223 lines
8.3 KiB
Python
223 lines
8.3 KiB
Python
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#!/usr/bin/env python3
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"""
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CHAR-004 诸葛风 · VA-05-001-R2 · 纯文生图执行脚本
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分两步：先锁服装 → 再调面部
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禁用任何图像参考，全程纯文字prompt
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"""
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import os, sys, json, time, base64, 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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# ── API 配置 ──
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API_KEY = secret("SC-001")
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BASE_URL = endpoint("EPT-001")
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IMAGE_MODEL = "doubao-seedream-4-0-250828" # 已验证通过
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# ── 路径配置 ──
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REPO_ROOT = Path(__file__).resolve().parents[1]
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JZAO_BASE = Path("/Volumes/JZAO/铸渊-ICE-GL-ZY001/OUT-输出/图片/zai-fu-fei-xiu-xian/ep01")
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CANDIDATES_DIR = REPO_ROOT / "assets/candidates/D157-VA-05-001-R2" / "CHAR-004-ZhugeFeng"
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# ── R2规范 · 全文字prompt ──
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CHAR004_PROMPT = """
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3D动漫卡通渲染，国风玄幻动态漫风格，画面质感与光影水平统一。
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男性，16岁，清瘦挺拔，全身立绘，正面站立姿势。身高约175cm，肩宽偏窄，身形单薄但有力量感，无佝偻萎靡感。
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面部：小麦色肤色，面部轮廓棱角分明，剑眉星目，眼神锐利有韧劲，鼻梁挺直，嘴唇偏薄，下颌线清晰。气质偏冷硬，少年气强，与温润型角色明确区分。
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发型：纯黑色短发，高束半马尾，发尾有零散碎发。用一根普通深棕色木簪固定，无华丽发饰。额前散落几缕碎发，整体整洁不凌乱。
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上衣：灰蓝色粗布交领短打，右衽，袖口收窄贴合手腕。衣服洗得微微褪色，领口、袖口边缘有轻微磨毛痕迹。无破洞、无污渍、无补丁，干净整洁。腰间系一根深棕色粗麻绳腰带，系法简单。
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下装：深灰蓝色同色系粗布长裤，裤脚收紧塞进靴筒，膝盖位置有轻微磨白痕迹。无破损、无污渍。
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鞋子：黑色粗布短靴，厚鞋底，鞋头有轻微磨损痕迹，干净无泥污。
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配饰：无玉佩、香囊、首饰。仅腰间麻绳上挂一个拳头大的深灰色旧布包，布包平整无破损。
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整体：清贫但不落魄，整洁有骨气。纯白背景，全身从头到鞋完整展示，画面干净。
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负面：不要破洞，不要污渍，不要补丁，不要乞丐，不要乞丐服，不要麻绳缠身，不要短袖，不要破损衣服，不要无鞋，不要半身。
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""".strip().replace("\n", " ")
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def call_seedream(prompt_text, seed=None):
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"""调用Seedream文生图API"""
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url = f"{BASE_URL}/images/generations"
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headers = {
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"Authorization": f"Bearer {API_KEY}",
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"Content-Type": "application/json"
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}
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payload = {
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"model": IMAGE_MODEL,
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"prompt": prompt_text,
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"size": "1440x2560",
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"n": 1,
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}
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if seed:
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payload["seed"] = seed
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print(f" → POST {url}")
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print(f" → model: {IMAGE_MODEL}")
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# 使用curl调用（避免requests SSL问题）
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payload_json = json.dumps(payload)
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cmd = [
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"curl", "-s", "-m", "120", "--noproxy", "*",
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"-X", "POST", url,
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"-H", f"Authorization: Bearer {API_KEY}",
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"-H", "Content-Type: application/json",
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"-d", payload_json
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]
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result = subprocess.run(cmd, capture_output=True, text=True, timeout=130)
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if result.returncode != 0:
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print(f" ✗ curl error: {result.stderr}")
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return None
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try:
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data = json.loads(result.stdout)
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except json.JSONDecodeError:
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print(f" ✗ JSON parse error: {result.stdout[:200]}")
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return None
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if "error" in data:
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print(f" ✗ API error: {data['error']}")
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return None
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# Seedream4 响应结构：data[0].url
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if "data" in data and len(data["data"]) > 0:
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img_url = data["data"][0].get("url", "")
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print(f" ✓ 生成成功: {img_url[:80]}...")
