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Update app.py
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app.py
CHANGED
@@ -33,22 +33,23 @@ async def generate_accurate_srt(batch_text, batch_num, start_offset):
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# Initialize SRT content
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srt_content = ""
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words = batch_text.split()
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num_segments = max(1, len(words) //
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segment_duration = actual_length / num_segments # Duration for each segment
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start_time = start_offset
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# Build SRT content with accurate timing
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for i in range(0, len(words),
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segment_words = words[i:i+
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end_time = start_time + segment_duration
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srt_content += f"{i //
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srt_content += f"{format_time(start_time)} --> {format_time(end_time)}\n"
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srt_content += " ".join(segment_words) + "\n\n"
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start_time = end_time
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return srt_content, audio_file, start_time
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# Batch processing function with
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async def batch_process_srt_and_audio(script_text, progress=gr.Progress()):
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batches = [script_text[i:i+500] for i in range(0, len(script_text), 500)]
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all_srt_content = ""
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@@ -56,16 +57,8 @@ async def batch_process_srt_and_audio(script_text, progress=gr.Progress()):
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start_offset = 0.0 # Track cumulative time offset for SRT timing
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# Prepare tasks for concurrent batch processing
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generate_accurate_srt(batch_text, batch_num, start_offset)
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for batch_num, batch_text in enumerate(batches)
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]
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# Execute tasks concurrently and update progress after each completion
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completed_tasks = 0
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total_tasks = len(tasks)
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for task in asyncio.as_completed(tasks):
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srt_content, audio_file, end_offset = await task
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all_srt_content += srt_content
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# Append the audio of each batch to the combined audio
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@@ -77,8 +70,7 @@ async def batch_process_srt_and_audio(script_text, progress=gr.Progress()):
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os.remove(audio_file)
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# Update progress
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progress(completed_tasks / total_tasks)
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# Generate unique names for the final files
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unique_id = uuid.uuid4()
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# Initialize SRT content
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srt_content = ""
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words = batch_text.split()
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num_segments = max(1, len(words) // 15) # Group words into segments of ~15 words each
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segment_duration = actual_length / num_segments # Duration for each segment
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start_time = start_offset
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min_display_duration = 1.5 # Set a minimum display time of 1.5 seconds per subtitle
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# Build SRT content with accurate timing
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for i in range(0, len(words), 15): # Process ~15 words per subtitle
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segment_words = words[i:i+15]
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end_time = start_time + max(segment_duration, min_display_duration) # Ensure each subtitle shows at least min_display_duration
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srt_content += f"{i // 15 + 1 + (batch_num * 100)}\n"
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srt_content += f"{format_time(start_time)} --> {format_time(end_time)}\n"
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srt_content += " ".join(segment_words) + "\n\n"
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start_time = end_time
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return srt_content, audio_file, start_time # Return updated start time for cumulative tracking
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# Batch processing function with cumulative timing and progress indicator
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async def batch_process_srt_and_audio(script_text, progress=gr.Progress()):
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batches = [script_text[i:i+500] for i in range(0, len(script_text), 500)]
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all_srt_content = ""
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start_offset = 0.0 # Track cumulative time offset for SRT timing
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# Prepare tasks for concurrent batch processing
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for batch_num, batch_text in enumerate(batches):
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srt_content, audio_file, end_offset = await generate_accurate_srt(batch_text, batch_num, start_offset)
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all_srt_content += srt_content
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# Append the audio of each batch to the combined audio
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os.remove(audio_file)
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# Update progress
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progress((batch_num + 1) / len(batches))
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# Generate unique names for the final files
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unique_id = uuid.uuid4()
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