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# Inspired by
# - https://github.com/anindita127/Complextext2animation/blob/main/src/utils/visualization.py
# - https://github.com/facebookresearch/QuaterNet/blob/main/common/visualization.py
from typing import List, Tuple
import numpy as np
from mGPT.utils.joints import mmm_kinematic_tree, mmm_to_smplh_scaling_factor
mmm_colors = ['black', 'magenta', 'red', 'green', 'blue']
def init_axis(fig, title, radius=1.5, dist=10):
ax = fig.add_subplot(1, 1, 1, projection='3d')
ax.view_init(elev=20., azim=-60)
fact = 2
ax.set_xlim3d([-radius / fact, radius / fact])
ax.set_ylim3d([-radius / fact, radius / fact])
ax.set_zlim3d([0, radius])
ax.set_aspect('auto')
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_zticklabels([])
ax.set_axis_off()
ax.dist = dist
ax.grid(b=False)
ax.set_title(title, loc='center', wrap=True)
return ax
def plot_floor(ax, minx, maxx, miny, maxy, minz):
from mpl_toolkits.mplot3d.art3d import Poly3DCollection
# Plot a plane XZ
verts = [
[minx, miny, minz],
[minx, maxy, minz],
[maxx, maxy, minz],
[maxx, miny, minz]
]
xz_plane = Poly3DCollection([verts], zorder=1)
xz_plane.set_facecolor((0.5, 0.5, 0.5, 1))
ax.add_collection3d(xz_plane)
# Plot a bigger square plane XZ
radius = max((maxx - minx), (maxy - miny))
# center +- radius
minx_all = (maxx + minx) / 2 - radius
maxx_all = (maxx + minx) / 2 + radius
miny_all = (maxy + miny) / 2 - radius
maxy_all = (maxy + miny) / 2 + radius
verts = [
[minx_all, miny_all, minz],
[minx_all, maxy_all, minz],
[maxx_all, maxy_all, minz],
[maxx_all, miny_all, minz]
]
xz_plane = Poly3DCollection([verts], zorder=1)
xz_plane.set_facecolor((0.5, 0.5, 0.5, 0.5))
ax.add_collection3d(xz_plane)
return ax
def update_camera(ax, root, radius=1.5):
fact = 2
ax.set_xlim3d([-radius / fact + root[0], radius / fact + root[0]])
ax.set_ylim3d([-radius / fact + root[1], radius / fact + root[1]])
def render_animation(joints: np.ndarray, output: str = "notebook", title: str = "",
fps: float = 12.5,
kinematic_tree: List[List[int]] = mmm_kinematic_tree,
colors: List[str] = mmm_colors,
figsize: Tuple[int] = (4, 4),
fontsize: int = 15):
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
import matplotlib.patheffects as pe
plt.rcParams.update({'font.size': fontsize})
# Z is gravity here
x, y, z = 0, 1, 2
# Convert mmm joints for visualization
# into smpl-h "scale" and axis
joints = joints.copy()[..., [2, 0, 1]] * mmm_to_smplh_scaling_factor
# Create a figure and initialize 3d plot
fig = plt.figure(figsize=figsize)
ax = init_axis(fig, title)
# Create spline line
trajectory = joints[:, 0, [x, y]]
avg_segment_length = np.mean(np.linalg.norm(np.diff(trajectory, axis=0), axis=1)) + 1e-3
draw_offset = int(25 / avg_segment_length)
spline_line, = ax.plot(*trajectory.T, zorder=10, color="white")
# Create a floor
minx, miny, _ = joints.min(axis=(0, 1))
maxx, maxy, _ = joints.max(axis=(0, 1))
plot_floor(ax, minx, maxx, miny, maxy, 0)
# Put the character on the floor
height_offset = np.min(joints[:, :, z]) # Min height
joints = joints.copy()
joints[:, :, z] -= height_offset
# Initialization for redrawing
lines = []
initialized = False
def update(frame):
nonlocal initialized
skeleton = joints[frame]
root = skeleton[0]
update_camera(ax, root)
for index, (chain, color) in enumerate(zip(reversed(kinematic_tree), reversed(colors))):
if not initialized:
lines.append(ax.plot(skeleton[chain, x],
skeleton[chain, y],
skeleton[chain, z], linewidth=8.0, color=color, zorder=20,
path_effects=[pe.SimpleLineShadow(), pe.Normal()]))
else:
lines[index][0].set_xdata(skeleton[chain, x])
lines[index][0].set_ydata(skeleton[chain, y])
lines[index][0].set_3d_properties(skeleton[chain, z])
left = max(frame - draw_offset, 0)
right = min(frame + draw_offset, trajectory.shape[0])
spline_line.set_xdata(trajectory[left:right, 0])
spline_line.set_ydata(trajectory[left:right, 1])
spline_line.set_3d_properties(np.zeros_like(trajectory[left:right, 0]))
initialized = True
fig.tight_layout()
frames = joints.shape[0]
anim = FuncAnimation(fig, update, frames=frames, interval=1000 / fps, repeat=False)
if output == "notebook":
from IPython.display import HTML
HTML(anim.to_jshtml())
else:
anim.save(output, writer='ffmpeg', fps=fps)
plt.close()
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