Files
hair/local_test/bench_quality.py
T
xsl b61ea6f33b feat(接口5): 生发机制对齐接口2 + 统一ComfyUI重绘提示词
接口5改造(生发机制与接口2一致,按性别分流):
- generate_hairline_pngs: 生发图来源从 _grow_from_texture(局部inpaint)
  改为按性别分流——female走 generate_grow_results_swap(swapHair+Flux整帧重绘),
  male走 generate_grow_results(ComfyUI add_hair)
- 新增参数 redraw_max_side/unet_name/v2_defaults(female路径透传)
- 接口5 handler 加 flux_model/redraw_max_side Form参数
- 保留接口5独有输出: 3档叠图(middle/high/low)/中心点/face_measure
- 已验证: female日志出现"接口2女 管线降分辨率max_side=640"+swap+Flux;
  male走add_hair.json; generate_grow_image=false正确跳过生发

统一ComfyUI重绘提示词:
- "填充遮罩区域的头发,皮肤加一点磨皮,再加一点美颜" → "填充遮罩区域的头发"
- 覆盖: _REDRAW_PROMPT/_DEFAULT_PROMPT常量 + app.py各接口Form默认 +
  工作流JSON节点60(add_hair/0716add-hair-api/hair_repaint) + 全部测试页输入框
2026-07-27 23:36:15 +08:00

70 lines
2.6 KiB
Python

#!/usr/bin/env python3
"""Generate result images at different step counts for quality comparison."""
import io, time
import requests
import numpy as np
from PIL import Image, ImageFilter
import app as A
COMFY = "http://127.0.0.1:8188"
MODEL = "flux2.0/flux-2-klein-9b-fp8.safetensors"
DTYPE = "fp8_e4m3fn_fast"
OUT = "output"
image = Image.open("用来重绘.jpg").convert("RGB")
mask_img = Image.open("用来重绘.png").convert("RGBA")
mask_data = np.max(np.array(mask_img), axis=2)
m = Image.fromarray(mask_data, mode="L")
if m.size != image.size:
m = m.resize(image.size, Image.LANCZOS)
m = m.filter(ImageFilter.GaussianBlur(radius=4))
alpha = Image.eval(m, lambda x: 255 - x)
r, g, b = image.split()
rgba = Image.merge("RGBA", (r, g, b, alpha))
buf = io.BytesIO(); rgba.save(buf, format="PNG"); buf.seek(0)
fname = requests.post(f"{COMFY}/upload/image",
files={"image": ("hair_input.png", buf, "image/png")}).json()["name"]
# fixed seed for fair comparison
SEED = 123456789
imgs = []
labels = []
for steps in [2, 3, 4, 6]:
wf = A.build_workflow(fname, "填充遮罩区域的头发", seed=SEED)
wf["16"]["inputs"]["unet_name"] = MODEL
wf["16"]["inputs"]["weight_dtype"] = DTYPE
wf["1"]["inputs"]["steps"] = steps
pid = requests.post(f"{COMFY}/prompt", json={"prompt": wf}).json()["prompt_id"]
t0 = time.time()
while True:
time.sleep(0.1)
h = requests.get(f"{COMFY}/history/{pid}").json()
if pid in h and "17" in h[pid].get("outputs", {}):
ts = {mm[0]: mm[1].get("timestamp") for mm in h[pid]["status"]["messages"]}
dur = (ts["execution_success"] - ts["execution_start"]) / 1000.0
info = h[pid]["outputs"]["17"]["images"][0]
data = requests.get(f"{COMFY}/view", params={
"filename": info["filename"], "subfolder": info.get("subfolder", ""),
"type": info.get("type", "output")}).content
im = Image.open(io.BytesIO(data)).convert("RGB")
imgs.append(im)
labels.append(f"steps={steps} {dur:.2f}s")
print(f"steps={steps}: {dur:.2f}s", flush=True)
break
# build side-by-side contact sheet
from PIL import ImageDraw
h0 = imgs[0].height
w0 = imgs[0].width
pad = 10
bar = 28
sheet = Image.new("RGB", (w0 * len(imgs) + pad * (len(imgs) + 1),
h0 + bar + pad * 2), (26, 26, 46))
d = ImageDraw.Draw(sheet)
for i, (im, lb) in enumerate(zip(imgs, labels)):
x = pad + i * (w0 + pad)
sheet.paste(im, (x, bar + pad))
d.text((x + 4, 6), lb, fill=(233, 69, 96))
sheet.save(f"{OUT}/compare_steps.png")
print("saved:", f"{OUT}/compare_steps.png", flush=True)