feat: 接口5 新增 face_measure（复用接口1测量数值）+ 接口1 七眼 eye1~eye7
接口5（/api/v1/hairline/generate）在发际线结果基础上新增 data.face_measure， 复用接口1的四庭七眼测量数值（四庭/七眼 eye1~eye7/landmarks/姿态）， 不含标注图；独立流程容错，测量失败时为 null 不影响发际线主结果。 重构：提取 _run_face_measure_data() 共用函数，接口1/6 改调它再补标注图， 行为不变（43 测试全过，错误码 1001/1003/1008 回归正常）。 接口1/5 七眼新增 eye1~eye7 从左到右 7 段宽度（cm），eye1/eye7 耳朵不可见 时为 null（保留键）。 测试页 test_interface5.html：移除点击切换卡片网格改为所有发型平铺， 新增四庭七眼测量卡片。前端接入页 integration.html / 接口文档同步更新。
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@@ -310,6 +310,81 @@ class ImageJsonBody(BaseModel):
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# ---------------------------------------------------------------------------
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def _run_face_measure_data(image, variant="v1"):
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"""接口1测量数值核心：detect → 姿态校验 → 头发/耳朵分割 → measure_face → eye1~eye7。
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返回 (data_dict, result, hair_mask, ear_mask)，或检测/姿态失败时返回 None。
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不含标注图（annotated_image_*），供接口5 容错复用；接口1 调用后再自行生成标注图。
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任何分割/七眼计算异常均内部吞掉（七眼相关字段不出现），不影响主测量结果。
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variant="v1"（接口1/接口5）：完整四庭七眼 + eye1~eye7（含头部端线段）。
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variant="v6"（接口6）：去顶庭、不画端线、无 eye1~eye7。
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"""
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h, w = image.shape[:2]
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from face_analysis.detector import detector
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from face_analysis.pose import estimate_head_pose, check_frontal_face
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from face_analysis.measure import measure_face
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landmarks = detector.detect(image)
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if landmarks is None:
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return None
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if not check_frontal_face(landmarks, w, h):
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return None
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head_pose = estimate_head_pose(landmarks, w, h)
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# 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。
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hair_mask = None
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ear_mask = None
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try:
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from face_analysis.hair_segmenter import get_segmenter
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from face_analysis.calibration import normalized_to_pixel
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pxs = [normalized_to_pixel(p, w, h) for p in landmarks.landmark]
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face_box = (min(p[0] for p in pxs), min(p[1] for p in pxs),
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max(p[0] for p in pxs), max(p[1] for p in pxs))
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hair_mask, ear_mask = get_segmenter().segment_hair_and_ears(image, face_box=face_box)
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except Exception as seg_e: # noqa: BLE001
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logger.warning("头发/耳朵分割失败，回退方案A：%s", seg_e)
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result = measure_face(landmarks, hair_mask, w, h, head_pose=head_pose)
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data = result.to_response()
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if variant == "v6":
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vd = result.vertical
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base_px = vd["upper_court_px"] + vd["middle_court_px"] + vd["lower_court_px"]
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data["four_courts"]["ratios"] = {
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"upper_court": round(vd["upper_court_px"] / base_px, 3),
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"middle_court": round(vd["middle_court_px"] / base_px, 3),
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"lower_court": round(vd["lower_court_px"] / base_px, 3),
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}
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data["four_courts"].pop("top_court_cm", None)
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data["face_total_height_cm"] = round(
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result.upper_cm + result.middle_cm + result.lower_cm, 2)
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data["landmarks"].pop("hair_top", None)
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# 七眼：从左到右共 7 段宽度（cm），仅接口1（v1）含人头最左/最右端线段。
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# eye1=左耳外段 eye2=左脸颊段 eye3=左眼 eye4=两眼间距 eye5=右眼 eye6=右脸颊段 eye7=右耳外段
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# 端线取自耳朵分割外缘（与标注图同源）；某侧耳朵不可见 → 该侧端线缺失 → 对应 eye 置 null（保留键）。
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if variant != "v6":
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try:
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from face_analysis.annotation import _ear_edges_from_mask
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epts = result.eyes["points"]
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lcx, rcx = epts["left_cheek"][0], epts["right_cheek"][0]
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head_l, head_r = _ear_edges_from_mask(
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ear_mask, hair_mask,
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result.vertical["hair_top"][1], result.vertical["chin_tip"][1],
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lcx, rcx, (lcx + rcx) / 2)
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xs = [head_l, lcx, epts["left_outer"][0], epts["left_inner"][0],
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epts["right_inner"][0], epts["right_outer"][0], rcx, head_r]
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pc = result.px_per_cm
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for i in range(7):
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a, b = xs[i], xs[i + 1]
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data["seven_eyes"][f"eye{i + 1}"] = (
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None if (a is None or b is None) else round((b - a) / pc, 2))
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except Exception as seg_e: # noqa: BLE001
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logger.warning("七眼段宽度计算失败：%s", seg_e)
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return data, result, hair_mask, ear_mask
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async def _face_measure_impl(image_file, image_url, image_base64, variant="v1"):
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"""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)。
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@@ -326,60 +401,24 @@ async def _face_measure_impl(image_file, image_url, image_base64, variant="v1"):
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if image is None:
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return None, err(1008, "图片格式不支持（仅 JPG / PNG）")
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h, w = image.shape[:2]
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try:
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from face_analysis.detector import detector
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from face_analysis.pose import estimate_head_pose, check_frontal_face
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from face_analysis.measure import measure_face
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from face_analysis.annotation import create_annotated_image
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# 5. 人脸检测
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landmarks = detector.detect(image)
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if landmarks is None:
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return None, err(1001, "无法识别人像")
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# 6. 姿态校验
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if not check_frontal_face(landmarks, w, h):
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ret = _run_face_measure_data(image, variant=variant)
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if ret is None:
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# 区分错误码：未检出人脸 vs 非正面。重新检测一次以判断。
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from face_analysis.detector import detector
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from face_analysis.pose import check_frontal_face
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if detector.detect(image) is None:
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return None, err(1001, "无法识别人像")
