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visualize.py
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visualize.py
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import numpy as np
from typing import List
import plotly
import plotly.graph_objects as go
import plotly.express as px
import trimesh
import argparse
import smplx
import json
import torch
#import ipywidgets as widgets
from plotly.subplots import make_subplots
from measurement_definitions import MeasurementType
from utils import convex_hull_from_3D_points, filter_body_part_slices
from joint_definitions import SMPL_IND2JOINT, SMPLX_IND2JOINT
from landmark_definitions import SMPL_LANDMARK_INDICES, SMPLX_LANDMARK_INDICES
class Visualizer():
'''
Visualize the body model with measurements, landmarks and joints.
All the measurements are expressed in cm.
'''
def __init__(self,
verts: np.ndarray,
faces: np.ndarray,
joints: np.ndarray,
landmarks: dict,
measurements: dict,
measurement_types: dict,
length_definitions: dict,
circumf_definitions: dict,
joint2ind: dict,
circumf_2_bodypart: dict,
face_segmentation: dict,
visualize_body: bool = True,
visualize_landmarks: bool = True,
visualize_joints: bool = True,
visualize_measurements: bool=True,
title: str = "Measurement visualization"
):
self.verts = verts
self.faces = faces
self.joints = joints
self.landmarks = landmarks
self.measurements = measurements
self.measurement_types = measurement_types
self.length_definitions = length_definitions
self.circumf_definitions = circumf_definitions
self.joint2ind = joint2ind
self.circumf_2_bodypart = circumf_2_bodypart
self.face_segmentation = face_segmentation
self.visualize_body = visualize_body
self.visualize_landmarks = visualize_landmarks
self.visualize_joints = visualize_joints
self.visualize_measurements = visualize_measurements
self.title = title
@staticmethod
def create_mesh_plot(verts: np.ndarray, faces: np.ndarray):
'''
Visualize smpl body mesh.
:param verts: np.array (N,3) of vertices
:param faces: np.array (F,3) of faces connecting the vertices
Return:
plotly Mesh3d object for plotting
'''
mesh_plot = go.Mesh3d(
x=verts[:,0],
y=verts[:,1],
z=verts[:,2],
color="gray",
hovertemplate ='<i>Index</i>: %{text}',
text = [i for i in range(verts.shape[0])],
# i, j and k give the vertices of triangles
i=faces[:,0],
j=faces[:,1],
k=faces[:,2],
opacity=0.6,
name='body',
)
return mesh_plot
@staticmethod
def create_joint_plot(joints: np.ndarray):
return go.Scatter3d(x = joints[:,0],
y = joints[:,1],
z = joints[:,2],
mode='markers',
marker=dict(size=8,
color="black",
opacity=1,
symbol="cross"
),
name="joints"
)
@staticmethod
def create_wireframe_plot(verts: np.ndarray,faces: np.ndarray):
'''
Given vertices and faces, creates a wireframe of plotly segments.
Used for visualizing the wireframe.
:param verts: np.array (N,3) of vertices
:param faces: np.array (F,3) of faces connecting the verts
'''
i=faces[:,0]
j=faces[:,1]
k=faces[:,2]
triangles = np.vstack((i,j,k)).T
x=verts[:,0]
y=verts[:,1]
z=verts[:,2]
vertices = np.vstack((x,y,z)).T
tri_points = vertices[triangles]
#extract the lists of x, y, z coordinates of the triangle
# vertices and connect them by a "line" by adding None
# this is a plotly convention for plotting segments
Xe = []
Ye = []
Ze = []
for T in tri_points:
Xe.extend([T[k%3][0] for k in range(4)]+[ None])
Ye.extend([T[k%3][1] for k in range(4)]+[ None])
Ze.extend([T[k%3][2] for k in range(4)]+[ None])
# return Xe, Ye, Ze
wireframe = go.Scatter3d(
x=Xe,
y=Ye,
z=Ze,
mode='lines',
name='wireframe',
line=dict(color= 'rgb(70,70,70)', width=1)
)
return wireframe
def create_landmarks_plot(self,
landmark_names: List[str],
verts: np.ndarray
) -> List[plotly.graph_objs.Scatter3d]:
'''
Visualize landmarks from landmark_names list
:param landmark_names: List[str] of landmark names to visualize
Return
:param plots: list of plotly objects to plot
'''
plots = []
landmark_colors = dict(zip(self.landmarks.keys(),
px.colors.qualitative.Alphabet))
for lm_name in landmark_names:
if lm_name not in self.landmarks.keys():
print(f"Landmark {lm_name} is not defined.")
