e75c4d6f07
- Remove session-ses_2f27.md (161KB raw session log) - Remove 49 ROOT_* duplicate files across REFERENCE/ - Remove 14 duplicate files between REFERENCE/ root and history/ - Remove asr_legacy.rs (dead code, replaced by asr.rs) - Remove src/core/worker/ (duplicate JobWorker) - Remove src/core/layers/ (empty directory) - Remove 4 .bak files in src/ - Remove 7 dead private methods in worker/processor.rs - Remove backup directory from git tracking
236 lines
7.5 KiB
Python
236 lines
7.5 KiB
Python
#!/opt/homebrew/bin/python3.11
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"""
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CUT Processor Benchmark Runner
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测试场景辨识的性能和质量
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测试版本:
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A. cut_processor.py (PySceneDetect)
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B. cut_processor_contract_v1.py (Contract v1.0)
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测试指标:
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- 处理时间
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- 内存峰值 (MB)
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- 检测场景数
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- 场景平均时长
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"""
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import os
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import sys
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import json
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import time
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import subprocess
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from pathlib import Path
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from datetime import datetime
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SCRIPTS_DIR = Path(__file__).parent
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OUTPUT_DIR = SCRIPTS_DIR.parent / "output" / "benchmark" / "cut_processor"
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def get_memory_peak(pid):
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"""获取进程内存峰值"""
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try:
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cmd = ["ps", "-p", str(pid), "-o", "rss="]
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result = subprocess.run(cmd, capture_output=True, text=True)
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if result.returncode == 0:
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return int(result.stdout.strip()) / 1024
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except:
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pass
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return 0
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def run_processor(script_name, video_path, output_path, uuid=""):
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"""运行指定 CUT processor"""
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script_path = SCRIPTS_DIR / script_name
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if not script_path.exists():
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print(f"❌ 脚本不存在: {script_path}")
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return None
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cmd = [sys.executable, str(script_path), video_path, output_path]
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if uuid:
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cmd.extend(["--uuid", uuid])
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print(f"\n执行: {script_name}")
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print(f"命令: {' '.join(cmd)}")
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start_time = time.time()
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process = subprocess.Popen(
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cmd,
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stdout=subprocess.PIPE,
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stderr=subprocess.PIPE,
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text=True
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)
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peak_memory = 0
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while process.poll() is None:
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mem = get_memory_peak(process.pid)
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if mem > peak_memory:
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peak_memory = mem
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time.sleep(0.5)
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stdout, stderr = process.communicate()
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elapsed_time = time.time() - start_time
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if process.returncode != 0:
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print(f"❌ 处理失败: {stderr}")
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return None
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if os.path.exists(output_path):
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with open(output_path) as f:
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result = json.load(f)
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scenes = result.get("scenes", [])
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total_scenes = len(scenes)
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# 计算场景统计
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avg_scene_duration = 0
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min_scene_duration = 0
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max_scene_duration = 0
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if scenes:
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durations = [s.get("end_time", 0) - s.get("start_time", 0) for s in scenes]
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avg_scene_duration = sum(durations) / len(durations)
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min_scene_duration = min(durations)
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max_scene_duration = max(durations)
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file_size_kb = os.path.getsize(output_path) / 1024
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return {
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"elapsed_time": elapsed_time,
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"peak_memory_mb": peak_memory,
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"total_scenes": total_scenes,
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"avg_scene_duration": avg_scene_duration,
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"min_scene_duration": min_scene_duration,
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"max_scene_duration": max_scene_duration,
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"file_size_kb": file_size_kb,
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"fps": result.get("fps", 0),
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"frame_count": result.get("frame_count", 0),
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"stdout": stdout,
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"stderr": stderr,
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}
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return None
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def main():
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print("=" * 80)
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print("CUT Processor Benchmark 测试")
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print("=" * 80)
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OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
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# 测试视频
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video_path = "/Users/accusys/momentry/var/sftpgo/data/demo/Gamma Carry Saves the World..mp4"
