feat(接口2): ComfyUI重绘分辨率默认改为1024 + wave测试套件 + 报告统一部署
- hairline/service.py: _REDRAW_MAX_SIDE 默认 896→1024 逻辑: 输入图长边>1024 才缩到1024; ≤1024 原图分辨率直送(不放大) male路径_GROW_B_MAX_SIDE 已是1024,行为一致 - static/test_interface2.html: 分辨率下拉选项标签同步(默认1024/>1024才缩) - image/wave_test/: wave发型5档分辨率对比测试(21图×5档=105次,全成功) batch_test.py/gen_report.py/report-server-wave.service - image/reports/: 报告统一HTTP服务(单端口8850,路径区分/wave /v2 /v1) 含索引页index.html + report-server.service + 三报告软链接 - .gitignore: 补充 wave_test/out/ 及运行期文件忽略规则
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#!/usr/bin/env python3
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"""接口2 female wave发型 分辨率对比测试 v3: 21图 × 5档 = 105次。
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串行执行，记录耗时与成败，结果图按 图_档位 命名保存。支持断点续跑。
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"""
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import base64, csv, json, os, time, io
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import requests
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from PIL import Image
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API = "http://127.0.0.1:8187/api/v1/hair/grow"
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TOKEN = "dev-shared-secret-2026"
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TIMEOUT = 600
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OUT = "/home/ubuntu/hair/image/wave_test/out"
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PROGRESS = "/home/ubuntu/hair/image/wave_test/progress.json"
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IMG_DIR = "/home/ubuntu/hair/image"
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# 21张图：19张girl_img + asdf + qwer
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IMAGES = []
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for f in sorted(os.listdir(os.path.join(IMG_DIR, "girl_img"))):
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if f.lower().endswith((".jpg", ".jpeg", ".png")):
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IMAGES.append((os.path.splitext(f)[0], os.path.join(IMG_DIR, "girl_img", f)))
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IMAGES.append(("asdf", os.path.join(IMG_DIR, "asdf.jpg")))
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IMAGES.append(("qwer", os.path.join(IMG_DIR, "qwer.jpg")))
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# wave = female hair_style 5
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STYLE_IDX = 5
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# 5档: 原图(0) / 1024 / 896 / 768 / 640
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SIDES = [
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("origin", 0),
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("s1024", 1024),
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("s896", 896),
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("s768", 768),
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("s640", 640),
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]
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def load_progress():
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if os.path.exists(PROGRESS):
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try:
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return json.load(open(PROGRESS))
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except Exception:
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pass
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return {"done": [], "results": []}
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def save_progress(prog):
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json.dump(prog, open(PROGRESS, "w"), ensure_ascii=False, indent=1)
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def run_one(img_name, img_path, side_name, side_val):
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key = f"{img_name}_{side_name}"
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with open(img_path, "rb") as f:
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img_b64 = base64.b64encode(f.read()).decode()
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data = {
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"image_base64": "data:image/jpeg;base64," + img_b64,
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"gender": "female",
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"hair_style": str(STYLE_IDX),
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"redraw_max_side": str(side_val),
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}
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t0 = time.time()
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rec = {"key": key, "img": img_name, "side": side_name, "side_val": side_val,
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"ok": False, "elapsed": 0.0, "err": "", "out_w": 0, "out_h": 0, "bytes": 0}
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try:
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r = requests.post(API, data=data, headers={"X-Internal-Token": TOKEN}, timeout=TIMEOUT)
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rec["elapsed"] = round(time.time() - t0, 1)
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d = r.json()
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if d.get("code") != 0:
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rec["err"] = f"code={d.get('code')} {d.get('message','')}"[:200]
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return rec
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results = (d.get("data") or {}).get("results") or []
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if not results:
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rec["err"] = "空结果"
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return rec
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it = results[0]
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grown = it.get("grown_image_base64")
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if not grown:
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rec["err"] = "无生发图(重绘失败/OOM?)"
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return rec
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raw = base64.b64decode(grown)
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im = Image.open(io.BytesIO(raw))
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rec["out_w"], rec["out_h"] = im.size
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out_path = f"{OUT}/{key}.jpg"
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with open(out_path, "wb") as fo:
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fo.write(raw)
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rec["ok"] = True
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rec["bytes"] = len(raw)
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except requests.exceptions.Timeout:
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rec["elapsed"] = round(time.time() - t0, 1)
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rec["err"] = f"超时(>{TIMEOUT}s)"
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except Exception as e:
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rec["elapsed"] = round(time.time() - t0, 1)
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rec["err"] = f"{type(e).__name__}: {str(e)[:180]}"
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return rec
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def main():
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prog = load_progress()
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done_keys = set(prog["done"])
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total = len(IMAGES) * len(SIDES)
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print(f"=== 接口2 female wave 分辨率对比测试 v3 ===")
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print(f"矩阵: {len(IMAGES)}图 × {len(SIDES)}档 = {total} 次 (发型固定 wave)")
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print(f"已跳过 {len(done_keys)} 个已完成项\n")
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idx = 0
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for img_name, img_path in IMAGES:
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for side_name, side_val in SIDES:
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idx += 1
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key = f"{img_name}_{side_name}"
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if key in done_keys:
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print(f"[{idx}/{total}] ⏭ 跳过 {key}")
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continue
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print(f"[{idx}/{total}] ▶ {key} (side={side_val})...", end=" ", flush=True)
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rec = run_one(img_name, img_path, side_name, side_val)
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prog["results"].append(rec)
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prog["done"].append(key)
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save_progress(prog)
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if rec["ok"]:
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print(f"✅ {rec['elapsed']}s {rec['out_w']}x{rec['out_h']} ({rec['bytes']}B)")
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else:
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print(f"❌ {rec['elapsed']}s {rec['err']}")
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time.sleep(2)
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print("\n" + "=" * 70)
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print("汇总")
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print("=" * 70)
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write_report(prog["results"])
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print(f"\n结果图: {OUT}/")
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print(f"CSV: {OUT}/report.csv JSON: {OUT}/report.json")
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def write_report(results):
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with open(f"{OUT}/report.csv", "w", newline="") as f:
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w = csv.writer(f)
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w.writerow(["img", "side", "side_val", "ok", "elapsed_s", "out_w", "out_h", "bytes", "err"])
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for r in results:
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w.writerow([r["img"], r["side"], r["side_val"], r["ok"],
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r["elapsed"], r["out_w"], r["out_h"], r["bytes"], r["err"]])
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json.dump(results, open(f"{OUT}/report.json", "w"), ensure_ascii=False, indent=1)
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# 各档平均耗时
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print("\n--- 各档平均耗时（秒）---")
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for side_name, side_val in SIDES:
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ts = [r["elapsed"] for r in results if r["side"] == side_name and r["ok"]]
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if ts:
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avg = sum(ts) / len(ts)
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print(f" {side_name:8s} (={side_val:>4}): 平均 {avg:5.1f}s [{min(ts):.1f}~{max(ts):.1f}] 成功 {len(ts)}")
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if __name__ == "__main__":
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main()
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