pass
lm_index = self.landmarks[lm_name]
if isinstance(lm_index,tuple):
lm = (verts[lm_index[0]] + verts[lm_index[1]]) / 2
else:
lm = verts[lm_index]
plot = go.Scatter3d(x = [lm[0]],
y = [lm[1]],
z = [lm[2]],
mode='markers',
marker=dict(size=8,
color=landmark_colors[lm_name],
opacity=1,
),
name=lm_name
)
plots.append(plot)
return plots
def create_measurement_length_plot(self,
measurement_name: str,
verts: np.ndarray,
color: str
):
'''
Create length measurement plot.
:param measurement_name: str, measurement name to plot
:param verts: np.array (N,3) of vertices
:param color: str of color to color the measurement
Return
plotly object to plot
'''
measurement_landmarks_inds = self.length_definitions[measurement_name]
segments = {"x":[],"y":[],"z":[]}
for i in range(2):
if isinstance(measurement_landmarks_inds[i],tuple):
lm_tnp = (verts[measurement_landmarks_inds[i][0]] +
verts[measurement_landmarks_inds[i][1]]) / 2
else:
lm_tnp = verts[measurement_landmarks_inds[i]]
segments["x"].append(lm_tnp[0])
segments["y"].append(lm_tnp[1])
segments["z"].append(lm_tnp[2])
for ax in ["x","y","z"]:
segments[ax].append(None)
if measurement_name in self.measurements:
m_viz_name = f"{measurement_name}: {self.measurements[measurement_name]:.2f}cm"
else:
m_viz_name = measurement_name
return go.Scatter3d(x=segments["x"],
y=segments["y"],
z=segments["z"],
marker=dict(
size=4,
color="rgba(0,0,0,0)",
),
line=dict(
color=color,
width=10),
name=m_viz_name
)
def create_measurement_circumference_plot(self,
measurement_name: str,
verts: np.ndarray,
faces: np.ndarray,
color: str):
'''
Create circumference measurement plot
:param measurement_name: str, measurement name to plot
:param verts: np.array (N,3) of vertices
:param faces: np.array (F,3) of faces connecting the vertices
:param color: str of color to color the measurement
Return
plotly object to plot
'''
circumf_landmarks = self.circumf_definitions[measurement_name]["LANDMARKS"]
circumf_landmark_indices = [self.landmarks[l_name] for l_name in circumf_landmarks]
circumf_n1, circumf_n2 = self.circumf_definitions[measurement_name]["JOINTS"]
circumf_n1, circumf_n2 = self.joint2ind[circumf_n1], self.joint2ind[circumf_n2]
plane_origin = np.mean(verts[circumf_landmark_indices,:],axis=0)
plane_normal = self.joints[circumf_n1,:] - self.joints[circumf_n2,:]
mesh = trimesh.Trimesh(vertices=verts, faces=faces)
slice_segments, sliced_faces = trimesh.intersections.mesh_plane(mesh,
plane_normal=plane_normal,
plane_origin=plane_origin,
return_faces=True) # (N, 2, 3), (N,)
slice_segments = filter_body_part_slices(slice_segments,
sliced_faces,
measurement_name,
self.circumf_2_bodypart,
self.face_segmentation)
slice_segments_hull = convex_hull_from_3D_points(slice_segments)
draw_segments = {"x":[],"y":[],"z":[]}
map_ax = {0:"x",1:"y",2:"z"}
for i in range(slice_segments_hull.shape[0]):
for j in range(3):
draw_segments[map_ax[j]].append(slice_segments_hull[i,0,j])
draw_segments[map_ax[j]].append(slice_segments_hull[i,1,j])
draw_segments[map_ax[j]].append(None)
if measurement_name in self.measurements:
m_viz_name = f"{measurement_name}: {self.measurements[measurement_name]:.2f}cm"
else:
m_viz_name = measurement_name
return go.Scatter3d(
x=draw_segments["x"],
y=draw_segments["y"],
z=draw_segments["z"],
mode="lines",
line=dict(
color=color,
width=10),
name=m_viz_name
)
def visualize(self,
measurement_names: List[str] = [],
landmark_names: List[str] = [],
title="Measurement visualization"
):
'''
Visualize the body model with measurements, landmarks and joints.