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return None, err(1003, "角度问题，请上传正面照")
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head_pose = estimate_head_pose(landmarks, w, h)
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data, result, hair_mask, ear_mask = ret
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# 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。
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# 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）。
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hair_mask = None
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ear_mask = None
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try:
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from face_analysis.hair_segmenter import get_segmenter
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from face_analysis.calibration import normalized_to_pixel
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pxs = [normalized_to_pixel(p, w, h) for p in landmarks.landmark]
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face_box = (min(p[0] for p in pxs), min(p[1] for p in pxs),
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max(p[0] for p in pxs), max(p[1] for p in pxs))
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hair_mask, ear_mask = get_segmenter().segment_hair_and_ears(image, face_box=face_box)
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except Exception as seg_e: # noqa: BLE001
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logger.warning("头发/耳朵分割失败，回退方案A：%s", seg_e)
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# 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）
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result = measure_face(landmarks, hair_mask, w, h, head_pose=head_pose)
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# 标注图（接口1/6 才需要；接口5 复用 _run_face_measure_data 时不生成）
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from face_analysis.annotation import create_annotated_image
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annotated = create_annotated_image(
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image, result, ear_mask=ear_mask, hair_mask=hair_mask, variant=variant)
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buf = BytesIO()
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annotated.save(buf, format="PNG")
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# 9. 拆分架构：返回 base64，不落盘不拼 URL（落盘改 URL 由网关完成）
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data = result.to_response()
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if variant == "v6":
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# 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）
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vd = result.vertical
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base_px = vd["upper_court_px"] + vd["middle_court_px"] + vd["lower_court_px"]
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data["four_courts"]["ratios"] = {
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"upper_court": round(vd["upper_court_px"] / base_px, 3),
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"middle_court": round(vd["middle_court_px"] / base_px, 3),
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"lower_court": round(vd["lower_court_px"] / base_px, 3),
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}
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data["four_courts"].pop("top_court_cm", None)
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data["face_total_height_cm"] = round(
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result.upper_cm + result.middle_cm + result.lower_cm, 2)
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data["landmarks"].pop("hair_top", None)
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data["annotated_image_base64"] = base64.b64encode(buf.getvalue()).decode()
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return ok(data), None
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except Exception as ex: # noqa: BLE001
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@@ -442,6 +481,8 @@ async def _face_measure_impl(image_file, image_url, image_base64, variant="v1"):
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"face_width_cm": 24.08,
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"inter_eye_distance_cm": 3.44,
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"ratios": {"eye_width": 0.143, "inter_eye_distance": 0.143},
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"eye1": 3.44, "eye2": 3.44, "eye3": 3.44, "eye4": 3.44,
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"eye5": 3.44, "eye6": 3.44, "eye7": 3.44,
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},
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"landmarks": {
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"hair_top": {"x": 540, "y": 120},
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@@ -1012,6 +1053,31 @@ async def face_features(
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{"hairline_type": "flower", "image_middle_base64": "iVBORw0KGgo...", "image_high_base64": "iVBORw0KGgo...", "image_low_base64": "iVBORw0KGgo...", "grown_image_base64": None, "order": 2},
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],
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"best_hairline_center_point": {"x": 540, "y": 430},
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"face_measure": {
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"face_total_height_cm": 13.76,
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"four_courts": {
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"top_court_cm": 3.44, "upper_court_cm": 3.44,
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"middle_court_cm": 3.44, "lower_court_cm": 3.44,
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"ratios": {"top_court": 0.25, "upper_court": 0.25,
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"middle_court": 0.25, "lower_court": 0.25},
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},
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"seven_eyes": {
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"eye_width_cm": 3.44, "face_width_cm": 24.08,
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"inter_eye_distance_cm": 3.44,
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"ratios": {"eye_width": 0.143, "inter_eye_distance": 0.143},
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"eye1": 3.44, "eye2": 3.44, "eye3": 3.44, "eye4": 3.44,
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"eye5": 3.44, "eye6": 3.44, "eye7": 3.44,
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},
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"landmarks": {
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"hair_top": {"x": 540, "y": 120},
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"hairline": {"x": 540, "y": 430},
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"brow_center": {"x": 540, "y": 740},
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"nose_bottom": {"x": 540, "y": 1050},
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"chin_tip": {"x": 540, "y": 1360},
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},
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"hairline_source": "segmentation",
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"head_pose": {"yaw": -1.39, "pitch": 2.49, "roll": -0.06},
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},
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},
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}
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}
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@@ -1079,6 +1145,16 @@ async def hairline_generate(
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"hairline_images": hairline_images,
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"best_hairline_center_point": ({"x": c[0], "y": c[1]} if c else None),
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}
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# face_measure：复用接口1测量数值（四庭/七眼 eye1~eye7/landmarks/姿态），不含标注图。
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# 独立流程，容错：测量失败（无人脸/非正面/分割失败）→ null，不影响发际线主结果。
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try:
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fm = _run_face_measure_data(image, variant="v1")
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data["face_measure"] = fm[0] if fm is not None else None
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except Exception as fm_e: # noqa: BLE001
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logger.warning("接口5 face_measure 失败：%s", fm_e)
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data["face_measure"] = None
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return ok(data)
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except Exception as ex: # noqa: BLE001
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logger.exception("接口5 处理异常")
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