145 lines
4.1 KiB
Python
145 lines
4.1 KiB
Python
import numpy as np
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import cv2
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# 左眼
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LEFT_EYE = [33, 160, 158, 133, 153, 144]
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# 右眼
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RIGHT_EYE = [362, 385, 387, 263, 373, 380]
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# 左眼虹膜关键点索引
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LEFT_EYE_GAZE_IDXS = [33, 133, 159, 145, 468]
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# 右眼虹膜关键点索引
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RIGHT_EYE_GAZE_IDXS = [263, 362, 386, 374, 473]
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# 嘴唇 (内圈)
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LIPS = [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308, 415, 310, 311, 312, 13]
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def _euclidean_distance(point1, point2):
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return np.linalg.norm(point1 - point2)
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def calculate_ear(landmarks, width, height):
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"""计算眼睛纵横比 EAR"""
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# 坐标转换
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points = np.array([(p.x * width, p.y * height) for p in landmarks])
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# 垂直距离
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v1 = _euclidean_distance(points[1], points[5])
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v2 = _euclidean_distance(points[2], points[4])
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# 水平距离
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h = _euclidean_distance(points[0], points[3])
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ear = (v1 + v2) / (2.0 * h)
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return ear
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def calculate_iris_pos(landmarks, indices, width, height):
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p_left = np.array([landmarks[indices[0]].x * width, landmarks[indices[0]].y * height])
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p_right = np.array([landmarks[indices[1]].x * width, landmarks[indices[1]].y * height])
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p_top = np.array([landmarks[indices[2]].x * width, landmarks[indices[2]].y * height])
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p_bottom = np.array([landmarks[indices[3]].x * width, landmarks[indices[3]].y * height])
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p_iris = np.array([landmarks[indices[4]].x * width, landmarks[indices[4]].y * height])
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# 修改为欧几里得距离计算
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eye_width = _euclidean_distance(p_left, p_right)
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iris_left = _euclidean_distance(p_iris, p_left)
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if eye_width < 1e-3:
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raw_x = 0.5
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else :
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raw_x = iris_left / eye_width
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eye_height = _euclidean_distance(p_bottom, p_top)
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iris_top = _euclidean_distance(p_iris, p_top)
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if eye_height < 1e-3:
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raw_y = 0.5
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else:
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raw_y = iris_top / eye_height
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# x_min = 0.4
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# x_max = 0.6
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# ratio_x = abs(raw_x - x_min) / (x_max - x_min)
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# y_min = 0.2
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# y_max = 0.8
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# ratio_y = abs(raw_y - y_min) / (y_max - y_min)
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ratio_x = raw_x
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ratio_y = raw_y
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return max(0.0, min(1.0, ratio_x)), max(0.0, min(1.0, ratio_y))
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def calculate_mar(landmarks, width, height):
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"""计算嘴巴纵横比 MAR"""
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points = np.array([(p.x * width, p.y * height) for p in landmarks])
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pass
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def calculate_mar_simple(top, bottom, left, right):
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h = _euclidean_distance(top, bottom)
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w = _euclidean_distance(left, right)
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return h / w
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# geometry_utils.py 中的 estimate_head_pose 函数替换为以下内容
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def estimate_head_pose(landmarks, width, height):
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"""
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计算头部姿态 (Pitch, Yaw, Roll)
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返回单位：角度 (Degree)
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"""
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# 3D 模型点 (标准人脸模型)
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model_points = np.array(
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[
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(0.0, 0.0, 0.0), # Nose tip
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(0.0, -330.0, -65.0), # Chin
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(-225.0, 170.0, -135.0), # Left eye left corner
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(225.0, 170.0, -135.0), # Right eye right corner
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(-150.0, -150.0, -125.0), # Left Mouth corner
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(150.0, -150.0, -125.0), # Right mouth corner
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]
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)
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# MediaPipe 对应的关键点索引
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idx_list = [1, 152, 33, 263, 61, 291]
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image_points = []
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for idx in idx_list:
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p = landmarks[idx]
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image_points.append((p.x * width, p.y * height))
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image_points = np.array(image_points, dtype="double")
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focal_length = width
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center = (width / 2, height / 2)
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camera_matrix = np.array(
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[[focal_length, 0, center[0]], [0, focal_length, center[1]], [0, 0, 1]],
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dtype="double",
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)
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dist_coeffs = np.zeros((4, 1))
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# 求解PnP
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success, rotation_vector, translation_vector = cv2.solvePnP(
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model_points, image_points, camera_matrix, dist_coeffs
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)
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rmat, _ = cv2.Rodrigues(rotation_vector)
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angles, mtxR, mtxQ, Qx, Qy, Qz = cv2.RQDecomp3x3(rmat)
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pitch = angles[0]
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yaw = angles[1]
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roll = angles[2]
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if pitch < -180:
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pitch += 360
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if pitch > 180:
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pitch -= 360
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pitch = 180 - pitch if pitch > 0 else -pitch - 180
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if yaw < -180:
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yaw += 360
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if yaw > 180:
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yaw -= 360
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if roll < -180:
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roll += 360
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if roll > 180:
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roll -= 360
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return pitch, yaw, roll
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