:param measurement_names: List[str], list of strings with measurement names
:param landmark_names: List[str], list of strings with landmark names
:param title: str, title of plot
'''
fig = go.Figure()
if self.visualize_body:
# visualize model mesh
mesh_plot = self.create_mesh_plot(self.verts, self.faces)
fig.add_trace(mesh_plot)
# visualize wireframe
wireframe_plot = self.create_wireframe_plot(self.verts, self.faces)
fig.add_trace(wireframe_plot)
# visualize joints
if self.visualize_joints:
joint_plot = self.create_joint_plot(self.joints)
fig.add_trace(joint_plot)
# visualize landmarks
if self.visualize_landmarks:
landmarks_plot = self.create_landmarks_plot(landmark_names, self.verts)
fig.add_traces(landmarks_plot)
# visualize measurements
measurement_colors = dict(zip(self.measurement_types.keys(),
px.colors.qualitative.Alphabet))
if self.visualize_measurements:
for m_name in measurement_names:
if m_name not in self.measurement_types.keys():
print(f"Measurement {m_name} not defined.")
pass
if self.measurement_types[m_name] == MeasurementType().LENGTH:
measurement_plot = self.create_measurement_length_plot(measurement_name=m_name,
verts=self.verts,
color=measurement_colors[m_name])
elif self.measurement_types[m_name] == MeasurementType().CIRCUMFERENCE:
measurement_plot = self.create_measurement_circumference_plot(measurement_name=m_name,
verts=self.verts,
faces=self.faces,
color=measurement_colors[m_name])
fig.add_trace(measurement_plot)
fig.update_layout(scene_aspectmode='data',
width=1000, height=700,
title=title,
)
fig.show()
def viz_smplx_joints(visualize_body=True,fig=None,show=True,title="SMPLX joints"):
"""
Visualize smpl joints on the same plot.
:param visualize_body: bool, whether to visualize the body or not.
:param fig: plotly Figure object, if None, create new figure.
"""
betas = torch.zeros((1, 10), dtype=torch.float32)
smplx_model = smplx.create(model_path="data",
model_type="smplx",
gender="NEUTRAL",
use_face_contour=False,
num_betas=10,
#body_pose=torch.zeros((1, (55-1) * 3)),
ext='pkl')
smplx_model = smplx_model(betas=betas, return_verts=True)
smplx_joints = smplx_model.joints.detach().numpy()[0]
smplx_joint_pelvis = smplx_joints[0,:]
smplx_joints = smplx_joints - smplx_joint_pelvis
smplx_vertices = smplx_model.vertices.detach().numpy()[0]
smplx_vertices = smplx_vertices - smplx_joint_pelvis
smplx_faces = smplx.SMPLX("data/smplx",ext="pkl").faces
joint_colors = px.colors.qualitative.Alphabet + \
px.colors.qualitative.Dark24 + \
px.colors.qualitative.Alphabet + \
px.colors.qualitative.Dark24 + \
px.colors.qualitative.Alphabet + \
["#000000"]
if isinstance(fig,type(None)):
fig = go.Figure()
for i in range(smplx_joints.shape[0]):
if i in SMPLX_IND2JOINT.keys():
joint_name = SMPLX_IND2JOINT[i]
else:
joint_name = f"noname-{i}"
joint_plot = go.Scatter3d(x = [smplx_joints[i,0]],
y = [smplx_joints[i,1]],
z = [smplx_joints[i,2]],
mode='markers',
marker=dict(size=10,
color=joint_colors[i],
opacity=1,
symbol="circle"
),
name="smplx-"+joint_name
)
fig.add_trace(joint_plot)
if visualize_body:
plot_body = go.Mesh3d(
x=smplx_vertices[:,0],
y=smplx_vertices[:,1],
z=smplx_vertices[:,2],
color = "red",
i=smplx_faces[:,0],
j=smplx_faces[:,1],
k=smplx_faces[:,2],
name='smplx mesh',
showscale=True,
opacity=0.5
)
fig.add_trace(plot_body)
fig.update_layout(scene_aspectmode='data',
width=1000, height=700,
title=title,
)
if show:
fig.show()
else:
return fig
def viz_smpl_joints(visualize_body=True,fig=None,show=True,title="SMPL joints"):
"""
Visualize smpl joints on the same plot.
