Maybe faster.......
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@@ -6,9 +6,6 @@ import numpy as np
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from pathlib import Path
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from typing import Optional, Tuple, List
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import time
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import threading
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from concurrent.futures import ThreadPoolExecutor
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from queue import Queue
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class VideoEditor:
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@@ -547,96 +544,45 @@ class VideoEditor:
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print("Error: Could not open video writer!")
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return False
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# Simple sequential processing - the I/O is the bottleneck anyway
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total_output_frames = end_frame - start_frame + 1
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frames_written = 0
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last_progress_update = 0
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# Batch processing configuration
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batch_size = min(50, max(10, total_output_frames // 20)) # Adaptive batch size
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frame_queue = Queue(maxsize=batch_size * 2)
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processed_queue = Queue(maxsize=batch_size * 2)
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def frame_reader():
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"""Background thread for reading frames"""
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try:
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for frame_idx in range(start_frame, end_frame + 1):
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# Read frame
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self.cap.set(cv2.CAP_PROP_POS_FRAMES, frame_idx)
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ret, frame = self.cap.read()
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if ret:
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frame_queue.put((frame_idx, frame))
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else:
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break
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finally:
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frame_queue.put(None) # Signal end of frames
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def frame_processor():
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"""Background thread for processing frames"""
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try:
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while True:
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item = frame_queue.get()
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if item is None: # End signal
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if not ret:
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break
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frame_idx, frame = item
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# Process and write frame directly (minimize memory copies)
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processed_frame = self._process_frame_for_render(frame, output_width, output_height)
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if processed_frame is not None:
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processed_queue.put((frame_idx, processed_frame))
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out.write(processed_frame)
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frame_queue.task_done()
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finally:
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processed_queue.put(None) # Signal end of processing
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frames_written = frame_idx - start_frame + 1
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# Start background threads
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reader_thread = threading.Thread(target=frame_reader, daemon=True)
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processor_thread = threading.Thread(target=frame_processor, daemon=True)
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reader_thread.start()
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processor_thread.start()
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# Main thread writes frames in order
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expected_frame = start_frame
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frame_buffer = {} # Buffer for out-of-order frames
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while frames_written < total_output_frames:
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item = processed_queue.get()
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if item is None: # End signal
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break
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frame_idx, processed_frame = item
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frame_buffer[frame_idx] = processed_frame
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# Write frames in order
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while expected_frame in frame_buffer:
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out.write(frame_buffer.pop(expected_frame))
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frames_written += 1
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expected_frame += 1
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# Progress update (throttled to avoid too frequent updates)
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# Throttled progress update
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current_time = time.time()
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if current_time - last_progress_update > 0.5: # Update every 0.5 seconds
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if current_time - last_progress_update > 0.5:
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progress = frames_written / total_output_frames * 100
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elapsed = current_time - start_time
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if frames_written > 0:
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eta = (elapsed / frames_written) * (total_output_frames - frames_written)
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fps_rate = frames_written / elapsed
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eta = (elapsed / frames_written) * (total_output_frames - frames_written)
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print(f"Progress: {progress:.1f}% | {frames_written}/{total_output_frames} | "
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f"FPS: {fps_rate:.1f} | ETA: {eta:.1f}s\r", end="")
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last_progress_update = current_time
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processed_queue.task_done()
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# Wait for threads to complete
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reader_thread.join()
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processor_thread.join()
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out.release()
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total_time = time.time() - start_time
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avg_fps = frames_written / total_time if total_time > 0 else 0
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total_frames_written = end_frame - start_frame + 1
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avg_fps = total_frames_written / total_time if total_time > 0 else 0
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print(f"\nVideo rendered successfully to {output_path}")
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print(f"Rendered {frames_written} frames in {total_time:.2f}s (avg {avg_fps:.1f} FPS)")
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print(f"Rendered {total_frames_written} frames in {total_time:.2f}s (avg {avg_fps:.1f} FPS)")
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return True
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def _process_frame_for_render(self, frame, output_width: int, output_height: int):
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