xsl
531dcb8279
4图×2发型×(3步数档+3分辨率档) 热数据对比，48/48成功，0 OOM，峰值20.6GB。 - benchmark_steps_res.py: 测试脚本(预热+正式取热数据) - benchmark_steps_res_report.py: 报告生成 - static/bench2_report.html: 对比报告 - static/bench2/: 48张结果图 结论: B维度 steps10→20 swap 3.0s→3.9s; C维度 res640比896省3s(comfy 4.3s vs 7.3s)
122 lines
5.4 KiB
Python
122 lines
5.4 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""swap步数 + 重绘分辨率 对比测试（热数据）。
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每个组合: 预热1次(丢弃) + 正式测1次(取热数据)。
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B维度: steps=10/15/20 (分辨率固定896)
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C维度: 分辨率=640/896/1024 (steps固定15)
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4图×2发型=8组 × 6档 × 2次(预热+正式) = 96次
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"""
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import base64
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import json
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import os
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import time
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from pathlib import Path
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import requests
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API = "http://127.0.0.1:8187/api/v1/debug/grow-timing"
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TOKEN = "dev-shared-secret-2026"
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OUT = Path("/home/ubuntu/hair/benchmark_out/bench2")
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OUT.mkdir(parents=True, exist_ok=True)
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IMGS = [
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("asdf", "/home/ubuntu/hair/image/asdf.jpg"),
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("qwer", "/home/ubuntu/hair/image/qwer.jpg"),
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("girl2", "/home/ubuntu/hair/image/girl_img/girl2.jpg"),
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("girl5", "/home/ubuntu/hair/image/girl_img/girl5.jpg"),
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]
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HAIRSTYLES = [(5, "wave", "波浪"), (3, "heart", "心形")]
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# B维度: swap步数对比 (分辨率固定896)
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B_STEPS = [10, 15, 20]
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# C维度: 重绘分辨率对比 (steps固定15)
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C_RES = [640, 896, 1024]
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def call(img_path, hair_num, webui_steps=None, redraw_max_side=None, save_grown=None):
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"""调调试接口。返回 dict。save_grown 非None时把结果图存到该路径。"""
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data = {"hair_style": str(hair_num)}
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if webui_steps is not None:
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data["webui_steps"] = str(webui_steps)
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if redraw_max_side is not None:
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data["redraw_max_side"] = str(redraw_max_side)
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t0 = time.perf_counter()
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try:
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with open(img_path, "rb") as f:
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r = requests.post(API, headers={"X-Internal-Token": TOKEN},
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files={"image_file": (os.path.basename(img_path), f, "image/jpeg")},
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data=data, timeout=300)
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wall = time.perf_counter() - t0
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j = r.json()
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if j.get("code") != 0:
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return {"ok": False, "error": j.get("message", "")[:100], "wall": wall}
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d = j["data"]
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hs = d["per_hairstyle"][0]
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if save_grown and hs.get("grown_b64"):
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b = hs["grown_b64"].split(",")[1] if "," in hs["grown_b64"] else hs["grown_b64"]
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with open(save_grown, "wb") as gf:
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gf.write(base64.b64decode(b))
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return {
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"ok": hs.get("ok", False), "wall": wall,
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"total_ms": d["total_ms"], "ctx_ms": d["extract_context_ms"],
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"mask_ms": hs.get("mask_ms"), "swap_ms": hs.get("swap_ms"),
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"blend_ms": hs.get("blend_ms"), "comfy_ms": hs.get("comfyui_redraw_ms"),
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"error": hs.get("error"),
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}
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except Exception as e:
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return {"ok": False, "error": str(e)[:100], "wall": time.perf_counter() - t0}
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def main():
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results = {"B_steps": [], "C_res": []}
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total_calls = len(IMGS) * len(HAIRSTYLES) * (len(B_STEPS) + len(C_RES)) * 2
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idx = 0
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# ===== B维度: swap步数对比 (分辨率固定896) =====
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print("\n===== B维度: swap步数对比 (分辨率=896) =====", flush=True)
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for steps in B_STEPS:
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print(f"\n--- steps={steps} ---", flush=True)
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for ilabel, ipath in IMGS:
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for hnum, hkey, hname in HAIRSTYLES:
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# 预热(丢弃)
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idx += 1
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print(f"[{idx}/{total_calls}] 预热 {ilabel}|{hname}|steps={steps}", flush=True)
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call(ipath, hnum, webui_steps=steps, redraw_max_side=896)
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# 正式(热数据)
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idx += 1
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save = OUT / f"B_steps{steps}_{ilabel}_{hkey}.jpg"
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print(f"[{idx}/{total_calls}] 正式 {ilabel}|{hname}|steps={steps}", flush=True)
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r = call(ipath, hnum, webui_steps=steps, redraw_max_side=896, save_grown=save)
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r["steps"] = steps; r["img"] = ilabel; r["hair"] = hkey; r["hair_name"] = hname
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r["grown_path"] = str(save) if r.get("ok") else None
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print(f" -> total={r.get('total_ms')}ms swap={r.get('swap_ms')}ms comfy={r.get('comfy_ms')}ms ok={r.get('ok')}", flush=True)
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results["B_steps"].append(r)
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# ===== C维度: 重绘分辨率对比 (steps固定15) =====
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print("\n===== C维度: 重绘分辨率对比 (steps=15) =====", flush=True)
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for res in C_RES:
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print(f"\n--- res={res} ---", flush=True)
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for ilabel, ipath in IMGS:
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for hnum, hkey, hname in HAIRSTYLES:
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idx += 1
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print(f"[{idx}/{total_calls}] 预热 {ilabel}|{hname}|res={res}", flush=True)
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call(ipath, hnum, webui_steps=15, redraw_max_side=res)
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idx += 1
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save = OUT / f"C_res{res}_{ilabel}_{hkey}.jpg"
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print(f"[{idx}/{total_calls}] 正式 {ilabel}|{hname}|res={res}", flush=True)
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r = call(ipath, hnum, webui_steps=15, redraw_max_side=res, save_grown=save)
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r["res"] = res; r["img"] = ilabel; r["hair"] = hkey; r["hair_name"] = hname
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r["grown_path"] = str(save) if r.get("ok") else None
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print(f" -> total={r.get('total_ms')}ms swap={r.get('swap_ms')}ms comfy={r.get('comfy_ms')}ms ok={r.get('ok')}", flush=True)
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results["C_res"].append(r)
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with open(OUT / "results.json", "w", encoding="utf-8") as f:
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json.dump(results, f, ensure_ascii=False, indent=2)
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ok = sum(1 for r in results["B_steps"] + results["C_res"] if r.get("ok"))
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print(f"\n✓ 完成: {ok}/{len(results['B_steps'])+len(results['C_res'])} 成功 -> {OUT/'results.json'}", flush=True)
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if __name__ == "__main__":
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main()
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