:param visualize_body: bool, whether to visualize the body or not.
:param fig: plotly Figure object, if None, create new figure.
"""
betas = torch.zeros((1, 10), dtype=torch.float32)
smpl_model = smplx.create(model_path="data",
model_type="smpl",
gender="NEUTRAL",
use_face_contour=False,
num_betas=10,
ext='pkl')
smpl_model = smpl_model(betas=betas, return_verts=True)
smpl_joints = smpl_model.joints.detach().numpy()[0]
smpl_joints_pelvis = smpl_joints[0,:]
smpl_joints = smpl_joints - smpl_joints_pelvis
smpl_vertices = smpl_model.vertices.detach().numpy()[0]
smpl_vertices = smpl_vertices - smpl_joints_pelvis
smpl_faces = smplx.SMPL("data/smpl",ext="pkl").faces
joint_colors = px.colors.qualitative.Alphabet + \
px.colors.qualitative.Dark24 + \
px.colors.qualitative.Alphabet + \
px.colors.qualitative.Dark24 + \
px.colors.qualitative.Alphabet + \
["#000000"]
if isinstance(fig,type(None)):
fig = go.Figure()
for i in range(smpl_joints.shape[0]):
if i in SMPL_IND2JOINT.keys():
joint_name = SMPL_IND2JOINT[i]
else:
joint_name = f"noname-{i}"
joint_plot = go.Scatter3d(x = [smpl_joints[i,0]],
y = [smpl_joints[i,1]],
z = [smpl_joints[i,2]],
mode='markers',
marker=dict(size=10,
color=joint_colors[i],
opacity=1,
symbol="cross"
),
name="smpl-"+joint_name
)
fig.add_trace(joint_plot)
if visualize_body:
plot_body = go.Mesh3d(
x=smpl_vertices[:,0],
y=smpl_vertices[:,1],
z=smpl_vertices[:,2],
#facecolor=face_colors,
color = "blue",
i=smpl_faces[:,0],
j=smpl_faces[:,1],
k=smpl_faces[:,2],
name='smpl mesh',
showscale=True,
opacity=0.5
)
fig.add_trace(plot_body)
fig.update_layout(scene_aspectmode='data',
width=1000, height=700,
title=title,
)
if show:
fig.show()
else:
return fig
def viz_face_segmentation(verts,faces,face_colors,
title="Segmented body",name="mesh",show=True):
"""
Visualize face segmentation defined in face_colors.
:param verts: np.ndarray - (N,3) representing the vertices
:param faces: np.ndarray - (F,3) representing the indices of the faces
:param face_colors: np.ndarray - (F,3) representing the colors of the faces
"""
import plotly.graph_objects as go
fig = go.Figure()
mesh_plot = go.Mesh3d(
x=verts[:,0],
y=verts[:,1],
z=verts[:,2],
facecolor=face_colors,
i=faces[:,0],
j=faces[:,1],
k=faces[:,2],
name=name,
showscale=True,
opacity=1
)
fig.add_trace(mesh_plot)
fig.update_layout(scene_aspectmode='data',
width=1000, height=700,
title=title)
if show:
fig.show()
else:
return fig
def viz_smpl_face_segmentation(fig=None, show=True, title="SMPL face segmentation"):
body = smplx.SMPL("data/smpl",ext="pkl")
with open("data/smpl/smpl_body_parts_2_faces.json","r") as f:
face_segmentation = json.load(f)
faces = body.faces
verts = body.v_template
# create colors for each face
colors = px.colors.qualitative.Alphabet + \
px.colors.qualitative.Dark24
mapping_bp2ind = dict(zip(face_segmentation.keys(),
range(len(face_segmentation.keys()))
))
face_colors = [0]*faces.shape[0]
for bp_name,bp_indices in face_segmentation.items():
bp_label = mapping_bp2ind[bp_name]
for i in bp_indices:
face_colors[i] = colors[bp_label]
if isinstance(fig,type(None)):
fig = go.Figure()
fig = viz_face_segmentation(verts,faces,face_colors,title=title,name="smpl",show=False)
if show:
fig.show()
else:
return fig
def viz_smplx_face_segmentation(fig=None,show=True,title="SMPLX face segmentation"):
"""
Visualize face segmentations for smplx.
