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from smplx import SMPL
import torch
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import os
import glob
root_dir = os.path.dirname(os.path.realpath(__file__))
from analysis.visualization.convert_mat_to_euler import rot_mats_to_eulers
from .utils import generate_video_from_images, join_video_and_audio
def delete_images():
files = glob.glob(root_dir+'/img/*')
for f in files:
os.remove(f)
def generate_video_from_mats(pred_mats_file, output_folder, audio_file, trim_audio=0, fps=60, plot_mats=False):
filename = os.path.basename(pred_mats_file)
seq_id = filename.split(".")[0]
predicted_mats = np.load(pred_mats_file)
if plot_mats:
plt.matshow(predicted_mats[:1000,0,:-3])
plt.savefig(root_dir+"/last.predicted_mats.png")
smpl_thing = rot_mats_to_eulers(predicted_mats)
smpl_poses,smpl_scaling,smpl_trans = smpl_thing['smpl_poses'], smpl_thing['smpl_scaling'], smpl_thing['smpl_trans']
#this loads the SMPL_MALE pickle
smpl = SMPL(model_path="./aistplusplus_api", gender='MALE', batch_size=1) #what if we try gender='FEMALE'?
output = smpl.forward(
global_orient=torch.from_numpy(smpl_poses[:, 0:1]).float(),
body_pose=torch.from_numpy(smpl_poses[:, 1:]).float(),
transl=torch.from_numpy(smpl_trans).float(),
scaling=torch.from_numpy(smpl_scaling.reshape(1, 1)).float(),
)
keypoints3d = output.joints.detach().numpy()
keypoints3d = keypoints3d[:,:24] # the body joints (ignoring the extra head, feet and hand bones added onto it here https://github.com/vchoutas/smplx/blob/7547ee6656b942a68a97604d0cf7b6b834fad9eb/smplx/vertex_joint_selector.py)
# that file takes the position of the vertices corresponding to certain joints
# print(keypoints3d)
# Plot as images
delete_images()
fig = plt.figure()
plt.ion()
plt.show()
ax = Axes3D(fig)
ax.scatter(keypoints3d[0,:,2], keypoints3d[0,:,0], keypoints3d[0,:,1])
plt.xlim([-100,100])
plt.ylim([-100,100])
ax.set_zlim([75,275])
ax.view_init(0, 0)
plt.draw()
plt.pause(0.001)
for i in range(1,len(keypoints3d)):
print(i)
ax.clear()
ax.scatter(keypoints3d[i,:,2], keypoints3d[i,:,0], keypoints3d[i,:,1])
plt.xlim([-100,100])
plt.ylim([-100,100])
ax.set_zlim([75,275])
ax.view_init(0, 0)
plt.draw()
plt.pause(0.001)
plt.savefig(root_dir+"/img/img_"+str(i)+".png")
#video_file = output_folder+seq_id+".mp4"
video_file = f'{output_folder}/example.mp4'
generate_video_from_images(root_dir+"/img", video_file, fps)
if audio_file is not None:
join_video_and_audio(video_file, audio_file, trim_audio)
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