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ubuntu3090
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|---|---|---|---|
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74ccab0ff8 |
@@ -0,0 +1,327 @@
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||||
{
|
||||
"16": {
|
||||
"class_type": "UNETLoader",
|
||||
"inputs": {
|
||||
"unet_name": "flux-2-klein-4b-fp8.safetensors",
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"weight_dtype": "fp8_e4m3fn_fast"
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||||
}
|
||||
},
|
||||
"3": {
|
||||
"class_type": "VAELoader",
|
||||
"inputs": {
|
||||
"vae_name": "flux2-vae.safetensors"
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||||
}
|
||||
},
|
||||
"61": {
|
||||
"class_type": "CLIPLoader",
|
||||
"inputs": {
|
||||
"clip_name": "qwen_3_4b.safetensors",
|
||||
"type": "flux2",
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"device": "cpu"
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}
|
||||
},
|
||||
"26": {
|
||||
"class_type": "LoadImage",
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||||
"inputs": {
|
||||
"image": "placeholder.png"
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||||
}
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},
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"60": {
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"class_type": "JjkText",
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"inputs": {
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"text": "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜"
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}
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},
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||||
"22": {
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||||
"class_type": "CLIPTextEncode",
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||||
"inputs": {
|
||||
"clip": [
|
||||
"61",
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||||
0
|
||||
],
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||||
"text": [
|
||||
"60",
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||||
0
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||||
]
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||||
}
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||||
},
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||||
"31": {
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||||
"class_type": "easy imageSize",
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"inputs": {
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"image": [
|
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"26",
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||||
0
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||||
]
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}
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},
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"33": {
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"class_type": "Mask Fill Holes",
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"inputs": {
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"masks": [
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"26",
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||||
1
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||||
]
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||||
}
|
||||
},
|
||||
"36": {
|
||||
"class_type": "Convert Masks to Images",
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||||
"inputs": {
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||||
"masks": [
|
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"33",
|
||||
0
|
||||
]
|
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}
|
||||
},
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||||
"39": {
|
||||
"class_type": "ImageScale",
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||||
"inputs": {
|
||||
"image": [
|
||||
"36",
|
||||
0
|
||||
],
|
||||
"upscale_method": "nearest-exact",
|
||||
"width": [
|
||||
"31",
|
||||
0
|
||||
],
|
||||
"height": [
|
||||
"31",
|
||||
1
|
||||
],
|
||||
"crop": "disabled"
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||||
}
|
||||
},
|
||||
"37": {
|
||||
"class_type": "Image To Mask",
|
||||
"inputs": {
|
||||
"image": [
|
||||
"39",
|
||||
0
|
||||
],
|
||||
"method": "intensity"
|
||||
}
|
||||
},
|
||||
"32": {
|
||||
"class_type": "LayerUtility: ImageScaleByAspectRatio V2",
|
||||
"inputs": {
|
||||
"image": [
|
||||
"26",
|
||||
0
|
||||
],
|
||||
"mask": [
|
||||
"37",
|
||||
0
|
||||
],
|
||||
"aspect_ratio": "custom",
|
||||
"proportional_width": [
|
||||
"31",
|
||||
0
|
||||
],
|
||||
"proportional_height": [
|
||||
"31",
|
||||
1
|
||||
],
|
||||
"fit": "letterbox",
|
||||
"method": "lanczos",
|
||||
"round_to_multiple": "8",
|
||||
"scale_to_side": "None",
|
||||
"scale_to_length": 1024,
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"background_color": "#000000"
|
||||
}
|
||||
},
|
||||
"44": {
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||||
"class_type": "ImageAndMaskPreview",
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"inputs": {
|
||||
"image": [
|
||||
"32",
|
||||
0
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||||
],
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||||
"mask": [
|
||||
"32",
|
||||
1
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||||
],
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||||
"mask_opacity": 1,
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||||
"mask_color": "FFFF00",
|
||||
"pass_through": true
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}
|
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},
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"14": {
|
||||
"class_type": "GetImageSize+",
|
||||
"inputs": {
|
||||
"image": [
|
||||
"44",
|
||||
0
|
||||
]
|
||||
}
|
||||
},
|
||||
"13": {
|
||||
"class_type": "VAEEncode",
|
||||
"inputs": {
|
||||
"pixels": [
|
||||
"44",
|
||||
0
|
||||
],
|
||||
"vae": [
|
||||
"3",
|
||||
0
|
||||
]
|
||||
}
|
||||
},
|
||||
"2": {
|
||||
"class_type": "ModelSamplingFlux",
|
||||
"inputs": {
|
||||
"model": [
|
||||
"16",
|
||||
0
|
||||
],
|
||||
"max_shift": 1.15,
|
||||
"base_shift": 0.5,
|
||||
"width": [
|
||||
"14",
|
||||
0
|
||||
],
|
||||
"height": [
|
||||
"14",
|
||||
1
|
||||
]
|
||||
}
|
||||
},
|
||||
"19": {
|
||||
"class_type": "FluxGuidance",
|
||||
"inputs": {
|
||||
"conditioning": [
|
||||
"22",
|
||||
0
|
||||
],
|
||||
"guidance": 1
|
||||
}
|
||||
},
|
||||
"5": {
|
||||
"class_type": "ReferenceLatent",
|
||||
"inputs": {
|
||||
"conditioning": [
|
||||
"19",
|
||||
0
|
||||
],
|
||||
"latent": [
|
||||
"13",
|
||||
0
|
||||
]
|
||||
}
|
||||
},
|
||||
"7": {
|
||||
"class_type": "EmptySD3LatentImage",
|
||||
"inputs": {
|
||||
"width": [
|
||||
"14",
|
||||
0
|
||||
],
|
||||
"height": [
|
||||
"14",
|
||||
1
|
||||
],
|
||||
"batch_size": 1
|
||||
}
|
||||
},
|
||||
"1": {
|
||||
"class_type": "BasicScheduler",
|
||||
"inputs": {
|
||||
"model": [
|
||||
"2",
|
||||
0
|
||||
],
|
||||
"scheduler": "simple",
|
||||
"steps": 4,
|
||||
"denoise": 1
|
||||
}
|
||||
},
|
||||
"20": {
|
||||
"class_type": "BasicGuider",
|
||||
"inputs": {
|
||||
"model": [
|
||||
"2",
|
||||
0
|
||||
],
|
||||
"conditioning": [
|
||||
"5",
|
||||
0
|
||||
]
|
||||
}
|
||||
},
|
||||
"6": {
|
||||
"class_type": "RandomNoise",
|
||||
"inputs": {
|
||||
"noise_seed": 0
|
||||
}
|
||||
},
|
||||
"8": {
|
||||
"class_type": "KSamplerSelect",
|
||||
"inputs": {
|
||||
"sampler_name": "euler"
|
||||
}
|
||||
},
|
||||
"9": {
|
||||
"class_type": "SamplerCustomAdvanced",
|
||||
"inputs": {
|
||||
"noise": [
|
||||
"6",
|
||||
0
|
||||
],
|
||||
"guider": [
|
||||
"20",
|
||||
0
|
||||
],
|
||||
"sampler": [
|
||||
"8",
|
||||
0
|
||||
],
|
||||
"sigmas": [
|
||||
"1",
|
||||
0
|
||||
],
|
||||
"latent_image": [
|
||||
"7",
|
||||
0
|
||||
]
|
||||
}
|
||||
},
|
||||
"10": {
|
||||
"class_type": "VAEDecode",
|
||||
"inputs": {
|
||||
"samples": [
|
||||
"9",
|
||||
0
|
||||
],
|
||||
"vae": [
|
||||
"3",
|
||||
0
|
||||
]
|
||||
}
|
||||
},
|
||||
"62": {
|
||||
"class_type": "ColorMatch",
|
||||
"inputs": {
|
||||
"image_ref": [
|
||||
"26",
|
||||
0
|
||||
],
|
||||
"image_target": [
|
||||
"10",
|
||||
0
|
||||
],
|
||||
"method": "mkl",
|
||||
"strength": 1,
|
||||
"multithread": true
|
||||
}
|
||||
},
|
||||
"17": {
|
||||
"class_type": "SaveImage",
|
||||
"inputs": {
|
||||
"images": [
|
||||
"62",
|
||||
0
|
||||
],
|
||||
"filename_prefix": "hair_inpaint"
|
||||
}
|
||||
}
|
||||
}
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+1
-1
File diff suppressed because one or more lines are too long
+6
-6
@@ -2,7 +2,7 @@
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||||
"1": {
|
||||
"inputs": {
|
||||
"scheduler": "simple",
|
||||
"steps": 6,
|
||||
"steps": 4,
|
||||
"denoise": 1,
|
||||
"model": [
|
||||
"2",
|
||||
@@ -170,8 +170,8 @@
|
||||
},
|
||||
"16": {
|
||||
"inputs": {
|
||||
"unet_name": "flux2.0/flux-2-klein-9b-fp8.safetensors",
|
||||
"weight_dtype": "fp8_e4m3fn"
|
||||
"unet_name": "flux-2-klein-4b-fp8.safetensors",
|
||||
"weight_dtype": "fp8_e4m3fn_fast"
|
||||
},
|
||||
"class_type": "UNETLoader",
|
||||
"_meta": {
|
||||
@@ -410,7 +410,7 @@
|
||||
},
|
||||
"60": {
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||||
"inputs": {
|
||||
"text": "补充遮罩区补充遮罩区域内的头发，头发填满遮罩区域。发际线往下挡住额头"
|
||||
"text": "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜"
|
||||
},
|
||||
"class_type": "JjkText",
|
||||
"_meta": {
|
||||
@@ -419,9 +419,9 @@
|
||||
},
|
||||
"61": {
|
||||
"inputs": {
|
||||
"clip_name": "qwen_3_8b_fp8mixed.safetensors",
|
||||
"clip_name": "qwen_3_4b.safetensors",
|
||||
"type": "flux2",
|
||||
"device": "default"
|
||||
"device": "cpu"
|
||||
},
|
||||
"class_type": "CLIPLoader",
|
||||
"_meta": {
|
||||
|
||||
@@ -138,7 +138,47 @@ app = FastAPI(
|
||||
app.mount("/static", StaticFiles(directory="static"), name="static")
|
||||
|
||||
# 不校验鉴权的路径前缀（供网关探测 / 文档 / 静态）
|
||||
_AUTH_EXEMPT = ("/health", "/docs", "/openapi.json", "/redoc", "/static", "/api/v1/debug")
|
||||
_AUTH_EXEMPT = ("/health", "/docs", "/openapi.json", "/redoc", "/static",
|
||||
"/api/v1/debug", "/api/v1/redraw",
|
||||
"/api/swapHair", "/hairColor")
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# change_hair 代理路由（解决 CORS 问题）
|
||||
# ---------------------------------------------------------------------------
|
||||
_CHANGE_HAIR_BASE = "http://127.0.0.1:8801"
|
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|
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|
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@app.post("/api/swapHair/v1", tags=["change_hair"])
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async def proxy_swap_hair(request: Request):
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"""代理转发到 change_hair /api/swapHair/v1（换发型）"""
|
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try:
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import httpx
|
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body = await request.body()
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async with httpx.AsyncClient(timeout=300.0) as client:
|
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resp = await client.post(f"{_CHANGE_HAIR_BASE}/api/swapHair/v1",
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content=body,
|
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headers={"Content-Type": "application/json"})
|
||||
return JSONResponse(content=resp.json(), status_code=resp.status_code)
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except Exception as e:
|
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logger.exception("代理 swapHair 失败")
|
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return err(1007, f"换发型服务异常：{e}")
|
||||
|
||||
|
||||
@app.post("/hairColor/v2", tags=["change_hair"])
|
||||
async def proxy_hair_color(request: Request):
|
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"""代理转发到 change_hair /hairColor/v2（换发色）"""
|
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try:
|
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import httpx
|
||||
body = await request.body()
|
||||
async with httpx.AsyncClient(timeout=300.0) as client:
|
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resp = await client.post(f"{_CHANGE_HAIR_BASE}/hairColor/v2",
|
||||
content=body,
|
||||
headers={"Content-Type": "application/json"})
|
||||
return JSONResponse(content=resp.json(), status_code=resp.status_code)
|
||||
except Exception as e:
|
||||
logger.exception("代理 hairColor 失败")
|
||||
return err(1007, f"换发色服务异常：{e}")
|
||||
|
||||
|
||||
@app.middleware("http")
|
||||
@@ -361,21 +401,36 @@ def _run_face_measure_data(image, variant="v1"):
|
||||
logger.warning("头发/耳朵分割失败，回退方案A：%s", seg_e)
|
||||
|
||||
result = measure_face(landmarks, hair_mask, w, h, head_pose=head_pose)
|
||||
discarded = result.hairline_discarded
|
||||
data = result.to_response()
|
||||
vd = result.vertical
|
||||
if variant == "v6":
|
||||
vd = result.vertical
|
||||
base_px = vd["upper_court_px"] + vd["middle_court_px"] + vd["lower_court_px"]
|
||||
# 接口6 是三庭：去掉顶庭相关字段（top_court_cm / ratios.top_court / landmarks.hair_top）
|
||||
data["four_courts"]["ratios"] = {
|
||||
"upper_court": round(vd["upper_court_px"] / base_px, 3),
|
||||
"middle_court": round(vd["middle_court_px"] / base_px, 3),
|
||||
"lower_court": round(vd["lower_court_px"] / base_px, 3),
|
||||
}
|
||||
data["four_courts"].pop("top_court_cm", None)
|
||||
data["face_total_height_cm"] = round(
|
||||
result.upper_cm + result.middle_cm + result.lower_cm, 2)
|
||||
# 注：landmarks.hair_top 保留返回（供前端/下游定位头顶），但顶庭数值、
|
||||
# 占比、标注图仍按三庭处理，显示效果不变。
|
||||
if discarded:
|
||||
# 发际线弃用：接口6 的上庭也依赖发际线，一并置 null；只保留中/下庭。
|
||||
base_px = vd["middle_court_px"] + vd["lower_court_px"]
|
||||
data["four_courts"]["upper_court_cm"] = None
|
||||
data["four_courts"]["ratios"] = {
|
||||
"upper_court": None,
|
||||
"middle_court": round(vd["middle_court_px"] / base_px, 3),
|
||||
"lower_court": round(vd["lower_court_px"] / base_px, 3),
|
||||
}
|
||||
data["four_courts"].pop("top_court_cm", None)
|
||||
data["face_total_height_cm"] = round(
|
||||
result.middle_cm + result.lower_cm, 2)
|
||||
data["landmarks"]["hairline"] = None
|
||||
else:
|
||||
base_px = vd["upper_court_px"] + vd["middle_court_px"] + vd["lower_court_px"]
|
||||
# 接口6 是三庭：去掉顶庭相关字段（top_court_cm / ratios.top_court / landmarks.hair_top）
|
||||
data["four_courts"]["ratios"] = {
|
||||
"upper_court": round(vd["upper_court_px"] / base_px, 3),
|
||||
"middle_court": round(vd["middle_court_px"] / base_px, 3),
|
||||
"lower_court": round(vd["lower_court_px"] / base_px, 3),
|
||||
}
|
||||
data["four_courts"].pop("top_court_cm", None)
|
||||
data["face_total_height_cm"] = round(
|
||||
result.upper_cm + result.middle_cm + result.lower_cm, 2)
|
||||
# 注：landmarks.hair_top 保留返回（供前端/下游定位头顶），但顶庭数值、
|
||||
# 占比、标注图仍按三庭处理，显示效果不变。
|
||||
|
||||
# 七眼段宽度（cm）。eye1=左耳外段 eye2=左脸颊 eye3=左眼 eye4=两眼间距 eye5=右眼 eye6=右脸颊 eye7=右耳外段。
|
||||
# eye2~eye6（5段）只用内部分点，接口1/6 共用；eye1/eye7 需耳朵分割端线，仅接口1 有。
|
||||
@@ -390,11 +445,14 @@ def _run_face_measure_data(image, variant="v1"):
|
||||
data["seven_eyes"][f"eye{i + 2}"] = (
|
||||
None if (a is None or b is None) else round((b - a) / pc, 2))
|
||||
if variant != "v6":
|
||||
# 接口1 额外算 eye1/eye7（左/右耳外段），需耳朵分割端线
|
||||
# 接口1 额外算 eye1/eye7（左/右耳外段），需耳朵分割端线。
|
||||
# 竖向范围：发际线弃用时用眉心做上界（hair_top 不可靠），否则用头顶。
|
||||
from face_analysis.annotation import _ear_edges_from_mask
|
||||
top_y = (vd["brow_center"][1] if discarded
|
||||
else vd["hair_top"][1])
|
||||
head_l, head_r = _ear_edges_from_mask(
|
||||
ear_mask, hair_mask,
|
||||
result.vertical["hair_top"][1], result.vertical["chin_tip"][1],
|
||||
top_y, vd["chin_tip"][1],
|
||||
lcx, rcx, (lcx + rcx) / 2)
|
||||
data["seven_eyes"]["eye1"] = (
|
||||
None if (head_l is None) else round((lcx - head_l) / pc, 2))
|
||||
@@ -469,7 +527,7 @@ async def _face_measure_impl(image_file, image_url, image_base64, variant="v1"):
|
||||
**标注图片 UI 规范**（真实版本生效）：
|
||||
- 字体/线条/箭头颜色：`#FFFFFF 100%`，透明底
|
||||
- 字号/线宽/虚线/箭头按图片短边自适应缩放
|
||||
- 四庭数值（名+数值两行，不带 cm）在图片**左侧**呈现，七眼段宽**上下穿插**展示，底部标「单位cm」
|
||||
- 四庭（名 + 数值带cm + 百分比 三行）在图片**左侧**呈现，七眼段宽**上下穿插**展示（数值带cm，下方另起一行标占头宽百分比）
|
||||
- 横线/竖线渐变消失并略超出端点；段宽/庭高用虚线 + 实心三角双箭头标示
|
||||
- 竖线含人头最左/最右端线（取自头发分割轮廓），共 8 线 7 段
|
||||
""",
|
||||
@@ -574,7 +632,7 @@ async def face_measure(
|
||||
**标注图片 UI 规范**（真实版本生效）：
|
||||
- 字体/线条/箭头颜色：`#FFFFFF 100%`，透明底
|
||||
- 字号/线宽/虚线/箭头按图片短边自适应缩放
|
||||
- 三庭数值（名+数值两行，不带 cm）在图片**左侧**呈现，七眼段宽**上下穿插**展示，底部标「单位cm」
|
||||
- 三庭（名 + 数值带cm + 百分比 三行）在图片**左侧**呈现，七眼段宽**上下穿插**展示（数值带cm，下方另起一行标占头宽百分比）
|
||||
- 段宽/庭高用虚线 + 实心三角双箭头标示
|
||||
""",
|
||||
responses={
|
||||
@@ -717,7 +775,7 @@ async def hair_grow(
|
||||
hair_style: Optional[str] = Form(default=None, description="发型序号逗号分隔（必填），如 1,2,3。female:1-5 male:1-4"),
|
||||
beauty_enabled: bool = Form(default=False, description="是否开启美颜（本期不生效）"),
|
||||
use_mask: bool = Form(default=True, description="是否启用 inpaint 遮罩（测试对比用）。false 时用干净原图生成（空遮罩，不烧模板线）"),
|
||||
prompt: str = Form(default="补充遮罩区域的头发，加一点美颜", description="ComfyUI 提示词，会替换工作流节点60的文本"),
|
||||
prompt: str = Form(default="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜", description="ComfyUI 提示词，会替换工作流节点60的文本"),
