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luni
2023-03-07 12:54:53 +00:00
parent e192f6f9e3
commit cbecf668df
2 changed files with 110 additions and 16 deletions
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curvature_analysis.py
+99 -15
View File
@@ -22,18 +22,11 @@ from custom_utils.custom_utils import _maskFaces
from postprocessing import fix_collision
from custom_utils.supersmpl_io import readPC2, readPC2Frame, writePC2, readOBJ
from custom_utils.custom_utils import _maskFaces, save_stl
from custom_utils.custom_utils import _maskFaces, save_stl, write_obj
from auto_encoder_curv import dice_dense
def write_obj(file, vertices, faces, colors):
with open(file, 'w') as file:
for v, c in zip(vertices, colors):
line = 'v ' + ' '.join([str(_) for _ in v]) + ' ' + ' '.join([str(_) for _ in c]) + '\n'
file.write(line)
for f in faces:
line = 'f ' + ' '.join([str(_) for _ in f]) + '\n'
file.write(line)
def postprocess(mesh, faces, mask=None, body=None, do_smoothing=True):
@@ -261,15 +254,105 @@ def init_wandb():
artifact.add_file('curvature_analysis.py')
run.log_artifact(artifact)
if __name__ == '__main__':
init_wandb()
is_skirt = False
def visualize_neighbourhoods(folder, frame):
id = frame.split('_')[0]
frame_nr = frame.split('_')[1].split('.')[0]
mask = np.load(os.path.join(folder, 'mesh_mask', f'{id}.npy')).astype(bool)
_, faces = _maskFaces(np.zeros((14475,3)), F, mask)
verts = np.load(os.path.join(folder, 'mesh_posed', f'{id}_{frame_nr}.npz'))['mesh_posed'][mask,:]
curvature_labels_10 = generate_curvatures(verts, faces, mask, 10)
curvature_labels_25 = generate_curvatures(verts, faces, mask, 25)
curvature_labels_100 = generate_curvatures(verts, faces, mask, 100)
colors_binned_all = []
for curvature_labels in [curvature_labels_10, curvature_labels_25, curvature_labels_100]:
colors = np.array([cm.color('jet', 1 - i) for i in np.linspace(0, 1, int(curvature_labels.max()+1))])
colors_binned = np.zeros((curvature_labels.shape[0], 3))
for i in range(int(curvature_labels.max())+1):
# print(np.count_nonzero(curvature_labels == i))
colors_binned[curvature_labels == i, :] = colors[i]
colors_binned_all.append(colors_binned)
fig = make_subplots(rows=1, cols=3, start_cell="top-left", specs = [ [{ 'type': 'scene' } for _ in range(3)] ])
fig.add_trace(go.Mesh3d(
# 8 vertices of a cube
x=-verts[:,0],
y=verts[:,1],
z=verts[:,2],
# i, j and k give the vertices of triangles
i = faces[:,0],
j = faces[:,1],
k = faces[:,2],
vertexcolor=colors_binned_all[0]
),
row=1, col=1)
fig.add_trace(go.Mesh3d(
# 8 vertices of a cube
x=verts[:,0],
y=verts[:,1],
z=verts[:,2],
# i, j and k give the vertices of triangles
i = faces[:,0],
j = faces[:,1],
k = faces[:,2],
vertexcolor=colors_binned_all[1]
),
row=1, col=2)
fig.add_trace(go.Mesh3d(
# 8 vertices of a cube
x=-verts[:,0],
y=verts[:,1],
z=verts[:,2],
# i, j and k give the vertices of triangles
i = faces[:,0],
j = faces[:,1],
k = faces[:,2],
vertexcolor=colors_binned_all[2],
),
row=1, col=3)
fig.update_layout(scene_aspectmode='manual', scene_aspectratio=dict(x=1, y=1, z=1),
scene2_aspectmode='manual', scene2_aspectratio=dict(x=1, y=1, z=1),
scene3_aspectmode='manual', scene3_aspectratio=dict(x=1, y=1, z=1),
# scene4_aspectmode='manual', scene4_aspectratio=dict(x=1, y=1, z=1),
# scene5_aspectmode='manual', scene5_aspectratio=dict(x=1, y=1, z=1),
)
helper = dict(xaxis = dict(range=[-1,1], showbackground=False, showticklabels=False, showaxeslabels=False, showspikes=False, visible=False),
yaxis = dict(range=[-1,1], showbackground=False, showticklabels=False, showaxeslabels=False, showspikes=False, visible=False),
zaxis = dict(range=[-1,1], showbackground=False, showticklabels=False, showaxeslabels=False, showspikes=False, visible=False),)
fig.update_layout(scene = helper,
scene2 = helper,
scene3 = helper,
# scene4 = helper,
# scene5 = helper,
)
write_obj(f'examples/curvature_analysis/{id}_{frame_nr}_10.obj', verts, faces.astype(np.int32), colors_binned_all[0].astype(np.int32))
write_obj(f'examples/curvature_analysis/{id}_{frame_nr}_25.obj', verts, faces.astype(np.int32), colors_binned_all[1].astype(np.int32))
write_obj(f'examples/curvature_analysis/{id}_{frame_nr}_100.obj', verts, faces.astype(np.int32), colors_binned_all[2].astype(np.int32))
write_obj(f'examples/curvature_analysis/{id}_{frame_nr}_mesh.obj', verts, faces.astype(np.int32), np.ones((verts.shape[0], 3), dtype=np.int32) * 200)
fig.show()
return fig
if __name__ == '__main__':
# init_wandb()
is_skirt = True
skirt_modifier = '_skirt' if is_skirt else ''
F = np.load("custom_utils/smpl_faces" + skirt_modifier + ".npy").astype(np.int32)
# k_neighbours(k=25)
folder = '/home/workspace/local-data/test_ready'
folder = '/home/workspace/local-data_128/test_skirt_ready_2'
results_folder = '/home/workspace/data/results/iccv/iccv_pyr_32_64_128_256_512-120000'
# frames_file = 'frames_temp.txt'
@@ -291,7 +374,8 @@ if __name__ == '__main__':
frame = np.random.choice(frames)
# frame = '03265_193'
# frame = '03102_49'
fig, dice = visualize_curvature_labels(folder, results_folder, frame)
wandb.log({f'{frame}-dice:{dice}': fig}, step=i)
# fig, dice = visualize_curvature_labels(folder, results_folder, frame)
# wandb.log({f'{frame}-dice:{dice}': fig}, step=i)
visualize_neighbourhoods(folder, frame)
i += 1
print(frame)
custom_utils/custom_utils.py
+11 -1
View File
@@ -442,4 +442,14 @@ def save_stl(file, mesh, faces):
for j in range(3):
obj.vectors[i][j] = mesh[f[j],:]
obj.save(file)
obj.save(file)
def write_obj(file, vertices, faces, colors):
with open(file, 'w') as file:
for v, c in zip(vertices, colors):
line = 'v ' + ' '.join([str(_) for _ in v]) + ' ' + ' '.join([str(_) for _ in c]) + '\n'
file.write(line)
for f in faces:
line = 'f ' + ' '.join([str(_) for _ in f]) + '\n'
file.write(line)