hello. I am working on this for a while but cannot succeed to implement it and need your help.
My goal is to reproduce these images bellow from this data obtained from skeleton estimation of human pose using LCR-NET++
the pose estimation for one image frame is here:
“pose3d”: [-0.013501551933586597, -0.14018067717552185, 0.03889404982328415, -0.01468866690993309, -0.052195221185684204, -0.019107796251773834, 0.1497691571712494, 0.3384685516357422, -0.01354127749800682, 0.20444869995117188, -0.01537160761654377, 0.10283246636390686, 0.16161373257637024, -0.9542085528373718, -1.0142440795898438, -0.5674616694450378, -0.6482287049293518, -0.21104587614536285, -0.26092272996902466, 0.01090222503989935, -0.06246425583958626, 0.07578188925981522, -0.06475285440683365, 0.27830997109413147, 0.16628871858119965, 0.40817680954933167, 0.4491078853607178, 0.26747873425483704, 0.3288397789001465, 0.15092524886131287, 0.14701153337955475, -0.013860990293323994, 0.31942757964134216, -0.10401999950408936, 0.2921887934207916, -0.2079567015171051, 0.12265170365571976, -0.21420519053936005, -0.07994606345891953]
Here is my code. What is missing?
from mpl_toolkits import mplot3d
import numpy as np
import matplotlib.pyplot as plt
ax = plt.axes(projection='3d')
fig = plt.figure()
xdata = np.array([-0.013501551933586597, -0.14018067717552185, 0.03889404982328415, -0.01468866690993309, -0.052195221185684204, -0.019107796251773834, 0.1497691571712494, 0.3384685516357422, -0.01354127749800682, 0.20444869995117188, -0.01537160761654377, 0.10283246636390686, 0.16161373257637024])
ydata = np.array([-0.9542085528373718, -1.0142440795898438, -0.5674616694450378, -0.6482287049293518, -0.21104587614536285, -0.26092272996902466, 0.01090222503989935, -0.06246425583958626, 0.07578188925981522, -0.06475285440683365, 0.27830997109413147, 0.16628871858119965, 0.40817680954933167])
zdata = np.array([0.4491078853607178, 0.26747873425483704, 0.3288397789001465, 0.15092524886131287, 0.14701153337955475, -0.013860990293323994, 0.31942757964134216, -0.10401999950408936, 0.2921887934207916, -0.2079567015171051, 0.12265170365571976, -0.21420519053936005, -0.07994606345891953])
ax.scatter3D(xdata, ydata, zdata, c=zdata)
plt.show()