xsl
41bb164a52
发际线生发遮罩算法（mask_type=pushed）： - _extract_hairline：提取头发/皮肤交界线（逐列头发下沿），用 baseline 水平 y 线截断（无竖线） - _pushed_mask：以眉心(151点)为圆心逐点径向外推 push_cm，与 baseline 组闭合区域 - 径向归并锯齿用插值填补，避免遮罩碎裂 - pushed 模式过程可视化（①-f 交界线 / ①-g 外推+遮罩），eroded/closed 不展示无关步骤 multiband 金字塔融合修复（hairline_grow.py）： - mb_levels 按层数膨胀外缘 keep 区，让过渡带随层数变宽（旧硬二值钳回导致 mb_levels 形同虚设） 接口12 grow_v2（固定参数精简版）： - 固定 multiband/mb_levels=5/erode_cm=0.6，仅返回 final_base64 - 支持 mask_type=pushed + hairline_push_cm/hairline_edge 调试支持： - 调试页 test_interface11_debug.html（前后端日志面板 + 下载日志按钮） - hairline_grow.log 全链路日志（按 rid 关联），/api/v1/debug/hairline_log 下载接口 - 遮罩计算过程可视化（baseline/upper/头发分割/交界线/外推/最终遮罩） 文档与脚本： - docs/发际线生发遮罩算法_pushed模式.md 算法说明 - scripts/batch_grow_v2.py 批量调用、gen_report_hairline_v2.py 对比报告生成
1457 lines
68 KiB
Python
1457 lines
68 KiB
Python
"""旷视五接口 — worker 侧（高性能 GPU 后端）。
|
||
|
||
接口 1（四庭七眼测量）已为**真实算法实现**（见 face_analysis 包）；接口 2~5 仍为 Mock。
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拆分架构：worker 跑算法、返回 `annotated_image_base64`（不落盘、不拼 URL，由网关完成）。
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worker 对 `/api/*` 校验内网鉴权头 `X-Internal-Token`，`/health` 供网关探测不校验。
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||
"""
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import base64
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import json
|
||
import logging
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import os
|
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from contextlib import asynccontextmanager
|
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from io import BytesIO
|
||
from typing import Any, List, Optional
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||
|
||
import cv2
|
||
import numpy as np
|
||
from fastapi import FastAPI, File, Form, Request, UploadFile
|
||
from fastapi.responses import JSONResponse
|
||
from fastapi.staticfiles import StaticFiles
|
||
from pydantic import BaseModel, Field
|
||
|
||
logging.basicConfig(level=logging.INFO,
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format="%(asctime)s %(levelname)s %(name)s: %(message)s")
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logger = logging.getLogger("hair.worker")
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||
|
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# ---------------------------------------------------------------------------
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# App & 全局常量
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# ---------------------------------------------------------------------------
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||
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||
BASE_URL = "https://hair.xiangsilian.com"
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SAMPLE_IMAGE_URL = f"{BASE_URL}/static/sample.jpg"
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|
||
# 运行期状态：模型就绪标志（/health 据此返回 200/503）
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_STATE = {"ready": False}
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||
|
||
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def _load_accept_passwords() -> List[str]:
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"""worker 鉴权密码来源：环境变量 WORKER_ACCEPT_PASSWORDS（逗号分隔）优先，
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否则读 worker_config.json 的 accept_passwords 列表。"""
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env = os.getenv("WORKER_ACCEPT_PASSWORDS")
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if env:
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return [p.strip() for p in env.split(",") if p.strip()]
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||
cfg_path = os.path.join(os.path.dirname(__file__), "worker_config.json")
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if os.path.isfile(cfg_path):
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try:
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with open(cfg_path, encoding="utf-8") as f:
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return list(json.load(f).get("accept_passwords", []))
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except Exception as e: # noqa: BLE001
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logger.warning("读取 worker_config.json 失败：%s", e)
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return []
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ACCEPT_PASSWORDS = _load_accept_passwords()
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@asynccontextmanager
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async def lifespan(_app: FastAPI):
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"""启动时加载模型单例（detector 必需，segmenter 尽力而为），就绪后才放行 /health。"""
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from face_analysis.detector import detector # 触发 MediaPipe 单例初始化
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_ = detector
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try:
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from face_analysis.hair_segmenter import get_segmenter
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seg = get_segmenter()
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logger.info("BiSeNet 头发分割就绪，device=%s", seg.device)
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except Exception as e: # noqa: BLE001
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# 方案 B 不可用（如 torch 缺失）：降级为方案 A only，不阻塞服务
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logger.warning("头发分割不可用，接口1 将走方案A兜底：%s", e)
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# 接口2（C端生发）单例预热：FaceLandmarker + SegFormer + mesh/贴图映射
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try:
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from hairline.service import get_landmarker, get_parser, get_texture_map
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from hairline.render import load_ext_mesh
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get_landmarker(); get_parser(); load_ext_mesh(); get_texture_map()
