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| import pickle | |
| thing = pickle.load(open("SMPL_MALE.pkl","rb"), encoding="latin1") | |
| thing.keys() | |
| thing["kintree_table"][0].shape | |
| thing["kintree_table"][0] | |
| thing["J_regressor"].shape | |
| thing["J"].shape | |
| thing["v_template"].shape | |
| from aist_plusplus.loader import AISTDataset | |
| from smplx import SMPL | |
| import torch | |
| #%% | |
| # smpl_poses, smpl_scaling, smpl_trans = AISTDataset.load_motion( | |
| # "../multimodal-transformer/data/motions", "gWA_sFM_cAll_d26_mWA1_ch09") | |
| smpl_thing = pickle.load(open("last.generated.test.pkl", "rb")) | |
| smpl_poses,smpl_scaling,smpl_trans = smpl_thing['smpl_poses'], smpl_thing['smpl_scaling'], smpl_thing['smpl_trans'] | |
| #MY PICKLE IS PROBABLY WRONG | |
| smpl = SMPL(model_path="./", gender='MALE', batch_size=1) | |
| 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() | |
| output.vertices.shape | |
| smpl_poses.shape | |
| keypoints3d.shape | |
| keypoints3d = keypoints3d[:,:24] # the body joints (ignoring the 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 | |
| #%% | |
| import matplotlib.pyplot as plt | |
| from mpl_toolkits.mplot3d import Axes3D | |
| %matplotlib | |
| import time | |
| from celluloid import Camera | |
| fig = plt.figure() | |
| ax = Axes3D(fig) | |
| # camera = Camera(fig) | |
| import numpy as np | |
| np.max(keypoints3d) | |
| ax.scatter(keypoints3d[0,:,2], keypoints3d[0,:,0], keypoints3d[0,:,1]) | |
| plt.show() | |
| plt.xlim([-200,200]) | |
| plt.ylim([-200,200]) | |
| ax.set_zlim([75,475]) | |
| ax.view_init(0, 0) | |
| plt.draw() | |
| #%% | |
| # plt.zlim([-50,50]) | |
| for i in range(len(keypoints3d)): | |
| # for i in range(512): | |
| 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.savefig("img/img_"+str(i)+".png") | |
| # camera.snap() | |
| # i=300 | |
| # plt.gca().clear() | |
| # plt.scatter(keypoints3d[i,:,0], keypoints3d[i,:,1], keypoints3d[i,:,2]) | |
| # plt.show() | |
| # | |
| # a = camera.animate() | |
| # a.save("out.mp4") | |
| # thing['kintree_table'][0] | |
| 1 | |