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
281 lines
9.4 KiB
Python
281 lines
9.4 KiB
Python
#!/opt/homebrew/bin/python3.11
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"""
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OCR Processor Benchmark Runner
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测试 OCR 文字辨识的性能和质量
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测试版本:
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A. ocr_processor.py (EasyOCR CPU + Resume)
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B. ocr_processor_mps.py (EasyOCR MPS)
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C. ocr_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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- 检测帧数
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- 检测文字数
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- 平均置信度
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- 空帧率
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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" / "ocr_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, languages=["en"], uuid="", extra_args=None):
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"""运行指定 OCR 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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# 方案 B: 语言参数格式不同 (--video, --output)
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if script_name == "ocr_processor_mps.py":
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cmd = [sys.executable, str(script_path)]
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cmd.extend(["--video", video_path])
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cmd.extend(["--output", output_path])
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cmd.extend(["--languages"] + languages)
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cmd.extend(["--sample-interval", "30"])
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cmd.extend(["--confidence", "0.5"])
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if uuid:
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cmd.extend(["--device", "auto"])
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# 方案 C: Contract 版本 (positional args)
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elif script_name == "ocr_processor_contract_v1.py":
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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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cmd.extend(["--confidence", "0.5"])
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# 方案 A: 默认不支持多语言参数
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else:
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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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cmd.extend(["--sample-interval", "30"])
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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[:500]}")
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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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# 解析结果
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frames = result.get("frames", {})
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if isinstance(frames, dict):
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frames_list = list(frames.values())
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else:
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frames_list = frames
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total_frames = len(frames_list)
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total_texts = 0
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confidences = []
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empty_frames = 0
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for frame_data in frames_list:
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texts = frame_data.get("texts", [])
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if not texts:
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empty_frames += 1
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else:
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total_texts += len(texts)
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for text in texts:
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confidences.append(text.get("confidence", 0))
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avg_confidence = sum(confidences) / len(confidences) if confidences else 0
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empty_frame_rate = empty_frames / total_frames if total_frames > 0 else 0
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avg_texts_per_frame = total_texts / total_frames if total_frames > 0 else 0
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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_frames": total_frames,
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"total_texts": total_texts,
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"avg_confidence": avg_confidence,
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"empty_frame_rate": empty_frame_rate,
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"avg_texts_per_frame": avg_texts_per_frame,
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"empty_frames": empty_frames,
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"file_size_kb": file_size_kb,
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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("OCR 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: {float(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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# 测试语言（用户选择多语言）
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languages = ["en", "ch_sim", "ja"]
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processors = [
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("A", "ocr_processor.py", "EasyOCR CPU + Resume", ["en"]), # 方案A仅支持en
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("B", "ocr_processor_mps.py", "EasyOCR MPS", languages),
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("C", "ocr_processor_contract_v1.py", "Contract v1.0", languages),
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]
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results = []
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for scheme_id, script_name, description, langs 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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print(f"语言: {langs}")
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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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languages=langs,
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uuid=f"ocr_bench_{scheme_id}",
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extra_args=["--sample-interval", "30"]
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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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"languages": langs,
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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_frames": result["total_frames"],
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"total_texts": result["total_texts"],
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"avg_confidence": result["avg_confidence"],
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"empty_frame_rate": result["empty_frame_rate"],
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"avg_texts_per_frame": result["avg_texts_per_frame"],
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"empty_frames": result["empty_frames"],
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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" 检测帧数: {result['total_frames']}")
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print(f" 检测文字数: {result['total_texts']}")
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print(f" 平均置信度: {result['avg_confidence']:.2f}")
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print(f" 空帧率: {result['empty_frame_rate']*100:.1f}%")
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print(f" 每帧平均文字: {result['avg_texts_per_frame']:.1f}")
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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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"languages": langs,
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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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"languages": languages,
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"results": results,
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}
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report_path = OUTPUT_DIR / "OCR_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 | 语言 | 时间(秒) | 内存(MB) | 帧数 | 文字数 | 置信度 | 空帧率 |")
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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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langs_str = ",".join(r["languages"])
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print(f"| {r['scheme']} | {r['script']} | {langs_str} | {r['elapsed_time']:.2f} | {r['peak_memory_mb']:.1f} | {r['total_frames']} | {r['total_texts']} | {r['avg_confidence']:.2f} | {r['empty_frame_rate']*100:.1f}% |")
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else:
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langs_str = ",".join(r["languages"])
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print(f"| {r['scheme']} | {r['script']} | {langs_str} | - | - | - | - | - | - |")
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if __name__ == "__main__":
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main() |