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reproject/geometry_utils.py

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+import numpy as np
+import cv2
+
+# 左眼
+LEFT_EYE = [33, 160, 158, 133, 153, 144]
+# 右眼
+RIGHT_EYE = [362, 385, 387, 263, 373, 380]
+# 嘴唇 (内圈)
+LIPS = [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308, 415, 310, 311, 312, 13]
+
+def _euclidean_distance(point1, point2):
+    return np.linalg.norm(point1 - point2)
+
+def calculate_ear(landmarks, width, height):
+    """计算眼睛纵横比 EAR"""
+    # 坐标转换
+    points = np.array([(p.x * width, p.y * height) for p in landmarks])
+    
+    # 垂直距离
+    v1 = _euclidean_distance(points[1], points[5])
+    v2 = _euclidean_distance(points[2], points[4])
+    # 水平距离
+    h = _euclidean_distance(points[0], points[3])
+    
+    ear = (v1 + v2) / (2.0 * h)
+    return ear
+
+def calculate_mar(landmarks, width, height):
+    """计算嘴巴纵横比 MAR"""
+    points = np.array([(p.x * width, p.y * height) for p in landmarks])
+    pass 
+
+def calculate_mar_simple(top, bottom, left, right):
+    h = _euclidean_distance(top, bottom)
+    w = _euclidean_distance(left, right)
+    return h / w
+
+# geometry_utils.py 中的 estimate_head_pose 函数替换为以下内容
+
+def estimate_head_pose(landmarks, width, height):
+    """
+    计算头部姿态 (Pitch, Yaw, Roll)
+    返回单位：角度 (Degree)
+    """
+    # 3D 模型点 (标准人脸模型)
+    model_points = np.array([
+        (0.0, 0.0, 0.0),             # Nose tip
+        (0.0, -330.0, -65.0),        # Chin
+        (-225.0, 170.0, -135.0),     # Left eye left corner
+        (225.0, 170.0, -135.0),      # Right eye right corner
+        (-150.0, -150.0, -125.0),    # Left Mouth corner
+        (150.0, -150.0, -125.0)      # Right mouth corner
+    ])
+
+    # MediaPipe 对应的关键点索引
+    idx_list = [1, 152, 33, 263, 61, 291]
+    
+    image_points = []
+    for idx in idx_list:
+        p = landmarks[idx]
+        image_points.append((p.x * width, p.y * height))
+    
+    image_points = np.array(image_points, dtype="double")
+
+    focal_length = width
+    center = (width / 2, height / 2)
+    camera_matrix = np.array(
+        [[focal_length, 0, center[0]],
+         [0, focal_length, center[1]],
+         [0, 0, 1]], dtype="double"
+    )
+    dist_coeffs = np.zeros((4, 1)) 
+
+    # 求解PnP
+    success, rotation_vector, translation_vector = cv2.solvePnP(
+        model_points, image_points, camera_matrix, dist_coeffs
+    )
+
+    rmat, _ = cv2.Rodrigues(rotation_vector)
+    angles, mtxR, mtxQ, Qx, Qy, Qz = cv2.RQDecomp3x3(rmat)
+
+    pitch = angles[0]
+    yaw   = angles[1]
+    roll  = angles[2]
+
+    if pitch < -180: pitch += 360
+    if pitch > 180:  pitch -= 360
+    pitch = 180 - pitch if pitch > 0 else -pitch - 180
+    if yaw < -180: yaw += 360
+    if yaw > 180:  yaw -= 360
+    if roll < -180: roll += 360
+    if roll > 180:  roll -= 360
+
+    return pitch, yaw, roll