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logger.info("接口2 发际线管线就绪")
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except Exception as e: # noqa: BLE001
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logger.warning("接口2 发际线管线初始化失败（该接口将返回错误）：%s", e)
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_STATE["ready"] = True
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yield
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||
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||
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app = FastAPI(
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lifespan=lifespan,
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title="旷视五接口",
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version="0.1.0",
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description="""
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## 概述
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本服务提供五个人像分析接口，当前为 **Mock 第一版**：
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- 接口已全部上线，传任意合法参数均可正常响应
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- 所有字段返回固定示例值，图片字段统一指向示例图片
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- 真实算法逻辑后续接入，字段结构不变
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||
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## 图片传参说明
|
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|
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每个接口的图片参数均支持三种方式，**严格互斥，必须且只能选其一**：
|
||
|
||
| 方式 | 字段名 | 说明 |
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|------|--------|------|
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| 文件上传 | `image_file` | `multipart/form-data`，单文件上传 |
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||
| URL | `image_url` | 图片的完整 HTTP/HTTPS 地址 |
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||
| base64 | `image_base64` | 需携带前缀，如 `data:image/jpeg;base64,xxxx` |
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||
|
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> 传 0 个或同时传多个，均返回错误码 `1007`。
|
||
|
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## 图片要求
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||
|
||
- 格式：**JPG / PNG**
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||
- 分辨率：不限制
|
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- 人脸数量：仅支持**单人**，多人返回错误码 `1005`
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- 文件大小：不限制
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||
|
||
## 统一响应结构
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||
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||
```json
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||
{
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||
"code": 0,
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"message": "success",
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||
"request_id": "唯一请求标识",
|
||
"data": {}
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||
}
|
||
```
|
||
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||
`code = 0` 表示成功，非 0 表示失败，`message` 为具体原因。
|
||
|
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## 错误码一览
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| code | 说明 |
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|------|------|
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| 1001 | 无法识别人像 |
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| 1003 | 非正面照 / 角度过大 |
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||
| 1004 | 性别标签无法判定 |
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| 1005 | 检测到多张人脸（仅支持单人）|
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||
| 1007 | 图片参数错误（未传或同时传多个）|
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| 1008 | 图片格式不支持（仅 JPG / PNG）|
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""",
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)
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app.mount("/static", StaticFiles(directory="static"), name="static")
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# 不校验鉴权的路径前缀（供网关探测 / 文档 / 静态）
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_AUTH_EXEMPT = ("/health", "/docs", "/openapi.json", "/redoc", "/static", "/api/v1/debug")
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@app.middleware("http")
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async def internal_token_auth(request: Request, call_next):
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||
"""worker 内网鉴权：/api/* 必须带正确的 X-Internal-Token，否则 401。
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密码列表来自 worker 配置（accept_passwords）。未配置任何密码时放行（仅便于
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本地起步），生产务必通过 worker_config.json / 环境变量配置密码。
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"""
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path = request.url.path
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if path == "/" or path.startswith(_AUTH_EXEMPT):
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return await call_next(request)
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if path.startswith("/api/") and ACCEPT_PASSWORDS:
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token = request.headers.get("X-Internal-Token")
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if token not in ACCEPT_PASSWORDS:
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return JSONResponse(status_code=401, content={
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"code": 1009,
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"message": "未授权：缺少或错误的 X-Internal-Token",
|
||
"request_id": "worker",
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"data": None,
|
||
})
|
||
return await call_next(request)
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# 通用响应模型
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||
# ---------------------------------------------------------------------------
|
||
|
||
def ok(data: Any) -> dict:
|
||
return {
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||
"code": 0,