|
||||
):
|
||||
# 1. gender 必填校验（非法/缺失 → 1004）
|
||||
if gender not in ("male", "female"):
|
||||
@@ -770,117 +828,15 @@ async def hair_grow(
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# 接口 7：C 端生发 v2（add_hair2.json 工作流）
|
||||
# 接口 7：C 端生发 v2 —— 已弃用（add_hair2.json 用 Klein-9b 大模型，会把常驻的
|
||||
# Klein-4b/Flux 挤出显存，导致接口2/3/5 耗时抖动；且业务已不再调用）。
|
||||
# 保留路由返回明确错误，避免老客户端拿到裸 404。
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
_WORKFLOW2_PATH = os.path.join(os.path.dirname(__file__), "add_hair2.json")
|
||||
|
||||
|
||||
@app.post(
|
||||
"/api/v1/hair/grow-v2",
|
||||
summary="接口7 C端生发 v2（add_hair2 工作流）",
|
||||
tags=["生发"],
|
||||
description=f"""
|
||||
输入用户正面照 + **性别** + **发型序号**，使用 add_hair2.json 工作流生成指定发际线类型的预览图与生发图。
|
||||
功能与接口2 完全一致，仅 ComfyUI 工作流不同。
|
||||
|
||||
{_image_fields_desc}
|
||||
|
||||
图片同时支持 `multipart/form-data` 文件上传（字段名 `image_file`）。
|
||||
|
||||
---
|
||||
|
||||
- **gender**（必填）：`male` / `female`。决定返回的贴图集合（female 5 张 / male 4 张）。
|
||||
非法或缺失返回 `1004`。
|
||||
- **hair_style**（必填）：`int`，发型序号。`female`：1=ellipse, 2=flower, 3=heart, 4=straight, 5=wave；
|
||||
`male`：1=ellipse, 2=inverse_arc, 3=m, 4=straight。越界返回 `1007`。
|
||||
- **beauty_enabled**：本期保留但不生效。
|
||||
|
||||
`hairline_type` 取值：`ellipse` / `flower` / `heart` / `straight` / `wave`（female），
|
||||
`ellipse` / `m` / `straight` / `inverse_arc`（male）。
|
||||
""",
|
||||
responses={
|
||||
200: {
|
||||
"description": "成功",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"example": {
|
||||
"code": 0,
|
||||
"message": "success",
|
||||
"request_id": "mock-request-id",
|
||||
"data": {
|
||||
"results": [
|
||||
{"image_base64": "iVBORw0KGgo...", "hairline_type": "ellipse", "order": 1},
|
||||
]
|
||||
},
|
||||
}
|
||||
}
|
||||
},
|
||||
},
|
||||
400: {
|
||||
"description": "参数错误 / 图片识别失败",
|
||||
"content": {
|
||||
"application/json": {
|
||||
"examples": {
|
||||
"图片参数错误": {"value": {"code": 1007, "message": "图片参数错误：必须且只能传 image_file / image_url / image_base64 其中一个", "request_id": "x", "data": None}},
|
||||
"非正面照": {"value": {"code": 1003, "message": "角度问题，请上传正面照", "request_id": "x", "data": None}},
|
||||
}
|
||||
}
|
||||
},
|
||||
},
|
||||
},
|
||||
)
|
||||
async def hair_grow_v2(
|
||||
image_file: Optional[UploadFile] = File(default=None, description="上传图片文件（JPG/PNG）"),
|
||||
image_url: Optional[str] = Form(default=None, description="图片 URL"),
|
||||
image_base64: Optional[str] = Form(default=None, description="图片 base64（需带 data:image/...;base64, 前缀）"),
|
||||
gender: Optional[str] = Form(default=None, description="性别 male/female（必填）"),
|
||||
hair_style: Optional[str] = Form(default=None, description="发型序号逗号分隔（必填），如 1,2,3。female:1-5 male:1-4"),
|
||||
beauty_enabled: bool = Form(default=False, description="是否开启美颜（本期不生效）"),
|
||||
use_mask: bool = Form(default=True, description="是否启用 inpaint 遮罩（测试对比用）。false 时用干净原图生成（空遮罩，不烧模板线）"),
|
||||
prompt: str = Form(default="补充遮罩区域的头发，加一点美颜", description="ComfyUI 提示词，会替换工作流节点60的文本"),
|
||||
):
|
||||
# 1. gender 必填校验（非法/缺失 → 1004）
|
||||
if gender not in ("male", "female"):
|
||||
return err(1004, "gender 必填且只能为 male / female")
|
||||
|
||||
# 2. hair_style 必填校验（解析逗号分隔，越界 → 1007）
|
||||
max_styles = {"female": 5, "male": 4}[gender]
|
||||
hair_styles = _parse_hair_styles(hair_style, max_styles)
|
||||
if hair_styles is None:
|
||||
return err(1007, f"hair_style 必填且为 1..{max_styles} 的整数（逗号分隔），收到 {hair_style!r}")
|
||||
|
||||
# 3. 三选一取图
|
||||
raw, e = await resolve_image_bytes(image_file, image_url, image_base64)
|
||||
if e is not None:
|
||||
return e
|
||||
|
||||
image = cv2.imdecode(np.frombuffer(raw, np.uint8), cv2.IMREAD_COLOR)
|
||||
if image is None:
|
||||
return err(1008, "图片格式不支持（仅 JPG / PNG）")
|
||||
|
||||
try:
|
||||
from fastapi.concurrency import run_in_threadpool
|
||||
from hairline.service import generate_grow_results
|
||||
|
||||
# 预览 + 生发(ComfyUI) 都是阻塞且较慢，放线程池避免卡住事件循环
|
||||
items = await run_in_threadpool(generate_grow_results, image, gender, use_mask, prompt, hair_styles, _WORKFLOW2_PATH)
|
||||
if items is None:
|
||||
return err(1001, "无法识别人像")
|
||||
|
||||
results = []
|
||||
for p in items:
|
||||
results.append({
|
||||
"image_base64": _jpg_b64(p["image_bgr"]), # 预览图 JPG
|
||||
"grown_image_base64": (_png_to_jpg_b64(p["grown_png"]) # 生发图 JPG
|
||||
if p["grown_png"] else None),
|
||||
"hairline_type": p["hairline_type"],
|
||||
"order": p["order"],
|
||||
})
|
||||
return ok({"results": results})
|
||||
except Exception as ex: # noqa: BLE001
|
||||
logger.exception("接口7 处理异常")
|
||||
return err(1007, f"处理失败：{ex}")
|
||||
@app.post("/api/v1/hair/grow-v2", include_in_schema=False, deprecated=True)
|
||||
async def hair_grow_v2():
|
||||
"""接口7 已弃用：请改用 /api/v1/hair/grow（接口2）。"""
|
||||
return err(1007, "接口7（/api/v1/hair/grow-v2）已弃用，请使用 /api/v1/hair/grow")
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
@@ -930,7 +886,7 @@ async def hair_grow_b(
|
||||
marked_image_url: Optional[str] = Form(default=None, description="划线图片 URL"),
|
||||
marked_image_base64: Optional[str] = Form(default=None, description="划线图片 base64"),
|
||||
use_mask: bool = Form(default=True, description="是否画发际线（测试对比用）。false 时跳过划线检测、直接送划线图"),
|
||||
prompt: str = Form(default="补充遮罩区域的头发，加一点美颜", description="ComfyUI 提示词，会替换工作流节点60的文本"),
|
||||
prompt: str = Form(default="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜", description="ComfyUI 提示词，会替换工作流节点60的文本"),
|
||||
):
|
||||
# 划线图三选一取图（只需这一张）
|
||||
marked_raw, e = await resolve_image_bytes(marked_image_file, marked_image_url, marked_image_base64)
|
||||
@@ -1061,6 +1017,8 @@ async def face_features(
|
||||
`female`：1=ellipse,2=flower,3=heart,4=straight,5=wave；`male`：1=ellipse,2=inverse_arc,3=m,4=straight。
|
||||
- 可选 `use_mask` / `prompt`：同接口2 的生发控制参数。
|
||||
注：生发黑模板固定取 `hairline_texture_black/`（middle 档），即三档叠图分别用各自贴图、但生发目标固定 middle。
|
||||
- 可选 `generate_grow_image`（默认 `true`）：是否生成生发效果图（ComfyUI 生发，全流程最耗时）。
|
||||
`false` 时跳过生发，各发型 `grown_image_*` 恒为 `null`，仅返回三档发际线叠图与中心点，大幅降低耗时。
|
||||
|
||||
**返回说明**：
|
||||
|
||||
@@ -1138,7 +1096,8 @@ async def hairline_generate(
|
||||
gender: Optional[str] = Form(default=None, description="性别 male/female（必填）"),
|
||||
hair_style: Optional[str] = Form(default=None, description="发型序号逗号分隔（必填，如 1,2,3）。female:1-5 male:1-4"),
|
||||
use_mask: bool = Form(default=True, description="生发是否启用 inpaint 遮罩（同接口2，测试对比用）"),
|
||||
prompt: str = Form(default="补充遮罩区域的头发，加一点美颜", description="ComfyUI 提示词（同接口2），会替换工作流节点60的文本"),
|
||||
prompt: str = Form(default="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜", description="ComfyUI 提示词（同接口2），会替换工作流节点60的文本"),
|
||||
generate_grow_image: bool = Form(default=True, description="是否生成生发效果图（ComfyUI 生发，最耗时）。默认 true 出图；false 时跳过生发，各发型 grown_image 恒为 null，仅返回三档发际线叠图与中心点"),
|
||||
):
|
||||
if gender not in ("male", "female"):
|
||||
return err(1004, "gender 必填且只能为 male / female")
|
||||
@@ -1162,7 +1121,8 @@ async def hairline_generate(
|
||||
from hairline.service import generate_hairline_pngs
|
||||
|
||||
res = await run_in_threadpool(
|
||||
generate_hairline_pngs, image, gender, hair_styles, use_mask, prompt)
|
||||
generate_hairline_pngs, image, gender, hair_styles, use_mask, prompt,
|
||||
generate_grow_image=generate_grow_image)
|
||||
if res is None:
|
||||
return err(1001, "无法识别人像")
|
||||
|
||||
@@ -1530,7 +1490,7 @@ async def hairline_grow_v2(
|
||||
inpainting_fill: int = Form(default=1, description="change_hair服务端重绘填充：0=保留原图 | 1=噪声 | 2=纯色 | 3=潜变量。默认 1"),
|
||||
mask_blur: int = Form(default=11, description="change_hair服务端遮罩边缘模糊像素，默认 11"),
|
||||
mask_dilate_scale: float = Form(default=1.0, description="change_hair服务端遮罩膨胀缩放，默认 1.0"),
|
||||
comfyui_prompt: Optional[str] = Form(default=None, description="Flux-2 重绘提示词，None 用默认「补充遮罩区域的头发，加一点美颜」"),
|
||||
comfyui_prompt: Optional[str] = Form(default=None, description="Flux-2 重绘提示词，None 用默认「填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜」"),
|
||||
beauty_alpha: float = Form(default=0.6, description="redraw_band 版 band 外的全脸美颜融入强度（0=band外无美颜纯用final，1≈整帧版），默认 0.6"),
|
||||
band_lo_mult: float = Form(default=0.5, description="重绘带外推倍率下限（相对 hairline_push_cm，内轮廓=0×、原外推线=1.0×），默认 0.5"),
|
||||
band_hi_mult: float = Form(default=1.5, description="重绘带外推倍率上限（相对 hairline_push_cm），默认 1.5"),
|
||||
@@ -1677,6 +1637,42 @@ async def hairline_grow_v2_final_v2(
|
||||
return await _run_v2_final(image_file, image_url, image_base64, hairline_id, "接口12finalv2")
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# 重绘端点（替代 local_test /api/generate）
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
@app.post(
|
||||
"/api/v1/redraw",
|
||||
summary="ComfyUI 重绘",
|
||||
tags=["重绘"],
|
||||
description="""
|
||||
传入人物图片 + 遮罩图片，直接调 ComfyUI（0716add-hair 工作流）执行局部重绘。
|
||||
替代原 local_test :8899 的 /api/generate 接口。
|
||||
|
||||
**遮罩图片格式**：支持红色遮罩(R=255)、白色遮罩(R=G=B=255)、Alpha遮罩(A=255)，服务取所有通道最大值。
|
||||
**遮罩区域**表示需要重绘的部分，非遮罩区域保持原图不变。
|
||||
""",
|
||||
)
|
||||
async def api_redraw(
|
||||
image_file: UploadFile = File(..., description="人物图片（JPG/PNG）"),
|
||||
mask_file: UploadFile = File(..., description="遮罩图片（PNG，支持红/白/alpha 格式）"),
|
||||
prompt: str = Form(default="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜",
|
||||
description="ComfyUI 提示词"),
|
||||
):
|
||||
image_bytes = await image_file.read()
|
||||
mask_bytes = await mask_file.read()
|
||||
from fastapi.concurrency import run_in_threadpool
|
||||
from hairline.redraw import run_redraw
|
||||
try:
|
||||
png_bytes = await run_in_threadpool(
|
||||
run_redraw, image_bytes, mask_bytes, prompt)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("重绘失败: %s", e)
|
||||
return err(500, f"重绘失败: {e}")
|
||||
b64 = base64.b64encode(png_bytes).decode()
|
||||
return ok({"image_base64": f"data:image/png;base64,{b64}"})
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# 调试：下载后端日志（接口11 遮罩计算全过程）
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
@@ -0,0 +1,15 @@
|
||||
[Unit]
|
||||
Description=ComfyUI (127.0.0.1:8188)
|
||||
After=network-online.target
|
||||
Wants=network-online.target
|
||||
|
||||
[Service]
|
||||
Type=simple
|
||||
User=ubuntu
|
||||
WorkingDirectory=/home/ubuntu/ComfyUI
|
||||
ExecStart=/home/ubuntu/ComfyUI/venv/bin/python main.py --listen 127.0.0.1 --port 8188 --cache-classic --fast
|
||||
Restart=on-failure
|
||||
RestartSec=5
|
||||
|
||||
[Install]
|
||||
WantedBy=multi-user.target
|
||||
@@ -0,0 +1,177 @@
|
||||
# 接口3 B端生发 — 实现文档
|
||||
|
||||
> 文档日期：2026-07-18
|
||||
|
||||
---
|
||||
|
||||
## 一、接口概述
|
||||
|
||||
**接口3** 是 B端（医生/操作端）生发接口。医生在用户照片上手动用马克笔画出发际线后，只需上传这一张划线图，系统自动检测划线 → 生成遮罩 → 送 ComfyUI 生发，返回「植发3个月」效果图。
|
||||
|
||||
**与接口2 的核心区别**：
|
||||
|
||||
| 特性 | 接口2（C端生发） | 接口3（B端生发） |
|
||||
|------|----------------|----------------|
|
||||
| 输入 | 原始照片 | 划线图（含手绘线） |
|
||||
| 发际线来源 | 系统按发型模板自动生成 | 医生手绘标注 |
|
||||
| 发型类型 | ellipse/flower/heart/straight/wave | custom（自定义） |
|
||||
| 中间步骤 | extract_context + swapHair + ComfyUI重绘 | 划线检测 + 遮罩 + ComfyUI生发 |
|
||||
| 是否调 change_hair | 是（女性流程） | 否 |
|
||||
| ComfyUI 工作流 | 0716add-hair-api.json（重绘） | add_hair.json（生发） |
|
||||
| 典型耗时 | ~11s | ~6-8s |
|
||||
|
||||
---
|
||||
|
||||
## 二、接口定义
|
||||
|
||||
### 路由
|
||||
|
||||
```
|
||||
POST /api/v1/hair/grow-b
|
||||
```
|
||||
|
||||
### 入参
|
||||
|
||||
| 参数 | 类型 | 必填 | 说明 |
|
||||
|------|------|------|------|
|
||||
| `marked_image_file` | UploadFile | 三选一 | 划线图片文件（JPG/PNG） |
|
||||
| `marked_image_url` | str | 三选一 | 划线图片 URL |
|
||||
| `marked_image_base64` | str | 三选一 | 划线图片 base64 |
|
||||
| `use_mask` | bool | 否（默认True） | 是否自动检测划线并建遮罩。False时跳过检测，直接送划线图 |
|
||||
| `prompt` | str | 否 | ComfyUI 提示词，默认"补充遮罩区域的头发，加一点美颜" |
|
||||
|
||||
### 返回
|
||||
|
||||
```json
|
||||
{
|
||||
"code": 0,
|
||||
"message": "success",
|
||||
"data": {
|
||||
"hair_growth_image_base64": "iVBORw0KGgo...（生发图 JPG base64）",
|
||||
"hairline_type": "custom"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
错误码：
|
||||
- `1001`: 无法识别人像 / 未检测到发际线划线
|
||||
- `1007`: 处理失败
|
||||
- `1008`: 图片格式不支持
|
||||
|
||||
---
|
||||
|
||||
## 三、完整调用链
|
||||
|
||||
```
|
||||
POST /api/v1/hair/grow-b
|
||||
│
|
||||
├─ app.py hair_grow_b() [app.py:929]
|
||||
│ ├─ resolve_image_bytes() → marked_raw 解析图片（file/url/base64三选一）
|
||||
│ ├─ cv2.imdecode → marked_bgr 解码为 BGR
|
||||
│ └─ run_in_threadpool(generate_grow_b, ...)
|
||||
│
|
||||
├─ service.py generate_grow_b(marked_bgr, use_mask, prompt) [service.py:381]
|
||||
│ │
|
||||
│ ├─ 步骤1：人脸检测 + 头发分割（仅 use_mask=True 时）
|
||||
│ │ ├─ get_landmarker().detect(rgb) MediaPipe 478点人脸检测
|
||||
│ │ │ → landmarks（无人脸返回 no_face）
|
||||
│ │ ├─ get_parser().parse(rgb) SegFormer 面部分割（CPU ~0.9s）
|
||||
│ │ │ → parse_map（int label map）
|
||||
│ │ │
|
||||
│ ├─ 步骤2：手绘发际线检测（仅 use_mask=True 时）
|
||||
│ │ ├─ detect_marker_hairline(marked_bgr, landmarks, parse_map)
|
||||
│ │ │ │ [marker_detect.py:41]
|
||||
│ │ │ ├─ forehead_upper_region(landmarks) 额头上部 ROI
|
||||
│ │ │ ├─ head_silhouette(parse_map) 头部轮廓 ROI
|
||||
│ │ │ ├─ _blackhat(gray) 黑帽变换（响应比邻域暗的细结构）
|
||||
│ │ │ ├─ _snap_anchor(bh, 左鬓角21) 左锚点吸附
|
||||
│ │ │ ├─ _snap_anchor(bh, 右鬓角251) 右锚点吸附
|
||||
│ │ │ ├─ route_through_array(cost, 左, 右) Dijkstra最小代价路径
|
||||
│ │ │ └→ path (N,2) row,col（拒识返回 None → no_line）
|
||||
│ │ │
|
||||
│ │ ├─ path_to_curve_mask(path) 路径→曲线mask（uint8 0/255）
|
||||
│ │ └─ mask_from_curve(curve_mask, landmarks, parse_map)
|
||||
│ │ │ [mask.py]
|
||||
│ │ ├─ _above_curve_region(curve_mask) 曲线以上区域
|
||||
│ │ ├─ cv2.morphologyEx(闭运算) 填洞
|
||||
│ │ ├─ 最大连通域
|
||||
│ │ └─ 高斯羽化 → mask (uint8 0-255)
|
||||
│ │
|
||||
│ ├─ 步骤3：合成 RGBA PNG
|
||||
│ │ ├─ compose_comfy_rgba(marked_bgr, mask) RGB=原图，alpha=255×(1-mask)
|
||||
│ │ └─ PNG 编码 → rgba_png_bytes
|
||||
│ │
|
||||
│ └─ 步骤4：ComfyUI 生发
|
||||
│ └─ comfyui.run(rgba_png_bytes, prompt) [comfyui.py:87]
|
||||
│ ├─ 上传图片到 ComfyUI /upload/image
|
||||
│ ├─ 加载工作流 add_hair.json
|
||||
│ ├─ 替换节点26输入图 + 节点6随机seed + 节点60提示词
|
||||
│ ├─ POST /prompt 提交工作流
|
||||
│ ├─ 轮询 /history/{prompt_id}（间隔0.2s）
|
||||
│ └─ GET /view 取回输出 PNG → grown_png
|
||||
│
|
||||
└─ 返回 {"grown_png": bytes, "status": "ok"}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 四、用到的模型和外部服务
|
||||
|
||||
| 模型/服务 | 用途 | 位置 | 设备 |
|
||||
|----------|------|------|------|
|
||||
| **FaceLandmarker** (MediaPipe) | 478点人脸检测 | hairline/face_landmarks.py | CPU |
|
||||
| **FaceParser** (SegFormer) | 面部分割（hair/skin/...） | hairline/face_parsing.py | CPU (5090不兼容cu121) |
|
||||
| **ComfyUI** (Flux-2) | 生发图生成 | hairline/comfyui.py → :8188 | GPU |
|
||||
|
||||
**注意**：接口3 **不调用** change_hair 服务（:8801），不需要 swapHair。这是它与接口2女性流程的关键区别。
|
||||
|
||||
---
|
||||
|
||||
## 五、核心算法：手绘发际线检测
|
||||
|
||||
### 5.1 为什么不用简单阈值？
|
||||
|
||||
手绘马克笔线条的灰度值与皮肤阴影、抬头纹等重叠，全局阈值无法区分。采用**黑帽变换 + Dijkstra最小路径**方案。
|
||||
|
||||
### 5.2 黑帽变换（Black Hat）
|
||||
|
||||
```python
|
||||
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (k, k))
|
||||
bh = cv2.morphologyEx(gray, cv2.MORPH_BLACKHAT, kernel)
|
||||
```
|
||||
|
||||
黑帽 = 闭运算 − 原图，响应"比局部邻域暗的细结构"（即马克笔线条），对抬头纹/眉毛/发丝鲁棒。
|
||||
|
||||
### 5.3 Dijkstra 最小代价路径
|
||||
|
||||
1. **ROI 限定**：额头上部 ∩ 头部轮廓（排除背景）
|
||||
2. **锚点**：左鬓角(21) / 右鬓角(251) MediaPipe 关键点
|
||||
3. **代价图**：`cost = (bh.max() - bh) + 1.0`，ROI外设 1e6
|
||||
4. **路径**：`route_through_array(cost, 左锚, 右锚)` — skimage 的 Dijkstra 实现
|
||||
|
||||
### 5.4 拒识机制
|
||||
|
||||
路径平均黑帽响应 < 8.0 → 判定"未画线"，返回 `no_line`。
|
||||
|
||||
---
|
||||
|
||||
## 六、与接口1、接口2 的对比
|
||||
|
||||
| 维度 | 接口1 | 接口2 | 接口3 |
|
||||
|------|-------|-------|-------|
|
||||
| 功能 | 四庭七眼测量 | C端生发（5种发际线） | B端生发（手绘线） |
|
||||
| 路由 | /api/v1/face/measure | /api/v1/hair/grow | /api/v1/hair/grow-b |
|
||||
| 输入 | 正面照 | 正面照 | 划线图 |
|
||||
| MediaPipe | ✅ | ✅ | ✅ |
|
||||
| SegFormer | ✅ | ✅ | ✅ |
|
||||
| change_hair | ❌ | ✅（女性） | ❌ |
|
||||
| ComfyUI | ❌ | ✅（Flux-2重绘） | ✅（Flux-2生发） |
|
||||
| 典型耗时 | ~2s | ~11s | ~6-8s |
|
||||
| ComfyUI工作流 | — | 0716add-hair-api.json | add_hair.json |
|
||||
|
||||
---
|
||||
|
||||
## 七、测试
|
||||
|
||||
- **测试页面**：[static/test_interface3.html](file:///home/ubuntu/hair/static/test_interface3.html)
|
||||
- **测试图片**：[image/girl_img/girl13.jpg](file:///home/ubuntu/hair/image/girl_img/girl13.jpg)（需手动在图上画发际线后作为划线图上传）
|
||||
+9
-57
@@ -20,7 +20,6 @@
|
||||
| 3 B 端生发 | POST | `/api/v1/hair/grow-b` |
|
||||
| 4 用户特征 | POST | `/api/v1/face/features` |
|
||||
| 5 发际线 PNG 生成 | POST | `/api/v1/hairline/generate` |
|
||||
| 7 C 端生发 v2 | POST | `/api/v1/hair/grow-v2` |
|
||||
|
||||
---
|
||||
|
||||
@@ -87,6 +86,7 @@
|
||||
| 1006 | 文件超出大小限制 | 单文件超过 1 MB |
|
||||
| 1007 | 图片参数错误 | file / url / base64 未传，或同时传了多个（三者严格互斥） |
|
||||
| 1008 | 图片格式不支持 | 非 JPG / PNG |
|
||||
| 1009 | 未授权 | 缺少或错误的 `X-Internal-Token`（`/api/*` 路径鉴权） |
|
||||
|
||||
---
|
||||
|
||||
@@ -109,6 +109,8 @@
|
||||
| four_courts | object | 四庭数据，见下表 |
|
||||
| seven_eyes | object | 七眼数据，见下表 |
|
||||
| landmarks | object | 关键分界点坐标（头顶 / 发际线 / 眉心 / 鼻翼下缘 / 下巴尖），原图像素坐标 |
|
||||
| left_position | object | MediaPipe 21 号关键点坐标（左脸定位点），原图像素：`{ "x": int, "y": int }` |
|
||||
| right_position | object | MediaPipe 251 号关键点坐标（右脸定位点，与 21 号镜像），原图像素：`{ "x": int, "y": int }` |
|
||||
|
||||
`four_courts`（四庭，自上而下）：
|
||||
|
||||
@@ -211,6 +213,8 @@
|
||||
| four_courts | object | 三庭数据（上/中/下庭，各含 cm 与 ratio；**无顶庭**） |
|
||||
| seven_eyes | object | 七眼数据（眼宽/脸宽/两眼间距 cm + 占比 ratios + **eye2~eye6** 共 5 段宽度） |
|
||||
| landmarks | object | 四个关键点像素坐标（发际线/眉心/鼻翼下缘/下巴尖） |
|
||||
