File size: 3,211 Bytes
53ccd32 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 | import os
import json
import subprocess
import pandas as pd
import shutil
from pathlib import Path
GLOBAL_MODEL_PATH = "../stage2_object_v8_1200"
GLOBAL_NORMAL_PATH = "正常-normal_data"###正常图的绝对路径
# 任务配置：(脚本名, 规则显示名称)
TASK_CONFIGS = [
("rule_11_vllm.py", "文字占比"),
("rule_12_vllm.py", "样式数量"),
#("rule_13_vllm.py", "排布位置"),
#("rule_14_vllm.py", "设计搭配"),
("rule_17_vllm.py", "信息量"),
("rule_18_vllm.py", "排布间距"),
("rule_19_vllm.py", "内容构图"),
]
SUMMARY_OUTPUT = "vllm_audit_summary_normal.csv"
def run_vllm_task(script, label_name):
normal_path = Path(GLOBAL_NORMAL_PATH)
original_json = normal_path / f"audit_result_{normal_path.name}.json"
unique_json = normal_path / f"temp_{script.replace('.py', '')}.json"
if unique_json.exists():
unique_json.unlink()
cmd = [
"python", script,
"--input_dir", GLOBAL_NORMAL_PATH,
"--model_path", GLOBAL_MODEL_PATH
]
print(f"\n[EXEC] 正在运行规则: {label_name} ({script})")
try:
subprocess.run(cmd, check=True)
if original_json.exists():
shutil.move(str(original_json), str(unique_json))
print(f"[DONE] 结果已固化至: {unique_json.name}")
return unique_json
else:
print(f"[ERROR] 脚本运行完成但未找到生成文件: {original_json}")
return None
except subprocess.CalledProcessError as e:
print(f"[ERROR] 脚本 {script} 崩溃: {e}")
return None
def extract_metrics(json_path, script, label_name):
"""从重命名后的唯一 JSON 文件中读取数据"""
if not json_path or not json_path.exists():
return {"规则名称": label_name, "状态": "失败"}
with open(json_path, 'r', encoding='utf-8') as f:
data = json.load(f)
total = len(data)
unsuitable = sum(1 for item in data if item["label"] == "Unsuitable")
suitable = sum(1 for item in data if item["label"] == "Suitable")
fp_rate = (unsuitable / total) if total > 0 else 0
return {
"规则脚本": script,
"规则维度": label_name,
"测试总数": total,
"误报数(Unsuitable)": unsuitable,
"正确通过数(Suitable)": suitable,
"误报率(FP Rate)": f"{fp_rate:.2%}",
"结果文件": json_path.name
}
def main():
final_results = []
for script, label_name in TASK_CONFIGS:
unique_json_path = run_vllm_task(script, label_name)
if unique_json_path:
metrics = extract_metrics(unique_json_path, script, label_name)
final_results.append(metrics)
if final_results:
df = pd.DataFrame(final_results)
df.to_csv(SUMMARY_OUTPUT, index=False, encoding='utf-8-sig')
print("\n" + "="*80)
print(f"测试完成！汇总已写入: {SUMMARY_OUTPUT}")
print("-" * 80)
print(df.to_string(index=False))
print("="*80)
else:
print("[CRITICAL] 没有收集到任何有效数据。")
if __name__ == "__main__":
main() |