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||
"message": "success",
|
||
"request_id": "mock-request-id",
|
||
"data": data,
|
||
}
|
||
|
||
|
||
def err(code: int, message: str) -> dict:
|
||
return {
|
||
"code": code,
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||
"message": message,
|
||
"request_id": "mock-request-id",
|
||
"data": None,
|
||
}
|
||
|
||
|
||
# ---------------------------------------------------------------------------
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||
# 图片输入处理（三选一：file / url / base64）
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||
# ---------------------------------------------------------------------------
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||
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async def resolve_image_bytes(image_file, image_url, image_base64):
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||
"""三选一取图，返回 (raw_bytes, error_response)。
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||
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严格互斥：传 0 个或多个 → 1007；URL 下载失败/base64 解码失败 → 1008。
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不限制文件大小，此处只负责取到字节。
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||
"""
|
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provided = [x for x in (image_file, image_url, image_base64) if x]
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if len(provided) != 1:
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return None, err(1007, "图片参数错误：必须且只能传 image_file / image_url / image_base64 其中一个")
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|
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if image_file is not None:
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return await image_file.read(), None
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||
|
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if image_url:
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try:
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import httpx
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with httpx.Client(timeout=10.0, follow_redirects=True) as client:
|
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resp = client.get(image_url)
|
||
resp.raise_for_status()
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||
return resp.content, None
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||
except Exception: # noqa: BLE001
|
||
return None, err(1008, "图片下载失败或格式不支持")
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# base64：去掉 data:image/...;base64, 前缀
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try:
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b64 = image_base64.split(",", 1)[1] if image_base64.startswith("data:") else image_base64
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return base64.b64decode(b64), None
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except Exception: # noqa: BLE001
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return None, err(1008, "base64 解码失败")
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||
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||
|
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# 接口2/3/5 返回不透明照片，用 JPG 显著减小体积（接口1 标注图含透明，仍用 PNG）
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_JPG_QUALITY = int(os.getenv("JPG_QUALITY", "90"))
|
||
|
||
|
||
def _jpg_b64(bgr) -> str:
|
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"""BGR 图 → JPG base64。"""
|
||
_ok, buf = cv2.imencode(".jpg", bgr, [cv2.IMWRITE_JPEG_QUALITY, _JPG_QUALITY])
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return base64.b64encode(buf.tobytes()).decode()
|
||
|
||
|
||
def _png_to_jpg_b64(png_bytes) -> str:
|
||
"""ComfyUI 返回的 PNG 字节 → 重编码为 JPG base64；无法解码则原样透传。"""
|
||
img = cv2.imdecode(np.frombuffer(png_bytes, np.uint8), cv2.IMREAD_COLOR)
|
||
if img is None:
|
||
return base64.b64encode(png_bytes).decode()
|
||
return _jpg_b64(img)
|
||
|
||
|
||
def _parse_hair_styles(raw: Optional[str], max_styles: int) -> Optional[list[int]]:
|
||
"""解析逗号分隔的发型序号字符串 → 去重排序列表。非法返回 None。
|
||
|
||
"1,2,3" → [1, 2, 3] "3,1" → [1, 3] "1" → [1]
|
||
"""
|
||
if raw is None or not isinstance(raw, str) or not raw.strip():
|
||
return None
|
||
try:
|
||
styles = []
|
||
for part in raw.split(","):
|
||
part = part.strip()
|
||
if not part:
|
||
continue
|
||
v = int(part)
|
||
if v < 1 or v > max_styles:
|
||
return None
|
||
styles.append(v)
|
||
if not styles:
|
||
return None
|
||
# 去重保持顺序
|
||
seen = set()
|
||
unique = [s for s in styles if not (s in seen or seen.add(s))] # type: ignore[func-returns-value]
|
||
return unique
|
||
except (ValueError, TypeError):
|
||
return None
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# 通用图片请求 Body（JSON 方式，用于 url / base64）
|
||
# ---------------------------------------------------------------------------
|
||
|
||
_image_fields_desc = (
|
||
"图片传参方式严格互斥，必须且只能选其一：\n"
|
||
"- **image_file**（multipart/form-data 上传）\n"
|
||
"- **image_url**（完整 HTTP/HTTPS 地址）\n"
|
||
"- **image_base64**（需携带前缀，如 `data:image/jpeg;base64,xxxx`）\n\n"
|
||
"同时传多个或一个都不传，均返回错误码 `1007`。"
|
||
)
|
||
|
||
|
||
class ImageJsonBody(BaseModel):
|
||
image_url: Optional[str] = Field(
|
||
default=None,
|
||
description="图片 URL（与 image_base64 二选一，不可同时传）",
|
||
examples=["https://hair.xiangsilian.com/static/sample.jpg"],
|
||
)
|
||
image_base64: Optional[str] = Field(
|
||
default=None,
|
||
description="图片 base64，需带前缀，如 `data:image/jpeg;base64,xxxx`",
|
||
examples=["data:image/jpeg;base64,/9j/4AAQSkZJRgAB..."],
|
||
)
|
||
|
||
model_config = {
|
||
"json_schema_extra": {
|
||
"examples": [
|
||
{
|
||
"summary": "使用 URL 传图",
|
||
"value": {"image_url": "https://hair.xiangsilian.com/static/sample.jpg"},
|
||
},
|
||
{
|
||
"summary": "使用 base64 传图",
|
||
"value": {"image_base64": "data:image/jpeg;base64,/9j/4AAQSkZJRgAB..."},
|
||
},
|
||
]
|
||
}
|
||
}
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# 接口 1/6 共用实现
|
||
# ---------------------------------------------------------------------------
|
||
|
||
