Fix visualize_sdf

.gitignore

@@ -1,7 +1,9 @@
 .vscode
 build
 dist
+data
 __pycache__
 *.obj
 *.egg-info
-*.pyd
+*.pyd
+*.npy

example/test.py

@@ -1,9 +1,11 @@
 import os
 import trimesh
 import mesh2sdf
+import numpy as np
 import skimage.measure
 
-filename = os.path.join(os.path.dirname(__file__), 'plane.obj')
+
+filename = os.path.join(os.path.dirname(__file__), 'data', 'plane.obj')
 mesh = trimesh.load(filename, force='mesh')
 
 vertices = mesh.vertices
@@ -21,3 +23,4 @@
 v = v / scale + center
 mesh = trimesh.Trimesh(vertices=v, faces=f)
 mesh.export(filename[:-4] + '.fixed.obj')
+np.save(filename[:-4] + '.npy', sdf)

example/visualize_sdf.py

@@ -6,44 +6,27 @@
 
 parser = argparse.ArgumentParser()
 parser.add_argument('--filename', type=str, required=True)
-parser.add_argument('--rescale', type=str, required=False, default='false')
 args = parser.parse_args()
 
 filename = args.filename
-rescale = args.rescale.lower() == 'true'
+levels = [-0.02, 0.0, 0.02]
 
-# levels = [-0.2, -0.1, -0.05, -0.02, -0.01, 0.0, 0.01, 0.02, 0.05, 0.1, 0.2]
-levels = [-0.01, 0.0, 0.01]
-
-
-# marching cube
 sdf = np.load(filename)
-# sdf = sdf[::2, ::2, ::2]
 size = sdf.shape[0]
-if rescale:
-  # sdf = (1- sdf) * 2 - 1  # !!! rescale SDF
-  sdf = sdf * 2 - 1  # !!! rescale SDF
-
 print(sdf.max(), sdf.min())
 
+# extract level sets
 for i, level in enumerate(levels):
-  vtx, faces, _, _ = skimage.measure.marching_cubes_lewiner(sdf, level)
+  vtx, faces, _, _ = skimage.measure.marching_cubes(sdf, level)
 
-  ## save to ply
   vtx = vtx * (2.0 / size) - 1.0
   mesh = trimesh.Trimesh(vtx, faces)
   mesh.export(filename[:-3] + 'l%.2f.obj' % level)
 
-  # mesh = o3d.geometry.TriangleMesh()
-  # mesh.vertices = o3d.utility.Vector3dVector(vtx)
-  # mesh.triangles = o3d.utility.Vector3iVector(faces)
-  # plyname = filename[:-4] + '_%02d_l%0.2f.ply' % (i, level)
-  # o3d.io.write_triangle_mesh(plyname, mesh)
-
 
-## draw image
+# draw image
 for i in range(size):
-  array_2d = sdf[i,:,:]
+  array_2d = sdf[:, :, i]
 
   num_levels = 6
   fig, ax = plt.subplots(figsize=(2.75, 2.75), dpi=300)
@@ -52,12 +35,12 @@
   levels = np.concatenate((levels_neg, np.zeros((0)), levels_pos), axis=0)
   colors = plt.get_cmap("Spectral")(np.linspace(0., 1., num=num_levels*2+1))
 
-  sample = np.flipud(array_2d)
+  sample = array_2d
+  # sample = np.flipud(array_2d)
   CS = ax.contourf(sample, levels=levels, colors=colors)
-  # cbar = fig.colorbar(CS)
 
   ax.contour(sample, levels=levels, colors='k', linewidths=0.1)
   ax.contour(sample, levels=[0], colors='k', linewidths=0.3)
   ax.axis('off')
-  plt.savefig(filename + '.z.%03d.png' % i)
-  # plt.show()
+  plt.savefig(filename[:-4] + '.%03d.png' % i)
+  # plt.show()