185 lines
6.5 KiB
Python
185 lines
6.5 KiB
Python
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#!/usr/bin/env python3
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"""CHAR-004 R2 候选质检 · Qwen-VL · VA-05-001-R2标准"""
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import sys, os, json, base64, subprocess
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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from secrets_loader import secret, endpoint
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API_KEY = secret("SC-004")
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EP = endpoint("EPT-002")
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FALLBACK_EP = "https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation"
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CANDIDATES_DIR = os.path.expanduser("~/guanghulab/video-ai-system/assets/candidates/D157-VA-05-001-R2/CHAR-004-ZhugeFeng")
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CANDIDATES = [f"{CANDIDATES_DIR}/CHAR-004-R2-candidate-{i:02d}-1080x1920.jpg" for i in range(1, 5)]
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QC_PROMPT = """你是动画资产质量检查员。检查这张CHAR-004诸葛风立绘候选图，按以下标准逐项打分。
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## R2规范必查项
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1. 服装完整性（一票否决）：
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- 裤子膝盖是否有破洞/破损？是/否
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- 衣服下摆是否有毛边/破损/撕裂？是/否
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- 鞋子是否有泥污/脏污？是/否
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- 服装是否有污渍？是/否
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- 是否有补丁？是/否
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- 整体是否"乞丐化"（像乞丐而不是清贫少年）？
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2. 服装部件准确性：
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- 上衣是否为灰蓝色交领短打、右衽？是/否
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- 是否系深棕色粗麻绳腰带？是/否
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- 裤子是否深灰蓝色、裤脚塞进靴子？是/否
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- 鞋子是否黑色粗布短靴？是/否
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- 腰间是否有旧布包？是/否
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- 有无不该有的配饰（玉佩、香囊等）？是/否
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3. 面部质量：
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- 五官是否清晰无崩坏？是/否
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- 是否少年感强、气质偏冷硬？是/否
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- 有没有和苏白（温润仙气型）相似？是/否
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4. 整体：
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- 人物肢体比例是否正常？是/否
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- 画面是否清晰无噪点？是/否
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- 是否全身从头到鞋完整展示？是/否
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输出严格JSON，不要额外文字：
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{
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"candidate": N,
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"pass": true/false,
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"score": 0-100,
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"hole_in_pants": true/false,
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"frayed_hem": true/false,
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"dirty_shoes": true/false,
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"stains": true/false,
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"patches": true/false,
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"beggar_look": true/false,
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"correct_top": true/false,
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"correct_belt": true/false,
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"correct_pants": true/false,
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"correct_shoes": true/false,
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"has_bag": true/false,
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"extra_accessories": true/false,
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"face_intact": true/false,
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"cold_temperament": true/false,
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"similar_to_su_bai": true/false,
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"anatomy_ok": true/false,
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"clear_image": true/false,
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"full_body": true/false,
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"summary": "一句话总结"
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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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b64 = base64.b64encode(f.read()).decode()
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ext = path.rsplit(".", 1)[-1].lower()
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mime = {"jpg": "jpeg", "jpeg": "jpeg", "png": "png"}.get(ext, "jpeg")
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return f"data:image/{mime};base64,{b64}"
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def call_qwen(image_b64):
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body = json.dumps({
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"model": "qwen-vl-max",
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"input": {
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"messages": [{
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"role": "user",
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"content": [
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{"image": image_b64},
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{"text": QC_PROMPT}
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]
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}]
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}
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})
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endpoints = [EP, FALLBACK_EP]
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for ep in endpoints:
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try:
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proc = subprocess.run(
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["curl", "-s", "-m", "60", "--noproxy", "*",
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"-X", "POST", ep,
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"-H", f"Authorization: Bearer {API_KEY}",
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"-H", "Content-Type: application/json",
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"--data-binary", "@-"],
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input=body, capture_output=True, text=True, timeout=65
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)
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if proc.returncode != 0 or not proc.stdout.strip():
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continue
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resp = json.loads(proc.stdout)
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if "output" in resp:
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content = resp["output"]["choices"][0]["message"]["content"][0]["text"]
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# Clean markdown wrappers
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if "```" in content:
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content = content.split("```")[1]
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if content.startswith("json"):
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content = content[4:]
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content = content.split("```")[0]
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return json.loads(content.strip())
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elif "error" in resp:
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print(f" [Qwen error] {resp['error']}", file=sys.stderr)
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continue
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except Exception as e:
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print(f" [fail {ep}] {e}", file=sys.stderr)
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continue
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return None
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def main():
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print("=" * 60)
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print("CHAR-004 R2 候选质检 · Qwen-VL · VA-05-001-R2标准")
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print("=" * 60)
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results = []
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for i, path in enumerate(CANDIDATES):
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print(f"\n[{i+1}/4] 质检候选 {i+1}...")
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img = encode_image(path)
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qc = call_qwen(img)
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if qc:
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print(f" score={qc.get('score')} pass={qc.get('pass')}")
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print(f" 破洞={qc.get('hole_in_pants')} 毛边={qc.get('frayed_hem')} 脏鞋={qc.get('dirty_shoes')}")
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print(f" 乞丐化={qc.get('beggar_look')} 和苏白像={qc.get('similar_to_su_bai')}")
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print(f" {qc.get('summary')}")
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results.append(qc)
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else:
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print(f" ✗ Qwen-VL调用失败")
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results.append({"candidate": i+1, "pass": False, "error": "Qwen-VL call failed"})
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# 汇总
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print("\n" + "=" * 60)
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print("质检汇总")
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print("=" * 60)
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passed = sum(1 for r in results if r.get("pass"))
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print(f"通过: {passed}/4")
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for r in results:
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if not r.get("pass"):
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issues = []
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if r.get("hole_in_pants"): issues.append("裤子破洞")
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if r.get("frayed_hem"): issues.append("下摆毛边")
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if r.get("dirty_shoes"): issues.append("鞋子脏污")
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if r.get("stains"): issues.append("污渍")
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if r.get("patches"): issues.append("补丁")
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if r.get("beggar_look"): issues.append("乞丐化")
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if r.get("extra_accessories"): issues.append("多余配饰")
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print(f" 候选{r.get('candidate')} ✗: {', '.join(issues) if issues else 'other'}")
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# 写入JSON
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out_path = os.path.join(CANDIDATES_DIR, "QC-R2-BATCH.json")
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report = {
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"spec": "VA-05-001-R2",
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"asset_id": "CHAR-004-ZhugeFeng",
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"qc_tool": "Qwen-VL (qwen-vl-max)",
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"results": results,
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"summary": {
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"passed": passed,
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"total": 4,
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"verdict": "APPROVED" if passed >= 4 else "REJECTED"
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}
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}
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with open(out_path, "w") as f:
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json.dump(report, f, ensure_ascii=False, indent=2)
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print(f"\nQC报告已保存: {out_path}")
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return 0 if passed >= 4 else 1
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if __name__ == "__main__":
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sys.exit(main())
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