|
||
async def _face_measure_impl(image_file, image_url, image_base64, variant="v1"):
|
||
"""接口1/6 共用实现：四庭七眼测量 + 标注图生成。返回 (ok_dict, err_dict)。
|
||
|
||
variant="v1"（接口1）：完整四庭七眼 + 头部端线。
|
||
variant="v6"（接口6）：去掉头顶/顶庭、不画人头最左/最右端线、数据去顶庭。
|
||
"""
|
||
# 1. 三选一取图
|
||
raw, e = await resolve_image_bytes(image_file, image_url, image_base64)
|
||
if e is not None:
|
||
return None, e
|
||
|
||
# 2. 解码（不限制文件大小 / 分辨率）
|
||
image = cv2.imdecode(np.frombuffer(raw, np.uint8), cv2.IMREAD_COLOR)
|
||
if image is None:
|
||
return None, err(1008, "图片格式不支持（仅 JPG / PNG）")
|
||
|
||
h, w = image.shape[:2]
|
||
|
||
try:
|
||
from face_analysis.detector import detector
|
||
from face_analysis.pose import estimate_head_pose, check_frontal_face
|
||
from face_analysis.measure import measure_face
|
||
from face_analysis.annotation import create_annotated_image
|
||
|
||
# 5. 人脸检测
|
||
landmarks = detector.detect(image)
|
||
if landmarks is None:
|
||
return None, err(1001, "无法识别人像")
|
||
|
||
# 6. 姿态校验
|
||
if not check_frontal_face(landmarks, w, h):
|
||
return None, err(1003, "角度问题，请上传正面照")
|
||
head_pose = estimate_head_pose(landmarks, w, h)
|
||
|
||
# 7. 头发/耳朵分割（方案 B，单次推理），失败传 None 由 measure 内部回退方案 A。
|
||
# 传人脸包围盒 → 先按人脸裁剪再分割（全身/街拍等脸偏小的图也能稳出耳朵）。
|
||
hair_mask = None
|
||
ear_mask = None
|
||
try:
|
||
from face_analysis.hair_segmenter import get_segmenter
|
||
from face_analysis.calibration import normalized_to_pixel
|
||
pxs = [normalized_to_pixel(p, w, h) for p in landmarks.landmark]
|
||
face_box = (min(p[0] for p in pxs), min(p[1] for p in pxs),
|
||
max(p[0] for p in pxs), max(p[1] for p in pxs))
|
||
hair_mask, ear_mask = get_segmenter().segment_hair_and_ears(image, face_box=face_box)
|
||
except Exception as seg_e: # noqa: BLE001
|
||
logger.warning("头发/耳朵分割失败，回退方案A：%s", seg_e)
|
||
|
||
# 8. 测量 + 标注图（hair_mask 定发际线/头顶；ear_mask 定人头最左/最右竖线）
|
||
result = measure_face(landmarks, hair_mask, w, h, head_pose=head_pose)
|
||
annotated = create_annotated_image(
|
||
image, result, ear_mask=ear_mask, hair_mask=hair_mask, variant=variant)
|
||
buf = BytesIO()
|
||
annotated.save(buf, format="PNG")
|
||
|
||
# 9. 拆分架构：返回 base64，不落盘不拼 URL（落盘改 URL 由网关完成）
|
||
data = result.to_response()
|
||
if variant == "v6":
|
||
# 接口6：数据去顶庭（重算三庭比例与总高，移除顶庭/头顶字段）
|
||
vd = result.vertical
|
||
base_px = vd["upper_court_px"] + vd["middle_court_px"] + vd["lower_court_px"]
|
||
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)
|
||
data["landmarks"].pop("hair_top", None)
|
||
data["annotated_image_base64"] = base64.b64encode(buf.getvalue()).decode()
|
||
return ok(data), None
|
||
except Exception as ex: # noqa: BLE001
|
||
logger.exception("接口1/6 处理异常")
|
||
return None, err(1007, f"处理失败：{ex}")
|
||
|
||
|
||
@app.post(
|
||
"/api/v1/face/measure",
|
||
summary="接口1 四庭七眼测量标注",
|
||
tags=["人脸分析"],
|
||
description=f"""
|
||
输入用户正面照，返回：
|
||
- 标注好四庭七眼数据的 **PNG 图片**（仅标注图层，不含人物）
|
||
- 四庭（顶庭/上庭/中庭/下庭）各段**厘米数值及占比**
|
||
- 七眼（眼宽/脸宽/两眼间距）**厘米数值及占比**
|
||
- 五个关键分界点的**原图像素坐标**（头顶/发际线/眉心/鼻翼下缘/下巴尖）
|
||
|
||
{_image_fields_desc}
|
||
|
||
图片同时支持 `multipart/form-data` 文件上传（字段名 `image_file`），或 JSON Body 传 `image_url` / `image_base64`。
|
||
|
||
---
|
||
|
||
**坐标说明**：所有坐标以原图像素为基准，原点为图片左上角，x 向右，y 向下。
|
||
|
||
**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」
|
||
- 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
|
||
""",
|
||
responses={
|
||
200: {
|
||
"description": "成功",
|
||
"content": {
|
||
"application/json": {
|
||
"example": {
|
||
"code": 0,
|
||
"message": "success",
|
||
"request_id": "mock-request-id",
|
||
"data": {
|
||
"annotated_image_url": SAMPLE_IMAGE_URL,
|
||
"face_total_height_cm": 13.76,
|
||
"four_courts": {
|
||
"top_court_cm": 3.44,
|
||
"upper_court_cm": 3.44,
|
||
"middle_court_cm": 3.44,
|
||
"lower_court_cm": 3.44,
|
||
"ratios": {
|
||
"top_court": 0.25,
|
||
"upper_court": 0.25,
|
||
"middle_court": 0.25,
|
||
"lower_court": 0.25,
|
||
},
|
||
},
|
||
"seven_eyes": {
|
||
"eye_width_cm": 3.44,
|
||
"face_width_cm": 24.08,
|
||
"inter_eye_distance_cm": 3.44,
|
||
"ratios": {"eye_width": 0.143, "inter_eye_distance": 0.143},
|
||
},
|
||
"landmarks": {
|
||
"hair_top": {"x": 540, "y": 120},
|
||
"hairline": {"x": 540, "y": 430},
|
||
"brow_center": {"x": 540, "y": 740},
|
||
"nose_bottom": {"x": 540, "y": 1050},
|
||
"chin_tip": {"x": 540, "y": 1360},
|
||
},
|
||
},
|
||
}
|
||
}
|
||
},
|
||
},
|
||
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}},
|
||
"无法识别人像": {"value": {"code": 1001, "message": "无法识别人像", "request_id": "x", "data": None}},
|
||
"多张人脸": {"value": {"code": 1005, "message": "检测到多张人脸，仅支持单人照片", "request_id": "x", "data": None}},
|
||
}
|
||
}
|
||
},
|
||
},
|
||
},
|
||
)
|
||
async def face_measure(
|
||
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）"),
|
||
):
|
||
"""接口1：四庭七眼测量标注"""
|
||
ok_data, err_data = await _face_measure_impl(image_file, image_url, image_base64)
|
||
return ok_data if ok_data is not None else err_data
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# 接口 6：四庭七眼测量标注 v2（复刻接口1）
|
||
# ---------------------------------------------------------------------------
|
||
|
||
@app.post(
|
||
"/api/v1/face/measure-v2",
|
||
summary="接口6 四庭七眼测量标注 v2",
|
||
tags=["人脸分析"],
|
||
description=f"""
|
||
输入用户正面照，返回：
|
||
- 标注好四庭七眼数据的 **PNG 图片**（仅标注图层，不含人物）
|
||
- 三庭（上庭/中庭/下庭）各段**厘米数值及占比**（**不含顶庭**）
|
||
- 七眼（眼宽/脸宽/两眼间距）**厘米数值及占比**
|
||
- 四个关键分界点的**原图像素坐标**（发际线/眉心/鼻翼下缘/下巴尖）
|
||
|
||
基于接口1 的变体，与接口1 的差异：
|
||
- **去顶庭**：不画头顶横线、不返回顶庭数据；`face_total_height_cm` 为三庭之和
|
||
- **竖线范围**：纵向竖线从发际线画到下巴尖（接口1 为头顶→下巴尖）
|
||
- **不画人头最左/最右端线**：仅七眼 6 点共 5 段标尺，不取头发轮廓端线（接口1 为 8 线 7 段）
|
||
|
||
其余（箭头/虚线/字体/单位cm/七眼数据）与接口1 一致。
|
||
|
||
{_image_fields_desc}
|
||
|
||
图片同时支持 `multipart/form-data` 文件上传（字段名 `image_file`），或 JSON Body 传 `image_url` / `image_base64`。
|
||
|
||
---
|
||
|
||
**坐标说明**：所有坐标以原图像素为基准，原点为图片左上角，x 向右，y 向下。
|
||
|
||
**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」
|
||
- 段宽/庭高用虚线 + 实心三角双箭头标示
|
||
""",
|
||
responses={
|
||
200: {
|
||
"description": "成功",
|
||
"content": {
|
||
"application/json": {
|
||
"example": {