| left_position | object | MediaPipe 21 号关键点坐标（左脸定位点），原图像素：`{ "x": int, "y": int }` |
|
||||
| right_position | object | MediaPipe 251 号关键点坐标（右脸定位点，与 21 号镜像），原图像素：`{ "x": int, "y": int }` |
|
||||
|
||||
> 接口6 是**三庭五眼**：`four_courts`/`landmarks` 不含顶庭与头顶点（无 `top_court_cm`/`hair_top`）；`seven_eyes` 只含 **eye2~eye6**（左脸颊/左眼/两眼间距/右眼/右脸颊，5 段），**无 eye1/eye7**（耳外段需头发轮廓端线，仅接口1 有）。
|
||||
|
||||
@@ -405,6 +409,7 @@
|
||||
| hair_style | string | **是** | 发型序号，**逗号分隔多选**（如 `1,2,3`），决定返回哪些发际线类型。female：1=ellipse, 2=flower, 3=heart, 4=straight, 5=wave；male：1=ellipse, 2=inverse_arc, 3=m, 4=straight。缺失/越界/非法返回 `1007` |
|
||||
| use_mask | bool | 否 | 生发是否启用 inpaint 遮罩，默认 `true`。`false` 时用干净原图生成（空遮罩、不烧模板黑线），供测试对比 |
|
||||
| prompt | string | 否 | ComfyUI 提示词，默认「补充遮罩区域的头发，加一点美颜」，会替换工作流节点 60 的文本 |
|
||||
| generate_grow_image | bool | 否 | 是否生成生发效果图（ComfyUI 生发，全流程最耗时），默认 `true`。传 `false` 时跳过生发，各发型 `grown_image_*` 恒为 `null`，仅返回三档发际线叠图与中心点，可大幅降低耗时 |
|
||||
|
||||
> ⚠️ 三档叠图分别用 `hairline_texture` / `hairline_texture_high` / `hairline_texture_low` 三套同名贴图；**生发黑模板固定取自 `hairline_texture_black/`（middle 档）**，即生发目标固定压到 middle 档，每个发型仅 1 张生发图。
|
||||
|
||||
@@ -426,7 +431,7 @@
|
||||
| image_middle_url | string | middle 档发际线曲线**透明 PNG** URL（仅曲线，透明底，**不含人物**，需叠加原图显示） |
|
||||
| image_high_url | string | high 档发际线曲线**透明 PNG** URL（同上，high 档曲线） |
|
||||
| image_low_url | string | low 档发际线曲线**透明 PNG** URL（同上，low 档曲线） |
|
||||
| grown_image_url | string \| null | **生发后图片** URL（ComfyUI「植发」效果图，完整人像照片，生发失败时为 `null`） |
|
||||
| grown_image_url | string \| null | **生发后图片** URL（ComfyUI「植发」效果图，完整人像照片，生发失败或 `generate_grow_image=false` 时为 `null`） |
|
||||
| order | int | 发型序号（= 传入的 hair_style 值） |
|
||||
|
||||
> worker 侧返回 `image_middle_base64` / `image_high_base64` / `image_low_base64` / `grown_image_base64`，网关落盘后改写为上表对应的 `*_url`。
|
||||
@@ -443,6 +448,8 @@
|
||||
| landmarks | object | 5 个纵向关键点像素坐标（hair_top/hairline/brow_center/nose_bottom/chin_tip），结构同接口1 |
|
||||
| hairline_source | string | 发际线来源：`segmentation`（真实分割）/ `estimated`（比例估算） |
|
||||
| head_pose | object | 头部姿态角度（yaw/pitch/roll，单位：度） |
|
||||
| left_position | object | MediaPipe 21 号关键点坐标（左脸定位点），原图像素：`{ "x": int, "y": int }` |
|
||||
| right_position | object | MediaPipe 251 号关键点坐标（右脸定位点，与 21 号镜像），原图像素：`{ "x": int, "y": int }` |
|
||||
|
||||
> `eye1`~`eye7` 为从左到右共 7 段宽度，eye1=左耳外段、eye7=右耳外段，某侧耳朵不可见时对应段为 `null`。详见接口1说明。
|
||||
|
||||
@@ -508,60 +515,6 @@
|
||||
|
||||
---
|
||||
|
||||
## 接口 7：C 端生发 v2 接口
|
||||
|
||||
**说明**：功能与[接口 2](#接口-2c-端生发接口)完全一致，仅 ComfyUI 工作流不同——使用 `add_hair2.json` 替代 `add_hair.json`。
|
||||
|
||||
**请求**：`POST /api/v1/hair/grow-v2`
|
||||
|
||||
### 输入
|
||||
|
||||
与接口 2 完全相同。图片参数见「通用约定 → 图片传参字段」。专属参数：
|
||||
|
||||
| 参数 | 类型 | 必填 | 说明 |
|
||||
|------|------|------|------|
|
||||
| gender | string | **是** | 性别：`male` / `female`。决定使用的发际线贴图集合 |
|
||||
| hair_style | string | **是** | 发型序号，**逗号分隔多选**（如 `1,2,3`）。female：1=ellipse, 2=flower, 3=heart, 4=straight, 5=wave；male：1=ellipse, 2=inverse_arc, 3=m, 4=straight。越界/非法返回 `1007` |
|
||||
| beauty_enabled | bool | 否 | 生发图是否带美颜效果，默认 false（当前阶段不生效） |
|
||||
| use_mask | bool | 否 | 是否启用 inpaint 遮罩，默认 `true`。`false` 时用干净原图生成（空遮罩、不烧模板黑线） |
|
||||
| prompt | string | 否 | ComfyUI 提示词，默认「补充遮罩区域的头发，加一点美颜」，会替换工作流节点 60 的文本 |
|
||||
|
||||
### 输出（data）
|
||||
|
||||
与接口 2 完全相同。`results`：发际线方案数组，**数量 = 所选发型数**。每个元素：
|
||||
|
||||
| 字段 | 类型 | 说明 |
|
||||
|------|------|------|
|
||||
| image_url | string | 发际线曲线**透明 PNG** URL（仅曲线，透明底，**不含人物**，需叠加原图显示） |
|
||||
| grown_image_url | string | **生发后图片** URL（ComfyUI/Flux「植发 3 个月」效果图，完整人像照片） |
|
||||
| hairline_type | string | 发际线类型 key |
|
||||
| order | int | 排序序号 |
|
||||
|
||||
> ⚠️ 与接口 2 的区别：本接口使用 `add_hair2.json` 工作流（Flux-2 Klein 9b），输入/遮罩节点同为 26，
|
||||
> SaveImage 输出节点为 75。
|
||||
|
||||
### 响应示例
|
||||
|
||||
```json
|
||||
{
|
||||
"code": 0,
|
||||
"message": "success",
|
||||
"request_id": "mock-request-id",
|
||||
"data": {
|
||||
"results": [
|
||||
{
|
||||
"image_url": "https://hair.xiangsilian.com/static/sample.jpg",
|
||||
"grown_image_url": "https://hair.xiangsilian.com/static/sample.jpg",
|
||||
"hairline_type": "ellipse",
|
||||
"order": 1
|
||||
}
|
||||
]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 汇总：输入输出一览
|
||||
|
||||
| 接口 | 输入 | 主要输出 |
|
||||
@@ -572,7 +525,6 @@
|
||||
| 3 B 端生发 | 划线图片 | 最合适发际线图片 + 生发后图片 |
|
||||
| 4 用户特征 | 用户照片 | 6 个用户特征字段（脸形/眉形/年龄/动静/性别/基因风格） |
|
||||
| 5 发际线 PNG | 用户照片 + gender + hair_style（多选） | 每个选中发型 middle/high/low 三档发际线叠图 + 生发图 + 最合适发际线面部中间点坐标 |
|
||||
| 7 C 端生发 v2 | 用户照片 + gender + hair_style | 同接口2，使用 add_hair2.json 工作流 |
|
||||
|
||||
---
|
||||
|
||||
|
||||
+49
-31
@@ -6,9 +6,9 @@
|
||||
- 纵向竖线 8 条：人头最左 + 左脸颊/左眼外/内角/右眼内/外角/右脸颊 + 人头最右，
|
||||
把头宽切 7 段（七眼），段宽数值上下交替（上 3 / 下 4），带虚线双箭头。
|
||||
人头最左/最右取自耳朵分割外缘，看不到耳朵则省略该侧（最少 6 点 5 段）。
|
||||
- 四庭：图片左侧，「名」上「数值」下两行换行（不带 cm），带竖向虚线双箭头。
|
||||
- 四庭：图片左侧，「名」「数值(带 cm)」「百分比」三行换行，带竖向虚线双箭头。
|
||||
- 五条横线右侧标名：头顶/发际线/眉心/鼻翼下缘/下巴尖。
|
||||
- 单位 cm 统一标在底部「单位cm」。
|
||||
- 每段数值直接带 cm 后缀，下方另起一行标百分比（不再单独标底部「单位cm」）。
|
||||
中文字体用打包的思源黑体绝对路径加载，缺字体直接抛错（不静默降级成方块）。
|
||||
"""
|
||||
import os
|
||||
@@ -189,9 +189,8 @@ def create_annotated_image(image_bgr, measure_result, ear_mask=None, hair_mask=N
|
||||
取自耳朵分割掩膜的外缘（方案 B，BiSeNet 类 7/8）；耳朵不可见（被头发/侧脸
|
||||
遮挡 → 掩膜空）或无掩膜时省略该侧端线，只画对应脸颊线。
|
||||
- 横向 5 条分界线：头顶/发际线/眉心/鼻翼下缘/下巴尖，右侧标名。
|
||||
- 四庭（顶/上/中/下庭）在左侧：名 + 数值两行换行（无 cm），竖向虚线双箭头。
|
||||
- 七眼段宽数值上下交替（上 3 / 下 4，无 cm），横向虚线双箭头。
|
||||
- 底部统一标「单位cm」。
|
||||
- 四庭（顶/上/中/下庭）在左侧：名 + 数值(带 cm) + 百分比三行换行，竖向虚线双箭头。
|
||||
- 七眼段宽上下交替（上 3 / 下 4）：数值(带 cm) 上、百分比（占头宽比）下，横向虚线双箭头。
|
||||
|
||||
variant="v6"（接口6）：去掉头顶横线与顶庭（只画发际线/眉心/鼻翼下缘/下巴尖 4 条
|
||||
横线 + 上/中/下庭），竖线纵向范围改为发际线→下巴尖，且不画人头最左/最右端线
|
||||
@@ -203,7 +202,7 @@ def create_annotated_image(image_bgr, measure_result, ear_mask=None, hair_mask=N
|
||||
|
||||
# --- 自适应尺寸：字号/线宽/虚线/箭头按短边缩放 ---
|
||||
s = min(w, h)
|
||||
font_size = max(11, round(s * 0.026)) # 字体更小
|
||||
font_size = max(9, round(s * 0.020)) # 字号上调一档
|
||||
line_w = max(1, round(s * 0.0022))
|
||||
dash_len = max(4, round(s * 0.008))
|
||||
gap_len = max(2, round(dash_len * 0.7)) # 虚线更稠密（间隙<划线）
|
||||
@@ -213,7 +212,11 @@ def create_annotated_image(image_bgr, measure_result, ear_mask=None, hair_mask=N
|
||||
|
||||
buf = np.zeros((h, w, 4), dtype=np.uint8)
|
||||
|
||||
if variant == "v6":
|
||||
# 发际线弃用（hairline_discarded）：保留头顶横线，去掉发际线横线，
|
||||
# 也不标顶/上庭（缺发际线作边界，算不出）。横线 = 头顶/眉心/鼻翼下缘/下巴尖。
|
||||
if getattr(measure_result, "hairline_discarded", False):
|
||||
order = ["hair_top", "brow_center", "nose_bottom", "chin_tip"]
|
||||
elif variant == "v6":
|
||||
order = ["hairline", "brow_center", "nose_bottom", "chin_tip"]
|
||||
else:
|
||||
order = ["hair_top", "hairline", "brow_center", "nose_bottom", "chin_tip"]
|
||||
@@ -240,7 +243,7 @@ def create_annotated_image(image_bgr, measure_result, ear_mask=None, hair_mask=N
|
||||
face_cx = (fx0 + fx1) / 2
|
||||
over = max(6, round(s * 0.030)) # 线超出包围盒的长度（参考图风格）
|
||||
face_half = (fx1 - fx0) / 2 + over # 横线超出最外侧竖线一点
|
||||
# v6 竖线纵向范围 = 发际线→下巴尖（不超出）；v1 = 头顶→下巴尖并两端超出一点
|
||||
# 竖线纵向范围：v6 = 发际线→下巴尖（不超出）；v1（含发际线弃用）= 头顶→下巴尖并两端超出一点
|
||||
v_top = fy0 if variant == "v6" else fy0 - over
|
||||
v_bot = fy1 if variant == "v6" else fy1 + over
|
||||
|
||||
@@ -256,70 +259,85 @@ def create_annotated_image(image_bgr, measure_result, ear_mask=None, hair_mask=N
|
||||
draw = ImageDraw.Draw(canvas)
|
||||
font = _load_font(font_size)
|
||||
|
||||
# --- 3a. 横线右侧：线名（头顶/发际线/眉心/鼻翼下缘/下巴尖），文字在线上方 ---
|
||||
name_x = fx1 + pad
|
||||
name_gap = max(2, round(pad * 1.6)) # 文字底部到线的间距（再上移）
|
||||
# --- 3a. 横线右侧：线名（头顶/发际线/眉心/鼻翼下缘/下巴尖），文字纵向居中对齐到线 ---
|
||||
name_x = fx1 + over + pad # 移到横线右端外侧一点（往右）
|
||||
for i, name in enumerate(order):
|
||||
text = _LINE_NAMES[name]
|
||||
tw, th = _text_size(draw, text, font)
|
||||
tw, _ = _text_size(draw, text, font)
|
||||
x = min(name_x, w - 2 - tw) # 右侧越界时回收
|
||||
draw.text((x, max(2, ys[i] - th - name_gap)), text, fill=LINE_COLOR, font=font)
|
||||
# anchor="lm"：x 为左、y 为竖直中点 → 文字中线正好压在横线上（与线对齐）
|
||||
draw.text((x, ys[i]), text, fill=LINE_COLOR, font=font, anchor="lm")
|
||||
|
||||
# --- 3b. 左侧四庭：名 + 数值两行（无 cm）+ 竖向虚线双箭头 ---
|
||||
if variant == "v6":
|
||||
# court_start：庭段在 order 里的起始索引。发际线弃用时 order 首位是头顶（无下界发际线，
|
||||
# 顶/上庭不标），中庭从眉心开始 → 跳过 order[0]。
|
||||
if getattr(measure_result, "hairline_discarded", False):
|
||||
court_cm = [measure_result.middle_cm, measure_result.lower_cm]
|
||||
court_name = ["中庭", "下庭"]
|
||||
n_court = 2
|
||||
court_start = 1
|
||||
elif variant == "v6":
|
||||
court_cm = [measure_result.upper_cm, measure_result.middle_cm, measure_result.lower_cm]
|
||||
court_name = ["上庭", "中庭", "下庭"]
|
||||
n_court = 3
|
||||
court_start = 0
|
||||
else:
|
||||
court_cm = [measure_result.top_cm, measure_result.upper_cm,
|
||||
measure_result.middle_cm, measure_result.lower_cm]
|
||||
court_name = ["顶庭", "上庭", "中庭", "下庭"]
|
||||
n_court = 4
|
||||
court_start = 0
|
||||
arrow_x = max(arrow_size + 1, fx0 - pad) # 竖箭头所在 x（脸左侧，贴近最左竖线）
|
||||
court_total = sum(court_cm) or 1.0 # 各庭占比分母 = 四庭（v6 三庭）之和
|
||||
for i in range(n_court):
|
||||
y_a, y_b = ys[i], ys[i + 1]
|
||||
y_a, y_b = ys[court_start + i], ys[court_start + i + 1]
|
||||
# 竖向虚线双箭头，覆盖该庭高度（略收一点避免压到横线）
|
||||
inset = min(arrow_size, (y_b - y_a) * 0.12)
|
||||
draw_dashed_line_with_arrows(
|
||||
draw, arrow_x, y_a + inset, arrow_x, y_b - inset,
|
||||
dash_len=dash_len, gap_len=gap_len, arrow_size=arrow_size, width=line_w)
|
||||
# 名 + 数值两行，右对齐到箭头左侧
|
||||
# 名 + 数值(带 cm) + 百分比三行，右对齐到箭头左侧
|
||||
name = court_name[i]
|
||||
val = f"{court_cm[i]:.2f}"
|
||||
val = f"{court_cm[i]:.2f}cm"
|
||||
pct = f"{court_cm[i] / court_total * 100:.1f}%"
|
||||
nw, _ = _text_size(draw, name, font)
|
||||
vw, _ = _text_size(draw, val, font)
|
||||
pw, _ = _text_size(draw, pct, font)
|
||||
label_right = arrow_x - pad
|
||||
y_mid = (y_a + y_b) / 2
|
||||
y_top = y_mid - line_h
|
||||
y_top = y_mid - 1.5 * line_h
|
||||
draw.text((max(2, label_right - nw), y_top), name, fill=LINE_COLOR, font=font)
|
||||
draw.text((max(2, label_right - vw), y_top + line_h), val, fill=LINE_COLOR, font=font)
|
||||
draw.text((max(2, label_right - pw), y_top + 2 * line_h), pct, fill=LINE_COLOR, font=font)
|
||||
|
||||
# --- 4. 七眼每段宽度：上下交替（上 3 / 下 4），横向虚线双箭头 + 数值（无 cm） ---
|
||||
# 文字与箭头间留更大间距，避免文字压住箭头
|
||||
# --- 4. 七眼每段宽度：上下交替（上 3 / 下 4），横向虚线双箭头 + 数值(带 cm) + 百分比 ---
|
||||
# 每段两行：数值(带 cm) 上、百分比 下；百分比分母 = 整个头宽（七段之和）
|
||||
txt_off = arrow_size + pad * 2
|
||||
y_arrow_top = max(txt_off + font_size + 2, fy0 - pad - arrow_size)
|
||||
y_arrow_bot = min(h - txt_off - font_size - 2, fy1 + pad + arrow_size)
|
||||
txt_block = 2 * line_h # 两行文字总高（数值 + 百分比）
|
||||
y_arrow_top = max(txt_off + txt_block + 2, fy0 - pad - arrow_size)
|
||||
y_arrow_bot = min(h - txt_off - txt_block - 2, fy1 + pad + arrow_size)
|
||||
head_w = (xs[-1] - xs[0]) or 1.0 # 头宽（像素）= 百分比分母
|
||||
for i in range(len(xs) - 1):
|
||||
x_a, x_b = xs[i], xs[i + 1]
|
||||
if x_b - x_a < 1:
|
||||
continue
|
||||
seg_cm = (x_b - x_a) / pc
|
||||
seg_pct = (x_b - x_a) / head_w * 100
|
||||
cx_seg = (x_a + x_b) / 2
|
||||
text = f"{seg_cm:.2f}"
|
||||
tw, th = _text_size(draw, text, font)
|
||||
val = f"{seg_cm:.2f}cm"
|
||||
pct = f"{seg_pct:.1f}%"
|
||||
vw, _ = _text_size(draw, val, font)
|
||||
pw, _ = _text_size(draw, pct, font)
|
||||
inset = min(arrow_size, (x_b - x_a) * 0.12)
|
||||
on_top = (i % 2 == 1) # 奇数段在上 → 上 3 / 下 4
|
||||
y_arrow = y_arrow_top if on_top else y_arrow_bot
|
||||
draw_dashed_line_with_arrows(
|
||||
draw, x_a + inset, y_arrow, x_b - inset, y_arrow,
|
||||
dash_len=dash_len, gap_len=gap_len, arrow_size=arrow_size, width=line_w)
|
||||
ty = (y_arrow - th - txt_off) if on_top else (y_arrow + txt_off)
|
||||
draw.text((cx_seg - tw / 2, ty), text, fill=LINE_COLOR, font=font)
|
||||
|
||||
# --- 5. 底部统一单位 ---
|
||||
unit = "单位cm"
|
||||
uw, uh = _text_size(draw, unit, font)
|
||||
draw.text(((w - uw) / 2, h - uh - max(2, pad)), unit, fill=LINE_COLOR, font=font)
|
||||
# 数值行在上、百分比行在下；on_top 时整块置于箭头上方，否则下方
|
||||
text_top = (y_arrow - txt_off - txt_block) if on_top else (y_arrow + txt_off)
|
||||
draw.text((cx_seg - vw / 2, text_top), val, fill=LINE_COLOR, font=font)
|
||||
draw.text((cx_seg - pw / 2, text_top + line_h), pct, fill=LINE_COLOR, font=font)
|
||||
|
||||
return canvas
|
||||
|
||||
|
||||
@@ -18,6 +18,8 @@ RIGHT_EYE_INNER = 362 # 右眼内角
|
||||
RIGHT_EYE_OUTER = 263 # 右眼外角
|
||||
LEFT_CHEEK = 234 # 左脸颧弓（脸宽左端）
|
||||
RIGHT_CHEEK = 454 # 右脸颧弓（脸宽右端）
|
||||
LEFT_POSITION = 21 # 左脸前侧定位点（脸颊/耳前区域，与 251 镜像）
|
||||
RIGHT_POSITION = 251 # 右脸前侧定位点（与 21 镜像）
|
||||
|
||||
# --- 鼻尖（solvePnP 用，可选） ---
|
||||
NOSE_TIP = 1 # 鼻尖（也有用 4 的版本）
|
||||
|
||||
@@ -110,7 +110,7 @@ def _gray_b64(gray_float):
|
||||
def _red_mask_b64(mask_bool, h, w):
|
||||
"""布尔遮罩 → 纯红 alpha PNG data URI。
|
||||
遮罩区域 RGBA=(255,0,0,255)，其余区域 RGBA=(0,0,0,0)。
|
||||
供外部 ComfyUI 重绘服务（如 local_test）按 alpha 通道识别重绘区。
|
||||
供 ComfyUI 重绘接口（/api/v1/redraw）按 alpha 通道识别重绘区。
|
||||
|
||||
注意：cv2.imencode 写 PNG 用的是 **BGRA** 顺序（B,G,R,A），所以要得到
|
||||
浏览器显示的红色 R=255，需赋值 (B=0,G=0,R=255,A=255)。
|
||||
@@ -357,7 +357,8 @@ def _redraw_band_mask(inner_pts, outer_pts, h, w, rid="", upper=None,
|
||||
|
||||
|
||||
def compute_mask(image_bgr, landmarks, seg_model, mask_type, erode_cm, px_per_cm,
|
||||
hairline_push_cm=0.0, hairline_edge="column", rid="", render_viz=True):
|
||||
hairline_push_cm=0.0, hairline_edge="column", rid="", render_viz=True,
|
||||
hair_mask=None):
|
||||
"""算出布尔遮罩 + 可视化。
|
||||
|
||||
seg_model: bisenet | segformer。
|
||||
@@ -368,6 +369,7 @@ def compute_mask(image_bgr, landmarks, seg_model, mask_type, erode_cm, px_per_cm
|
||||
render_viz: 是否生成各阶段叠图 overlay JPG（接口11 调试页用）。接口2/12 路径传 False
|
||||
可跳过 6+ 张 base64 编码，省 ~80ms；数据字段（_inner_pts/_outer_pts/_upper_mask/
|
||||
mask_pixels 等）始终返回，不受影响。
|
||||
hair_mask: 预计算的头发布尔遮罩（来自 SegFormer parse）。传入时跳过重复分割，省 ~0.9s。
|
||||
返回 (mask_bool, viz_dict)。
|
||||
"""
|
||||
lg = lambda msg: logger.info("[%s] %s", rid, msg) if rid else None
|
||||
@@ -381,13 +383,16 @@ def compute_mask(image_bgr, landmarks, seg_model, mask_type, erode_cm, px_per_cm
|
||||
upper = _upper_region_mask(baseline_pts, w, h)
|
||||
lg(f"baseline 第一点={baseline_pts[0]} 末点={baseline_pts[-1]} upper像素={int(upper.sum())}")
|
||||
|
||||
if seg_model == "bisenet":
|
||||
hair_mask = _bisenet_hair_mask(image_bgr, landmarks, w, h)
|
||||
elif seg_model == "segformer":
|
||||
hair_mask = _segformer_hair_mask(image_bgr)
|
||||
if hair_mask is None:
|
||||
if seg_model == "bisenet":
|
||||
hair_mask = _bisenet_hair_mask(image_bgr, landmarks, w, h)
|
||||
elif seg_model == "segformer":
|
||||
hair_mask = _segformer_hair_mask(image_bgr)
|
||||
else:
|
||||
raise ValueError(f"未知 seg_model: {seg_model}")
|
||||
lg(f"头发分割完成 seg_model={seg_model} hair_pixels={int(hair_mask.sum())}")
|
||||
else:
|
||||
raise ValueError(f"未知 seg_model: {seg_model}")
|
||||
lg(f"头发分割完成 seg_model={seg_model} hair_pixels={int(hair_mask.sum())}")
|
||||
lg(f"头发分割跳过(复用外部传入) hair_pixels={int(hair_mask.sum())}")
|
||||
|
||||
top_fill = _fill_to_baseline(hair_mask, upper) # 含额头，延伸到图底
|
||||
closed = _largest_cc(top_fill & upper) # 闭合区域：头发+额头，底=基线
|
||||
@@ -849,7 +854,8 @@ def _grow_core(image_bgr, hairline_id, *, is_hr, seg_model, erode_cm, swap_mode,
|
||||
edge_erode_px, denoising_strength, gen_backend, hairgrow_strength,
|
||||
mb_levels, hairline_push_cm, hairline_edge, blend_method, color_match,
|
||||
color_match_strength, mb_feather_px, transition_band_px,
|
||||
inpainting_fill, mask_blur, mask_dilate_scale, rid, render_viz=True):
|
||||
inpainting_fill, mask_blur, mask_dilate_scale, rid, render_viz=True,
|
||||
hair_mask=None):
|
||||
"""接口11 共享核心：遮罩(pushed)→生成→硬贴回→接缝融合，产出 ④ final。
|
||||
|
||||
不做任何重绘。返回中间产物 dict（供接口11 构造响应、接口12 取 final+重绘带用）：
|
||||
@@ -879,7 +885,7 @@ def _grow_core(image_bgr, hairline_id, *, is_hr, seg_model, erode_cm, swap_mode,
|
||||
mask_bool, mask_viz = compute_mask(
|
||||
image_bgr, landmarks, seg_model, mask_type, erode_cm, px_per_cm,
|
||||
hairline_push_cm=hairline_push_cm, hairline_edge=hairline_edge, rid=rid,
|
||||
render_viz=render_viz)
|
||||
render_viz=render_viz, hair_mask=hair_mask)
|
||||
t_mask = time.time() - t0
|
||||
logger.info("[%s] 步骤1 遮罩完成 耗时=%dms mask_pixels=%d", rid, int(t_mask*1000), int(mask_bool.sum()))
|
||||
|
||||
@@ -1028,13 +1034,14 @@ def generate_hairline_redraw(image_bgr, hairline_id, is_hr=False, seg_model="seg
|
||||
transition_band_px=-1,
|
||||
inpainting_fill=1, mask_blur=11, mask_dilate_scale=1.0,
|
||||
comfyui_prompt=None, beauty_alpha=0.6,
|
||||
band_lo_mult=0.5, band_hi_mult=1.5, rid=None):
|
||||
band_lo_mult=0.5, band_hi_mult=1.5, rid=None,
|
||||
hair_mask=None):
|
||||
"""接口12 发际线带重绘。内部先跑接口11 核心拿到 ④ final，再取 ⑤-① 发际线重绘带
|
||||
（外推↔内推之间、经 baseline 截断只留上部）作遮罩。
|
||||
|
||||
**本接口不再做 Flux-2 重绘**：只产出 `final`（接缝融合基底）+ 纯红遮罩
|
||||
`redraw_band_mask`（RGBA，遮罩区=(255,0,0,255)、其余全透明），重绘交给前端调
|
||||
外部 ComfyUI 重绘服务（见 local_test）完成。旧的 `redraw_full` / `redraw_band`
|
||||
`redraw_band_mask`（RGBA，遮罩区=(255,0,0,255)、其余全透明），重绘交给后端
|
||||
ComfyUI 重绘接口（/api/v1/redraw）完成。旧的 `redraw_full` / `redraw_band`
|
||||
字段保留为空，仅作结构兼容。
|
||||
|
||||
返回可直接进 ok() 的 data dict。未检出人脸抛 NoFaceError。
|
||||
@@ -1056,7 +1063,8 @@ def generate_hairline_redraw(image_bgr, hairline_id, is_hr=False, seg_model="seg
|
||||
color_match=color_match, color_match_strength=color_match_strength,
|
||||
mb_feather_px=mb_feather_px, transition_band_px=transition_band_px,
|
||||