"""
body = smplx.SMPLX("data/smplx",ext="pkl")
with open("data/smplx/smplx_body_parts_2_faces.json","r") as f:
face_segmentation = json.load(f)
faces = body.faces
verts = body.v_template
# create colors for each face
colors = px.colors.qualitative.Alphabet + \
px.colors.qualitative.Dark24
mapping_bp2ind = dict(zip(face_segmentation.keys(),
range(len(face_segmentation.keys()))
))
face_colors = [0]*faces.shape[0]
for bp_name,bp_indices in face_segmentation.items():
bp_label = mapping_bp2ind[bp_name]
for i in bp_indices:
face_colors[i] = colors[bp_label]
if isinstance(fig,type(None)):
fig = go.Figure()
fig = viz_face_segmentation(verts,faces,face_colors,title=title,name="smpl",show=False)
if show:
fig.show()
else:
return fig
def viz_point_segmentation(verts,point_segm,title="Segmented body",fig=None,show=True):
"""
Visualze points and their segmentation defined in dict point_segm.
:param verts: np.ndarray - (N,3) representing the vertices
:param point_segm: dict - dict mapping body part to all points belonging
to it
"""
colors = px.colors.qualitative.Alphabet + \
px.colors.qualitative.Dark24
if isinstance(fig,type(None)):
fig = go.Figure()
for i, (body_part, body_indices) in enumerate(point_segm.items()):
plot = go.Scatter3d(x = verts[body_indices,0],
y = verts[body_indices,1],
z = verts[body_indices,2],
mode='markers',
marker=dict(size=5,
color=colors[i],
opacity=1,
#symbol="cross"
),
name=body_part
)
fig.add_trace(plot)
fig.update_layout(scene_aspectmode='data',
width=1000, height=700,
title=title)
if show:
fig.show()
return fig
def viz_smplx_point_segmentation(fig=None,show=True,title="SMPLX point segmentation"):
"""
Visualize point segmentations for smplx.
"""
model_path = "data/smplx"
smpl_verts = smplx.SMPLX(model_path,ext="pkl").v_template
with open("data/smplx/point_segmentation_meshcapade.json","r") as f:
point_segm = json.load(f)
fig = viz_point_segmentation(smpl_verts,point_segm,title=title,fig=fig,show=show)
if show:
fig.show()
else:
return fig
def viz_smpl_point_segmentation(fig=None,show=True,title="SMPL point segmentation"):
"""
Visualize point segmentations for smpl.
"""
model_path = "data/smpl"
smpl_verts = smplx.SMPL(model_path,ext="pkl").v_template
with open("data/smpl/point_segmentation_meshcapade.json","r") as f:
point_segm = json.load(f)
fig = viz_point_segmentation(smpl_verts,point_segm,title=title,fig=fig,show=show)
if show:
fig.show()
else:
return fig
def viz_landmarks(verts,landmark_dict,title="Visualize landmarks",fig=None,show=True,name="points"):
if isinstance(fig,type(None)):
fig = go.Figure()
plot = go.Scatter3d(x = verts[:,0],
y = verts[:,1],
z = verts[:,2],
mode='markers',
hovertemplate ='<i>Index</i>: %{text}',
text = [i for i in range(verts.shape[0])],
marker=dict(size=5,
color="black",
opacity=0.2,
# line=dict(color='black',width=1)
),
name=name
)
fig.add_trace(plot)
colors = px.colors.qualitative.Alphabet + \
px.colors.qualitative.Dark24 + \
px.colors.qualitative.Alphabet + \
px.colors.qualitative.Dark24
for i, (lm_name, lm_ind) in enumerate(landmark_dict.items()):
plot = go.Scatter3d(x = [verts[lm_ind,0]],
y = [verts[lm_ind,1]],
z = [verts[lm_ind,2]],
mode='markers',
marker=dict(size=10,
color=colors[i],
opacity=1,
symbol="cross"
),
name=name+"-"+lm_name
)
fig.add_trace(plot)
fig.update_layout(scene_aspectmode='data',
width=1000, height=700,
title=title)
if show:
fig.show()
else:
return fig
def viz_smpl_landmarks(fig=None,show=True,title="SMPL landmarks"):
"""
Visualize smpl landmarks.