|
||
"code": 0,
|
||
"message": "success",
|
||
"request_id": "mock-request-id",
|
||
"data": {
|
||
"annotated_image_url": SAMPLE_IMAGE_URL,
|
||
"face_total_height_cm": 10.32,
|
||
"four_courts": {
|
||
"upper_court_cm": 3.44,
|
||
"middle_court_cm": 3.44,
|
||
"lower_court_cm": 3.44,
|
||
"ratios": {
|
||
"upper_court": 0.333,
|
||
"middle_court": 0.333,
|
||
"lower_court": 0.333,
|
||
},
|
||
},
|
||
"seven_eyes": {
|
||
"eye_width_cm": 3.44,
|
||
"face_width_cm": 24.08,
|
||
"inter_eye_distance_cm": 3.44,
|
||
"ratios": {"eye_width": 0.143, "inter_eye_distance": 0.143},
|
||
},
|
||
"landmarks": {
|
||
"hairline": {"x": 540, "y": 430},
|
||
"brow_center": {"x": 540, "y": 740},
|
||
"nose_bottom": {"x": 540, "y": 1050},
|
||
"chin_tip": {"x": 540, "y": 1360},
|
||
},
|
||
},
|
||
}
|
||
}
|
||
},
|
||
},
|
||
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}},
|
||
"无法识别人像": {"value": {"code": 1001, "message": "无法识别人像", "request_id": "x", "data": None}},
|
||
"多张人脸": {"value": {"code": 1005, "message": "检测到多张人脸，仅支持单人照片", "request_id": "x", "data": None}},
|
||
}
|
||
}
|
||
},
|
||
},
|
||
},
|
||
)
|
||
async def face_measure_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）"),
|
||
):
|
||
"""接口6：四庭七眼测量标注 v2（复刻接口1，去顶庭 + 去头部端线）"""
|
||
ok_data, err_data = await _face_measure_impl(
|
||
image_file, image_url, image_base64, variant="v6")
|
||
return ok_data if ok_data is not None else err_data
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# 接口 2：C 端生发
|
||
# ---------------------------------------------------------------------------
|
||
|
||
@app.post(
|
||
"/api/v1/hair/grow",
|
||
summary="接口2 C端生发",
|
||
tags=["生发"],
|
||
description=f"""
|
||
输入用户正面照 + **性别** + **发型序号**，返回指定发际线类型的预览图与生发图。每个方案包含：
|
||
- 预览图（worker 返回 `image_base64`，网关落盘后改写为 `image_url`）
|
||
- 发际线类型 `hairline_type`（英文 key）
|
||
- 顺序 `order`（本期固定 `1..N`，不排序）
|
||
|
||
{_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）：发型序号，**逗号分隔多选**（如 `1,2,3`），最多不超过该性别的预设数量。
|
||
`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**：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},
|
||
{"image_base64": "iVBORw0KGgo...", "hairline_type": "flower", "order": 2},
|
||
]
|
||
},
|
||
}
|
||
}
|
||
},
|
||
},
|
||
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(
|
||
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", 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)
|
||
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2 处理异常")
|
||
return err(1007, f"处理失败：{ex}")
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# 接口 7：C 端生发 v2（add_hair2.json 工作流）
|
||
# ---------------------------------------------------------------------------
|
||
|
||
_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", 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}")
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# 接口 3：B 端生发
|
||
# ---------------------------------------------------------------------------
|
||
|
||
@app.post(
|
||
"/api/v1/hair/grow-b",
|
||
summary="接口3 B端生发（医生/操作端）",
|
||
tags=["生发"],
|
||
description="""
|
||
医生/操作端在用户照片上**手动用马克笔划线标注**目标发际线后，**只需上传这一张划线图**，返回：
|
||
- 生发后效果图（系统检测划线 → 据此生成「植发 3 个月」效果）
|
||
- 发际线形（手绘为定制，固定 `custom`）
|
||
|
||
**划线图片**：字段名前缀为 `marked_image_`，支持文件/URL/base64 三选一。**不需要原始照片**。
|
||
""",
|
||
responses={
|
||
200: {
|
||
"description": "成功",
|
||
"content": {
|
||
"application/json": {
|
||
"example": {
|
||
"code": 0,
|
||
"message": "success",
|
||
"request_id": "mock-request-id",
|
||
"data": {
|
||
"hair_growth_image_base64": "iVBORw0KGgo...（生发图）",
|
||
"hairline_type": "custom",
|
||
},
|
||
}
|
||
}
|
||
},
|
||
},
|
||
400: {
|
||
"description": "参数错误",
|
||
"content": {
|
||
"application/json": {
|
||
"example": {"code": 1007, "message": "图片参数错误", "request_id": "x", "data": None}
|
||
}
|
||
},
|
||
},
|
||
},
|
||
)
|
||
async def hair_grow_b(
|
||
marked_image_file: Optional[UploadFile] = File(default=None, description="划线图片文件（JPG/PNG）"),
|
||
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", 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)
|
||
if e is not None:
|
||
return e
|
||
|
||
marked = cv2.imdecode(np.frombuffer(marked_raw, np.uint8), cv2.IMREAD_COLOR)
|
||
if marked 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_b
|
||
|
||
res = await run_in_threadpool(generate_grow_b, marked, use_mask, prompt)
|
||
if res["status"] == "no_face":
|
||
return err(1001, "无法识别人像")
|
||
if res["status"] == "no_line":
|
||
return err(1001, "未检测到发际线划线，请确认划线图额头有清晰的手绘发际线")
|
||
|
||
grown_b64 = _png_to_jpg_b64(res["grown_png"]) if res["grown_png"] else None # 生发图 JPG
|
||
data = {
|
||
"hair_growth_image_base64": grown_b64,
|
||
"hairline_type": "custom",
|
||
}
|
||
return ok(data)
|
||
except Exception as ex: # noqa: BLE001
|
||
logger.exception("接口3 处理异常")
|
||
return err(1007, f"处理失败：{ex}")
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# 接口 4：用户特征
|
||
# ---------------------------------------------------------------------------
|
||
|
||
@app.post(
|
||
"/api/v1/face/features",
|
||
summary="接口4 用户特征分析",
|
||
tags=["人脸分析"],
|
||
description=f"""
|
||
输入用户照片，返回 N 个用户面部特征字段。
|
||
|
||
{_image_fields_desc}
|
||
|
||
图片同时支持 `multipart/form-data` 文件上传（字段名 `image_file`）。
|
||
|
||
---
|
||
|
||
由**火山方舟 豆包视觉模型**分析，返回**固定 6 个英文字段**。
|
||
|
||
**返回格式**：`data.features` 为一个 **JSON 字符串**（不是对象），需要在客户端 `JSON.parse()` 后使用。
|
||
|
||
| 字段 | 说明 |
|
||
|------|------|
|
||
| face_shape | 脸形（如"鹅蛋脸"） |
|
||
| eyebrow_shape | 眉形（如"平眉"） |
|
||
| facial_age | 面部年龄（区间，如"18-25岁"） |
|
||
| dynamic_static_type | 动静类型（"静态型"/"动态型"） |
|
||
| gender | 性别（"男"/"女"） |
|
||
| gene_style | 基因风格（如"自然型"） |
|
||
|
||
> 无人脸返回 `1001`。
|
||
""",
|
||
responses={
|
||
200: {
|
||
"description": "成功",
|
||
"content": {
|
||
"application/json": {
|
||
"example": {
|
||
"code": 0,
|
||
"message": "success",
|
||
"request_id": "mock-request-id",
|
||
"data": {
|
||
"features": '{"face_shape":"鹅蛋脸","eyebrow_shape":"平眉","facial_age":"18-25岁","dynamic_static_type":"静态型","gender":"女","gene_style":"少年型"}',
|
||
},
|
||
}
|
||
}
|
||
},
|
||
},
