16337
942244bd88
- Engine build scripts (FP16/INT8) - Benchmark validation scripts - Result parsing and analysis tools - COCO dataset configuration
110 lines
3.5 KiB
Python
110 lines
3.5 KiB
Python
import re
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import json
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from pathlib import Path
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from datetime import datetime
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def parse_file(filepath):
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with open(filepath, 'r', encoding='utf-8', errors='replace') as f:
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content = f.read()
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result = {'file': filepath}
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# Speed
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speed_match = re.search(r'Speed:\s*([\d.]+)ms\s+preprocess,\s*([\d.]+)ms\s+inference', content)
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if speed_match:
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result['preprocess'] = float(speed_match.group(1))
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result['inference'] = float(speed_match.group(2))
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result['fps'] = round(1000/float(speed_match.group(2)), 1)
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# Overall
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overall = re.search(r'^\s*all\s+\d+\s+\d+\s+([\d.]+)\s+([\d.]+)\s+([\d.]+)\s+([\d.]+)', content, re.MULTILINE)
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if overall:
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result['P'] = float(overall.group(1))
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result['R'] = float(overall.group(2))
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result['mAP50'] = float(overall.group(3))
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result['mAP50_95'] = float(overall.group(4))
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# Person
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person = re.search(r'^\s*person\s+\d+\s+\d+\s+([\d.]+)\s+([\d.]+)\s+([\d.]+)\s+([\d.]+)', content, re.MULTILINE)
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if person:
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result['person'] = {
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'P': float(person.group(1)), 'R': float(person.group(2)),
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'AP50': float(person.group(3)), 'AP50_95': float(person.group(4))
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}
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# Vehicles (car)
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car = re.search(r'^\s*car\s+\d+\s+\d+\s+([\d.]+)\s+([\d.]+)\s+([\d.]+)\s+([\d.]+)', content, re.MULTILINE)
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if car:
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result['car'] = {
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'P': float(car.group(1)), 'R': float(car.group(2)),
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'AP50': float(car.group(3)), 'AP50_95': float(car.group(4))
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}
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return result
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print("="*60)
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print("YOLO11n INT8 640p vs FP16 480p Benchmark")
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print("="*60)
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print(f"Time: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
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print()
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# Parse both
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int8 = parse_file('int8_640_results.txt')
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fp16 = parse_file('fp16_480_results.txt')
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# Summary table
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print("-"*60)
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print("1. Overall Performance")
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print("-"*60)
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print(f"{'Config':<15} {'mAP50-95':<12} {'mAP50':<12} {'Inf(ms)':<10} {'FPS':<10}")
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print("-"*60)
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for name, data in [("INT8_640p", int8), ("FP16_480p", fp16)]:
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m = data.get('mAP50_95', 0)
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m50 = data.get('mAP50', 0)
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inf = data.get('inference', 0)
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fps = data.get('fps', 0)
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print(f"{name:<15} {m:<12.4f} {m50:<12.4f} {inf:<10.2f} {fps:<10.1f}")
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print()
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print("-"*60)
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print("2. Person Detection (Class 0)")
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print("-"*60)
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print(f"{'Config':<15} {'P':<10} {'R':<10} {'AP50':<12} {'AP50-95':<12}")
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print("-"*60)
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for name, data in [("INT8_640p", int8), ("FP16_480p", fp16)]:
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p = data.get('person', {}).get('P', 0)
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r = data.get('person', {}).get('R', 0)
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ap50 = data.get('person', {}).get('AP50', 0)
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ap5095 = data.get('person', {}).get('AP50_95', 0)
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print(f"{name:<15} {p:<10.3f} {r:<10.3f} {ap50:<12.4f} {ap5095:<12.4f}")
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print()
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print("-"*60)
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print("3. Car Detection (Class 2)")
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print("-"*60)
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print(f"{'Config':<15} {'P':<10} {'R':<10} {'AP50':<12} {'AP50-95':<12}")
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print("-"*60)
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for name, data in [("INT8_640p", int8), ("FP16_480p", fp16)]:
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p = data.get('car', {}).get('P', 0)
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r = data.get('car', {}).get('R', 0)
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ap50 = data.get('car', {}).get('AP50', 0)
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ap5095 = data.get('car', {}).get('AP50_95', 0)
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print(f"{name:<15} {p:<10.3f} {r:<10.3f} {ap50:<12.4f} {ap5095:<12.4f}")
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print()
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print("-"*60)
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print("4. Speed Comparison")
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print("-"*60)
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for name, data in [("INT8_640p", int8), ("FP16_480p", fp16)]:
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inf = data.get('inference', 0)
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fps = data.get('fps', 0)
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print(f" {name}: {inf:.2f}ms ({fps:.1f} FPS)")
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print()
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print("="*60)
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print("Done!")
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print("="*60)
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