59 lines
1.5 KiB
Python
59 lines
1.5 KiB
Python
from scipy.signal import savgol_filter
|
|
import numpy as np
|
|
import pickle
|
|
from matplotlib import pyplot as plt
|
|
|
|
with open("replay_xyz.pkl", "rb") as f:
|
|
points3DList = pickle.load(f)
|
|
|
|
skeleton = [
|
|
[0, 1], [0, 2],
|
|
[1, 3], [2, 4],
|
|
[5, 7], [7, 9],
|
|
[6, 8], [8, 10],
|
|
[5, 6],
|
|
[5, 11], [6, 12],
|
|
[11, 12],
|
|
[11, 13], [13, 15],
|
|
[12, 14], [14, 16]
|
|
]
|
|
|
|
keys_sorted = sorted(points3DList.keys())
|
|
points_sequence = np.array([points3DList[k] for k in keys_sorted]) # (frames, points, 3)
|
|
|
|
# --- Filtr Savitzky-Golaya ---
|
|
window_length = 7 # musi być nieparzyste
|
|
polyorder = 2
|
|
smoothed_sequence = savgol_filter(points_sequence, window_length=window_length,
|
|
polyorder=polyorder, axis=0, mode='nearest')
|
|
|
|
plt.ion()
|
|
fig = plt.figure()
|
|
ax = fig.add_subplot(111, projection='3d')
|
|
|
|
points_plot = ax.scatter([], [], [], c='r', marker='o', s=50)
|
|
lines_plot = [ax.plot([0,0],[0,0],[0,0], c='b')[0] for _ in skeleton]
|
|
|
|
ax.set_xlabel('X')
|
|
ax.set_ylabel('Y')
|
|
ax.set_zlabel('Z')
|
|
ax.set_xlim(-0.6, 0.4)
|
|
ax.set_ylim(1.2, 2.2)
|
|
ax.set_zlim(-0.5, 1.1)
|
|
ax.view_init(elev=20, azim=-60)
|
|
|
|
for frame_points in smoothed_sequence:
|
|
X = frame_points[:,0] - 0.25
|
|
Z = -frame_points[:,1] + 0.5
|
|
Y = frame_points[:,2]
|
|
|
|
points_plot._offsets3d = (X, Y, Z)
|
|
|
|
for idx, (i, j) in enumerate(skeleton):
|
|
lines_plot[idx].set_data([X[i], X[j]], [Y[i], Y[j]])
|
|
lines_plot[idx].set_3d_properties([Z[i], Z[j]])
|
|
|
|
fig.canvas.draw()
|
|
fig.canvas.flush_events()
|
|
plt.pause(0.001)
|