|
||
400: {
|
||
"description": "参数错误 / 图片识别失败",
|
||
"content": {
|
||
"application/json": {
|
||
"example": {"code": 1001, "message": "无法识别人像", "request_id": "x", "data": None}
|
||
}
|
||
},
|
||
},
|
||
},
|
||
)
|
||
async def face_features(
|
||
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）"),
|
||
):
|
||
# ⚠️ 接口4 已迁到**网关本机**实现（直接调豆包视觉模型，见 gateway/app.py）。
|
||
# 网关不会把本接口转发到 worker，故此处仅留 Mock 占位、保持 worker 无外网依赖。
|
||
features = json.dumps(
|
||
{
|
||
"face_shape": "鹅蛋脸", "eyebrow_shape": "平眉", "facial_age": "18-25岁",
|
||
"dynamic_static_type": "静态型", "gender": "女", "gene_style": "少年型",
|
||
},
|
||
ensure_ascii=False,
|
||
)
|
||
return ok({"features": features})
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# 接口 5：发际线 PNG 生成
|
||
# ---------------------------------------------------------------------------
|
||
|
||
@app.post(
|
||
"/api/v1/hairline/generate",
|
||
summary="接口5 发际线PNG生成",
|
||
tags=["人脸分析"],
|
||
description=f"""
|
||
输入用户照片 + 性别 + 多选发型，对每个选中发型返回 middle/high/low 三档发际线叠图与生发图，
|
||
并标注最合适发际线的面部中间点坐标。
|
||
|
||
{_image_fields_desc}
|
||
|
||
图片同时支持 `multipart/form-data` 文件上传（字段名 `image_file`）。
|
||
|
||
---
|
||
|
||
**入参**（同接口2：先选性别，再多选发型）：
|
||
- 必填 `gender`（`male`/`female`），决定发型集合（female 5 / male 4）。
|
||
- 必填 `hair_style`（发型序号，逗号分隔如 `1,2,3`），决定返回哪些发际线类型。缺失/越界/非法返回 `1007`。
|
||
`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。
|
||
|
||
**返回说明**：
|
||
|
||
- `hairline_images`：**选中发型**的列表，数量 = 所选发型数，`order` = 发型序号。每项含：
|
||
- `image_middle_url` / `image_high_url` / `image_low_url`：该发型 middle/high/low 三档发际线叠图（同接口2预览）。
|
||
- `grown_image_url`：该发型的**生发图**（生发失败时为 `null`）。
|
||
- `hairline_type`：发际线类型 key。
|
||
worker 返回 `*_base64`，网关落盘后改写为 `*_url`。
|
||
- `best_hairline_center_point`：**首个选中发型**的 middle 档发际线曲线**面部中间点**坐标，
|
||
以**原图像素**为基准（左上角为原点，x 向右，y 向下）。
|
||
""",
|
||
responses={
|
||
200: {
|
||
"description": "成功",
|
||
"content": {
|
||
"application/json": {
|
||
"example": {
|
||
"code": 0,
|
||
"message": "success",
|
||
"request_id": "mock-request-id",
|
||
"data": {
|
||
"hairline_images": [
|
||
{"hairline_type": "ellipse", "image_middle_base64": "iVBORw0KGgo...", "image_high_base64": "iVBORw0KGgo...", "image_low_base64": "iVBORw0KGgo...", "grown_image_base64": "iVBORw0KGgo...", "order": 1},
|
||
{"hairline_type": "flower", "image_middle_base64": "iVBORw0KGgo...", "image_high_base64": "iVBORw0KGgo...", "image_low_base64": "iVBORw0KGgo...", "grown_image_base64": None, "order": 2},
|
||
],
|
||
"best_hairline_center_point": {"x": 540, "y": 430},
|
||
},
|
||
}
|
||
}
|
||
},
|
||
},
|
||
400: {
|
||
"description": "参数错误 / 图片识别失败",
|
||
"content": {
|
||
"application/json": {
|
||
"example": {"code": 1001, "message": "无法识别人像", "request_id": "x", "data": None}
|
||
}
|
||
},
|
||
},
|
||
},
|
||
)
|
||
async def hairline_generate(
|
||
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"),
|
||
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", description="ComfyUI 提示词（同接口2），会替换工作流节点60的文本"),
|
||
):
|
||
if gender not in ("male", "female"):
|
||
return err(1004, "gender 必填且只能为 male / female")
|
||
|
||
# hair_style 必填（同接口2）：解析逗号分隔，缺失/越界/非法 → 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}")
|
||
|
||
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_hairline_pngs
|
||
|
||
res = await run_in_threadpool(
|
||
generate_hairline_pngs, image, gender, hair_styles, use_mask, prompt)
|
||
if res is None:
|
||
return err(1001, "无法识别人像")
|
||
|
||
hairline_images = []
|
||
for it in res["images"]:
|
||
ov = it["overlays"]
|
||
hairline_images.append({
|
||
"hairline_type": it["hairline_type"],
|
||
"image_middle_base64": _jpg_b64(ov["middle"]), # 发际线叠图 middle 档 JPG
|
||
"image_high_base64": _jpg_b64(ov["high"]), # 发际线叠图 high 档 JPG
|
||
"image_low_base64": _jpg_b64(ov["low"]), # 发际线叠图 low 档 JPG
|
||
"grown_image_base64": (_png_to_jpg_b64(it["grown_png"]) # 生发图 JPG（失败为 null）
|
||
if it.get("grown_png") else None),
|
||
"order": it["order"],
|
||
})
|
||
c = res["best_center"]
|
||
data = {
|
||
"hairline_images": hairline_images,
|
||
"best_hairline_center_point": ({"x": c[0], "y": c[1]} if c else None),
|
||
}
|
||
return ok(data)
|
||
except Exception as ex: # noqa: BLE001
|
||
logger.exception("接口5 处理异常")
|
||
return err(1007, f"处理失败：{ex}")
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# 接口 9：头发遮罩生成
|
||
# ---------------------------------------------------------------------------
|
||
|
||
@app.post(
|
||
"/api/v1/head/mask",
|
||
summary="接口9 头发遮罩生成",
|
||
tags=["人脸分析"],
|
||
description=f"""
|
||
输入一张含人头的照片，生成头发遮罩，并返回**每一步的可视化图**（供对比调试）：
|
||
|
||
1. MediaPipe 关键点 → 底部分割线（关键点 21,68,104,69,108,151,337,299,333,298,251 的连线，
|
||
21 水平延伸到最左边、251 延伸到最右边）。
|
||
2. 分割线以上为「上半区」。
|
||
3. 头发分割（**BiSeNet** 与 **SegFormer** 两套）；从每列最顶端头发向下填充到分割线，
|
||
得到**含额头**的闭合区域（头发+额头，不割断）。
|
||
4. 外缘朝中心点 151 内缩 **erode_cm（默认 1.2cm，可调）**（虹膜标定换算像素）、底线不动 → 最终遮罩。
|
||
|
||
{_image_fields_desc}
|
||
|
||
返回 `data` 内含 `steps_common`（关键点/分割线、上半区）与 `bisenet` / `segformer`
|
||
两组结果（各含 `hair_mask` / `closed_region` / `final_overlay` / `mask`）。经网关时所有
|
||
`*_base64` 图片字段会被落盘改写为 `*_url`。
|
||
""",
|
||
responses={
|
||
200: {
|
||
"description": "成功",
|
||
"content": {
|
||
"application/json": {
|
||
"example": {
|
||
"code": 0,
|
||
"message": "success",
|
||
"request_id": "mock-request-id",
|
||
"data": {
|
||
"px_per_cm": 48.12,
|
||
"erode_cm": 1.2,
|
||
"erode_px": 58,
|
||
"image_size": {"width": 1080, "height": 1440},
|
||
"steps_common": {"landmarks_baseline_url": SAMPLE_IMAGE_URL,
|
||
"upper_region_url": SAMPLE_IMAGE_URL},
|
||
"bisenet": {"hair_pixels": 123456, "closed_pixels": 110000, "mask_pixels": 98765,
|
||
"hair_mask_url": SAMPLE_IMAGE_URL,
|
||
"closed_region_url": SAMPLE_IMAGE_URL,
|
||
"final_overlay_url": SAMPLE_IMAGE_URL,
|
||
"mask_url": SAMPLE_IMAGE_URL},
|
||
"segformer": {"hair_pixels": 130000, "closed_pixels": 112000, "mask_pixels": 99000,
|
||
"hair_mask_url": SAMPLE_IMAGE_URL,
|
||
"closed_region_url": SAMPLE_IMAGE_URL,
|
||
"final_overlay_url": SAMPLE_IMAGE_URL,
|
||
"mask_url": SAMPLE_IMAGE_URL},
