def plot_predictions(expmap_gt, expmap_pred, fig, ax, f_title):
# Load all the data
parent, offset, rotInd, expmapInd = fk._some_variables()
nframes_pred = expmap_pred.shape[0]
# Compute 3d points for each frame
xyz_gt = np.zeros((nframes_pred, 96))
for i in range(nframes_pred):
xyz_gt[i, :] = fk.fkl(expmap_gt[i, :], parent, offset, rotInd,
expmapInd).reshape([96])
xyz_pred = np.zeros((nframes_pred, 96))
for i in range(nframes_pred):
xyz_pred[i, :] = fk.fkl(expmap_pred[i, :], parent, offset, rotInd,
expmapInd).reshape([96])
# === Plot and animate ===
ob = Ax3DPose(ax)
# Plot the prediction
for i in range(nframes_pred):
ob.update(xyz_gt[i, :], xyz_pred[i, :])
ax.set_title(f_title + ' frame:{:d}'.format(i + 1), loc="left")
plt.show(block=False)
fig.canvas.draw()
plt.pause(0.05)
def plot_predictions(expmap_gt, expmap_pred, fig, ax, f_title):
# Load all the data
parent, offset, rotInd, expmapInd = fk._some_variables()
nframes_pred = expmap_pred.shape[0]
# Compute 3d points for each frame
xyz_gt = np.zeros((nframes_pred, 96))
for i in range(nframes_pred):
xyz_gt[i, :] = fk.fkl(expmap_gt[i, :], parent, offset, rotInd, expmapInd).reshape([96])
xyz_pred = np.zeros((nframes_pred, 96))
for i in range(nframes_pred):
xyz_pred[i, :] = fk.fkl(expmap_pred[i, :], parent, offset, rotInd, expmapInd).reshape([96])
#print(xyz_gt.shape)
#print(xyz_gt)
#print("separation")
#print(xyz_pred.shape)
#print(xyz_pred)
# === Plot and animate ===
ob = Ax3DPose(ax)
# Plot the prediction
for i in range(nframes_pred):
ob.update(xyz_gt[i, :], xyz_pred[i, :])
#ax.set_title(f_title + ' frame:{:d}'.format(i + 1), loc="left")
plt.savefig('demo/' + f_title + ' frame:{:d}.png'.format(i + 1))
def expmap2xyz_torch(expmap):
"""
convert expmaps to joint locations
:param expmap: N*99
:return: N*32*3
"""
parent, offset, rotInd, expmapInd = forward_kinematics._some_variables()
xyz = forward_kinematics.fkl_torch(expmap, parent, offset, rotInd, expmapInd)
return xyz