将姿势估计结果添加到列表中，包含深度信息

pose_results.append([folder_name, results.pose_landmarks.landmark[mp_pose.PoseLandmark.NOSE].x,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.NOSE].y,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.NOSE].z,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_SHOULDER].x,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_SHOULDER].y,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_SHOULDER].z,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_SHOULDER].x,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_SHOULDER].y,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_SHOULDER].z,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_ELBOW].x,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_ELBOW].y,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_ELBOW].z,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_ELBOW].x,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_ELBOW].y,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_ELBOW].z,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_WRIST].x,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_WRIST].y,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_WRIST].z,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_WRIST].x,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_WRIST].y,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_WRIST].z,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_HIP].x,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_HIP].y,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_HIP].z,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_HIP].x,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_HIP].y,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_HIP].z,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_KNEE].x,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_KNEE].y,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_KNEE].z,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_KNEE].x,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_KNEE].y,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_KNEE].z,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_ANKLE].x,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_ANKLE].y,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.LEFT_ANKLE].z,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_ANKLE].x,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_ANKLE].y,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.RIGHT_ANKLE].z])

这段代码将姿势估计结果添加到名为 pose_results 的列表中。每个结果包含文件夹名称，以及每个关键点的 x，y，z 坐标。

注意：

results 是 mediapipe.solutions.pose 模块的输出结果。
mp_pose.PoseLandmark 是一个枚举类型，用于表示人体姿势的关键点。
每个关键点都有 x，y，z 坐标，分别代表关键点在三维空间中的位置。

示例：

pose_results = []
folder_name = 'images'
results = # 姿势估计结果

pose_results.append([folder_name, results.pose_landmarks.landmark[mp_pose.PoseLandmark.NOSE].x,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.NOSE].y,
                         results.pose_landmarks.landmark[mp_pose.PoseLandmark.NOSE].z,
                         # 其他关键点的坐标...
                        ])

注意：

以上代码仅供参考，实际使用时需要根据具体情况进行调整。
确保您已正确安装 mediapipe 库。
确保您已正确加载和处理姿势估计结果。

相关资源：

希望本文档能够帮助您理解如何将姿势估计结果添加到列表中，并包含深度信息。如有任何问题，请随时提问。