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if not os.path.exists(video_path):
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print(f"❌ 测试视频不存在: {video_path}")
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sys.exit(1)
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# 获取视频信息
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cmd = [
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"ffprobe",
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"-v", "quiet",
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"-print_format", "json",
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"-show_format",
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"-show_streams",
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video_path
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]
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try:
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result = subprocess.run(cmd, capture_output=True, text=True, check=True)
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video_info = json.loads(result.stdout)
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video_stream = next((s for s in video_info["streams"] if s["codec_type"] == "video"), None)
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print("\n测试视频:")
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print(f" 文件: {int(video_info['format'].get('size', 0)) / 1024 / 1024:.1f} MB")
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print(f" 时长: {float(video_info['format'].get('duration', 0)):.1f} 秒")
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print(f" 分辨率: {video_stream.get('width', 0)}x{video_stream.get('height', 0)}")
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print(f" FPS: {video_stream.get('r_frame_rate', 'unknown')}")
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except:
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print("⚠️ 无法获取视频信息")
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processors = [
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("A", "cut_processor.py", "PySceneDetect"),
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("B", "cut_processor_contract_v1.py", "Contract v1.0"),
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]
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results = []
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for scheme_id, script_name, description in processors:
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print(f"\n{'=' * 80}")
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print(f"方案 {scheme_id}: {description}")
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print(f"{'=' * 80}")
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output_path = OUTPUT_DIR / f"scheme_{scheme_id}_{script_name.replace('.py', '.json')}"
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if os.path.exists(output_path):
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os.remove(output_path)
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result = run_processor(
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script_name,
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video_path,
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str(output_path),
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uuid=f"cut_bench_{scheme_id}"
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)
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if result:
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results.append({
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"scheme": scheme_id,
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"script": script_name,
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"description": description,
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"elapsed_time": result["elapsed_time"],
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"peak_memory_mb": result["peak_memory_mb"],
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"total_scenes": result["total_scenes"],
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"avg_scene_duration": result["avg_scene_duration"],
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"min_scene_duration": result["min_scene_duration"],
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"max_scene_duration": result["max_scene_duration"],
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"fps": result["fps"],
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"frame_count": result["frame_count"],
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"file_size_kb": result["file_size_kb"],
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})
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print("\n✅ 处理完成:")
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print(f" 时间: {result['elapsed_time']:.2f}秒")
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print(f" 内存峰值: {result['peak_memory_mb']:.1f} MB")
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print(f" 检测场景数: {result['total_scenes']}")
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print(f" 场景平均时长: {result['avg_scene_duration']:.2f}秒")
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print(f" 场景最短时长: {result['min_scene_duration']:.2f}秒")
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print(f" 场景最长时长: {result['max_scene_duration']:.2f}秒")
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print(f" FPS: {result['fps']}")
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print(f" 输出大小: {result['file_size_kb']:.1f} KB")
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else:
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print(f"❌ 方案 {scheme_id} 处理失败")
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results.append({
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"scheme": scheme_id,
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"script": script_name,
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"description": description,
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"error": "processing failed"
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})
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# 保存报告
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report = {
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"test_date": datetime.now().isoformat(),
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"video_path": video_path,
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"results": results,
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}
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report_path = OUTPUT_DIR / "CUT_BENCHMARK_REPORT.json"
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with open(report_path, "w") as f:
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json.dump(report, f, indent=2, ensure_ascii=False)
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print(f"\n{'=' * 80}")
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print("测试报告已保存:")
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print(f" {report_path}")
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print(f"{'=' * 80}")
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print("\n【对比总结】")
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print("\n| 方案 | 脚本 | 时间(秒) | 内存(MB) | 场景数 | 平均时长(秒) |")
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print("|------|------|---------|---------|--------|-------------|")
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for r in results:
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if "error" not in r:
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print(f"| {r['scheme']} | {r['script']} | {r['elapsed_time']:.2f} | {r['peak_memory_mb']:.1f} | {r['total_scenes']} | {r['avg_scene_duration']:.2f} |")
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else:
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print(f"| {r['scheme']} | {r['script']} | - | - | - | - |")
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if __name__ == "__main__":
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main() |