xslandClaude Opus 4.8
8d3b145111
worker 侧从 Mock 替换为真实算法： - face_analysis 包：detector(MediaPipe 478点) / pose(solvePnP 姿态) / calibration(虹膜直径法) / hair_segmenter+bisenet_model(方案B 头发分割) / measure(方案A兜底+B/A决策+七眼+换算) / annotation(numpy渐变线+中文标注) - app.py：/api/v1/face/measure 接真实实现，返回 annotated_image_base64 （不落盘不拼URL，落盘由网关做）；加 X-Internal-Token 鉴权、/health 就绪态、 可配置分辨率门槛、异常兜底 - 部署：start.sh/run_worker.sh/hair-worker.service 监听 8187；worker_config 示例 - 测试 tests/：Tier1合成真值<1e-6 + Tier2缩放不变 + Tier3叠加 + 错误码集成 + 数值回归，pytest 24 项全绿 - 文档补实测基线表 + RTX5090/torch 说明 注：worker 为 RTX 5090(sm_120)，pinned torch 2.2.2(cu121) 只到 sm_90， BiSeNet 已自动回退 CPU（方案B 正常）；要用 GPU 需换 torch cu128(≥2.7)。 Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
86 lines
3.1 KiB
Python
86 lines
3.1 KiB
Python
"""尺度校准：像素 → 厘米（虹膜直径法，眼宽降级）。
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人类虹膜直径高度稳定（成人平均 11.7mm），作为天然标尺把像素距离换算成厘米。
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虹膜点（索引 469/471、474/476）需 refine_landmarks=True 才输出；缺失时降级用
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眼宽（外→内眼角，均值约 2.85cm）。详见技术方案 §3。
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"""
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from face_analysis.face_mesh_landmarks import (
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IRIS_LEFT_LEFT, IRIS_LEFT_RIGHT, IRIS_RIGHT_LEFT, IRIS_RIGHT_RIGHT,
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LEFT_EYE_OUTER, LEFT_EYE_INNER, RIGHT_EYE_INNER, RIGHT_EYE_OUTER,
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)
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AVG_IRIS_DIAMETER_CM = 1.17 # 虹膜平均直径 11.7mm
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AVG_EYE_WIDTH_CM = 2.85 # 眼裂平均宽度约 28.5mm（降级标尺）
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def _lm_list(landmarks):
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"""兼容 NormalizedLandmarkList（有 .landmark）与裸 list 两种入参。"""
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return landmarks.landmark if hasattr(landmarks, "landmark") else landmarks
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def normalized_to_pixel(landmark, image_width, image_height):
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"""归一化坐标 → 像素坐标。"""
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return landmark.x * image_width, landmark.y * image_height
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def pixel_distance(p1, p2):
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"""两点像素欧氏距离。"""
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return ((p1[0] - p2[0]) ** 2 + (p1[1] - p2[1]) ** 2) ** 0.5
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def _iris_diameter_px(lm, w, h):
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"""左右虹膜直径像素均值；任一边缘点缺失/为 0 返回 None。"""
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try:
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ll = normalized_to_pixel(lm[IRIS_LEFT_LEFT], w, h)
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lr = normalized_to_pixel(lm[IRIS_LEFT_RIGHT], w, h)
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rl = normalized_to_pixel(lm[IRIS_RIGHT_LEFT], w, h)
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rr = normalized_to_pixel(lm[IRIS_RIGHT_RIGHT], w, h)
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except (IndexError, KeyError):
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return None
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left_d = pixel_distance(ll, lr)
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right_d = pixel_distance(rl, rr)
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if left_d <= 0 or right_d <= 0:
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return None
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return (left_d + right_d) / 2
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def _eye_width_px(lm, w, h):
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"""左右眼宽（外→内眼角）像素均值，作为虹膜降级标尺。"""
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l = pixel_distance(normalized_to_pixel(lm[LEFT_EYE_OUTER], w, h),
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normalized_to_pixel(lm[LEFT_EYE_INNER], w, h))
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r = pixel_distance(normalized_to_pixel(lm[RIGHT_EYE_OUTER], w, h),
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normalized_to_pixel(lm[RIGHT_EYE_INNER], w, h))
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return (l + r) / 2
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def estimate_scale_factor(landmarks, image_width, image_height):
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"""估算 px_per_cm（每厘米对应像素数）。
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优先用虹膜直径法；虹膜点不可用时降级用眼宽。返回正浮点数。
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"""
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lm = _lm_list(landmarks)
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iris_px = _iris_diameter_px(lm, image_width, image_height)
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if iris_px is not None:
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return iris_px / AVG_IRIS_DIAMETER_CM
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# 降级：眼宽法
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eye_px = _eye_width_px(lm, image_width, image_height)
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return eye_px / AVG_EYE_WIDTH_CM
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if __name__ == "__main__":
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import sys
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import cv2
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from face_analysis.detector import detector
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path = sys.argv[1] if len(sys.argv) > 1 else "tests/fixtures/frontal.jpg"
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img = cv2.imread(path)
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if img is None:
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print(f"无法读取图片: {path}")
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sys.exit(1)
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h, w = img.shape[:2]
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lms = detector.detect(img)
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if lms is None:
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print("未检出人脸")
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sys.exit(1)
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print(f"px_per_cm: {estimate_scale_factor(lms, w, h):.4f}")
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