inpainting_fill=inpainting_fill, mask_blur=mask_blur,
|
||||
mask_dilate_scale=mask_dilate_scale, rid=rid, render_viz=False)
|
||||
mask_dilate_scale=mask_dilate_scale, rid=rid, render_viz=False,
|
||||
hair_mask=hair_mask)
|
||||
final = core["final"]
|
||||
mask_viz = core["mask_viz"]
|
||||
w, h = core["w"], core["h"]
|
||||
@@ -1089,7 +1097,7 @@ def generate_hairline_redraw(image_bgr, hairline_id, is_hr=False, seg_model="seg
|
||||
redraw_info = {"enabled": False, "error": f"band: {ex}"}
|
||||
|
||||
# ② Flux-2 重绘已下线：本接口现在只产出 final（接缝融合基底）+ 纯红重绘带遮罩，
|
||||
# 重绘交给前端调外部 ComfyUI 重绘服务（见 local_test）完成。
|
||||
# 重绘交给后端 ComfyUI 重绘接口（/api/v1/redraw）完成。
|
||||
# 下面保留 redraw_full_b64 / redraw_band_b64 为空，保持返回结构兼容（旧字段）。
|
||||
redraw_full_b64 = ""
|
||||
redraw_band_b64 = ""
|
||||
@@ -1099,7 +1107,7 @@ def generate_hairline_redraw(image_bgr, hairline_id, is_hr=False, seg_model="seg
|
||||
"hairline_id": hairline_id,
|
||||
"blend_method": blend_method,
|
||||
"hairline_push_cm": round(float(hairline_push_cm), 2),
|
||||
"comfyui_prompt": comfyui_prompt or "补充遮罩区域的头发，加一点美颜",
|
||||
"comfyui_prompt": comfyui_prompt or "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜",
|
||||
"beauty_alpha": beauty_alpha,
|
||||
"px_per_cm": round(float(px_per_cm), 4),
|
||||
"mask_pixels": mask_viz["mask_pixels"],
|
||||
|
||||
+113
-47
@@ -12,9 +12,9 @@ from face_analysis.calibration import (
|
||||
estimate_scale_factor, normalized_to_pixel, pixel_distance, _lm_list,
|
||||
)
|
||||
from face_analysis.face_mesh_landmarks import (
|
||||
GLABELLA_9, GLABELLA_151, NOSE_BOTTOM, CHIN_TIP,
|
||||
GLABELLA_9, NOSE_BOTTOM, CHIN_TIP,
|
||||
LEFT_EYE_OUTER, LEFT_EYE_INNER, RIGHT_EYE_INNER, RIGHT_EYE_OUTER,
|
||||
LEFT_CHEEK, RIGHT_CHEEK,
|
||||
LEFT_CHEEK, RIGHT_CHEEK, LEFT_POSITION, RIGHT_POSITION,
|
||||
)
|
||||
from face_analysis.hair_segmenter import locate_hairline_by_segmentation
|
||||
|
||||
@@ -24,10 +24,8 @@ _TOP_RATIO = 0.22 / 0.28 # 顶庭 ÷ 中庭（≈ 0.786）
|
||||
|
||||
|
||||
def _brow_center(lm, w, h):
|
||||
"""眉心 = 索引 9 / 151 中点。"""
|
||||
g9 = normalized_to_pixel(lm[GLABELLA_9], w, h)
|
||||
g151 = normalized_to_pixel(lm[GLABELLA_151], w, h)
|
||||
return (g9[0] + g151[0]) / 2, (g9[1] + g151[1]) / 2
|
||||
"""眉心 = 索引 9（眉间上点）。"""
|
||||
return normalized_to_pixel(lm[GLABELLA_9], w, h)
|
||||
|
||||
|
||||
def estimate_vertical_landmarks(landmarks, image_width, image_height):
|
||||
@@ -144,22 +142,47 @@ def measure_seven_eyes(landmarks, image_width, image_height):
|
||||
}
|
||||
|
||||
|
||||
def pt_or_none(vertical, name):
|
||||
"""vertical dict 的点 → {"x","y"}，值为 None 时返回 None。"""
|
||||
v = vertical.get(name)
|
||||
if v is None:
|
||||
return None
|
||||
return {"x": int(round(v[0])), "y": int(round(v[1]))}
|
||||
|
||||
|
||||
class MeasureResult:
|
||||
"""测量结果，提供 to_response() 输出与接口文档同构的 data 字段。"""
|
||||
|
||||
def __init__(self, vertical, eyes, px_per_cm, hairline_source, head_pose):
|
||||
# 发际线弃用阈值：发际线离头顶（顶庭）< 此值时判定分割不可靠，弃用发际线。
|
||||
# hairline 与 hair_top 几乎重合（如稀疏头发中轴漏检只剩一小撮），说明发际线
|
||||
# 定位无意义 → 顶/上庭置 null、标注图不画头顶/发际线。
|
||||
HAIRLINE_DISCARD_TOP_CM = 0.7
|
||||
|
||||
def __init__(self, vertical, eyes, px_per_cm, hairline_source, head_pose,
|
||||
landmarks=None, image_width=None, image_height=None):
|
||||
self.vertical = vertical
|
||||
self.eyes = eyes
|
||||
self.px_per_cm = px_per_cm
|
||||
self.hairline_source = hairline_source
|
||||
self.head_pose = head_pose # (yaw, pitch, roll) 或 None
|
||||
# 原始 mediapipe 点集 + 图像尺寸，供 to_response 输出 21/251 号定位点
|
||||
self.landmarks = landmarks
|
||||
self.w = image_width
|
||||
self.h = image_height
|
||||
|
||||
# 各庭厘米
|
||||
self.top_cm = vertical["top_court_px"] / px_per_cm
|
||||
self.upper_cm = vertical["upper_court_px"] / px_per_cm
|
||||
self.middle_cm = vertical["middle_court_px"] / px_per_cm
|
||||
self.lower_cm = vertical["lower_court_px"] / px_per_cm
|
||||
self.face_total_cm = self.top_cm + self.upper_cm + self.middle_cm + self.lower_cm
|
||||
# 发际线弃用判定：顶庭（头顶→发际线）过小视为发际线贴近头顶、不可靠。
|
||||
# 弃用时 hairline_source 改为 "discarded"，face_total 只算中庭+下庭。
|
||||
self.hairline_discarded = self.top_cm < self.HAIRLINE_DISCARD_TOP_CM
|
||||
if self.hairline_discarded:
|
||||
self.hairline_source = "discarded"
|
||||
self.face_total_cm = self.middle_cm + self.lower_cm
|
||||
else:
|
||||
self.face_total_cm = self.top_cm + self.upper_cm + self.middle_cm + self.lower_cm
|
||||
|
||||
# 七眼厘米
|
||||
self.eye_width_cm = eyes["eye_width_px"] / px_per_cm
|
||||
@@ -167,46 +190,88 @@ class MeasureResult:
|
||||
self.inter_eye_cm = eyes["inter_eye_distance_px"] / px_per_cm
|
||||
|
||||
def to_response(self):
|
||||
total_px = (self.vertical["top_court_px"] + self.vertical["upper_court_px"]
|
||||
+ self.vertical["middle_court_px"] + self.vertical["lower_court_px"])
|
||||
fw_px = self.eyes["face_width_px"]
|
||||
|
||||
def pt(name):
|
||||
x, y = self.vertical[name]
|
||||
return {"x": int(round(x)), "y": int(round(y))}
|
||||
|
||||
data = {
|
||||
"face_total_height_cm": round(self.face_total_cm, 2),
|
||||
"four_courts": {
|
||||
"top_court_cm": round(self.top_cm, 2),
|
||||
"upper_court_cm": round(self.upper_cm, 2),
|
||||
"middle_court_cm": round(self.middle_cm, 2),
|
||||
"lower_court_cm": round(self.lower_cm, 2),
|
||||
"ratios": {
|
||||
"top_court": round(self.vertical["top_court_px"] / total_px, 3),
|
||||
"upper_court": round(self.vertical["upper_court_px"] / total_px, 3),
|
||||
"middle_court": round(self.vertical["middle_court_px"] / total_px, 3),
|
||||
"lower_court": round(self.vertical["lower_court_px"] / total_px, 3),
|
||||
# 发际线弃用：顶/上庭相关字段置 null（保留键），ratio 分母只算中下庭；
|
||||
# landmarks.hair_top/hairline 置 null。否则按四庭正常输出。
|
||||
if self.hairline_discarded:
|
||||
base_px = (self.vertical["middle_court_px"] + self.vertical["lower_court_px"])
|
||||
data = {
|
||||
"face_total_height_cm": round(self.face_total_cm, 2),
|
||||
"four_courts": {
|
||||
"top_court_cm": None,
|
||||
"upper_court_cm": None,
|
||||
"middle_court_cm": round(self.middle_cm, 2),
|
||||
"lower_court_cm": round(self.lower_cm, 2),
|
||||
"ratios": {
|
||||
"top_court": None,
|
||||
"upper_court": None,
|
||||
"middle_court": round(self.vertical["middle_court_px"] / base_px, 3),
|
||||
"lower_court": round(self.vertical["lower_court_px"] / base_px, 3),
|
||||
},
|
||||
},
|
||||
},
|
||||
"seven_eyes": {
|
||||
"eye_width_cm": round(self.eye_width_cm, 2),
|
||||
"face_width_cm": round(self.face_width_cm, 2),
|
||||
"inter_eye_distance_cm": round(self.inter_eye_cm, 2),
|
||||
"ratios": {
|
||||
"eye_width": round(self.eyes["eye_width_px"] / fw_px, 3),
|
||||
"inter_eye_distance": round(self.eyes["inter_eye_distance_px"] / fw_px, 3),
|
||||
"seven_eyes": {
|
||||
"eye_width_cm": round(self.eye_width_cm, 2),
|
||||
"face_width_cm": round(self.face_width_cm, 2),
|
||||
"inter_eye_distance_cm": round(self.inter_eye_cm, 2),
|
||||
"ratios": {
|
||||
"eye_width": round(self.eyes["eye_width_px"] / self.eyes["face_width_px"], 3),
|
||||
"inter_eye_distance": round(self.eyes["inter_eye_distance_px"] / self.eyes["face_width_px"], 3),
|
||||
},
|
||||
},
|
||||
},
|
||||
"landmarks": {
|
||||
"hair_top": pt("hair_top"),
|
||||
"hairline": pt("hairline"),
|
||||
"brow_center": pt("brow_center"),
|
||||
"nose_bottom": pt("nose_bottom"),
|
||||
"chin_tip": pt("chin_tip"),
|
||||
},
|
||||
"hairline_source": self.hairline_source,
|
||||
}
|
||||
"landmarks": {
|
||||
"hair_top": None,
|
||||
"hairline": None,
|
||||
"brow_center": pt_or_none(self.vertical, "brow_center"),
|
||||
"nose_bottom": pt_or_none(self.vertical, "nose_bottom"),
|
||||
"chin_tip": pt_or_none(self.vertical, "chin_tip"),
|
||||
},
|
||||
"hairline_source": self.hairline_source,
|
||||
}
|
||||
else:
|
||||
total_px = (self.vertical["top_court_px"] + self.vertical["upper_court_px"]
|
||||
+ self.vertical["middle_court_px"] + self.vertical["lower_court_px"])
|
||||
data = {
|
||||
"face_total_height_cm": round(self.face_total_cm, 2),
|
||||
"four_courts": {
|
||||
"top_court_cm": round(self.top_cm, 2),
|
||||
"upper_court_cm": round(self.upper_cm, 2),
|
||||
"middle_court_cm": round(self.middle_cm, 2),
|
||||
"lower_court_cm": round(self.lower_cm, 2),
|
||||
"ratios": {
|
||||
"top_court": round(self.vertical["top_court_px"] / total_px, 3),
|
||||
"upper_court": round(self.vertical["upper_court_px"] / total_px, 3),
|
||||
"middle_court": round(self.vertical["middle_court_px"] / total_px, 3),
|
||||
"lower_court": round(self.vertical["lower_court_px"] / total_px, 3),
|
||||
},
|
||||
},
|
||||
"seven_eyes": {
|
||||
"eye_width_cm": round(self.eye_width_cm, 2),
|
||||
"face_width_cm": round(self.face_width_cm, 2),
|
||||
"inter_eye_distance_cm": round(self.inter_eye_cm, 2),
|
||||
"ratios": {
|
||||
"eye_width": round(self.eyes["eye_width_px"] / self.eyes["face_width_px"], 3),
|
||||
"inter_eye_distance": round(self.eyes["inter_eye_distance_px"] / self.eyes["face_width_px"], 3),
|
||||
},
|
||||
},
|
||||
"landmarks": {
|
||||
"hair_top": pt_or_none(self.vertical, "hair_top"),
|
||||
"hairline": pt_or_none(self.vertical, "hairline"),
|
||||
"brow_center": pt_or_none(self.vertical, "brow_center"),
|
||||
"nose_bottom": pt_or_none(self.vertical, "nose_bottom"),
|
||||
"chin_tip": pt_or_none(self.vertical, "chin_tip"),
|
||||
},
|
||||
"hairline_source": self.hairline_source,
|
||||
}
|
||||
# left/right_position：mediapipe 21/251 号定位点（原图像素，与 landmarks 同坐标系）。
|
||||
# landmarks 缺省（如测试直构 MeasureResult）时不输出，保持向后兼容。
|
||||
if self.landmarks is not None and self.w and self.h:
|
||||
lm = _lm_list(self.landmarks)
|
||||
|
||||
def _pt_lm(idx):
|
||||
px, py = normalized_to_pixel(lm[idx], self.w, self.h)
|
||||
return {"x": int(round(px)), "y": int(round(py))}
|
||||
|
||||
data["left_position"] = _pt_lm(LEFT_POSITION)
|
||||
data["right_position"] = _pt_lm(RIGHT_POSITION)
|
||||
if self.head_pose is not None:
|
||||
yaw, pitch, roll = self.head_pose
|
||||
data["head_pose"] = {
|
||||
@@ -220,7 +285,8 @@ def measure_face(landmarks, hair_mask, image_width, image_height, head_pose=None
|
||||
vertical, source = decide_vertical(landmarks, image_width, image_height, hair_mask)
|
||||
eyes = measure_seven_eyes(landmarks, image_width, image_height)
|
||||
px_per_cm = estimate_scale_factor(landmarks, image_width, image_height)
|
||||
return MeasureResult(vertical, eyes, px_per_cm, source, head_pose)
|
||||
return MeasureResult(vertical, eyes, px_per_cm, source, head_pose,
|
||||
landmarks, image_width, image_height)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
+10
-1
@@ -50,12 +50,21 @@ def estimate_head_pose(landmarks, image_width, image_height):
|
||||
[0, 0, 1]], dtype=np.float64)
|
||||
dist = np.zeros((4, 1)) # 假设无畸变
|
||||
|
||||
success, rvec, _tvec = cv2.solvePnP(
|
||||
success, rvec, tvec = cv2.solvePnP(
|
||||
_MODEL_POINTS, image_points, cam_matrix, dist,
|
||||
flags=cv2.SOLVEPNP_ITERATIVE,
|
||||
)
|
||||
if not success:
|
||||
return None
|
||||
# ITERATIVE 偶发收敛到相机后方的翻转解（tz<0），此时 roll 落在 ±180° 附近，
|
||||
# 会把真正的正面照误判为 1003。改用 SQPNP 重解正深度解。
|
||||
if float(tvec[2, 0]) < 0:
|
||||
ok2, rvec2, tvec2 = cv2.solvePnP(
|
||||
_MODEL_POINTS, image_points, cam_matrix, dist,
|
||||
flags=cv2.SOLVEPNP_SQPNP,
|
||||
)
|
||||
if ok2 and float(tvec2[2, 0]) > 0:
|
||||
rvec = rvec2
|
||||
rot, _ = cv2.Rodrigues(rvec)
|
||||
# 在「相机坐标系」(x右 y下 z内) 下抽取 Tait-Bryan 欧拉角，物理含义对齐：
|
||||
# yaw = 绕 Y（竖轴）转 → 左右扭头
|
||||
|
||||
+8
-9
@@ -1,16 +1,15 @@
|
||||
[Unit]
|
||||
Description=Hair Worker (GPU) - 四庭七眼测量 接口1
|
||||
After=network.target
|
||||
Description=hair GPU worker FastAPI (0.0.0.0:8187)
|
||||
After=network-online.target comfyui.service change_hair-hair.service
|
||||
Wants=comfyui.service change_hair-hair.service
|
||||
|
||||
[Service]
|
||||
Type=simple
|
||||
User=xsl
|
||||
WorkingDirectory=/home/xsl/hair
|
||||
# 鉴权密码：优先 worker_config.json；也可在此用环境变量覆盖
|
||||
# Environment=WORKER_ACCEPT_PASSWORDS=your-strong-secret
|
||||
ExecStart=/home/xsl/hair/venv/bin/uvicorn app:app --host 0.0.0.0 --port 8187
|
||||
Restart=always
|
||||
RestartSec=3
|
||||
User=ubuntu
|
||||
WorkingDirectory=/home/ubuntu/hair
|
||||
ExecStart=/home/ubuntu/hair/venv/bin/uvicorn app:app --host 0.0.0.0 --port 8187
|
||||
Restart=on-failure
|
||||
RestartSec=5
|
||||
|
||||
[Install]
|
||||
WantedBy=multi-user.target
|
||||
|
||||
+1
-1
@@ -410,7 +410,7 @@
|
||||
},
|
||||
"60": {
|
||||
"inputs": {
|
||||
"text": "补充遮罩区域的头发，加一点美颜"
|
||||
"text": "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜"
|
||||
},
|
||||
"class_type": "JjkText",
|
||||
"_meta": {
|
||||
|
||||
+19
-5
@@ -11,6 +11,7 @@ from __future__ import annotations
|
||||
|
||||
import copy
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import random
|
||||
import time
|
||||
@@ -18,7 +19,7 @@ import uuid
|
||||
|
||||
import httpx
|
||||
|
||||
COMFYUI_URL = os.getenv("COMFYUI_URL", "http://10.60.74.221:8188").rstrip("/")
|
||||
COMFYUI_URL = os.getenv("COMFYUI_URL", "http://127.0.0.1:8188").rstrip("/")
|
||||
_WORKFLOW_DEFAULT = os.getenv(
|
||||
"ADD_HAIR_WORKFLOW",
|
||||
os.path.join(os.path.dirname(os.path.dirname(__file__)), "add_hair.json"),
|
||||
@@ -85,11 +86,13 @@ def _get_output_node(workflow_path: str | None = None) -> str:
|
||||
|
||||
|
||||
def run(rgba_png_bytes: bytes, timeout: float = COMFY_TIMEOUT, prompt: str = None,
|
||||
workflow_path: str | None = None) -> bytes:
|
||||
workflow_path: str | None = None, front: bool = False) -> bytes:
|
||||
"""提交一次生发任务，返回输出 PNG 字节。失败抛异常。
|
||||
|
||||
prompt：非 None 时替换工作流节点60(JjkText)的文本；None 时用工作流内置默认提示词。
|
||||
workflow_path：工作流 JSON 路径，None 则用默认 add_hair.json。
|
||||
front：True 时任务插到 ComfyUI 队列最前（server 端 "front" 字段，队列号取负）。
|
||||
接口2 对时延敏感用 True，避免排在接口3/5 的批量任务后面；其余接口保持 False。
|
||||
"""
|
||||
path = workflow_path or _WORKFLOW_DEFAULT
|
||||
output_node = _get_output_node(path)
|
||||
@@ -104,6 +107,14 @@ def run(rgba_png_bytes: bytes, timeout: float = COMFY_TIMEOUT, prompt: str = Non
|
||||
name = (up.get("subfolder") + "/" if up.get("subfolder") else "") + up["name"]
|
||||
|
||||
# 2. 改工作流：节点26 输入图 + 随机 seed
|
||||
try:
|
||||
import io as _io
|
||||
from PIL import Image as _Img
|
||||
_sz = _Img.open(_io.BytesIO(rgba_png_bytes)).size
|
||||
logging.getLogger("hair.worker").info(
|
||||
"ComfyUI 输入尺寸 %dx%d workflow=%s", _sz[0], _sz[1], os.path.basename(path))
|
||||
except Exception: # noqa: BLE001
|
||||
pass
|
||||
wf = copy.deepcopy(_load_workflow(path))
|
||||
wf[_INPUT_NODE]["inputs"]["image"] = name
|
||||
wf[_SEED_NODE]["inputs"]["noise_seed"] = random.randint(0, 2**63 - 1)
|
||||
@@ -125,8 +136,11 @@ def run(rgba_png_bytes: bytes, timeout: float = COMFY_TIMEOUT, prompt: str = Non
|
||||
except Exception: # noqa: BLE001
|
||||
pass
|
||||
|
||||
# 3. 提交
|
||||
r = cli.post("/prompt", json={"prompt": wf, "client_id": client_id})
|
||||
# 3. 提交（front=True 时插队到队列最前）
|
||||
payload = {"prompt": wf, "client_id": client_id}
|
||||
if front:
|
||||
payload["front"] = True
|
||||
r = cli.post("/prompt", json=payload)
|
||||
r.raise_for_status()
|
||||
prompt_id = r.json()["prompt_id"]
|
||||
|
||||
@@ -145,7 +159,7 @@ def run(rgba_png_bytes: bytes, timeout: float = COMFY_TIMEOUT, prompt: str = Non
|
||||
outputs = entry.get("outputs")
|
||||
if outputs and output_node in outputs:
|
||||
break
|
||||
time.sleep(1.0)
|
||||
time.sleep(0.05)
|
||||
if not outputs or output_node not in outputs:
|
||||
raise TimeoutError(f"ComfyUI 出图超时({timeout}s) prompt_id={prompt_id}")
|
||||
|
||||
|
||||
@@ -186,6 +186,53 @@ def smooth_hairline_corner_aware(
|
||||
return out
|
||||
|
||||
|
||||
def clamp_hairline_to_silhouette(
|
||||
hairline_norm: np.ndarray,
|
||||
parse_map: np.ndarray,
|
||||
margin_px: float = 2.0,
|
||||
) -> np.ndarray:
|
||||
"""把发际线点的 y 钳制在 (skin∪hair) silhouette 上沿之下（不含 margin 以上）。
|
||||
|
||||
根因（见 issue：男性 ellipse 发际线贴到头部外面）：`sample_hairline` 对射线
|
||||
未命中 hair 像素的锚点会 fallback 成「锚点 + 固定 0.18 归一化偏移」，与头部实际
|
||||
大小/位置无关 —— 短发/剃光头场景下这个偏移量常常把点顶到头部轮廓外面的背景里，
|
||||
在有效/失效锚点交界处形成尖角，被贴图上的不透明像素蒙到就会露出戳出头部的线条。
|
||||
|
||||
本函数在几何检测之后追加一步「安全网」：对每个点按其 x 所在列，取 silhouette
|
||||
（SegFormer skin∪hair 类，近似头部实际轮廓）上沿 y，若点比这个上沿还高（y 更
|
||||
小），直接钳制到 上沿 + margin_px —— 保证曲线永远不会跑到头部轮廓外面的背景。
|
||||
"""
|
||||
h, w = parse_map.shape
|
||||
cols_with_head, top_y = _head_top_y_per_column(parse_map, use_full_hair=True)
|
||||
if cols_with_head.size == 0:
|
||||
return hairline_norm
|
||||
out = hairline_norm.copy()
|
||||
for i in range(out.shape[0]):
|
||||
x_px = float(out[i, 0]) * w
|
||||
idx = int(np.searchsorted(cols_with_head, x_px))
|
||||
idx = min(max(idx, 0), cols_with_head.size - 1)
|
||||
sil_y = float(top_y[idx]) + margin_px
|
||||
y_px = float(out[i, 1]) * h
|
||||
if y_px < sil_y:
|
||||
out[i, 1] = sil_y / h
|
||||
return out
|
||||
|
||||
|
||||
def sample_hairline_clamped(
|
||||
landmarks_norm: np.ndarray,
|
||||
parse_map: np.ndarray,
|
||||
fallback_extrapolation: float = 0.18,
|
||||
) -> tuple[np.ndarray, np.ndarray]:
|
||||
"""策略 A（baseline + 头部轮廓钳制）：与默认 `sample_hairline` 完全一致的检测，
|
||||
额外用 `clamp_hairline_to_silhouette` 兜底 —— 检测失效 fallback 出的点不再可能
|
||||
跑到头部外面的背景，而是贴着头部实际轮廓顶部。改动小、风险低，只在检测失效/
|
||||
fallback 越界时才生效，正常长发照片的结果与 baseline 完全一致。
|
||||
"""
|
||||
hairline, valid = sample_hairline(landmarks_norm, parse_map, fallback_extrapolation)
|
||||
hairline = clamp_hairline_to_silhouette(hairline, parse_map)
|
||||
return hairline, valid
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Alternative hairline sampling strategies.