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return img_url
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print(f" ✗ 未找到图片URL. 响应: {json.dumps(data)[:300]}")
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return None
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def download_image(url, filepath):
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"""下载图片到指定路径"""
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Path(filepath).parent.mkdir(parents=True, exist_ok=True)
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print(f" ↓ 下载到 {filepath}")
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cmd = ["curl", "-s", "-m", "60", "-L", "--noproxy", "*", "-o", filepath, url]
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result = subprocess.run(cmd, capture_output=True, text=True, timeout=65)
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if result.returncode != 0:
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print(f" ✗ 下载失败: {result.stderr}")
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return False
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size = os.path.getsize(filepath) if os.path.exists(filepath) else 0
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print(f" ✓ 已保存 {size/1024:.0f}KB")
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return size > 1024 # 至少1KB
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def scale_to_1080(src_path, dst_path):
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"""1440x2560 → 1080x1920 等比缩放"""
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print(f" ⇄ 缩放 {src_path} → {dst_path}")
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cmd = [
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"sips", "-z", "1920", "1080",
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str(src_path),
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"--out", str(dst_path)
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]
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result = subprocess.run(cmd, capture_output=True, text=True)
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return result.returncode == 0
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def main():
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print("=" * 60)
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print("CHAR-004 诸葛风 · VA-05-001-R2 · 纯文生图")
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print(f"模型: {IMAGE_MODEL}")
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print(f"分辨率: 1440x2560 → 1080x1920")
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print(f"备选数: 4")
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print(f"策略: 全程纯文字 · 禁用图像参考")
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print("=" * 60)
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if not API_KEY:
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print("✗ 未找到JIMENG_API_KEY，退出")
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sys.exit(1)
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# ── 第一步：生成4张（锁服装身形） ──
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print("\n── 第一步：生成4张候选 ──")
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timestamp = time.strftime("%Y%m%d-%H%M%S")
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run_dir = JZAO_BASE / "D157-R2" / timestamp
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run_dir.mkdir(parents=True, exist_ok=True)
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candidates_dir = CANDIDATES_DIR
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candidates_dir.mkdir(parents=True, exist_ok=True)
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results = []
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seeds = [42, 137, 256, 399] # 不同seed产生不同变体
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for i, seed in enumerate(seeds):
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print(f"\n[{i+1}/4] 生成候选 {i+1} (seed={seed})")
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# 微调prompt增加面部变化
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variations = [
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"面部角度：正脸直视镜头",
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"面部角度：微微侧头，目光坚毅",
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"面部角度：略微仰视，眼神向上",
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"面部角度：3/4侧脸，侧视左前方",
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]
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full_prompt = f"{CHAR004_PROMPT} {variations[i]}"
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img_url = call_seedream(full_prompt, seed=seed)
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if not img_url:
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print(f" ✗ 候选 {i+1} 生成失败")
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results.append({"candidate": i+1, "status": "failed", "error": "API call failed"})
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continue
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# 保存原始1440×2560
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raw_name = f"CHAR-004-R2-candidate-{i+1:02d}-1440x2560.jpg"
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raw_path = run_dir / raw_name
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if not download_image(img_url, raw_path):
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results.append({"candidate": i+1, "status": "failed", "error": "download failed"})
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continue
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# 缩放至1080×1920
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scaled_name = f"CHAR-004-R2-candidate-{i+1:02d}-1080x1920.jpg"
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scaled_path = candidates_dir / scaled_name
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if not scale_to_1080(raw_path, scaled_path):
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results.append({"candidate": i+1, "status": "failed", "error": "scale failed"})
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continue
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results.append({
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"candidate": i+1,
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"status": "generated",
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"raw": str(raw_path),
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"scaled": str(scaled_path),
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"seed": seed
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})
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print(f" ✓ 候选 {i+1} 完成")
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time.sleep(2) # 避免请求过快
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# ── 汇总 ──
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print("\n── 生成汇总 ──")
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success = sum(1 for r in results if r["status"] == "generated")
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failed = len(results) - success
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print(f"成功: {success}/4")
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print(f"失败: {failed}/4")
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if failed > 0:
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for r in results:
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if r["status"] != "generated":
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print(f" ✗ 候选{r['candidate']}: {r.get('error', 'unknown')}")
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# 写入元数据
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meta = {
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"spec": "VA-05-001-R2",
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"asset_id": "CHAR-004-ZhugeFeng",
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"timestamp": timestamp,
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"model": IMAGE_MODEL,
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"resolution_raw": "1440x2560",
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"resolution_final": "1080x1920",
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"strategy": "pure_text_prompt_no_image_reference",
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"results": results
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}
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meta_path = candidates_dir / "generation-meta.json"
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with open(meta_path, "w") as f:
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json.dump(meta, f, ensure_ascii=False, indent=2)
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print(f"\n元数据已保存: {meta_path}")
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return 0 if success >= 4 else 1
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if __name__ == "__main__":
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sys.exit(main())
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