|
||
},
|
||
}
|
||
}
|
||
},
|
||
},
|
||
},
|
||
)
|
||
async def head_mask(
|
||
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）"),
|
||
erode_cm: float = Form(default=1.2, description="外缘朝中心151内缩的距离（厘米），默认 1.2"),
|
||
):
|
||
"""接口9：头发遮罩生成 + 分步可视化"""
|
||
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 face_analysis.head_mask import generate_head_mask, NoFaceError
|
||
try:
|
||
data = await run_in_threadpool(generate_head_mask, image, erode_cm)
|
||
except NoFaceError:
|
||
return err(1001, "无法识别人像")
|
||
return ok(data)
|
||
except Exception as ex: # noqa: BLE001
|
||
logger.exception("接口9 处理异常")
|
||
return err(1007, f"处理失败：{ex}")
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# 接口 10：头部外缘膨胀带遮罩
|
||
# ---------------------------------------------------------------------------
|
||
|
||
@app.post(
|
||
"/api/v1/head/band",
|
||
summary="接口10 头部外缘膨胀带遮罩",
|
||
tags=["人脸分析"],
|
||
description=f"""
|
||
先和接口9 一样得到**内缩后的基准遮罩**（含额头的闭合区域外缘朝151内缩 erode_cm、底线不动，默认1.2cm），
|
||
在此基础上生成一条沿头部外缘的膨胀带遮罩：
|
||
|
||
1. 取基准遮罩的**外轮廓线**，去掉贴着底部分割线的那一段（只留头发/头部外缘弧线）。
|
||
2. 把外轮廓线膨胀成带子（**总宽 dilate_cm，默认 2cm，可调**；半径=总宽/2，虹膜标定换算像素）。
|
||
3. 裁到分割线以上（不越过底线）。
|
||
|
||
{_image_fields_desc}
|
||
|
||
返回 `data` 内含 `steps_common`（关键点/分割线、上半区）与 `bisenet` / `segformer`
|
||
两组结果（各含 `base_mask` / `contour` / `band_overlay` / `mask`）。经网关时所有
|
||
`*_base64` 图片字段会被落盘改写为 `*_url`。
|
||
""",
|
||
responses={
|
||
200: {
|
||
"description": "成功",
|
||
"content": {
|
||
"application/json": {
|
||
"example": {
|
||
"code": 0,
|
||
"message": "success",
|
||
"request_id": "mock-request-id",
|
||
"data": {
|
||
"px_per_cm": 48.12,
|
||
"erode_cm": 1.2,
|
||
"erode_px": 58,
|
||
"dilate_cm": 2.0,
|
||
"dilate_radius_px": 48,
|
||
"image_size": {"width": 1080, "height": 1440},
|
||
"steps_common": {"landmarks_baseline_url": SAMPLE_IMAGE_URL,
|
||
"upper_region_url": SAMPLE_IMAGE_URL},
|
||
"bisenet": {"base_pixels": 96000, "band_pixels": 42000,
|
||
"base_mask_url": SAMPLE_IMAGE_URL,
|
||
"contour_url": SAMPLE_IMAGE_URL,
|
||
"band_overlay_url": SAMPLE_IMAGE_URL,
|
||
"mask_url": SAMPLE_IMAGE_URL},
|
||
"segformer": {"base_pixels": 97000, "band_pixels": 43000,
|
||
"base_mask_url": SAMPLE_IMAGE_URL,
|
||
"contour_url": SAMPLE_IMAGE_URL,
|
||
"band_overlay_url": SAMPLE_IMAGE_URL,
|
||
"mask_url": SAMPLE_IMAGE_URL},
|
||
},
|
||
}
|
||
}
|
||
},
|
||
},
|
||
},
|
||
)
|
||
async def head_band(
|
||
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）"),
|
||
erode_cm: float = Form(default=1.2, description="基准遮罩外缘朝151内缩距离（厘米，同接口9），默认 1.2"),
|
||
dilate_cm: float = Form(default=2.0, description="外轮廓线膨胀后带子总宽（厘米），默认 2.0"),
|
||
):
|
||
"""接口10：头部外缘膨胀带遮罩 + 分步可视化"""
|
||
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 face_analysis.head_band import generate_head_band, NoFaceError
|
||
try:
|
||
data = await run_in_threadpool(generate_head_band, image, erode_cm, dilate_cm)
|
||
except NoFaceError:
|
||
return err(1001, "无法识别人像")
|
||
return ok(data)
|
||
except Exception as ex: # noqa: BLE001
|
||
logger.exception("接口10 处理异常")
|
||
return err(1007, f"处理失败：{ex}")
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# 接口 11：发际线生发（接口9 遮罩 + change_hair 换发型 + 按遮罩羽化贴回）
|
||
# ---------------------------------------------------------------------------
|
||
|
||
@app.post(
|
||
"/api/v1/hairline/grow",
|
||
summary="接口11 发际线生发",
|
||
tags=["生发"],
|
||
description=f"""
|
||
输入一张**发际线较高 / 头发稀少**的正脸图 + **发际线类型 ID**（= change_hair 的 `hair_id`，
|
||
如 `chang_tuoyuan`/`chang_bolang`/`chang_zhixian`/`chang_xinxing`/`chang_huaban`），
|
||
输出同一个人、同一发型、按该发际线类型压低发际线后的图片，并返回**每一步可视化**。
|
||
|
||
管线（见 `docs/发际线增强算法.md`）：
|
||
1. 用接口9 算法算头发遮罩（含额头闭合区域，外缘内缩 `erode_cm`）。`seg_model` 选
|
||
BiSeNet/SegFormer，`mask_type` 选 eroded(内缩)/closed(闭合区域)。
|
||
2. 调 change_hair 换发型服务生成该发际线类型图（返回图已与原图同分辨率同对齐）。
|
||
`swap_mode=ext_mask`：把接口9 遮罩作为 `ext_mask` 传给换发型，webui 精确重绘该区域
|
||
（忠于算法文档）；`swap_mode=as_is`：不改换发型，贴回时再裁到接口9 遮罩。
|
||
3. 严格按接口9 遮罩把生成图贴回原图（遮罩外=原图不动）。
|
||
4. 接缝融合：`blend_method` 选 feather(高斯羽化)/alpha_gradient(距离变换内渐变)/
|
||
seamless(泊松无缝克隆)/multiband(多频段金字塔融合)；`feather_px`、`edge_erode_px` 控制过渡细节
|
||
（feather_px 仅 feather/alpha_gradient 用；multiband 用 `mb_levels` 控制金字塔层数 2~6）。
|
||
`color_match=true` 时先在遮罩区做 Reinhard 颜色统计迁移，消除生成图与原图的整体色差
|
||
（对 feather/alpha_gradient/multiband 有效；seamless 自带色彩调和，自动跳过）。
|
||
|
||
{_image_fields_desc}
|
||
|
||
返回 `data.steps` 含 `input`/`baseline`/`hair_mask`/`mask_overlay`/`mask`/`swap_raw`/
|
||
`alpha`/`final` 各步图（`*_base64`，经网关改写为 `*_url`）。
|
||
""",
|
||
)
|
||
async def hairline_grow(
|
||
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）"),
|
||
hairline_id: str = Form(..., description="发际线类型 ID（= change_hair hair_id，如 chang_tuoyuan）"),
|
||
gen_backend: str = Form(default="swaphair", description="生成后端：swaphair(换发型LoRA) | hairgrow(区域生发inpaint，压低发际线)（默认 swaphair）"),
|
||
hairgrow_strength: float = Form(default=0.75, description="区域生发强度（仅 hairgrow 后端），默认 0.75"),
|
||
is_hr: bool = Form(default=False, description="高清模式（换发型输出 1152×1536，否则 576×768）"),
|
||
seg_model: str = Form(default="segformer", description="头发分割模型：bisenet | segformer（默认 segformer）"),
|
||
mask_type: str = Form(default="eroded", description="遮罩类型：eroded(内缩) | closed(闭合区域) | pushed(发际线外推)（默认 eroded）"),
|
||
erode_cm: float = Form(default=1.2, description="遮罩外缘朝中心151内缩距离（厘米，同接口9），默认 1.2"),
|
||
hairline_push_cm: float = Form(default=1.0, description="发际线外推距离（厘米，往头发方向推进；仅 mask_type=pushed 生效），默认 1.0"),
|
||
hairline_edge: str = Form(default="column", description="发际线提取方式：column(逐列最低点) | contour(形态学轮廓)（仅 pushed 生效），默认 column"),
|
||
swap_mode: str = Form(default="ext_mask", description="换发型取图模式：ext_mask(改造换发型用接口9遮罩) | as_is(不改换发型，贴回再裁)（默认 ext_mask）"),
|
||
blend_method: str = Form(default="feather", description="接缝融合：feather(高斯羽化) | alpha_gradient(距离渐变) | seamless(泊松无缝) | multiband(多频段金字塔)（默认 feather）"),
|
||
feather_px: int = Form(default=15, description="羽化/渐变过渡宽度（像素），默认 15"),
|
||
edge_erode_px: int = Form(default=3, description="贴图前遮罩内缩像素（防边缘露皮/光晕），默认 3"),
|
||
denoising_strength: float = Form(default=0.6, description="换发型 webui 重绘强度（越大生发越激进），默认 0.6"),