|
||||
#
|
||||
|
||||
@@ -0,0 +1,78 @@
|
||||
"""直接调 ComfyUI 重绘 — 替代 local_test HTTP 服务。
|
||||
|
||||
将 local_test/app.py 的核心逻辑（遮罩处理 + ComfyUI 调用）提取为 Python 函数，
|
||||
不再需要独立 Flask 服务。使用 0716add-hair-api.json 工作流（steps=4）。
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import io
|
||||
import logging
|
||||
import os
|
||||
|
||||
import numpy as np
|
||||
from PIL import Image, ImageFilter
|
||||
|
||||
from . import comfyui
|
||||
|
||||
logger = logging.getLogger("hair.worker")
|
||||
|
||||
_DEFAULT_PROMPT = "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜"
|
||||
_REPO = os.path.dirname(os.path.dirname(__file__))
|
||||
_REPAINT_WORKFLOW = os.path.join(_REPO, "0716add-hair-api.json")
|
||||
|
||||
|
||||
def _process_mask_to_rgba(image_bytes: bytes, mask_bytes: bytes) -> bytes:
|
||||
"""将分开的 image + mask 处理为 ComfyUI 用的 RGBA PNG bytes。
|
||||
|
||||
复制 local_test/app.py 的遮罩处理逻辑：
|
||||
1. 加载 image 为 RGB
|
||||
2. 加载 mask 为 RGBA，取所有通道 max 值（支持红/白/alpha 遮罩）
|
||||
3. resize mask 到与 image 一致
|
||||
4. 高斯模糊(radius=4) 柔化边缘
|
||||
5. alpha = 255 - mask（绘制区=255 → alpha=0 → 重绘区）
|
||||
6. 合成 RGBA PNG
|
||||
"""
|
||||
image = Image.open(io.BytesIO(image_bytes)).convert("RGB")
|
||||
mask_img = Image.open(io.BytesIO(mask_bytes)).convert("RGBA")
|
||||
mask_arr = np.array(mask_img)
|
||||
mask_data = np.max(mask_arr, axis=2) # (H, W) uint8
|
||||
|
||||
mask_data_img = Image.fromarray(mask_data, mode="L")
|
||||
if mask_data_img.size != image.size:
|
||||
mask_data_img = mask_data_img.resize(image.size, Image.LANCZOS)
|
||||
mask_data_img = mask_data_img.filter(ImageFilter.GaussianBlur(radius=4))
|
||||
|
||||
# ComfyUI LoadImage: mask = 1.0 - (alpha/255)
|
||||
# alpha=0 -> mask=1.0 (inpaint), alpha=255 -> mask=0.0 (keep)
|
||||
comfyui_alpha = Image.eval(mask_data_img, lambda x: 255 - x)
|
||||
|
||||
r, g, b = image.split()
|
||||
rgba = Image.merge("RGBA", (r, g, b, comfyui_alpha))
|
||||
|
||||
buf = io.BytesIO()
|
||||
rgba.save(buf, format="PNG")
|
||||
return buf.getvalue()
|
||||
|
||||
|
||||
def run_redraw(image_bytes: bytes, mask_bytes: bytes,
|
||||
prompt: str | None = None, timeout: float = 300.0,
|
||||
front: bool = False) -> bytes:
|
||||
"""直接调 ComfyUI 重绘 — 替代 local_test /api/generate。
|
||||
|
||||
Args:
|
||||
image_bytes: 人物图片字节（JPG/PNG）
|
||||
mask_bytes: 遮罩图片字节（支持红/白/alpha 遮罩格式）
|
||||
prompt: 提示词，None 用默认 "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜"
|
||||
timeout: ComfyUI 超时秒数
|
||||
front: True 时任务插到 ComfyUI 队列最前（接口2 时延敏感路径用）
|
||||
|
||||
Returns:
|
||||
重绘后的 PNG 图片字节
|
||||
|
||||
Raises:
|
||||
RuntimeError: ComfyUI 执行失败
|
||||
TimeoutError: ComfyUI 超时
|
||||
"""
|
||||
rgba_png = _process_mask_to_rgba(image_bytes, mask_bytes)
|
||||
return comfyui.run(rgba_png, timeout=timeout, prompt=prompt,
|
||||
workflow_path=_REPAINT_WORKFLOW, front=front)
|
||||
+171
-38
@@ -14,7 +14,9 @@ from . import constants as C
|
||||
from . import comfyui
|
||||
from .face_landmarks import FaceLandmarker
|
||||
from .face_parsing import FaceParser
|
||||
from .hairline_2d import sample_hairline, smooth_hairline
|
||||
from .hairline_2d import (
|
||||
smooth_hairline, sample_hairline_clamped,
|
||||
)
|
||||
from .lift_3d import lift_hairline_to_3d, build_middle_row, assemble_full
|
||||
from .render import load_ext_mesh, load_texture_rgba, render_hairline_overlay, build_overlay_layer
|
||||
from .mask import build_inpaint_mask, compose_comfy_rgba, mask_from_curve
|
||||
@@ -40,27 +42,47 @@ _REPO = os.path.dirname(os.path.dirname(__file__))
|
||||
_TEXTURE_DIR = os.path.join(_REPO, "hairline_texture")
|
||||
_BLACK_TEXTURE_DIR = os.path.join(_REPO, "hairline_texture_black")
|
||||
|
||||
# 外部重绘服务（local_test，0716add-hair.json 工作流）。接口2 female 用它替代原 Flux-2 重绘。
|
||||
# 重绘服务已独立到远程机器；可用 HAIR_LOCAL_REDRAW_URL 覆盖。
|
||||
# gpu_worker 同内网走 10.60.74.221，外网（本地开发机）需走公网 117.50.183.232。
|
||||
_LOCAL_REDRAW_URL = os.getenv("HAIR_LOCAL_REDRAW_URL", "http://10.60.74.221:8899").rstrip("/")
|
||||
# 三接口（接口2女重绘 / 接口2男 / 接口3）统一的 ComfyUI 重绘 prompt。
|
||||
# 关键：ComfyUI 单卡显存装不下 Flux(7.7G)+qwen CLIP(3.9G) 同驻，靠缓存 CLIP 文本条件避免重载。
|
||||
# prompt 不同会使缓存失效 → 重载 CLIP 并挤出 Flux（每次 +4s）。三接口用同一字符串即可全程命中。
|
||||
# 与 app.py 接口2/接口3 的默认 prompt 保持一致；可用 REDRAW_PROMPT 覆盖。
|
||||
_REDRAW_PROMPT = os.getenv("REDRAW_PROMPT", "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜")
|
||||
|
||||
# 接口2 女重绘整条管线（swapHair + ComfyUI）送模型前限边。真实照片常达 1257x1495：
|
||||
# 全分辨率 ComfyUI 重绘要 13~21s 且激活显存把模型挤出。女性路径含 swapHair(SD WebUI ~5.3s
|
||||
# 固定地板) + ComfyUI 两段串行。1024 档画质更好但部分大图会踩 12s 线，
|
||||
# 默认压到 896 兜底（ComfyUI ~4s，女性总耗时 9~11s）；追画质可设 REDRAW_MAX_SIDE=1024。
|
||||
_REDRAW_MAX_SIDE = int(os.getenv("REDRAW_MAX_SIDE", "896"))
|
||||
|
||||
def _call_local_redraw(image_png_bytes, mask_png_bytes, timeout=300.0):
|
||||
"""调外部重绘服务（local_test /api/generate）：传 final 图 + 纯红遮罩 PNG，
|
||||
返回重绘后的 PNG bytes。失败抛异常（调用方负责 try/except 跳过）。
|
||||
"""直接调 ComfyUI 重绘（替代原 local_test HTTP 服务）。
|
||||
|
||||
传 final 图 + 纯红遮罩 PNG，返回重绘后的 PNG bytes。
|
||||
失败抛异常（调用方负责 try/except 跳过）。
|
||||
"""
|
||||
import requests
|
||||
files = {
|
||||
"image": ("final.jpg", image_png_bytes, "image/jpeg"),
|
||||
"mask": ("mask.png", mask_png_bytes, "image/png"),
|
||||
}
|
||||
resp = requests.post(_LOCAL_REDRAW_URL + "/api/generate", files=files, timeout=timeout)
|
||||
resp.raise_for_status()
|
||||
if "image/" not in resp.headers.get("Content-Type", ""):
|
||||
# 服务返回了 JSON 错误
|
||||
raise RuntimeError(f"local_test 返回非图片: {resp.text[:200]}")
|
||||
return resp.content
|
||||
from .redraw import run_redraw
|
||||
img = cv2.imdecode(np.frombuffer(image_png_bytes, np.uint8), cv2.IMREAD_UNCHANGED)
|
||||
scale = 1.0
|
||||
orig_w = orig_h = 0
|
||||
if img is not None:
|
||||
orig_h, orig_w = img.shape[:2]
|
||||
m = max(orig_h, orig_w)
|
||||
if _REDRAW_MAX_SIDE > 0 and m > _REDRAW_MAX_SIDE:
|
||||
scale = _REDRAW_MAX_SIDE / float(m)
|
||||
nw, nh = max(1, round(orig_w * scale)), max(1, round(orig_h * scale))
|
||||
msk = cv2.imdecode(np.frombuffer(mask_png_bytes, np.uint8), cv2.IMREAD_UNCHANGED)
|
||||
img_s = cv2.resize(img, (nw, nh), interpolation=cv2.INTER_AREA)
|
||||
msk_s = cv2.resize(msk, (nw, nh), interpolation=cv2.INTER_NEAREST)
|
||||
image_png_bytes = cv2.imencode(".png", img_s)[1].tobytes()
|
||||
mask_png_bytes = cv2.imencode(".png", msk_s)[1].tobytes()
|
||||
logger.info("接口2女 缩图送 Comfy: %dx%d → %dx%d (max_side=%d)",
|
||||
orig_w, orig_h, nw, nh, _REDRAW_MAX_SIDE)
|
||||
# front=True：接口2 时延敏感，插到 ComfyUI 队列最前，避免排在接口3/5 的批量任务后面
|
||||
out = run_redraw(image_png_bytes, mask_png_bytes, timeout=timeout,
|
||||
prompt=_REDRAW_PROMPT, front=True)
|
||||
if scale < 1.0 and out:
|
||||
out = _upscale_png_to(out, orig_w, orig_h)
|
||||
return out
|
||||
|
||||
# 发际线贴图档位：middle=默认(hairline_texture/)，high/low 各自独立文件夹。
|
||||
_TEXTURE_DIRS = {
|
||||
@@ -69,9 +91,8 @@ _TEXTURE_DIRS = {
|
||||
"low": os.path.join(_REPO, "hairline_texture_low"),
|
||||
}
|
||||
|
||||
# ⚠️ 本 worker 是 RTX 5090(sm_120)，torch 2.2.2(cu121) 只编到 sm_90，CUDA 跑算子会报
|
||||
# "no kernel image"。SegFormer 默认走 CPU（~2.5s/张）。换 torch cu128 后可设 SEG_DEVICE=cuda。
|
||||
_SEG_DEVICE = os.getenv("SEG_DEVICE", "cpu")
|
||||
# torch 2.7.1+cu128 已支持 RTX 5090 (sm_120)，SegFormer 走 GPU（~0.05s/张）
|
||||
_SEG_DEVICE = os.getenv("SEG_DEVICE", "cuda")
|
||||
|
||||
_landmarker = None
|
||||
_parser = None
|
||||
@@ -133,13 +154,19 @@ def extract_502(image_bgr: np.ndarray):
|
||||
|
||||
|
||||
def extract_context(image_bgr: np.ndarray):
|
||||
"""照片(BGR) → {landmarks, parse_map, points, valid}。无人脸返回 None。"""
|
||||
"""照片(BGR) → {landmarks, parse_map, points, valid}。无人脸返回 None。
|
||||
|
||||
发际线几何检测固定用 `sample_hairline_clamped`（射线检测 + 头部轮廓钳制）：
|
||||
短发/剃光头照片（如 man_test.jpg）中间锚点检测失效时，纯射线检测的固定 fallback
|
||||
偏移会把点顶到头部轮廓外面的背景，产生"发际线贴到头部外面"的视觉 bug；钳制兜底后
|
||||
fallback 点不会再跑出头部轮廓，正常长发照片结果与旧行为一致。
|
||||
"""
|
||||
rgb = cv2.cvtColor(image_bgr, cv2.COLOR_BGR2RGB)
|
||||
landmarks = get_landmarker().detect(rgb)
|
||||
if landmarks is None:
|
||||
return None
|
||||
parse_map = get_parser().parse(rgb)
|
||||
hairline_2d, valid = sample_hairline(landmarks, parse_map)
|
||||
hairline_2d, valid = sample_hairline_clamped(landmarks, parse_map)
|
||||
hairline_2d = smooth_hairline(hairline_2d, valid)
|
||||
hairline_3d = lift_hairline_to_3d(landmarks, hairline_2d)
|
||||
middle_3d = build_middle_row(landmarks, hairline_3d)
|
||||
@@ -204,9 +231,14 @@ def generate_grow_results(image_bgr: np.ndarray, gender: str, use_mask: bool = T
|
||||
if not use_mask:
|
||||
try:
|
||||
h, w = image_bgr.shape[:2]
|
||||
img_s, msk_s, gsc = _prep_comfy_input(image_bgr, np.zeros((h, w), np.uint8))
|
||||
buf = io.BytesIO()
|
||||
compose_comfy_rgba(image_bgr, np.zeros((h, w), np.uint8)).save(buf, format="PNG")
|
||||
shared_grown = comfyui.run(buf.getvalue(), prompt=prompt, workflow_path=workflow_path)
|
||||
compose_comfy_rgba(img_s, msk_s).save(buf, format="PNG", compress_level=1)
|
||||
# front=True：接口2 时延敏感，插到 ComfyUI 队列最前
|
||||
shared_grown = comfyui.run(buf.getvalue(), prompt=prompt,
|
||||
workflow_path=workflow_path, front=True)
|
||||
if gsc < 1.0 and shared_grown:
|
||||
shared_grown = _upscale_png_to(shared_grown, w, h)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("接口2 生发图失败(无遮罩)：%s", e)
|
||||
|
||||
@@ -224,9 +256,14 @@ def generate_grow_results(image_bgr: np.ndarray, gender: str, use_mask: bool = T
|
||||
black = load_texture_rgba(_black_texture_path(white_path))
|
||||
marked, mask = build_inpaint_mask(
|
||||
image_bgr, ctx["landmarks"], ctx["parse_map"], ctx["points"], black)
|
||||
m_s, msk_s, gsc = _prep_comfy_input(marked, mask)
|
||||
buf = io.BytesIO()
|
||||
compose_comfy_rgba(marked, mask).save(buf, format="PNG")
|
||||
grown_png = comfyui.run(buf.getvalue(), prompt=prompt, workflow_path=workflow_path)
|
||||
compose_comfy_rgba(m_s, msk_s).save(buf, format="PNG", compress_level=1)
|
||||
# front=True：接口2 时延敏感，插到 ComfyUI 队列最前
|
||||
grown_png = comfyui.run(buf.getvalue(), prompt=prompt,
|
||||
workflow_path=workflow_path, front=True)
|
||||
if gsc < 1.0 and grown_png:
|
||||
grown_png = _upscale_png_to(grown_png, w, h)
|
||||
except Exception as e: # noqa: BLE001 单张失败不拖垮整请求
|
||||
logger.warning("接口2 生发图失败 type=%s：%s", key, e)
|
||||
|
||||
@@ -241,20 +278,24 @@ def generate_grow_results_swap(image_bgr: np.ndarray, hair_styles: list[int] | N
|
||||
|
||||
grown 图来源（新流程）：对每个选中发型把 female key 映射到 change_hair 的 chang_* hair_id，
|
||||
调 face_analysis.hairline_grow.generate_hairline_redraw（= 接口12 final 管线，参数用
|
||||
redraw_defaults）拿到 ④ final（接缝融合基底）+ ⑤-② 纯红遮罩 PNG，再**后端调外部重绘服务
|
||||
local_test**（0716add-hair.json 工作流）完成发际线带重绘，重绘结果作为生发图。
|
||||
redraw_defaults）拿到 ④ final（接缝融合基底）+ ⑤-② 纯红遮罩 PNG，再**后端直接调
|
||||
ComfyUI**（0716add-hair-api.json 工作流）完成发际线带重绘，重绘结果作为生发图。
|
||||
|
||||
overlay 仍是发际线曲线透明层（与 generate_grow_results 完全一致）。
|
||||
Returns: list[dict] {"hairline_type","order","overlay","grown_png"(jpg bytes 或 None)}；
|
||||
无人脸返回 None。单个发型换发型/重绘失败时 grown_png=None，不抛异常。
|
||||
"""
|
||||
from face_analysis.hairline_grow import generate_hairline_redraw, NoFaceError
|
||||
from face_analysis.head_mask import SEGFORMER_HAIR
|
||||
|
||||
ctx = extract_context(image_bgr)
|
||||
if ctx is None:
|
||||
return None
|
||||
uv, ext_faces = load_ext_mesh()
|
||||
|
||||
# 复用 extract_context 已算好的 SegFormer parse_map，避免 generate_hairline_redraw 内部重复分割
|
||||
hair_mask_reuse = (ctx["parse_map"] == SEGFORMER_HAIR)
|
||||
|
||||
textures = get_texture_map()["female"] # [(key, path), ...] 已排序
|
||||
if hair_styles is not None:
|
||||
items = [(s, textures[s - 1]) for s in hair_styles]
|
||||
@@ -263,6 +304,20 @@ def generate_grow_results_swap(image_bgr: np.ndarray, hair_styles: list[int] | N
|
||||
|
||||
results = []
|
||||
h, w = image_bgr.shape[:2]
|
||||
|
||||
# 重绘管线（swapHair + ComfyUI）统一降分辨率：真实照片 swap(SD WebUI)~5s、blend、ComfyUI
|
||||
# 均随分辨率线性下降。overlay 预览仍用全分辨率；grown_png 最后放大回原尺寸。
|
||||
redraw_img = image_bgr
|
||||
hair_mask_redraw = hair_mask_reuse
|
||||
if _REDRAW_MAX_SIDE > 0 and max(h, w) > _REDRAW_MAX_SIDE:
|
||||
redraw_img, _rs = _downscale_max_side(image_bgr, _REDRAW_MAX_SIDE)
|
||||
_nh, _nw = redraw_img.shape[:2]
|
||||
if hair_mask_redraw is not None:
|
||||
hair_mask_redraw = cv2.resize(hair_mask_reuse.astype(np.uint8), (_nw, _nh),
|
||||
interpolation=cv2.INTER_NEAREST).astype(bool)
|
||||
logger.info("接口2女 管线降分辨率: %dx%d → %dx%d (max_side=%d)",
|
||||
w, h, _nw, _nh, _REDRAW_MAX_SIDE)
|
||||
|
||||
for order, (key, white_path) in items:
|
||||
white = load_texture_rgba(white_path)
|
||||
overlay = build_overlay_layer(h, w, ctx["points"], ext_faces, uv, white)
|
||||
@@ -273,7 +328,10 @@ def generate_grow_results_swap(image_bgr: np.ndarray, hair_styles: list[int] | N
|
||||
logger.warning("接口2 换发型：female key=%s 无对应 chang_id，跳过生发图", key)
|
||||
else:
|
||||
try:
|
||||
data = generate_hairline_redraw(image_bgr, chang_id, **redraw_defaults)
|
||||
import time as _t
|
||||
_ts0 = _t.perf_counter()
|
||||
data = generate_hairline_redraw(redraw_img, chang_id, hair_mask=hair_mask_redraw, **redraw_defaults)
|
||||
_ts1 = _t.perf_counter()
|
||||
steps = data.get("steps") or {}
|
||||
# ④ final（接缝融合基底）+ ⑤-② 纯红遮罩 PNG
|
||||
final_b64 = steps.get("final_base64") or ""
|
||||
@@ -289,10 +347,20 @@ def generate_grow_results_swap(image_bgr: np.ndarray, hair_styles: list[int] | N
|
||||
mask_b64 = mask_b64.split(",", 1)[1]
|
||||
final_bytes = base64.b64decode(final_b64)
|
||||
mask_bytes = base64.b64decode(mask_b64)
|
||||
# 后端调外部重绘服务（local_test），返回重绘后的 PNG
|
||||
# 后端直接调 ComfyUI 重绘，返回重绘后的 PNG
|
||||
_tr0 = _t.perf_counter()
|
||||
grown_png = _call_local_redraw(final_bytes, mask_bytes)
|
||||
_tr1 = _t.perf_counter()
|
||||
_tm = data.get("timings_ms") or {}
|
||||
logger.info("接口2女 分段计时 type=%s: swapHair管线=%.2fs (mask=%dms swap=%dms blend=%dms), ComfyUI重绘=%.2fs",
|
||||
key, _ts1 - _ts0,
|
||||
_tm.get("mask", 0), _tm.get("swap", 0), _tm.get("blend", 0),
|
||||
_tr1 - _tr0)
|
||||
if grown_png is None:
|
||||
logger.warning("接口2 换发型：type=%s 重绘结果为空", key)
|
||||
elif redraw_img is not image_bgr:
|
||||
# 管线在降分辨率图上跑，结果放大回原尺寸
|
||||
grown_png = _upscale_png_to(grown_png, w, h)
|
||||
except NoFaceError:
|
||||
logger.warning("接口2 换发型：type=%s 未检出人脸", key)
|
||||
except Exception as e: # noqa: BLE001 单张失败不拖垮整请求
|
||||
@@ -319,7 +387,7 @@ def _grow_from_texture(image_bgr: np.ndarray, ctx: dict, white_path: str | None,
|
||||
h, w = image_bgr.shape[:2]
|
||||
marked, mask = image_bgr, np.zeros((h, w), np.uint8)
|
||||
buf = io.BytesIO()
|
||||
compose_comfy_rgba(marked, mask).save(buf, format="PNG")
|
||||
compose_comfy_rgba(marked, mask).save(buf, format="PNG", compress_level=1)
|
||||
return comfyui.run(buf.getvalue(), prompt=prompt)
|
||||
except Exception as e: # noqa: BLE001 单张失败不拖垮整请求
|
||||
logger.warning("接口5 生发图失败：%s", e)
|
||||
@@ -328,13 +396,16 @@ def _grow_from_texture(image_bgr: np.ndarray, ctx: dict, white_path: str | None,
|
||||
|
||||
def generate_hairline_pngs(image_bgr: np.ndarray, gender: str,
|
||||
hair_styles: list[int], use_mask: bool = True,
|
||||
prompt: str | None = None):
|
||||
prompt: str | None = None,
|
||||
generate_grow_image: bool = True):
|
||||
"""接口5：对选中发型返回 middle/high/low 三档发际线透明叠图 + 生发图(同接口2)。
|
||||
|
||||
入参同接口2：先选 gender，再多选 hair_styles（必填，1-indexed 按贴图排序）。
|
||||
每个选中发型返回三档叠图（middle/high/low，RGBA 透明层只含发际线曲线）与一张生发图；
|
||||
三档贴图同名，生发黑模板固定取自 hairline_texture_black/（middle），故生发目标固定 middle 档。
|
||||
use_mask/prompt：同接口2 的生发参数。
|
||||
generate_grow_image（默认 True）：是否生成生发图（ComfyUI，最耗时）。False 时跳过生发，
|
||||
各发型 grown_png 恒为 None，可大幅降低耗时（仅留三档发际线叠图与中心点）。
|
||||
Returns: {"images":[{hairline_type,order,overlays:{middle,high,low}((H,W,4) RGBA 透明层),grown_png}],
|
||||
"best_centers":{"middle":(x,y),"high":(x,y),"low":(x,y)}}；无人脸 None。
|
||||
best_centers 取首个选中发型三档各自的发际线中点。
|
||||
@@ -356,8 +427,9 @@ def generate_hairline_pngs(image_bgr: np.ndarray, gender: str,
|
||||
