| | import torch |
| | import matplotlib.pyplot as plt |
| | import numpy as np |
| | import io |
| | import matplotlib |
| | from mpl_toolkits.mplot3d.art3d import Poly3DCollection |
| | import mpl_toolkits.mplot3d.axes3d as p3 |
| | from textwrap import wrap |
| | import imageio |
| |
|
| |
|
| | def plot_3d_motion(args, figsize=(10, 10), fps=120, radius=4): |
| | matplotlib.use('Agg') |
| |
|
| | joints, out_name, title = args |
| | |
| | title_sp = title.split(' ') |
| | if len(title_sp) > 20: |
| | title = '\n'.join([' '.join(title_sp[:10]), ' '.join(title_sp[10:20]), ' '.join(title_sp[20:])]) |
| | elif len(title_sp) > 10: |
| | title = '\n'.join([' '.join(title_sp[:10]), ' '.join(title_sp[10:])]) |
| |
|
| | data = joints.copy().reshape(len(joints), -1, 3) |
| |
|
| | nb_joints = joints.shape[1] |
| | smpl_kinetic_chain = [ |
| | [0, 11, 12, 13, 14, 15], [0, 16, 17, 18, 19, 20], [0, 1, 2, 3, 4], |
| | [3, 5, 6, 7], [3, 8, 9, 10] |
| | ] if nb_joints == 21 else [[0, 2, 5, 8, 11], [0, 1, 4, 7, 10], |
| | [0, 3, 6, 9, 12, 15], [9, 14, 17, 19, 21], |
| | [9, 13, 16, 18, 20]] |
| | limits = 1000 if nb_joints == 21 else 2 |
| |
|
| | MINS = data.min(axis=0).min(axis=0) |
| | MAXS = data.max(axis=0).max(axis=0) |
| |
|
| | colors = [ |
| | 'red', 'blue', 'black', 'red', 'blue', 'darkblue', 'darkblue', |
| | 'darkblue', 'darkblue', 'darkblue', 'darkred', 'darkred', 'darkred', |
| | 'darkred', 'darkred' |
| | ] |
| | frame_number = data.shape[0] |
| | |
| |
|
| | height_offset = MINS[1] |
| | data[:, :, 1] -= height_offset |
| | trajec = data[:, 0, [0, 2]] |
| |
|
| | data[..., 0] -= data[:, 0:1, 0] |
| | data[..., 2] -= data[:, 0:1, 2] |
| |
|
| | def update(index): |
| | def init(): |
| | ax.set_xlim3d([-radius / 2, radius / 2]) |
| | ax.set_ylim3d([0, radius]) |
| | ax.set_zlim3d([0, radius]) |
| | ax.grid(b=False) |
| |
|
| | def plot_xzPlane(minx, maxx, miny, minz, maxz): |
| | |
| | verts = [[minx, miny, minz], [minx, miny, maxz], |
| | [maxx, miny, maxz], [maxx, miny, minz]] |
| | xz_plane = Poly3DCollection([verts]) |
| | xz_plane.set_facecolor((0.5, 0.5, 0.5, 0.5)) |
| | ax.add_collection3d(xz_plane) |
| |
|
| | fig = plt.figure(figsize=(480 / 96., 320 / 96.), |
| | dpi=96) if nb_joints == 21 else plt.figure( |
| | figsize=(10, 10), dpi=96) |
| | |
| | if title is not None: |
| | wraped_title = '\n'.join(wrap(title, 40)) |
| | fig.suptitle(wraped_title, fontsize=16) |
| | ax = p3.Axes3D(fig, auto_add_to_figure=False) |
| | fig.add_axes(ax) |
| |
|
| | init() |
| |
|
| | |
| | |
| | ax.view_init(elev=110, azim=-90) |
| | ax.dist = 7.5 |
| | |
| | plot_xzPlane(MINS[0] - trajec[index, 0], MAXS[0] - trajec[index, 0], 0, |
| | MINS[2] - trajec[index, 1], MAXS[2] - trajec[index, 1]) |
| | |
| |
|
| | if index > 1: |
| | ax.plot3D(trajec[:index, 0] - trajec[index, 0], |
| | np.zeros_like(trajec[:index, 0]), |
| | trajec[:index, 1] - trajec[index, 1], |
| | linewidth=1.0, |
| | color='blue') |
| | |
| |
|
| | for i, (chain, color) in enumerate(zip(smpl_kinetic_chain, colors)): |
| | |
| | if i < 5: |
| | linewidth = 4.0 |
| | else: |
| | linewidth = 2.0 |
| | ax.plot3D(data[index, chain, 0], |
| | data[index, chain, 1], |
| | data[index, chain, 2], |
| | linewidth=linewidth, |
| | color=color) |
| | |
| |
|
| | plt.axis('off') |
| |
|
| | ax.set_xticklabels([]) |
| | ax.set_yticklabels([]) |
| | ax.set_zticklabels([]) |
| |
|
| | if out_name is not None: |
| | plt.savefig(out_name, dpi=96) |
| | plt.close() |
| |
|
| | else: |
| | io_buf = io.BytesIO() |
| | fig.savefig(io_buf, format='raw', dpi=96) |
| | io_buf.seek(0) |
| | |
| | arr = np.reshape(np.frombuffer(io_buf.getvalue(), dtype=np.uint8), |
| | newshape=(int(fig.bbox.bounds[3]), |
| | int(fig.bbox.bounds[2]), -1)) |
| | io_buf.close() |
| | plt.close() |
| | return arr |
| |
|
| | out = [] |
| | for i in range(frame_number): |
| | out.append(update(i)) |
| | out = np.stack(out, axis=0) |
| | return torch.from_numpy(out) |
| |
|
| |
|
| | def draw_to_batch(smpl_joints_batch, title_batch=None, outname=None): |
| |
|
| | batch_size = len(smpl_joints_batch) |
| | out = [] |
| | for i in range(batch_size): |
| | out.append( |
| | plot_3d_motion([ |
| | smpl_joints_batch[i], None, |
| | title_batch[i] if title_batch is not None else None |
| | ])) |
| | if outname is not None: |
| | imageio.mimsave(outname[i], np.array(out[-1]), duration=50) |
| | out = torch.stack(out, axis=0) |
| | return out |
| |
|