"""
verts = smplx.SMPL("data/smpl",ext="pkl").v_template
landmark_dict = SMPL_LANDMARK_INDICES
if isinstance(fig,type(None)):
fig=go.Figure()
fig = viz_landmarks(verts,
landmark_dict,
title="Visualize landmarks",
fig=fig,
show=show,
name="smpl")
if show:
fig.show()
else:
return fig
def viz_smplx_landmarks(fig=None,show=True,title="SMPLX landmarks"):
"""
Visualize smplx landmarks.
"""
verts = smplx.SMPLX("data/smplx",ext="pkl").v_template
landmark_dict = SMPLX_LANDMARK_INDICES
if isinstance(fig,type(None)):
fig=go.Figure()
fig = viz_landmarks(verts,
landmark_dict,
title="Visualize landmarks",
fig=fig,
show=show,
name="smplx")
if show:
fig.show()
else:
return fig
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Visualize body models, joints and segmentations..')
parser.add_argument('--visualize_smpl_and_smplx_face_segmentation', action='store_true',
help="Visualize face segmentations for smplx model.")
parser.add_argument('--visualize_smpl_and_smplx_joints', action='store_true',
help="visualize smpl and smplx joints on same plot.")
parser.add_argument('--visualize_smpl_and_smplx_point_segmentation', action='store_true',
help="visualize smpl and smplx point segmentation on two separate plots.")
parser.add_argument('--visualize_smpl_and_smplx_landmarks', action='store_true',
help="visualize smpl and smplx landmarks on two separate plots.")
args = parser.parse_args()
if args.visualize_smpl_and_smplx_face_segmentation:
# mesh is not compatible with subplots so these are plotted
# onto separate plots
viz_smpl_face_segmentation(fig=None, show=True)
viz_smplx_face_segmentation(fig=None,show=True)
if args.visualize_smpl_and_smplx_joints:
title = "SMPL and SMPLX joints"
fig = viz_smpl_joints(visualize_body=True,
fig=None,
show=False,
title=title)
viz_smplx_joints(visualize_body=True,
fig=fig,
show=True,
title=title)
if args.visualize_smpl_and_smplx_point_segmentation:
fig = make_subplots(rows=1, cols=2,
specs=[[{'type': 'scene'},
{'type': 'scene'}]],
subplot_titles=("SMPL", "SMPLX"))
title="SMPL and SMPLX point segmentation"
fig_smpl = viz_smpl_point_segmentation(fig=None,show=False,title=title)
fig_smplx = viz_smplx_point_segmentation(fig=None,show=False,title=title)
for i in range(len(fig_smpl.data)):
fig.add_trace(fig_smpl.data[i],row=1,col=1)
for i in range(len(fig_smplx.data)):
fig.add_trace(fig_smplx.data[i],row=1,col=2)
fig.update_layout(fig_smpl.layout)
fig.update_layout(scene2_aspectmode="data",
showlegend=False,
width=1200,
height=700)
fig.show()
if args.visualize_smpl_and_smplx_landmarks:
fig = make_subplots(rows=1, cols=2,
specs=[[{'type': 'scene'},
{'type': 'scene'}]],
subplot_titles=("SMPL", "SMPLX"))
title="SMPL and SMPLX landmarks"
fig_smpl = viz_smpl_landmarks(fig=None,show=False,title=title)
fig_smplx = viz_smplx_landmarks(fig=None,show=False,title=title)
for i in range(len(fig_smpl.data)):
fig.add_trace(fig_smpl.data[i],row=1,col=1)
for i in range(len(fig_smplx.data)):
fig.add_trace(fig_smplx.data[i],row=1,col=2)
fig.update_layout(fig_smpl.layout)
fig.update_layout(scene2_aspectmode="data",
showlegend=False,
width=1200,
height=700)
fig.show()