tex_by_level = {lv: get_texture_map(lv)[gender] for lv in _TEXTURE_DIRS}
|
||||
|
||||
# use_mask=False：干净原图+空遮罩与贴图无关，只跑一次 ComfyUI，选中项复用
|
||||
# generate_grow_image=False：完全跳过生发（最耗时），grown_png 恒为 None
|
||||
shared_grown = None
|
||||
if not use_mask:
|
||||
if generate_grow_image and not use_mask:
|
||||
shared_grown = _grow_from_texture(image_bgr, ctx, None, use_mask=False, prompt=prompt)
|
||||
|
||||
def _center_of(overlay):
|
||||
@@ -376,9 +448,13 @@ def generate_hairline_pngs(image_bgr: np.ndarray, gender: str,
|
||||
for lv in _TEXTURE_DIRS:
|
||||
white = load_texture_rgba(tex_by_level[lv][s - 1][1])
|
||||
overlays[lv] = build_overlay_layer(h, w, ctx["points"], ext_faces, uv, white)
|
||||
# 生发：固定 middle 黑模板
|
||||
grown_png = shared_grown if not use_mask else \
|
||||
_grow_from_texture(image_bgr, ctx, mid_path, use_mask=True, prompt=prompt)
|
||||
# 生发：固定 middle 黑模板（generate_grow_image=False 时跳过，恒 None）
|
||||
if not generate_grow_image:
|
||||
grown_png = None
|
||||
elif not use_mask:
|
||||
grown_png = shared_grown
|
||||
else:
|
||||
grown_png = _grow_from_texture(image_bgr, ctx, mid_path, use_mask=True, prompt=prompt)
|
||||
images.append({"hairline_type": key, "order": s,
|
||||
"overlays": overlays, "grown_png": grown_png})
|
||||
# best_centers：首个选中发型三档（middle/high/low）发际线中点
|
||||
@@ -387,18 +463,73 @@ def generate_hairline_pngs(image_bgr: np.ndarray, gender: str,
|
||||
return {"images": images, "best_centers": best_centers}
|
||||
|
||||
|
||||
# 接口3 送 ComfyUI 前限边，降低峰值显存，避免与接口2 切换时把 Flux 挤出。
|
||||
# 统一 prompt 后 Flux 不再被 CLIP 挤出，接口3 可用较高分辨率。可用 GROW_B_MAX_SIDE 覆盖。
|
||||
_GROW_B_MAX_SIDE = int(os.getenv("GROW_B_MAX_SIDE", "1024"))
|
||||
|
||||
def _downscale_max_side(img_bgr: np.ndarray, max_side: int) -> tuple[np.ndarray, float]:
|
||||
"""长边超过 max_side 时等比例缩小；返回 (图, scale)，scale=新/旧。"""
|
||||
h, w = img_bgr.shape[:2]
|
||||
m = max(h, w)
|
||||
if max_side <= 0 or m <= max_side:
|
||||
return img_bgr, 1.0
|
||||
scale = max_side / float(m)
|
||||
nw = max(1, int(round(w * scale)))
|
||||
nh = max(1, int(round(h * scale)))
|
||||
out = cv2.resize(img_bgr, (nw, nh), interpolation=cv2.INTER_AREA)
|
||||
return out, scale
|
||||
|
||||
|
||||
def _upscale_png_to(png_bytes: bytes, out_w: int, out_h: int) -> bytes:
|
||||
"""把 Comfy 输出 PNG 双线性拉回原图尺寸（仅展示对齐，不增加推理细节）。"""
|
||||
arr = np.frombuffer(png_bytes, np.uint8)
|
||||
img = cv2.imdecode(arr, cv2.IMREAD_UNCHANGED)
|
||||
if img is None:
|
||||
return png_bytes
|
||||
if img.shape[1] == out_w and img.shape[0] == out_h:
|
||||
return png_bytes
|
||||
resized = cv2.resize(img, (out_w, out_h), interpolation=cv2.INTER_LINEAR)
|
||||
ok, buf = cv2.imencode(".png", resized)
|
||||
return buf.tobytes() if ok else png_bytes
|
||||
|
||||
|
||||
def _prep_comfy_input(img_bgr: np.ndarray, mask: np.ndarray) -> tuple[np.ndarray, np.ndarray, float]:
|
||||
"""单段 ComfyUI 生发（接口2男 / 接口3）送图前限边到 GROW_B_MAX_SIDE。
|
||||
返回 (缩后图, 缩后遮罩, scale)；scale<1 时调用方需把结果放大回原尺寸。"""
|
||||
h, w = img_bgr.shape[:2]
|
||||
if _GROW_B_MAX_SIDE <= 0 or max(h, w) <= _GROW_B_MAX_SIDE:
|
||||
return img_bgr, mask, 1.0
|
||||
out, scale = _downscale_max_side(img_bgr, _GROW_B_MAX_SIDE)
|
||||
nh, nw = out.shape[:2]
|
||||
msk = cv2.resize(mask, (nw, nh), interpolation=cv2.INTER_NEAREST)
|
||||
logger.info("接口2男/接口3 缩图送 Comfy: %dx%d → %dx%d (max_side=%d)",
|
||||
w, h, nw, nh, _GROW_B_MAX_SIDE)
|
||||
return out, msk, scale
|
||||
|
||||
|
||||
def generate_grow_b(marked_bgr: np.ndarray, use_mask: bool = True, prompt: str = None):
|
||||
"""接口3：检测医生手绘发际线 → 遮罩 → 送 ComfyUI 生发（仅需划线图一张）。
|
||||
|
||||
检测路径只用来**建遮罩**；ComfyUI 输入图用 **marked 原图**（含医生手绘线，
|
||||
工作流提示词会清除黑线再生发）。
|
||||
|
||||
进 Comfy 前若长边 > GROW_B_MAX_SIDE（默认 896）会先等比例缩小，降低峰值显存；
|
||||
输出再拉回原图尺寸。
|
||||
|
||||
use_mask（默认 True）：是否启用自动检测的遮罩，用于测试对比。
|
||||
- True：检测手绘线 → 建遮罩 → alpha=255−mask（透明区=重绘区，节点44 画黄色参考区）。
|
||||
- False：跳过检测，直接送划线图，alpha 全 255（空遮罩，节点26 mask 为空），
|
||||
模型仅凭医生黑线参考生发。无需改工作流，唯一变量是遮罩。
|
||||
Returns: {"grown_png": bytes 或 None, "status": "ok"|"no_face"|"no_line"}。
|
||||
"""
|
||||
orig_h, orig_w = marked_bgr.shape[:2]
|
||||
marked_bgr, _scale = _downscale_max_side(marked_bgr, _GROW_B_MAX_SIDE)
|
||||
if _scale < 1.0:
|
||||
logger.info(
|
||||
"接口3 缩图送 Comfy: %dx%d → %dx%d (max_side=%d)",
|
||||
orig_w, orig_h, marked_bgr.shape[1], marked_bgr.shape[0], _GROW_B_MAX_SIDE,
|
||||
)
|
||||
|
||||
h, w = marked_bgr.shape[:2]
|
||||
if use_mask:
|
||||
rgb = cv2.cvtColor(marked_bgr, cv2.COLOR_BGR2RGB)
|
||||
@@ -416,8 +547,10 @@ def generate_grow_b(marked_bgr: np.ndarray, use_mask: bool = True, prompt: str =
|
||||
mask = np.zeros((h, w), np.uint8) # 空遮罩：alpha 全 255，跳过检测
|
||||
|
||||
buf = io.BytesIO()
|
||||
compose_comfy_rgba(marked_bgr, mask).save(buf, format="PNG") # marked 原图 + 遮罩
|
||||
compose_comfy_rgba(marked_bgr, mask).save(buf, format="PNG", compress_level=1) # marked + 遮罩
|
||||
grown_png = comfyui.run(buf.getvalue(), prompt=prompt)
|
||||
if _scale < 1.0 and grown_png:
|
||||
grown_png = _upscale_png_to(grown_png, orig_w, orig_h)
|
||||
return {"grown_png": grown_png, "status": "ok"}
|
||||
|
||||
|
||||
|
||||
+1
-1
@@ -206,7 +206,7 @@ def generate():
|
||||
return jsonify({"error": msg}), 400
|
||||
image_file = request.files["image"]
|
||||
mask_file = request.files["mask"]
|
||||
prompt_text = request.form.get("prompt", "填充遮罩区域的头发，皮肤加一点磨皮")
|
||||
prompt_text = request.form.get("prompt", "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜")
|
||||
log.info(
|
||||
"收到请求: image=%s mask=%s prompt=%r",
|
||||
image_file.filename, mask_file.filename, prompt_text,
|
||||
|
||||
+1
-1
@@ -27,7 +27,7 @@ def prep_and_upload():
|
||||
|
||||
|
||||
def run_once(fname, model, dtype, steps):
|
||||
wf = A.build_workflow(fname, "填充遮罩区域的头发，皮肤加一点磨皮")
|
||||
wf = A.build_workflow(fname, "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜")
|
||||
wf["16"]["inputs"]["unet_name"] = model
|
||||
wf["16"]["inputs"]["weight_dtype"] = dtype
|
||||
wf["1"]["inputs"]["steps"] = steps
|
||||
|
||||
@@ -33,7 +33,7 @@ def upload(scale=1.0):
|
||||
|
||||
|
||||
def run(fname, steps):
|
||||
wf = A.build_workflow(fname, "填充遮罩区域的头发，皮肤加一点磨皮")
|
||||
wf = A.build_workflow(fname, "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜")
|
||||
wf["16"]["inputs"]["unet_name"] = MODEL
|
||||
wf["16"]["inputs"]["weight_dtype"] = DTYPE
|
||||
wf["1"]["inputs"]["steps"] = steps
|
||||
|
||||
@@ -30,7 +30,7 @@ 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，皮肤加一点磨皮", seed=SEED)
|
||||
wf = A.build_workflow(fname, "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜", seed=SEED)
|
||||
wf["16"]["inputs"]["unet_name"] = MODEL
|
||||
wf["16"]["inputs"]["weight_dtype"] = DTYPE
|
||||
wf["1"]["inputs"]["steps"] = steps
|
||||
|
||||
@@ -55,7 +55,7 @@ button { padding: 10px 24px; border: none; border-radius: 6px; cursor: pointer;
|
||||
</div>
|
||||
<div class="controls" style="margin-top:16px">
|
||||
<label>提示词:</label>
|
||||
<input type="text" id="promptInput" value="填充遮罩区域的头发，皮肤加一点磨皮">
|
||||
<input type="text" id="promptInput" value="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜">
|
||||
</div>
|
||||
<div style="text-align:center; margin-top:16px">
|
||||
<button class="btn-generate" id="generateBtn" disabled>🚀 生成</button>
|
||||
|
||||
@@ -25,7 +25,7 @@ resp = requests.post(
|
||||
"image": ("original.jpg", img_data, "image/jpeg"),
|
||||
"mask": ("mask.png", mask_data, "image/png"),
|
||||
},
|
||||
data={"prompt": "填充遮罩区域的头发，皮肤加一点磨皮"},
|
||||
data={"prompt": "填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜"},
|
||||
timeout=600,
|
||||
)
|
||||
|
||||
|
||||
@@ -52,4 +52,35 @@
|
||||
}
|
||||
|
||||
window.downscaleImageFile = downscaleImageFile;
|
||||
|
||||
/**
|
||||
* 将接口返回的图片字段规范成 <img src> 可用值。
|
||||
* 同时兼容：
|
||||
* - 网关改写后的 *_url（http/https/相对路径）
|
||||
* - worker 直连的 *_base64（原始 base64，或已带 data:image/...;base64, 前缀）
|
||||
* @param {string|null|undefined} url
|
||||
* @param {string|null|undefined} b64
|
||||
* @param {string} [mimeHint='image/jpeg'] 原始 base64 时的 MIME 提示（会按魔数再嗅探）
|
||||
* @returns {string}
|
||||
*/
|
||||
function resolveImgSrc(url, b64, mimeHint) {
|
||||
var v = url || b64 || '';
|
||||
if (!v || typeof v !== 'string') return '';
|
||||
v = v.trim();
|
||||
if (!v) return '';
|
||||
// 已是可用 URL / data URI / blob / 协议相对 URL
|
||||
if (/^(https?:|blob:|data:|\/\/)/i.test(v)) return v;
|
||||
// 同站相对路径（仅匹配明确的 /static/...；勿把 JPEG base64 的 /9j/ 前缀当路径）
|
||||
if (/^\/static\//.test(v)) return v;
|
||||
// 原始 base64：去掉可能残留的 data URI 前缀后再拼，避免双重前缀导致无法显示
|
||||
var raw = v.replace(/^data:image\/[a-zA-Z0-9+.-]+;base64,/i, '');
|
||||
if (!raw) return '';
|
||||
var mime = mimeHint || 'image/jpeg';
|
||||
if (raw.indexOf('iVBOR') === 0) mime = 'image/png';
|
||||
else if (raw.indexOf('/9j/') === 0) mime = 'image/jpeg';
|
||||
else if (raw.indexOf('R0lGOD') === 0) mime = 'image/gif';
|
||||
else if (raw.indexOf('UklGR') === 0) mime = 'image/webp';
|
||||
return 'data:' + mime + ';base64,' + raw;
|
||||
}
|
||||
window.resolveImgSrc = resolveImgSrc;
|
||||
})();
|
||||
|
||||
+16
-40
@@ -57,7 +57,6 @@
|
||||
<a href="#if4">接口4</a>
|
||||
<a href="#if5">接口5</a>
|
||||
<a href="#if6">接口6</a>
|
||||
<a href="#if7">接口7</a>
|
||||
<a href="#errors">错误码</a>
|
||||
<a href="#test">在线测试</a>
|
||||
</div>
|
||||
@@ -109,6 +108,8 @@
|
||||
<tr><td><code>landmarks</code></td><td>object</td><td>5 个关键点像素坐标：hair_top/hairline/brow_center/nose_bottom/chin_tip</td></tr>
|
||||
<tr><td><code>hairline_source</code></td><td>string</td><td>发际线来源：<code>"segmentation"</code>（真实分割，可信度高）/ <code>"estimated"</code>（比例估算，可信度低）</td></tr>
|
||||
<tr><td><code>head_pose</code></td><td>object</td><td>头部姿态角度：<code>{ yaw, pitch, roll }</code>（度），接近 0 表示正面照</td></tr>
|
||||
<tr><td><code>left_position</code></td><td>object</td><td>MediaPipe 21 号关键点坐标（左脸定位点），原图像素：<code>{ x: number, y: number }</code></td></tr>
|
||||
<tr><td><code>right_position</code></td><td>object</td><td>MediaPipe 251 号关键点坐标（右脸定位点，与 21 号镜像），原图像素：<code>{ x: number, y: number }</code></td></tr>
|
||||
</table>
|
||||
|
||||
<p style="margin-top:12px;font-size:12px;color:#64748b">💡 前端把标注图叠加到原图上即可呈现测量效果（标注图白色线条 #FFFFFF，透明底）。</p>
|
||||
@@ -189,17 +190,17 @@ const { code, data } = await res.json();
|
||||
<div class="card" id="if4">
|
||||
<h2>4. 用户特征分析 <span class="badge post">POST</span> <code>/api/v1/face/features</code></h2>
|
||||
<div class="card-body">
|
||||
<p class="desc">上传照片 → 火山方舟豆包视觉模型分析 → 返回几十项面部特征（脸型/眉形/肤色/四季色彩…）。</p>
|
||||
<p class="desc">上传照片 → 火山方舟豆包视觉模型分析 → 返回固定 6 项面部特征（脸型/眉形/面部年龄/动静类型/性别/基因风格）。</p>
|
||||
|
||||
<p><strong>入参</strong>：image_file / image_url / image_base64 三选一。无其他参数。</p>
|
||||
|
||||
<p style="margin-top:12px"><strong>data 字段</strong></p>
|
||||
<table>
|
||||
<tr><th>字段</th><th>类型</th><th>说明</th></tr>
|
||||
<tr><td><code>features</code></td><td>string</td><td><strong>JSON 字符串</strong>（不是对象！客户端需 <code>JSON.parse()</code>）</td></tr>
|
||||
<tr><td><code>features</code></td><td>string</td><td><strong>JSON 字符串</strong>（不是对象！客户端需 <code>JSON.parse()</code>）。解析后得到<strong>固定 6 个英文字段</strong></td></tr>
|
||||
</table>
|
||||
|
||||
<p style="margin-top:8px"><strong>features 英文优先字段</strong>（其余中文字段同时返回，共~42个）：</p>
|
||||
<p style="margin-top:8px"><strong>features 字段</strong>（固定返回 6 个）：</p>
|
||||
<table>
|
||||
<tr><th>字段</th><th>说明</th><th>字段</th><th>说明</th></tr>
|
||||
<tr><td>face_shape</td><td>脸型</td><td>eyebrow_shape</td><td>眉形</td></tr>
|
||||
@@ -214,7 +215,7 @@ const { code, data } = await res.json();
|
||||
const { code, data } = await res.json();
|
||||
const features = JSON.parse(data.features); // ← 注意：data.features 是字符串！
|
||||
console.log(features.face_shape); // "鹅蛋脸"
|
||||
console.log(features['四季色彩季型']); // "冷夏型"（中文字段也保留）</pre>
|
||||
console.log(features.gene_style); // "自然型"</pre>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@@ -230,12 +231,13 @@ console.log(features['四季色彩季型']); // "冷夏型"（中文字段也保
|
||||
<tr><td>image_file / image_url / image_base64</td><td>—</td><td>三选一</td><td>用户正面照</td></tr>
|
||||
<tr><td>gender</td><td>string</td><td>✅ 必填</td><td><code>"male"</code> / <code>"female"</code></td></tr>
|
||||
<tr><td>hair_style</td><td>string</td><td>✅ 必填</td><td>发型序号，逗号分隔多选（如 <code>1,2,3</code>）。缺失/越界返回 1007</td></tr>
|
||||
<tr><td>generate_grow_image</td><td>bool</td><td>否</td><td>是否生成生发效果图（ComfyUI 生发，全流程最耗时），默认 <code>true</code>。传 <code>false</code> 时跳过生发，各发型 <code>grown_image_url</code> 恒为 <code>null</code>，仅返回三档发际线叠图与中心点，大幅降低耗时</td></tr>
|
||||
</table>
|
||||
|
||||
<p style="margin-top:12px"><strong>data 字段</strong></p>
|
||||
<table>
|
||||
<tr><th>字段</th><th>类型</th><th>说明</th></tr>
|
||||
<tr><td><code>hairline_images[]</code></td><td>object[]</td><td>选中发型列表，每项含 <code>hairline_type</code>、<code>image_middle_url</code>/<code>image_high_url</code>/<code>image_low_url</code> 三档<strong>透明 PNG 叠图</strong>（仅曲线，需叠加原图）、<code>grown_image_url</code> 生发图（完整人像，失败为 null）、<code>order</code></td></tr>
|
||||
<tr><td><code>hairline_images[]</code></td><td>object[]</td><td>选中发型列表，每项含 <code>hairline_type</code>、<code>image_middle_url</code>/<code>image_high_url</code>/<code>image_low_url</code> 三档<strong>透明 PNG 叠图</strong>（仅曲线，需叠加原图）、<code>grown_image_url</code> 生发图（完整人像，失败或 <code>generate_grow_image=false</code> 时为 null）、<code>order</code></td></tr>
|
||||
<tr><td><code>best_hairline_center_point</code></td><td>object \| null</td><td>首个选中发型 <strong>middle 档</strong>发际线中心点像素坐标 <code>{ x: number, y: number }</code></td></tr>
|
||||
<tr><td><code>high_hairline_center_point</code></td><td>object \| null</td><td>同上，<strong>high 档</strong>发际线中点（发际线偏高，y 更小）</td></tr>
|
||||
<tr><td><code>low_hairline_center_point</code></td><td>object \| null</td><td>同上，<strong>low 档</strong>发际线中点（发际线偏低，y 更大）</td></tr>
|
||||
@@ -251,6 +253,8 @@ console.log(features['四季色彩季型']); // "冷夏型"（中文字段也保
|
||||
<tr><td><code>landmarks</code></td><td>object</td><td>5 个关键点像素坐标：hair_top/hairline/brow_center/nose_bottom/chin_tip</td></tr>
|
||||
<tr><td><code>hairline_source</code></td><td>string</td><td>发际线来源：<code>"segmentation"</code>（真实分割）/ <code>"estimated"</code>（比例估算）</td></tr>
|
||||
<tr><td><code>head_pose</code></td><td>object</td><td>头部姿态角度：<code>{ yaw, pitch, roll }</code>（度）</td></tr>
|
||||
<tr><td><code>left_position</code></td><td>object</td><td>MediaPipe 21 号关键点坐标（左脸定位点），原图像素：<code>{ x: number, y: number }</code></td></tr>
|
||||
<tr><td><code>right_position</code></td><td>object</td><td>MediaPipe 251 号关键点坐标（右脸定位点，与 21 号镜像），原图像素：<code>{ x: number, y: number }</code></td></tr>
|
||||
</table>
|
||||
|
||||
<p style="margin-top:12px;font-size:12px;color:#64748b">💡 前端无需额外请求接口1 即可拿到四庭七眼测量数值；<code>face_measure</code> 为 <code>null</code> 时（角度过大/无人脸等）仅隐藏测量区块，发际线结果照常展示。</p>
|
||||
@@ -282,41 +286,12 @@ console.log(features['四季色彩季型']); // "冷夏型"（中文字段也保
|
||||
<tr><td><code>four_courts</code></td><td>object</td><td>三庭：upper/middle/lower，各含 _cm 和 ratios（<strong>无 top_court</strong>）</td></tr>
|
||||
<tr><td><code>seven_eyes</code></td><td>object</td><td>七眼：<code>eye_width_cm</code>/<code>face_width_cm</code>/<code>inter_eye_distance_cm</code> + <code>ratios</code> + <strong><code>eye2</code>~<code>eye6</code></strong>（左脸颊/左眼/两眼间距/右眼/右脸颊，5 段宽度 cm；<strong>无 eye1/eye7</strong>）</td></tr>
|
||||
<tr><td><code>landmarks</code></td><td>object</td><td>4 个关键点：hairline/brow_center/nose_bottom/chin_tip（<strong>无 hair_top</strong>）</td></tr>
|
||||
<tr><td><code>left_position</code></td><td>object</td><td>MediaPipe 21 号关键点坐标（左脸定位点），原图像素：<code>{ x: number, y: number }</code></td></tr>
|
||||
<tr><td><code>right_position</code></td><td>object</td><td>MediaPipe 251 号关键点坐标（右脸定位点，与 21 号镜像），原图像素：<code>{ x: number, y: number }</code></td></tr>
|
||||
</table>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- ======== 接口7 ======== -->
|
||||
<div class="card" id="if7">
|
||||
<h2>7. C端生发 v2 <span class="badge post">POST</span> <code>/api/v1/hair/grow-v2</code> <span class="badge warn">v2</span></h2>
