#初始化一个列表来存储检测到的关键点。
landmarks = []
#遍历Mediapipe检测到的关键点。
for landmark in results.pose_landmarks.landmark:
    
    #将Mediapipe关键点添加到列表中。
    landmarks.append((int(landmark.x * width), int(landmark.y * height),
                            (landmark.z * width)))
#为特定的关键点创建索引列表
body_landmark_indices = [11,12,13,14,15,16,23,24,25,26,27,28,29,30,31,32]
landmark_list_body = []
#创建一个仅包含所需关键点的列表
for index in body_landmark_indices:
    landmark_list_body.append(landmarks[index - 1])
mp_drawing.draw_landmarks(
                    image=output_image,
                    landmark_list=landmark_list_body,
                    connections=mp_pose.POSE_CONNECTIONS,
                    landmark_drawing_spec=landmark_drawing_spec,
                    connection_drawing_spec=connection_drawing_spec)`
执行上述代码时，我收到错误信息`'list' object has no attribute 'pose_landmarks'`。
我已经用`landmark_list=landmark_list_body`替换了`landmark_list=landmark_list_body.pose_landmarks`，但仍然出现错误。
我现在非常疲倦并且没有更多的想法。是否有无需斗篷的英雄可以帮助？
谢谢。
<details>
<summary>英文:</summary>
I have installed Mediapipe (0.9.0.1) using Python (3.7.0) on windows 11.
I have been able to successfully get Mediapipe to generate landmarks (for face and body); for an image, video, and webcam stream.
I would like to now get Mediapipe to **only** draw body specific landmarks (i.e. exclude facial landmarks).
I understand that I may use OpenCV (or Czone) to accomplish this goal, however, I am looking to achieve my objective using Mediapipe (i.e. using the `draw_landmarks` function in the MediaPipe library).
The specific bit of code I am trying (but with errors) is the following:

# Iterate over the Mediapipe detected landmarks.
for landmark in results.pose_landmarks.landmark:
    
    # Append the Mediapipe landmark into the list.
    landmarks.append((int(landmark.x * width), int(landmark.y * height),
                            (landmark.z * width)))
#create index list for specific landmarks 
body_landmark_indices = [11,12,13,14,15,16,23,24,25,26,27,28,29,30,31,32]
landmark_list_body = []
#Create a list which only has the required landmarks
for index in body_landmark_indices:
    landmark_list_body.append(landmarks[index - 1])
mp_drawing.draw_landmarks(
                    image=output_image,
                    landmark_list=landmark_list_body.pose_landmarks,
                    connections=mp_pose.POSE_CONNECTIONS,
                    landmark_drawing_spec=landmark_drawing_spec,
                    connection_drawing_spec=connection_drawing_spec)`

I have replaced `landmark_list=landmark_list_body.pose_landmarks,` with `landmark_list=landmark_list_body` but with errors.
I am now very tiered and out of ideas. Is there a capeless hero out there?
Thanks.
</details>
# 答案1
**得分**: 5
你可以尝试以下方法：
```python
import cv2
import mediapipe as mp
import numpy as np
from mediapipe.python.solutions.pose import PoseLandmark
from mediapipe.python.solutions.drawing_utils import DrawingSpec
mp_drawing = mp.solutions.drawing_utils
mp_drawing_styles = mp.solutions.drawing_styles
mp_pose = mp.solutions.pose
custom_style = mp_drawing_styles.get_default_pose_landmarks_style()
custom_connections = list(mp_pose.POSE_CONNECTIONS)
# 要从绘图中排除的关键点列表
excluded_landmarks = [
    PoseLandmark.LEFT_EYE, 
    PoseLandmark.RIGHT_EYE, 
    PoseLandmark.LEFT_EYE_INNER, 
    PoseLandmark.RIGHT_EYE_INNER, 
    PoseLandmark.LEFT_EAR,
    PoseLandmark.RIGHT_EAR,
    PoseLandmark.LEFT_EYE_OUTER,
    PoseLandmark.RIGHT_EYE_OUTER,
    PoseLandmark.NOSE,
    PoseLandmark.MOUTH_LEFT,
    PoseLandmark.MOUTH_RIGHT ]
for landmark in excluded_landmarks:
    # 改变被排除关键点的绘制方式
    custom_style[landmark] = DrawingSpec(color=(255,255,0), thickness=None) 
    # 删除包含这些关键点的所有连接
    custom_connections = [connection_tuple for connection_tuple in custom_connections 
                            if landmark.value not in connection_tuple]
IMAGE_FILES = ["test.jpg"]
BG_COLOR = (192, 192, 192) 
with mp_pose.Pose(
    static_image_mode=True,
    model_complexity=2,
    enable_segmentation=True,
    min_detection_confidence=0.5) as pose:
    for idx, file in enumerate(IMAGE_FILES):
        image = cv2.imread(file)
        image_height, image_width, _ = image.shape
        results = pose.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
        annotated_image = image.copy()
        mp_drawing.draw_landmarks(
            annotated_image,
            results.pose_landmarks,
            connections = custom_connections, # 传递修改后的连接列表
            landmark_drawing_spec=custom_style) # 和绘制样式 
        cv2.imshow('landmarks', annotated_image)
        cv2.waitKey(0)

if drawing_spec.thickness == None: continue

...
      drawing_spec = landmark_drawing_spec[idx] if isinstance(
          landmark_drawing_spec, Mapping) else landmark_drawing_spec
      if drawing_spec.thickness == None: continue
      # White circle border
      circle_border_radius = max(drawing_spec.circle_radius + 1,
                                 int(drawing_spec.circle_radius * 1.2))
...