141 lines
5.3 KiB
Python
141 lines
5.3 KiB
Python
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#!/usr/bin/env python3
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"""QC: PROP-002牌匾 + PROP-003广告牌 R2候选图 · 闸门1"""
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import sys, os, json, base64, time, subprocess
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from pathlib import Path
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sys.path.insert(0, os.path.dirname(__file__))
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from secrets_loader import secret, endpoint
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AK = secret("SC-004")
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URL = endpoint("EPT-002")
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ROOT = Path(__file__).resolve().parents[1]
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# 候选图路径
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CANDIDATES = {
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"PROP-002": {
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"name": "天道宗无字牌匾",
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"spec": "深棕色木质无字牌匾，长方形横版，边缘古朴雕花装饰，3D动漫卡通渲染风格，纯白背景，无文字",
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"reject": ["写实", "照片感", "真实木纹", "产品摄影", "文字", "汉字", "字母"],
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"dir": ROOT / "assets/candidates/D157-PROP-002-R2/PROP-002-Tiandao-Plaque",
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"files": [f"PROP-002-R2-candidate-{i:02d}-1080x1920.jpg" for i in range(1, 5)]
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},
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"PROP-003": {
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"name": "免费招徒广告牌",
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"spec": "木制立式支架+米黄色空白宣纸底板，原木色支架朴素稳固，宣纸干净无字墨迹，修仙世界摊位宣传木板，3D动漫卡通渲染，纯白背景",
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"reject": ["写实", "照片感", "画架", "easel", "美术画架", "真实木纹", "产品图", "文字", "墨迹"],
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"dir": ROOT / "assets/candidates/D157-PROP-003-R2/PROP-003-Recruit-Board",
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"files": [f"PROP-003-R2-candidate-{i:02d}-1080x1920.jpg" for i in range(1, 5)]
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}
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}
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def encode_image(path):
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with open(path, "rb") as f:
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return base64.b64encode(f.read()).decode()
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def qwen_vl_qc(img_b64, asset_name, spec, reject_words):
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"""调用Qwen-VL质检单张图"""
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prompt = f"""你是一个动态漫资产生成质检员。请严格检查这张图片。
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资产名称：{asset_name}
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规范要求：{spec}
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请逐项检查并打分（0-100）：
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1. 风格匹配度（是否为3D动漫卡通渲染风格，非写实/照片感）
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2. 内容准确性（是否包含规范要求的所有元素）
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3. 一票否决项检查（以下任意一项出现直接判不合格）：
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- 是否有文字/汉字/字母？
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- 是否是写实/照片感风格？
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- 是否像产品摄影图？
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- 对于PROP-003：是否是画架(easel)样式而不是摊位木板？
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输出格式（严格JSON）：
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{{"score": <0-100>, "style_ok": <bool>, "content_ok": <bool>, "has_text": <bool>, "is_photorealistic": <bool>, "is_easel": <bool>, "issues": ["问题列表"], "verdict": "PASS/FAIL"}}"""
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payload = {
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"model": "qwen-vl-max-latest",
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"input": {
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"messages": [
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{"role": "user", "content": [
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{"image": f"data:image/jpeg;base64,{img_b64}"},
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{"text": prompt}
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]}
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]
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},
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"parameters": {"enable_thinking": False}
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}
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r = subprocess.run(
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["curl", "-s", "-m", "60", "--noproxy", "*", "-X", "POST", URL,
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"-H", f"Authorization: Bearer {AK}",
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"-H", "Content-Type: application/json",
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"-d", json.dumps(payload)],
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capture_output=True, text=True, timeout=65
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)
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try:
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d = json.loads(r.stdout)
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content = d["output"]["choices"][0]["message"]["content"]
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# 提取JSON
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import re
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m = re.search(r'\{[^{}]*\}', content)
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if m:
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return json.loads(m.group())
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return {"score": 0, "verdict": "FAIL", "issues": ["无法解析VL响应"], "raw": content[:200]}
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except Exception as e:
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return {"score": 0, "verdict": "FAIL", "issues": [f"API错误: {e}"]}
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def main():
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if not AK:
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print("✗ SC-004密钥未找到"); return 1
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results = {}
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for aid, cfg in CANDIDATES.items():
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print(f"\n{'='*50}")
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print(f"QC: {aid} · {cfg['name']}")
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print(f"{'='*50}")
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results[aid] = []
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for fname in cfg["files"]:
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fpath = cfg["dir"] / fname
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if not fpath.exists():
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print(f" ✗ 文件不存在: {fname}")
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continue
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print(f"\n 检查: {fname} ...", end=" ", flush=True)
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img_b64 = encode_image(str(fpath))
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qc = qwen_vl_qc(img_b64, cfg["name"], cfg["spec"], cfg["reject"])
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v = qc.get("verdict", "?")
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s = qc.get("score", "?")
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issues = qc.get("issues", [])
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print(f"[{v}] score={s}")
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for iss in issues:
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print(f" ⚠️ {iss}")
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qc["_file"] = fname
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results[aid].append(qc)
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time.sleep(1)
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# 输出汇总
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print(f"\n\n{'='*60}")
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print("QC 汇总报告")
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print(f"{'='*60}")
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for aid, qlist in results.items():
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print(f"\n【{aid}】")
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for q in qlist:
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fn = q.get("_file", "?")
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v = q.get("verdict", "?")
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s = q.get("score", "?")
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ph = q.get("is_photorealistic", False)
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easel = q.get("is_easel", False)
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has_txt = q.get("has_text", False)
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flag = ""
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if ph: flag += " 写实"
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if easel: flag += " 画架"
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if has_txt: flag += " 有字"
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print(f" {fn}: {v} (score={s}){flag}")
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# 写入QC报告
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report_path = ROOT / "assets/candidates/D157-PROP-QC-report.json"
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with open(report_path, "w") as f:
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json.dump(results, f, ensure_ascii=False, indent=2)
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print(f"\n📋 QC报告已写入: {report_path}")
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return 0
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if __name__ == "__main__":
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sys.exit(main())
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