|
||||
<div class="card-body">
|
||||
<p class="desc">功能与<a href="#if2">接口2</a>完全一致，仅 ComfyUI 工作流不同——使用 <code>add_hair2.json</code> 替代 <code>add_hair.json</code>（Flux-2 Klein 9b）。</p>
|
||||
|
||||
<p><strong>入参</strong></p>
|
||||
<table>
|
||||
<tr><th>参数</th><th>类型</th><th>必填</th><th>说明</th></tr>
|
||||
<tr><td>image_file / image_url / image_base64</td><td>—</td><td>三选一</td><td>用户正面照</td></tr>
|
||||
<tr><td>gender</td><td>string</td><td>✅ 必填</td><td><code>"male"</code> / <code>"female"</code></td></tr>
|
||||
<tr><td>hair_style</td><td>int</td><td>✅ 必填</td><td>发型序号。female: 1~5，male: 1~4</td></tr>
|
||||
</table>
|
||||
|
||||
<p style="margin-top:12px"><strong>data.results[] 元素</strong>（同接口2）</p>
|
||||
<table>
|
||||
<tr><th>字段</th><th>类型</th><th>说明</th></tr>
|
||||
<tr><td><code>image_url</code></td><td>string</td><td>发际线曲线<strong>透明 PNG</strong>（仅曲线，需叠加原图显示，同接口2）</td></tr>
|
||||
<tr><td><code>grown_image_url</code></td><td>string</td><td>生发后效果图（完整人像）⚠ 可空</td></tr>
|
||||
<tr><td><code>hairline_type</code></td><td>string</td><td>发际线类型 key</td></tr>
|
||||
<tr><td><code>order</code></td><td>int</td><td>排序</td></tr>
|
||||
</table>
|
||||
|
||||
<p style="margin-top:8px;font-size:12px;color:#64748b">
|
||||
Female 5 种：ellipse/flower/heart/straight/wave |
|
||||
Male 4 种：ellipse/m/straight/inverse_arc<br>
|
||||
⚠ 工作流: add_hair2.json（Flux-2 Klein 9b），输入节点 26，输出节点 75。
|
||||
</p>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- ======== 错误码 ======== -->
|
||||
<div class="card" id="errors">
|
||||
<h2>⚠ 错误码</h2>
|
||||
@@ -326,12 +301,14 @@ console.log(features['四季色彩季型']); // "冷夏型"（中文字段也保
|
||||
<tr><td>1001</td><td>无法识别人像</td><td>未检测到人脸</td></tr>
|
||||
|
||||
<tr><td>1003</td><td>角度问题，非正面照</td><td>非正面 / 角度过大</td></tr>
|
||||
<tr><td>1004</td><td>gender 必填且只能为 male / female</td><td>接口2/5 的 <code>gender</code> 缺失或非法</td></tr>
|
||||
<tr><td>1005</td><td>检测到多张人脸</td><td>仅支持单人</td></tr>
|
||||
|
||||
<tr><td>1007</td><td>图片参数错误 / 后端不可用</td><td>参数传错 / 服务繁忙请稍后重试</td></tr>
|
||||
<tr><td>1008</td><td>图片格式不支持</td><td>非 JPG/PNG / base64 解码失败</td></tr>
|
||||
<tr><td>1009</td><td>未授权</td><td>缺少或错误的 <code>X-Internal-Token</code>（<code>/api/*</code> 路径鉴权）</td></tr>
|
||||
</table>
|
||||
<p style="font-size:12px;color:#94a3b8;margin-top:8px">1004 已废弃（接口2 不再自动判性别，改由客户端传 gender 参数）。</p>
|
||||
<p style="font-size:12px;color:#94a3b8;margin-top:8px">注：1004 仍在使用（接口2/5 的 gender 校验）；接口7（grow-v2）已弃用，请改用接口2。</p>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@@ -344,10 +321,9 @@ console.log(features['四季色彩季型']); // "冷夏型"（中文字段也保
|
||||
<tr><td>1. 四庭七眼</td><td><a href="/static/test_interface1.html" class="link">/static/test_interface1.html</a></td><td>上传照片 → 原图+标注叠加，底图/标注开关，指标卡片</td></tr>
|
||||
<tr><td>2. C端生发</td><td><a href="/static/test_interface2.html" class="link">/static/test_interface2.html</a></td><td>上传+性别 → 方案一覧（原图/叠加/生发），双图对比</td></tr>
|
||||
<tr><td>3. B端生发</td><td><a href="/static/test_interface3.html" class="link">/static/test_interface3.html</a></td><td>划线图上传 → 生发效果图</td></tr>
|
||||
<tr><td>4. 用户特征</td><td><a href="/static/test_interface4.html" class="link">/static/test_interface4.html</a></td><td>上传照片 → 42项面部特征表格 + 原始JSON</td></tr>
|
||||
<tr><td>4. 用户特征</td><td><a href="/static/test_interface4.html" class="link">/static/test_interface4.html</a></td><td>上传照片 → 6项面部特征 + 原始JSON</td></tr>
|
||||
<tr><td>5. 发际线PNG</td><td><a href="/static/test_interface5.html" class="link">/static/test_interface5.html</a></td><td>上传+性别 → 发际线方案+中心点坐标</td></tr>
|
||||
<tr><td>6. 四庭七眼 v2</td><td><a href="/static/test_interface6.html" class="link">/static/test_interface6.html</a></td><td>同接口1，去顶庭 · 竖线发际线→下巴 · 无头部端线</td></tr>
|
||||
<tr><td>7. C端生发 v2</td><td><a href="/static/test_interface7.html" class="link">/static/test_interface7.html</a></td><td>同接口2，使用 add_hair2.json 工作流（Flux-2 Klein 9b）</td></tr>
|
||||
</table>
|
||||
<p style="font-size:12px;color:#94a3b8;margin-top:12px">
|
||||
完整 API 文档：<a href="/docs" class="link">/docs</a>（Swagger UI）
|
||||
|
||||
@@ -62,7 +62,7 @@
|
||||
@media (max-width: 768px) { .results { flex-direction: column; } }
|
||||
.hidden { display: none !important; }
|
||||
</style>
|
||||
<script src="/static/img_downscale.js"></script>
|
||||
<script src="/static/img_downscale.js?v=2"></script>
|
||||
</head>
|
||||
<body>
|
||||
<div class="container">
|
||||
@@ -159,12 +159,9 @@ async function submitTest() {
|
||||
|
||||
if (json.code === 0) {
|
||||
setStatus('✅ 请求成功 (' + _elapsed + 's) — request_id: ' + json.request_id, 'success');
|
||||
// 兼容本地直连 worker（返回 *_base64）与网关（改写为 *_url）两种情况
|
||||
// 兼容本地直连 worker（*_base64）与网关（*_url）
|
||||
const _d = json.data || {};
|
||||
const annoUrl = _d.annotated_image_url
|
||||
|| (_d.annotated_image_base64
|
||||
? ('data:image/png;base64,' + _d.annotated_image_base64.replace(/^data:image\/\w+;base64,/, ''))
|
||||
: '');
|
||||
const annoUrl = resolveImgSrc(_d.annotated_image_url, _d.annotated_image_base64, 'image/png');
|
||||
showOverlay(annoUrl);
|
||||
renderMetrics(json.data);
|
||||
$('metricsBar').classList.remove('hidden');
|
||||
|
||||
@@ -53,11 +53,11 @@
|
||||
</head>
|
||||
<body>
|
||||
<div class="container">
|
||||
<h1>接口12 — 发际线带重绘 <span style="font-size:13px;color:#888">（final + 纯红遮罩 → 外部 ComfyUI 重绘）</span></h1>
|
||||
<h1>接口12 — 发际线带重绘 <span style="font-size:13px;color:#888">（final + 纯红遮罩 → ComfyUI 重绘）</span></h1>
|
||||
<div class="subtitle">
|
||||
内部先跑<b>接口11</b>拿到 ④接缝融合最终图（final），再取 <b>⑤-① 发际线重绘带</b>（发际线外推 band_lo_mult×push ~ band_hi_mult×push、经 baseline 截断只留上部）生成
|
||||
<b>纯红遮罩 PNG</b>（遮罩区=(255,0,0,255)，其余全透明）。<br>
|
||||
前端拿到 final + 遮罩后，调 <b>外部重绘服务（local_test，默认 :8899）</b>完成重绘。⚠️ 需 ComfyUI(:8188) 在跑。
|
||||
前端拿到 final + 遮罩后，调 <b>后端重绘接口（/api/v1/redraw）</b>完成重绘。⚠️ 需 ComfyUI(:8188) 在跑。
|
||||
对照仅生成不重绘：<a href="/static/test_interface11_debug.html">接口11 调试页</a>。
|
||||
</div>
|
||||
|
||||
@@ -65,15 +65,11 @@
|
||||
<div class="upload-row">
|
||||
<input type="file" id="imageFile" accept="image/*">
|
||||
<button class="btn btn-primary" id="submitBtn" onclick="submitTest()">🎨 生成 final+遮罩</button>
|
||||
<button class="btn btn-green" id="redrawBtn" onclick="runLocalRedraw()" disabled>🧪 调 local_test 重绘</button>
|
||||
</div>
|
||||
<div class="upload-row" style="margin-top:10px">
|
||||
<label style="font-size:13px;font-weight:600;white-space:nowrap">重绘服务地址</label>
|
||||
<input type="text" id="localTestUrl" value="http://10.60.74.221:8899" style="flex:1;min-width:200px;padding:8px;border:1px solid #ddd;border-radius:8px">
|
||||
<button class="btn btn-green" id="redrawBtn" onclick="runLocalRedraw()" disabled>🧪 重绘</button>
|
||||
</div>
|
||||
<div class="upload-row" style="margin-top:10px">
|
||||
<label style="font-size:13px;font-weight:600;white-space:nowrap">重绘提示词</label>
|
||||
<input type="text" id="localTestPrompt" value="填充遮罩区域的头发，皮肤加一点磨皮" style="flex:1;min-width:200px;padding:8px;border:1px solid #ddd;border-radius:8px">
|
||||
<input type="text" id="localTestPrompt" value="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜" style="flex:1;min-width:200px;padding:8px;border:1px solid #ddd;border-radius:8px">
|
||||
</div>
|
||||
<div class="upload-row" style="margin-top:10px">
|
||||
<label style="font-size:13px;font-weight:600;white-space:nowrap">X-Internal-Token</label>
|
||||
@@ -144,9 +140,9 @@
|
||||
<div class="steps" style="grid-template-columns: repeat(auto-fill, minmax(300px, 1fr))">
|
||||
<div class="step big"><div class="cap">接口11 final <small>④ 接缝融合（重绘输入基底，无美颜）</small></div><img id="finalBase"></div>
|
||||
<div class="step big"><div class="cap">⑤-① 发际线重绘带遮罩 <small>纯红 alpha PNG（遮罩区=红+不透明，其余全透明）</small></div><img id="maskPng"></div>
|
||||
<div class="step big"><div class="cap">🧪 local_test 重绘结果 <small>final + 遮罩 → 外部 ComfyUI(0716add-hair.json)</small></div><img id="localResult"></div>
|
||||
<div class="step big"><div class="cap">🧪 重绘结果 <small>final + 遮罩 → ComfyUI(0716add-hair)</small></div><img id="localResult"></div>
|
||||
</div>
|
||||
<div style="font-size:12px;color:#888;margin-top:10px">流程：后端产出 final（接缝融合基底）+ 纯红遮罩 PNG，前端把两者 POST 到 local_test 重绘服务完成发际线补发。</div>
|
||||
<div style="font-size:12px;color:#888;margin-top:10px">流程：后端产出 final（接缝融合基底）+ 纯红遮罩 PNG，再调后端 /api/v1/redraw 完成发际线补发。</div>
|
||||
</div>
|
||||
|
||||
<div class="card">
|
||||
@@ -191,10 +187,10 @@ const STEPS = [
|
||||
{ key: 'input', title: '原图', sub: '接口输入' },
|
||||
{ key: 'final', title: '接口11 ④ final', sub: '接缝融合最终图（重绘输入基底，无美颜）' },
|
||||
{ key: 'redraw_band_overlay', title: '⑤-① 发际线重绘带', sub: '紫=lo×push↔hi×push之间、经 baseline 截断只留上部' },
|
||||
{ key: 'redraw_band_mask', title: '⑤-② 纯红遮罩 PNG', sub: '遮罩区=(255,0,0,255)、其余全透明；交给 local_test' },
|
||||
{ key: 'redraw_band_mask', title: '⑤-② 纯红遮罩 PNG', sub: '遮罩区=(255,0,0,255)、其余全透明；交给后端重绘' },
|
||||
];
|
||||
|
||||
// 缓存最近一次后端返回的 final（JPG data URI）和纯红遮罩（PNG data URI），供 local_test 重绘使用
|
||||
// 缓存最近一次后端返回的 final（JPG data URI）和纯红遮罩（PNG data URI），供重绘使用
|
||||
let _finalDataUri = '';
|
||||
let _maskDataUri = '';
|
||||
|
||||
@@ -237,7 +233,7 @@ function renderResult(d) {
|
||||
flog(' 渲染 ' + st.key + ': ' + (hasImg ? '有图(' + src.length + '字符)' : '无图'), hasImg ? 'info' : 'warn');
|
||||
grid.appendChild(stepCard(st.title, st.sub, src));
|
||||
});
|
||||
// final + 遮罩 都有 → 允许调 local_test 重绘
|
||||
// final + 遮罩 都有 → 允许调后端重绘
|
||||
const canRedraw = !!(finalSrc && maskSrc);
|
||||
$('redrawBtn').disabled = !canRedraw;
|
||||
flog('renderResult 完成 canRedraw=' + canRedraw, 'info');
|
||||
@@ -346,7 +342,7 @@ async function submitTest() {
|
||||
}
|
||||
}
|
||||
|
||||
// data URI → Blob，用于把后端返回的 final/遮罩图作为文件 POST 给 local_test
|
||||
// data URI → Blob，用于把后端返回的 final/遮罩图作为文件 POST 给后端重绘
|
||||
function dataUriToBlob(dataUri) {
|
||||
const [meta, b64] = dataUri.split(',');
|
||||
const mime = (meta.match(/data:([^;]+)/) || [, 'application/octet-stream'])[1];
|
||||
@@ -358,44 +354,39 @@ function dataUriToBlob(dataUri) {
|
||||
|
||||
async function runLocalRedraw() {
|
||||
if (!_finalDataUri || !_maskDataUri) { setStatus('缺少 final 或遮罩，请先生成', 'error'); return; }
|
||||
const base = $('localTestUrl').value.trim().replace(/\/+$/, '');
|
||||
if (!base) { setStatus('请填写重绘服务地址', 'error'); return; }
|
||||
const prompt = $('localTestPrompt').value.trim() || '填充遮罩区域的头发，皮肤加一点磨皮';
|
||||
const prompt = $('localTestPrompt').value.trim() || '填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜';
|
||||
const btn = $('redrawBtn');
|
||||
btn.disabled = true; btn.textContent = '⏳ 重绘中...';
|
||||
flog('===== 调 local_test 重绘 =====', 'info');
|
||||
flog('服务地址=' + base + ' 提示词=' + prompt, 'info');
|
||||
flog('===== 调后端重绘 =====', 'info');
|
||||
flog('提示词=' + prompt, 'info');
|
||||
|
||||
const form = new FormData();
|
||||
form.append('image', dataUriToBlob(_finalDataUri), 'final.jpg');
|
||||
form.append('mask', dataUriToBlob(_maskDataUri), 'mask.png');
|
||||
form.append('image_file', dataUriToBlob(_finalDataUri), 'final.jpg');
|
||||
form.append('mask_file', dataUriToBlob(_maskDataUri), 'mask.png');
|
||||
form.append('prompt', prompt);
|
||||
|
||||
const t0 = performance.now();
|
||||
try {
|
||||
flog('fetch POST ' + base + '/api/generate', 'info');
|
||||
const resp = await fetch(base + '/api/generate', { method: 'POST', body: form });
|
||||
flog('收到响应 http=' + resp.status + ' type=' + resp.headers.get('content-type'), resp.ok ? 'info' : 'error');
|
||||
flog('fetch POST ' + API_BASE + '/api/v1/redraw', 'info');
|
||||
const resp = await fetch(API_BASE + '/api/v1/redraw', { method: 'POST', body: form });
|
||||
flog('收到响应 http=' + resp.status, resp.ok ? 'info' : 'error');
|
||||
const dt = ((performance.now() - t0) / 1000).toFixed(2);
|
||||
if (resp.ok && resp.headers.get('content-type', '').includes('image/')) {
|
||||
const blob = await resp.blob();
|
||||
const url = URL.createObjectURL(blob);
|
||||
$('localResult').src = url;
|
||||
const json = await resp.json();
|
||||
if (json.code === 0 && json.data && json.data.image_base64) {
|
||||
$('localResult').src = json.data.image_base64;
|
||||
$('localResult').onclick = function(){ zoom(this.src); };
|
||||
setStatus('✅ local_test 重绘完成 (' + dt + 's)', 'success');
|
||||
flog('local_test 重绘完成 耗时=' + dt + 's 大小=' + blob.size + 'B', 'info');
|
||||
setStatus('✅ 重绘完成 (' + dt + 's)', 'success');
|
||||
flog('重绘完成 耗时=' + dt + 's', 'info');
|
||||
} else {
|
||||
// 非图片响应 → 多半是 JSON 错误
|
||||
let msg = resp.status + '';
|
||||
try { const j = await resp.json(); msg = j.error || JSON.stringify(j); } catch (_) {}
|
||||
setStatus('❌ local_test 重绘失败：' + msg, 'error');
|
||||
flog('local_test 重绘失败: ' + msg, 'error');
|
||||
const msg = json.message || JSON.stringify(json);
|
||||
setStatus('❌ 重绘失败：' + msg, 'error');
|
||||
flog('重绘失败: ' + msg, 'error');
|
||||
}
|
||||
} catch (err) {
|
||||
setStatus('❌ local_test 网络错误：' + err.message + '（确认服务在跑且已加 CORS）', 'error');
|
||||
flog('local_test 网络错误: ' + err.message, 'error');
|
||||
setStatus('❌ 重绘网络错误：' + err.message, 'error');
|
||||
flog('重绘网络错误: ' + err.message, 'error');
|
||||
} finally {
|
||||
btn.disabled = false; btn.textContent = '🧪 调 local_test 重绘';
|
||||
btn.disabled = false; btn.textContent = '🧪 重绘';
|
||||
}
|
||||
}
|
||||
|
||||
@@ -426,8 +417,8 @@ async function downloadBackendLog() {
|
||||
|
||||
$('imageFile').addEventListener('change', function(){ if(this.files.length) flog('选择图片: ' + this.files[0].name, 'info'); });
|
||||
|
||||
flog('接口12 重绘测试页加载完成（后端产出 final+纯红遮罩 → 前端调 local_test 重绘）', 'info');
|
||||
flog('默认: hairline=chang_bolang, push=0.8, blend=two_stage, cm_strength=0.4；需 ComfyUI(:8188) 在跑；重绘需 local_test(:8899) 在跑', 'info');
|
||||
flog('接口12 重绘测试页加载完成（后端产出 final+纯红遮罩 → 后端 /api/v1/redraw 重绘）', 'info');
|
||||
flog('默认: hairline=chang_bolang, push=0.8, blend=two_stage, cm_strength=0.4；需 ComfyUI(:8188) 在跑', 'info');
|
||||
</script>
|
||||
</body>
|
||||
</html>
|
||||
|
||||
@@ -41,10 +41,10 @@
|
||||
</head>
|
||||
<body>
|
||||
<div class="container">
|
||||
<h1>接口12 final — 发际线带重绘 <span style="font-size:13px;color:#888">（精简版：final + 纯红遮罩 → 外部 ComfyUI 重绘）</span></h1>
|
||||
<h1>接口12 final — 发际线带重绘 <span style="font-size:13px;color:#888">（精简版：final + 纯红遮罩 → ComfyUI 重绘）</span></h1>
|
||||
<div class="subtitle">
|
||||
只需上传图片 + 选择发型，其余参数全部用当前调优默认值（<code>/api/v1/hairline/grow_v2_final</code>）。<br>
|
||||
后端产出 <b>④ final（接缝融合基底）</b> + <b>⑤-② 纯红遮罩 PNG</b>，前端调 <b>外部重绘服务（local_test，默认 :8899）</b>完成发际线带重绘。⚠️ 需 ComfyUI(:8188) 在跑。
|
||||
后端产出 <b>④ final（接缝融合基底）</b> + <b>⑤-② 纯红遮罩 PNG</b>，再调 <b>后端重绘接口（/api/v1/redraw）</b>完成发际线带重绘。⚠️ 需 ComfyUI(:8188) 在跑。
|
||||
局部加发版见 <a href="/static/test_interface12_final_v2.html">接口12 final v2</a>；完整参数调试见 <a href="/static/test_interface12.html">接口12 调试页</a>。
|
||||
</div>
|
||||
|
||||
@@ -52,15 +52,11 @@
|
||||
<div class="upload-row">
|
||||
<input type="file" id="imageFile" accept="image/*">
|
||||
<button class="btn btn-primary" id="submitBtn" onclick="submitTest()">🎨 生成 final+遮罩</button>
|
||||
<button class="btn btn-green" id="redrawBtn" onclick="runLocalRedraw()" disabled>🧪 调 local_test 重绘</button>
|
||||
</div>
|
||||
<div class="upload-row" style="margin-top:10px">
|
||||
<label style="font-size:13px;font-weight:600;white-space:nowrap">重绘服务地址</label>
|
||||
<input type="text" id="localTestUrl" value="http://10.60.74.221:8899" style="flex:1;min-width:200px;padding:8px;border:1px solid #ddd;border-radius:8px">
|
||||
<button class="btn btn-green" id="redrawBtn" onclick="runLocalRedraw()" disabled>🧪 重绘</button>
|
||||
</div>
|
||||
<div class="upload-row" style="margin-top:10px">
|
||||
<label style="font-size:13px;font-weight:600;white-space:nowrap">重绘提示词</label>
|
||||
<input type="text" id="localTestPrompt" value="填充遮罩区域的头发，皮肤加一点磨皮" style="flex:1;min-width:200px;padding:8px;border:1px solid #ddd;border-radius:8px">
|
||||
