sorry for the whole code

I’m very inexperienced and don’t know how to correctly simplify

Context

Pose Keypoint extraction of picture/video

keypoint coordinates & calculated angles export to .csv for later analysis

import csv
import pandas as pd
from ultralytics import YOLO
from pathlib import Path
import numpy as np

model = YOLO("yolo11n-pose.pt")
results = model.track(source='file.png', save=False)

def calculate_angle(p1, p2, p3):
    # p1, p2, p3 are the points in format [x, y]
    # Calculate the vectors
    v1 = np.array(p1) - np.array(p2)
    v2 = np.array(p3) - np.array(p2)
    
    # Calculate the angle in radians
    angle_rad = np.arccos(np.dot(v1, v2) / (np.linalg.norm(v1) * np.linalg.norm(v2)))
    
    # Convert to degrees
    angle_deg = np.degrees(angle_rad)
    
    return angle_deg


ja_list = [[9,7,5], [10,8,6], [7,5,11], [8,6,12], [5,11,13], [6,12,14], [11,13,15], [12,14,16]]

# Initialize an empty list to store data
data = []

for frame_id, (frame_results) in enumerate(results):
    for person_id, person in enumerate(frame_results.keypoints):
        xy = person.xyn.numpy()  # keypoints coordinates 
        conf = person.conf.numpy()  # confidence scores of keypoints
        for kp_id, (xy, kp_conf) in enumerate(zip(xy, conf)):
            xy_str = ', '.join(map(str, xy))  # Convert the array to a comma-separated string
            
            data.append({"frame_id": frame_id, "person_id": person_id, "nose, left eye, right eye, left ear, right ear, left shoulder, right shoulder, left elbow, right elbow, left wrist, right wrist, left hip, right hip, left knee, right knee, left ankle, right ankle": xy_str})

        for ja in ja_list:
            angle = calculate_angle(xy[ja[0]],xy[ja[1]],xy[ja[2]])
            str_angle = angle

            data.append({"left elbow angle, right elbow angle, left shoulder angle, right shoulder angle, left hip angle, right hip angle, left knee angle, right knee angle": str_angle})

    df = pd.DataFrame(data)
    df.to_csv('file.csv', escapechar=' ', quoting=csv.QUOTE_NONE, index=False)

Current Output

frame_id,person_id,nose ,  left  eye ,  right  eye ,  left  ear ,  right  ear ,  left  shoulder ,  right  shoulder ,  left  elbow ,  right  elbow ,  left  wrist ,  right  wrist ,  left  hip ,  right  hip ,  left  knee ,  right  knee ,  left  ankle ,  right  ankle,left  elbow  angle ,  right  elbow  angle ,  left  shoulder  angle ,  right  shoulder  angle ,  left  hip  angle ,  right  hip  angle ,  left  knee  angle ,  right  knee  angle
0.0,0.0,[        0.27054          0.32959] ,  [        0.27079          0.32787] ,  [        0.26698          0.32339] ,  [                    0                      0] ,  [        0.25605          0.33095] ,  [        0.27429          0.39124] ,  [        0.24764          0.34531] ,  [        0.29295          0.40439] ,  [        0.25213            0.2805] ,  [        0.31294          0.41499] ,  [        0.26839          0.21751] ,  [        0.25684          0.49569] ,  [        0.23976          0.47824] ,  [        0.26361          0.59153] ,  [        0.25314          0.57706] ,  [        0.26301          0.68071] ,  [        0.25716          0.68032],
,,,172.7757568359375
,,,169.49624633789062
,,,64.31809997558594
,,,179.4266357421875
,,,166.47421264648438
,,,168.8917999267578
,,,175.57078552246094
,,,174.5126953125

Desired Output

frame_id,person_id,nose ,  left  eye ,  right  eye ,  left  ear ,  right  ear ,  left  shoulder ,  right  shoulder ,  left  elbow ,  right  elbow ,  left  wrist ,  right  wrist ,  left  hip ,  right  hip ,  left  knee ,  right  knee ,  left  ankle ,  right  ankle,left  elbow  angle ,  right  elbow  angle ,  left  shoulder  angle ,  right  shoulder  angle ,  left  hip  angle ,  right  hip  angle ,  left  knee  angle ,  right  knee  angle
0.0,0.0,[        0.27054          0.32959] ,  [        0.27079          0.32787] ,  [        0.26698          0.32339] ,  [                    0                      0] ,  [        0.25605          0.33095] ,  [        0.27429          0.39124] ,  [        0.24764          0.34531] ,  [        0.29295          0.40439] ,  [        0.25213            0.2805] ,  [        0.31294          0.41499] ,  [        0.26839          0.21751] ,  [        0.25684          0.49569] ,  [        0.23976          0.47824] ,  [        0.26361          0.59153] ,  [        0.25314          0.57706] ,  [        0.26301          0.68071] ,  [        0.25716          0.68032], 172.7757568359375, 169.49624633789062, 64.31809997558594, 179.4266357421875, 166.47421264648438, 168.8917999267578, 175.57078552246094, 174.5126953125

Problem:

for ja in ja_list:
            angle = calculate_angle(xy[ja[0]],xy[ja[1]],xy[ja[2]])
            str_angle = angle

            data.append({"left elbow angle, right elbow angle, left shoulder angle, right shoulder angle, left hip angle, right hip angle, left knee angle, right knee angle": str_angle})

I think the problem is the data.append is being looped.

I need a way to append all 8 angle values once

I don’t know how to integrate properly…

Sorry if this is trivial, I’ve been stuck on this for hours searching anywhere I could but I give up