(0, len(processed_tokens), word_count):
|
|
group = processed_tokens[i : i + word_count]
|
|
if group:
|
|
text = "".join(
|
|
t["text"] + (t.get("whitespace", "") or "") for t in group
|
|
)
|
|
subtitle_entries.append(
|
|
(group[0]["start"], group[-1]["end"], text.strip())
|
|
)
|
|
|
|
def cancel(self):
|
|
self.cancel_requested = True
|
|
self.waiting_for_user_input = (
|
|
False # Also release the wait if we're waiting for input
|
|
)
|
|
|
|
|
|
class VoicePreviewThread(QThread):
|
|
finished = pyqtSignal()
|
|
error = pyqtSignal(str)
|
|
|
|
def __init__(
|
|
self,
|
|
np_module,
|
|
kpipeline_class,
|
|
lang_code,
|
|
voice,
|
|
speed,
|
|
use_gpu=False,
|
|
parent=None,
|
|
):
|
|
super().__init__(parent)
|
|
self.np_module = np_module
|
|
self.kpipeline_class = kpipeline_class
|
|
self.lang_code = lang_code
|
|
self.voice = voice
|
|
self.speed = speed
|
|
self.use_gpu = use_gpu
|
|
|
|
def run(self):
|
|
print(
|
|
f"\nVoice: {self.voice}\nLanguage: {self.lang_code}\nSpeed: {self.speed}\nGPU: {self.use_gpu}\n"
|
|
)
|
|
try:
|
|
device = "cuda" if self.use_gpu else "cpu"
|
|
tts = self.kpipeline_class(
|
|
lang_code=self.lang_code, repo_id="hexgrad/Kokoro-82M", device=device
|
|
)
|
|
# Enable voice formula support for preview
|
|
if "*" in self.voice:
|
|
loaded_voice = get_new_voice(tts, self.voice, self.use_gpu)
|
|
else:
|
|
loaded_voice = self.voice
|
|
sample_text = get_sample_voice_text(self.lang_code)
|
|
audio_segments = []
|
|
for result in tts(
|
|
sample_text, voice=loaded_voice, speed=self.speed, split_pattern=None
|
|
):
|
|
audio_segments.append(result.audio)
|
|
if audio_segments:
|
|
audio = self.np_module.concatenate(audio_segments)
|
|
# Create temp wav file in a folder in the system temp directory
|
|
temp_dir = os.path.join(tempfile.gettempdir(), PROGRAM_NAME)
|
|
os.makedirs(temp_dir, exist_ok=True)
|
|
fd, temp_path = tempfile.mkstemp(
|
|
prefix="abogen_", suffix=".wav", dir=temp_dir
|
|
)
|
|
os.close(fd)
|
|
sf.write(temp_path, audio, 24000)
|
|
self.temp_wav = temp_path
|
|
self.finished.emit()
|
|
except Exception as e:
|
|
self.error.emit(f"Voice preview error: {str(e)}")
|
|
|
|
|
|
class PlayAudioThread(QThread):
|
|
finished = pyqtSignal()
|
|
error = pyqtSignal(str)
|
|
|
|
def __init__(self, wav_path, parent=None):
|
|
super().__init__(parent)
|
|
self.wav_path = wav_path
|
|
|
|
def run(self):
|
|
try:
|
|
import pygame
|
|
import time as _time
|
|
|
|
pygame.mixer.init()
|
|
pygame.mixer.music.load(self.wav_path)
|
|
pygame.mixer.music.play()
|
|
# Wait until playback is finished
|
|
while pygame.mixer.music.get_busy():
|
|
_time.sleep(0.1)
|
|
pygame.mixer.music.unload()
|
|
self.finished.emit()
|
|
except Exception as e:
|
|
self.error.emit(f"Audio playback error: {str(e)}")
|