<input type="text" id="localTestPrompt" value="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜" style="flex:1;min-width:200px;padding:8px;border:1px solid #ddd;border-radius:8px">
|
||||
</div>
|
||||
<div class="params">
|
||||
<div class="pf">
|
||||
@@ -84,9 +80,9 @@
|
||||
<div class="steps" style="grid-template-columns: repeat(auto-fill, minmax(300px, 1fr))">
|
||||
<div class="step big"><div class="cap">接口11 final <small>④ 接缝融合（重绘输入基底，无美颜）</small></div><img id="finalBase"></div>
|
||||
<div class="step big"><div class="cap">⑤-① 发际线重绘带遮罩 <small>纯红 alpha PNG（遮罩区=红+不透明，其余全透明）</small></div><img id="maskPng"></div>
|
||||
<div class="step big"><div class="cap">🧪 local_test 重绘结果 <small>final + 遮罩 → 外部 ComfyUI(0716add-hair.json)</small></div><img id="localResult"></div>
|
||||
<div class="step big"><div class="cap">🧪 重绘结果 <small>final + 遮罩 → ComfyUI(0716add-hair)</small></div><img id="localResult"></div>
|
||||
</div>
|
||||
<div style="font-size:12px;color:#888;margin-top:10px">流程：后端产出 final（接缝融合基底）+ 纯红遮罩 PNG，前端把两者 POST 到 local_test 重绘服务完成发际线补发。</div>
|
||||
<div style="font-size:12px;color:#888;margin-top:10px">流程：后端产出 final（接缝融合基底）+ 纯红遮罩 PNG，再调后端 /api/v1/redraw 完成发际线补发。</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
@@ -98,7 +94,7 @@ const API_BASE = window.location.origin;
|
||||
const ENDPOINT = '/api/v1/hairline/grow_v2_final';
|
||||
const TOKEN = 'dev-shared-secret-2026';
|
||||
|
||||
// 缓存最近一次后端返回的 final（data URI）和纯红遮罩（data URI），供 local_test 重绘使用
|
||||
// 缓存最近一次后端返回的 final（data URI）和纯红遮罩（data URI），供重绘使用
|
||||
let _finalDataUri = '';
|
||||
let _maskDataUri = '';
|
||||
|
||||
@@ -121,7 +117,7 @@ function renderResult(d) {
|
||||
$('redrawBtn').disabled = !canRedraw;
|
||||
}
|
||||
|
||||
// data URI → Blob，用于把后端返回的 final/遮罩图作为文件 POST 给 local_test
|
||||
// data URI → Blob，用于把后端返回的 final/遮罩图作为文件 POST 给后端重绘
|
||||
function dataUriToBlob(dataUri) {
|
||||
const [meta, b64] = dataUri.split(',');
|
||||
const mime = (meta.match(/data:([^;]+)/) || [, 'application/octet-stream'])[1];
|
||||
@@ -173,36 +169,34 @@ async function submitTest() {
|
||||
|
||||
async function runLocalRedraw() {
|
||||
if (!_finalDataUri || !_maskDataUri) { setStatus('缺少 final 或遮罩，请先生成', 'error'); return; }
|
||||
const base = $('localTestUrl').value.trim().replace(/\/+$/, '');
|
||||
if (!base) { setStatus('请填写重绘服务地址', 'error'); return; }
|
||||
const prompt = $('localTestPrompt').value.trim() || '填充遮罩区域的头发，皮肤加一点磨皮';
|
||||
const prompt = $('localTestPrompt').value.trim() || '填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜';
|
||||
const btn = $('redrawBtn');
|
||||
btn.disabled = true; btn.textContent = '⏳ 重绘中...';
|
||||
|
||||
const form = new FormData();
|
||||
form.append('image', dataUriToBlob(_finalDataUri), 'final.jpg');
|
||||
form.append('mask', dataUriToBlob(_maskDataUri), 'mask.png');
|
||||
form.append('image_file', dataUriToBlob(_finalDataUri), 'final.jpg');
|
||||
form.append('mask_file', dataUriToBlob(_maskDataUri), 'mask.png');
|
||||
form.append('prompt', prompt);
|
||||
|
||||
const t0 = performance.now();
|
||||
try {
|
||||
const resp = await fetch(base + '/api/generate', { method: 'POST', body: form });
|
||||
const resp = await fetch(API_BASE + '/api/v1/redraw', {
|
||||
method: 'POST',
|
||||
body: form,
|
||||
});
|
||||
const dt = ((performance.now() - t0) / 1000).toFixed(2);
|
||||
if (resp.ok && resp.headers.get('content-type', '').includes('image/')) {
|
||||
const blob = await resp.blob();
|
||||
const url = URL.createObjectURL(blob);
|
||||
$('localResult').src = url;
|
||||
const json = await resp.json();
|
||||
if (json.code === 0 && json.data && json.data.image_base64) {
|
||||
$('localResult').src = json.data.image_base64;
|
||||
$('localResult').onclick = function(){ zoom(this.src); };
|
||||
setStatus('✅ local_test 重绘完成 (' + dt + 's)', 'success');
|
||||
setStatus('✅ 重绘完成 (' + dt + 's)', 'success');
|
||||
} else {
|
||||
let msg = resp.status + '';
|
||||
try { const j = await resp.json(); msg = j.error || JSON.stringify(j); } catch (_) {}
|
||||
setStatus('❌ local_test 重绘失败：' + msg, 'error');
|
||||
setStatus('❌ 重绘失败：' + (json.message || JSON.stringify(json)), 'error');
|
||||
}
|
||||
} catch (err) {
|
||||
setStatus('❌ local_test 网络错误：' + err.message + '（确认服务在跑且已加 CORS）', 'error');
|
||||
setStatus('❌ 重绘网络错误：' + err.message, 'error');
|
||||
} finally {
|
||||
btn.disabled = false; btn.textContent = '🧪 调 local_test 重绘';
|
||||
btn.disabled = false; btn.textContent = '🧪 重绘';
|
||||
}
|
||||
}
|
||||
</script>
|
||||
|
||||
@@ -69,7 +69,7 @@
|
||||
|
||||
.hidden { display: none !important; }
|
||||
</style>
|
||||
<script src="/static/img_downscale.js"></script>
|
||||
<script src="/static/img_downscale.js?v=2"></script>
|
||||
</head>
|
||||
<body>
|
||||
<div class="container">
|
||||
@@ -107,7 +107,7 @@
|
||||
<div class="hint">JPG/PNG | 生发图生成较慢（数十秒~数分钟），请耐心等待</div>
|
||||
<div style="margin-top:10px;display:flex;align-items:center;gap:8px">
|
||||
<label style="font-size:13px;font-weight:600;color:#374151;white-space:nowrap">💬 提示词</label>
|
||||
<input type="text" id="promptInput" value="补充遮罩区域的头发，加一点美颜" style="flex:1;padding:8px 12px;border:1px solid #d1d5db;border-radius:6px;font-size:13px;max-width:500px">
|
||||
<input type="text" id="promptInput" value="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜" style="flex:1;padding:8px 12px;border:1px solid #d1d5db;border-radius:6px;font-size:13px;max-width:500px">
|
||||
</div>
|
||||
<div id="statusBar" class="status hidden"></div>
|
||||
</div>
|
||||
@@ -180,9 +180,9 @@ function renderSchemes(results) {
|
||||
let html = '';
|
||||
results.forEach((r, i) => {
|
||||
const lb = TYPE_LABELS[r.hairline_type] || r.hairline_type;
|
||||
// 直连 worker 时后端返回 base64（网关才会改写为 *_url），URL 缺失则回退 data URI
|
||||
const overlaySrc = r.image_url || (r.image_base64 ? 'data:image/png;base64,' + r.image_base64 : '');
|
||||
const grownSrc = r.grown_image_url || (r.grown_image_base64 ? 'data:image/jpeg;base64,' + r.grown_image_base64 : '');
|
||||
// 兼容网关 *_url 与 worker *_base64（原始或 data URI）
|
||||
const overlaySrc = resolveImgSrc(r.image_url, r.image_base64, 'image/png');
|
||||
const grownSrc = resolveImgSrc(r.grown_image_url, r.grown_image_base64, 'image/jpeg');
|
||||
|
||||
// 原图
|
||||
const origSlot = '<div class="img-slot">'+
|
||||
@@ -206,7 +206,7 @@ function renderSchemes(results) {
|
||||
} else {
|
||||
grownSlot = '<div class="img-slot">'+
|
||||
'<div class="label"><span class="dot grown"></span>生发效果</div>'+
|
||||
'<div class="na">⚠ 未返回<br><span style="font-size:10px;color:#9ca3af">ComfyUI 未就绪或生成失败</span></div></div>';
|
||||
'<div class="na">⚠ 未返回<br><span style="font-size:10px;color:#9ca3af">生发失败（female=换发型/重绘，male=ComfyUI）</span></div></div>';
|
||||
}
|
||||
|
||||
html += '<div class="scheme-card">'+
|
||||
|
||||
@@ -71,7 +71,7 @@
|
||||
|
||||
@media (max-width: 800px) { .results-layout, .preview-row { flex-direction: column; } }
|
||||
</style>
|
||||
<script src="/static/img_downscale.js"></script>
|
||||
<script src="/static/img_downscale.js?v=2"></script>
|
||||
</head>
|
||||
<body>
|
||||
<div class="container">
|
||||
@@ -94,7 +94,7 @@
|
||||
</div>
|
||||
<div class="upload-group" style="margin-top:14px">
|
||||
<div class="label">💬 提示词（prompt）</div>
|
||||
<input type="text" id="promptInput" value="补充遮罩区域的头发，加一点美颜" style="width:100%;padding:8px 12px;border:1px solid #d1d5db;border-radius:8px;font-size:14px;max-width:500px">
|
||||
<input type="text" id="promptInput" value="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜" style="width:100%;padding:8px 12px;border:1px solid #d1d5db;border-radius:8px;font-size:14px;max-width:500px">
|
||||
</div>
|
||||
<div style="margin-top:14px;display:flex;gap:12px;align-items:center">
|
||||
<button class="btn btn-primary" id="submitBtn" onclick="submitTest()">🚀 提交</button>
|
||||
@@ -175,7 +175,7 @@ async function submitTest() {
|
||||
$('hairlineType').style.display = 'inline-block';
|
||||
}
|
||||
|
||||
const grownSrc = d.hair_growth_image_url || d.hair_growth_image_base64;
|
||||
const grownSrc = resolveImgSrc(d.hair_growth_image_url, d.hair_growth_image_base64, 'image/jpeg');
|
||||
if (grownSrc) {
|
||||
$('blendTop').src = grownSrc;
|
||||
$('blendTop').style.display = 'block';
|
||||
|
||||
+23
-12
@@ -88,7 +88,7 @@
|
||||
.hidden { display: none !important; }
|
||||
@media (max-width: 800px) { .results-layout { flex-direction: column; } }
|
||||
</style>
|
||||
<script src="/static/img_downscale.js"></script>
|
||||
<script src="/static/img_downscale.js?v=2"></script>
|
||||
</head>
|
||||
<body>
|
||||
<div class="container">
|
||||
@@ -113,6 +113,12 @@
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="form-group">
|
||||
<label>生发效果图</label>
|
||||
<label class="checkbox-inline" style="font-weight:normal;display:flex;align-items:center;gap:6px">
|
||||
<input type="checkbox" id="genGrowImg" checked> generate_grow_image（默认开；关闭后跳过最耗时的生发，仅返回三档叠图与中心点）
|
||||
</label>
|
||||
</div>
|
||||
<button class="btn btn-primary" id="submitBtn" onclick="submitTest()">🚀 提交</button>
|
||||
<button class="btn btn-outline btn-sm" onclick="clearResults()">清除</button>
|
||||
</div>
|
||||
@@ -206,7 +212,7 @@ async function submitTest() {
|
||||
$('submitBtn').disabled = true; $('submitBtn').textContent = '⏳ ...';
|
||||
setStatus('请求中...', 'info'); $('resultsArea').classList.add('hidden');
|
||||
|
||||
const fd = new FormData(); fd.append('image_file', f); fd.append('gender', $('gender').value); fd.append('hair_style', checked.join(','));
|
||||
const fd = new FormData(); fd.append('image_file', f); fd.append('gender', $('gender').value); fd.append('hair_style', checked.join(',')); fd.append('generate_grow_image', $('genGrowImg').checked ? 'true' : 'false');
|
||||
const _reqStart = performance.now();
|
||||
try {
|
||||
const r = await fetch(API_BASE + '/api/v1/hairline/generate', { method:'POST', headers: { 'X-Internal-Token': 'dev-shared-secret-2026' }, body:fd });
|
||||
@@ -237,25 +243,30 @@ async function submitTest() {
|
||||
function renderGrid() {
|
||||
if (!_images.length) { $('resultsGrid').innerHTML = '<span style="color:#9ca3af">无数据</span>'; return; }
|
||||
let h = '';
|
||||
// 叠图档：原图打底 + 透明 PNG 叠加（无原图或无叠图 → 显示占位）
|
||||
const overlayCell = (label, url) => (url && _origUrl)
|
||||
// 叠图档：原图打底 + 透明 PNG 图层（无原图或无叠图 → 显示占位）
|
||||
const overlayCell = (label, src) => (src && _origUrl)
|
||||
? '<div class="level-cell"><div class="level-label">'+label+'</div><div class="img-stack">'+
|
||||
'<img class="layer-base" src="'+_origUrl+'" alt="原图">'+
|
||||
'<img class="layer-anno" src="'+url+'" alt="'+label+'"></div></div>'
|
||||
'<img class="layer-anno" src="'+src+'" alt="'+label+'"></div></div>'
|
||||
: '<div class="level-cell"><div class="level-label">'+label+'</div><div class="level-none">无</div></div>';
|
||||
// 生发图：独立 img（已是 ComfyUI 完整人像照片）
|
||||
const grownCell = (label, url) => url
|
||||
? '<div class="level-cell"><div class="level-label">'+label+'</div><img src="'+url+'" alt="'+label+'"></div>'
|
||||
const grownCell = (label, src) => src
|
||||
? '<div class="level-cell"><div class="level-label">'+label+'</div><img src="'+src+'" alt="'+label+'"></div>'
|
||||
: '<div class="level-cell"><div class="level-label">'+label+'</div><div class="level-none">无</div></div>';
|
||||
_images.forEach(function(it) {
|
||||
// 兼容网关 *_url 与 worker *_base64
|
||||
const mid = resolveImgSrc(it.image_middle_url, it.image_middle_base64, 'image/png');
|
||||
const high = resolveImgSrc(it.image_high_url, it.image_high_base64, 'image/png');
|
||||
const low = resolveImgSrc(it.image_low_url, it.image_low_base64, 'image/png');
|
||||
const grown = resolveImgSrc(it.grown_image_url, it.grown_image_base64, 'image/jpeg');
|
||||
h += '<div class="hair-block">' +
|
||||
'<div class="hair-block-title">#' + (it.order||'—') + ' ' + (it.hairline_type||'') +
|
||||
(it.grown_image_url ? ' <span style="font-size:11px;color:#7c3aed">含生发图</span>' : '') + '</div>' +
|
||||
(grown ? ' <span style="font-size:11px;color:#7c3aed">含生发图</span>' : '') + '</div>' +
|
||||
'<div class="level-row">' +
|
||||
overlayCell('middle', it.image_middle_url) +
|
||||
overlayCell('high', it.image_high_url) +
|
||||
overlayCell('low', it.image_low_url) +
|
||||
grownCell('生发图', it.grown_image_url) +
|
||||
overlayCell('middle', mid) +
|
||||
overlayCell('high', high) +
|
||||
overlayCell('low', low) +
|
||||
grownCell('生发图', grown) +
|
||||
'</div>' +
|
||||
'</div>';
|
||||
});
|
||||
|
||||
@@ -59,7 +59,7 @@
|
||||
.diff-list { font-size: 12px; color: #6b7280; margin-top: 6px; line-height: 1.7; }
|
||||
.diff-list li { margin-left: 18px; }
|
||||
</style>
|
||||
<script src="/static/img_downscale.js"></script>
|
||||
<script src="/static/img_downscale.js?v=2"></script>
|
||||
</head>
|
||||
<body>
|
||||
<div class="container">
|
||||
@@ -161,12 +161,9 @@ async function submitTest() {
|
||||
|
||||
if (json.code === 0) {
|
||||
setStatus('✅ 请求成功 (' + _elapsed + 's) — request_id: ' + json.request_id, 'success');
|
||||
// 兼容本地直连 worker（返回 *_base64）与网关（改写为 *_url）两种情况
|
||||
// 兼容本地直连 worker（*_base64）与网关（*_url）
|
||||
const _d = json.data || {};
|
||||
const annoUrl = _d.annotated_image_url
|
||||
|| (_d.annotated_image_base64
|
||||
? ('data:image/png;base64,' + _d.annotated_image_base64.replace(/^data:image\/\w+;base64,/, ''))
|
||||
: '');
|
||||
const annoUrl = resolveImgSrc(_d.annotated_image_url, _d.annotated_image_base64, 'image/png');
|
||||
showOverlay(annoUrl);
|
||||
renderMetrics(json.data);
|
||||
$('metricsBar').classList.remove('hidden');
|
||||
|
||||
@@ -104,7 +104,7 @@
|
||||
<div class="hint">JPG/PNG | 生发图生成较慢（数十秒~数分钟），请耐心等待 | 工作流: add_hair2.json</div>
|
||||
<div style="margin-top:10px;display:flex;align-items:center;gap:8px">
|
||||
<label style="font-size:13px;font-weight:600;color:#374151;white-space:nowrap">💬 提示词</label>
|
||||
<input type="text" id="promptInput" value="补充遮罩区域的头发，加一点美颜" style="flex:1;padding:8px 12px;border:1px solid #d1d5db;border-radius:6px;font-size:13px;max-width:500px">
|
||||
<input type="text" id="promptInput" value="填充遮罩区域的头发，皮肤加一点磨皮，再加一点美颜" style="flex:1;padding:8px 12px;border:1px solid #d1d5db;border-radius:6px;font-size:13px;max-width:500px">
|
||||
</div>
|
||||
<div id="statusBar" class="status hidden"></div>
|
||||
</div>
|
||||
|
||||
@@ -62,3 +62,41 @@ def test_threshold_gating_rejects_when_zeroed():
|
||||
def test_pose_none_is_not_blocked():
|
||||
"""solvePnP 失败（返回 None）时不拦截，check_frontal_face 返回 True。"""
|
||||
assert pose.estimate_head_pose.__doc__ # 占位，确保导入
|
||||
|
||||
|
||||
def test_iterative_flipped_solution_falls_back_to_sqpnp():
|
||||
"""回归：部分正面照上 ITERATIVE 会解出 tz<0、roll≈±180°，应回退 SQPNP。
|
||||
|
||||
像素点取自一张真实正面短发照（720×945）；裸跑 ITERATIVE 会得到负深度。
|
||||
"""
|
||||
W, H = 720, 945
|
||||
# 鼻尖 / 下巴 / 左眼外 / 右眼外 / 左嘴角 / 右嘴角（像素）
|
||||
px = [
|
||||
(358.32715988, 600.98652095),
|
||||
(346.83344364, 779.63507116),
|
||||
(242.94779778, 466.76155195),
|
||||
(478.43703747, 480.10321766),
|
||||
(284.13277388, 679.95527387),
|
||||
(422.19510555, 684.31899190),
|
||||
]
|
||||
lm = [_LM(0.5, 0.5) for _ in range(478)]
|
||||
for idx, (u, v) in zip(PNP_INDICES, px):
|
||||
lm[idx] = _LM(u / W, v / H)
|
||||
|
||||
class _Holder:
|
||||
landmark = lm
|
||||
|
||||
holder = _Holder()
|
||||
# 确认裸 ITERATIVE 确实是翻转解（否则本回归失去意义）
|
||||
image_points = np.array(px, dtype=np.float64)
|
||||
cam = np.array([[float(W), 0, W / 2], [0, float(W), H / 2], [0, 0, 1]],
|
||||
dtype=np.float64)
|
||||
ok, rvec, tvec = cv2.solvePnP(
|
||||
_MODEL_POINTS, image_points, cam, np.zeros((4, 1)),
|
||||
flags=cv2.SOLVEPNP_ITERATIVE,
|
||||
)
|
||||
assert ok and float(tvec[2, 0]) < 0
|
||||
|
||||
yaw, pitch, roll = estimate_head_pose(holder, W, H)
|
||||
assert abs(roll) < 30, f"roll 应被纠正，实际 roll={roll}"
|
||||
assert check_frontal_face(holder, W, H) is True
|
||||
|
||||
Reference in New Issue
Block a user