|
||
color_match: bool = Form(default=False, description="融合前对生成图做 Reinhard 颜色校正（消除整体色差，seamless 下自动跳过），默认 false"),
|
||
mb_levels: int = Form(default=5, description="multiband 多频段金字塔层数（2~6，越大低频色差抹得越宽，仅 multiband 生效），默认 5"),
|
||
):
|
||
"""接口11：发际线生发 + 分步可视化"""
|
||
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 face_analysis.hairline_grow import generate_hairline_grow, NoFaceError, SwapError
|
||
from uuid import uuid4 as _uuid4
|
||
rid = _uuid4().hex[:8]
|
||
logger.info("[%s] 接口11 收到请求: mask_type=%s hairline_push_cm=%s hairline_edge=%s",
|
||
rid, mask_type, hairline_push_cm, hairline_edge)
|
||
try:
|
||
data = await run_in_threadpool(
|
||
generate_hairline_grow, image, hairline_id, is_hr, seg_model,
|
||
mask_type, erode_cm, swap_mode, blend_method, feather_px, edge_erode_px,
|
||
denoising_strength, gen_backend, hairgrow_strength, color_match, mb_levels,
|
||
hairline_push_cm=hairline_push_cm, hairline_edge=hairline_edge, rid=rid)
|
||
except NoFaceError:
|
||
return err(1001, "无法识别人像")
|
||
except SwapError as se:
|
||
return err(1007, f"换发型失败：{se}")
|
||
logger.info("[%s] 接口11 成功返回", rid)
|
||
return ok(data)
|
||
except Exception as ex: # noqa: BLE001
|
||
logger.exception("接口11 处理异常")
|
||
return err(1007, f"处理失败：{ex}")
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# 接口 12：发际线生发（接口11 固定参数精简版）
|
||
# ---------------------------------------------------------------------------
|
||
|
||
@app.post(
|
||
"/api/v1/hairline/grow_v2",
|
||
summary="接口12 发际线生发（固定金字塔融合，仅返回最终图）",
|
||
tags=["生发"],
|
||
description=f"""
|
||
接口11 的固定参数精简版，适合生产直调。与接口11 共用同一管线，区别仅在于：
|
||
|
||
- **固定** `blend_method=multiband`（多频段金字塔融合）、`mb_levels=5`、`erode_cm=0.6`
|
||
（外缘朝中心151 内缩 0.6cm）。这三项不可调，故本接口不暴露。
|
||
- **返回值精简**：只返回 `final_base64`（最终合成图），不再附带接口11 的分步可视化。
|
||
|
||
其余参数（hairline_id、seg_model、gen_backend、is_hr、denoising_strength、color_match、
|
||
edge_erode_px 等）仍保留为可选 Form，调用方可按需覆盖，未传则用接口11 同款默认值。
|
||
|
||
{_image_fields_desc}
|
||
""",
|
||
)
|
||
async def hairline_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）"),
|
||
hairline_id: str = Form(..., description="发际线类型 ID（= change_hair hair_id，如 chang_tuoyuan）"),
|
||
gen_backend: str = Form(default="swaphair", description="生成后端：swaphair(换发型LoRA) | hairgrow(区域生发inpaint，压低发际线)（默认 swaphair）"),
|
||
hairgrow_strength: float = Form(default=0.75, description="区域生发强度（仅 hairgrow 后端），默认 0.75"),
|
||
is_hr: bool = Form(default=False, description="高清模式（换发型输出 1152×1536，否则 576×768）"),
|
||
seg_model: str = Form(default="segformer", description="头发分割模型：bisenet | segformer（默认 segformer）"),
|
||
mask_type: str = Form(default="eroded", description="遮罩类型：eroded(内缩) | closed(闭合区域) | pushed(发际线外推)（默认 eroded）"),
|
||
swap_mode: str = Form(default="ext_mask", description="换发型取图模式：ext_mask(改造换发型用接口9遮罩) | as_is(不改换发型，贴回再裁)（默认 ext_mask）"),
|
||
feather_px: int = Form(default=15, description="羽化/渐变过渡宽度（像素，本接口固定 multiband 故不生效，仅留作兼容）"),
|
||
edge_erode_px: int = Form(default=3, description="贴图前遮罩内缩像素（防边缘露皮/光晕），默认 3"),
|
||
denoising_strength: float = Form(default=0.6, description="换发型 webui 重绘强度（越大生发越激进），默认 0.6"),
|
||
color_match: bool = Form(default=False, description="融合前对生成图做 Reinhard 颜色校正（消除整体色差），默认 false"),
|
||
hairline_push_cm: float = Form(default=1.0, description="发际线外推距离（厘米，仅 mask_type=pushed 生效），默认 1.0"),
|
||
hairline_edge: str = Form(default="column", description="发际线提取方式：column | contour（仅 pushed 生效），默认 column"),
|
||
):
|
||
"""接口12：发际线生发（固定 multiband/mb_levels=5/erode_cm=0.6，仅返回最终图）。"""
|
||
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 face_analysis.hairline_grow import generate_hairline_grow, NoFaceError, SwapError
|
||
try:
|
||
# 固定三项：blend_method=multiband、mb_levels=5、erode_cm=0.6
|
||
data = await run_in_threadpool(
|
||
generate_hairline_grow, image, hairline_id, is_hr, seg_model,
|
||
mask_type, 0.6, swap_mode, "multiband", feather_px, edge_erode_px,
|
||
denoising_strength, gen_backend, hairgrow_strength, color_match, 5,
|
||
hairline_push_cm=hairline_push_cm, hairline_edge=hairline_edge)
|
||
except NoFaceError:
|
||
return err(1001, "无法识别人像")
|
||
except SwapError as se:
|
||
return err(1007, f"换发型失败：{se}")
|
||
# 精简返回：只取最终合成图，丢掉接口11 的全部分步可视化
|
||
return ok({
|
||
"hairline_id": data["hairline_id"],
|
||
"image_size": data["image_size"],
|
||
"final_base64": data["steps"]["final_base64"],
|
||
})
|
||
except Exception as ex: # noqa: BLE001
|
||
logger.exception("接口12 处理异常")
|
||
return err(1007, f"处理失败：{ex}")
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# 调试：下载后端日志（接口11 遮罩计算全过程）
|
||
# ---------------------------------------------------------------------------
|
||
|
||
@app.get("/api/v1/debug/hairline_log", include_in_schema=False)
|
||
async def download_hairline_log(rid: Optional[str] = None, tail: int = 500):
|
||
"""返回 /home/xsl/hair/log/hairline_grow.log 的内容。
|
||
|
||
rid 非空时只返回该 request id 相关的行；tail 限制返回最后 N 行（默认 500）。
|
||
供调试页"下载日志"按钮调用。
|
||
"""
|
||
from fastapi.responses import PlainTextResponse
|
||
log_path = "/home/xsl/hair/log/hairline_grow.log"
|
||
try:
|
||
with open(log_path, encoding="utf-8") as fh:
|
||
lines = fh.readlines()
|
||
except FileNotFoundError:
|
||
return PlainTextResponse("(日志文件不存在，可能服务还没处理过请求)", media_type="text/plain")
|
||
if rid:
|
||
lines = [l for l in lines if f"[{rid}]" in l]
|
||
lines = lines[-tail:] if tail > 0 else lines
|
||
return PlainTextResponse("".join(lines), media_type="text/plain; charset=utf-8")
|
||
|
||
|
||
# ---------------------------------------------------------------------------
|
||
# 健康检查
|
||
# ---------------------------------------------------------------------------
|
||
|
||
@app.get("/health", include_in_schema=False)
|
||
async def health():
|
||
# 模型就绪后才返回 200，供网关探测；未就绪返回 503。
|
||
if not _STATE["ready"]:
|
||
return JSONResponse(status_code=503, content={"status": "starting"})
|
||
return {"status": "ok"}
|
||
|
||
|
||
@app.get("/", include_in_schema=False)
|
||
async def index():
|
||
return {"service": "旷视五接口", "version": "0.1.0", "docs": f"{BASE_URL}/docs"}
|