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utils.py
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utils.py
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import numpy as np
import h5py
#read sdf files produced by SDFGen
def read_sdf_file_as_3d_array(name):
#fp = open(name, 'rb')
#line = fp.readline().strip()
#if not line.startswith(b'#sdf'):
# raise IOError('Not a sdf file')
#dims = list(map(int, fp.readline().strip().split(b' ')[1:]))
#line = fp.readline()
#data = np.frombuffer(fp.read(), dtype=np.float32)
#data = data.reshape(dims)
#fp.close()
data = np.fromfile(name, dtype=np.float32)[1:]
data = np.ascontiguousarray(data.reshape([256, 256, 256]).transpose([2, 0, 1]))
return data
#a simplified reader for binvox files
#mostly copied from binvox_rw.py
#https://github.com/dimatura/binvox-rw-py
def read_binvox_file_as_3d_array(name,fix_coords=True):
fp = open(name, 'rb')
line = fp.readline().strip()
if not line.startswith(b'#binvox'):
raise IOError('Not a binvox file')
dims = list(map(int, fp.readline().strip().split(b' ')[1:]))
translate = list(map(float, fp.readline().strip().split(b' ')[1:]))
scale = list(map(float, fp.readline().strip().split(b' ')[1:]))[0]
line = fp.readline()
raw_data = np.frombuffer(fp.read(), dtype=np.uint8)
# if just using reshape() on the raw data:
# indexing the array as array[i,j,k], the indices map into the
# coords as:
# i -> x
# j -> z
# k -> y
# if fix_coords is true, then data is rearranged so that
# mapping is
# i -> x
# j -> y
# k -> z
values, counts = raw_data[::2], raw_data[1::2]
data = np.repeat(values, counts).astype(np.bool)
data = data.reshape(dims)
if fix_coords:
data = np.transpose(data, (0, 2, 1))
data = np.ascontiguousarray(data, np.uint8)
fp.close()
return data
def read_data_input_only(hdf5_dir,grid_size,input_type,out_bool,out_float,is_undc):
hdf5_file = h5py.File(hdf5_dir, 'r')
if out_bool:
if is_undc:
LOD_gt_int = np.zeros([grid_size+1,grid_size+1,grid_size+1,3],np.int32)
else:
LOD_gt_int = np.zeros([grid_size+1,grid_size+1,grid_size+1,1],np.int32)
else:
LOD_gt_int = None
if out_float:
LOD_gt_float = np.zeros([grid_size+1,grid_size+1,grid_size+1,3],np.float32)
else:
LOD_gt_float = None
if input_type=="sdf" or input_type=="udf":
LOD_input = hdf5_file[str(grid_size)+"_sdf"][:]
LOD_input = LOD_input*grid_size #denormalize
elif input_type=="voxel":
LOD_input = hdf5_file[str(grid_size)+"_voxel"][:]
elif input_type=="pointcloud" or input_type=="noisypc":
LOD_input = hdf5_file["pointcloud"][:].astype(np.float32)
LOD_input = (LOD_input+0.5)*grid_size #denormalize
hdf5_file.close()
return LOD_gt_int, LOD_gt_float, LOD_input
def read_data(hdf5_dir,grid_size,input_type,out_bool,out_float,is_undc):
hdf5_file = h5py.File(hdf5_dir, 'r')
if out_bool:
LOD_gt_int = hdf5_file[str(grid_size)+"_int"][:].astype(np.int32)
else:
LOD_gt_int = None
if out_float:
LOD_gt_float = hdf5_file[str(grid_size)+"_float"][:].astype(np.float32)
else:
LOD_gt_float = None
if input_type=="sdf" or input_type=="udf":
LOD_input = hdf5_file[str(grid_size)+"_sdf"][:]
LOD_input = LOD_input*grid_size #denormalize
elif input_type=="voxel":
LOD_input = hdf5_file[str(grid_size)+"_voxel"][:]
elif input_type=="pointcloud" or input_type=="noisypc":
LOD_input = hdf5_file["pointcloud"][:].astype(np.float32)
LOD_input = (LOD_input+0.5)*grid_size #denormalize
hdf5_file.close()
return LOD_gt_int, LOD_gt_float, LOD_input
def read_and_augment_data_ndc(hdf5_dir,grid_size,input_type,out_bool,out_float,aug_permutation=True,aug_reversal=True,aug_inversion=True):
grid_size_1 = grid_size+1
#read input hdf5
LOD_gt_int, LOD_gt_float, LOD_input = read_data(hdf5_dir,grid_size,input_type,out_bool,out_float,is_undc=False)
newdict = {}
if out_bool:
newdict['int_V_signs'] = LOD_gt_int[:,:,:,0]
if out_float:
newdict['float_center_x_'] = LOD_gt_float[:-1,:-1,:-1,0]
newdict['float_center_y_'] = LOD_gt_float[:-1,:-1,:-1,1]
newdict['float_center_z_'] = LOD_gt_float[:-1,:-1,:-1,2]
if input_type=="sdf" or input_type=="udf":
newdict['input_sdf'] = LOD_input[:,:,:]
elif input_type=="voxel":
newdict['input_voxel'] = LOD_input[:-1,:-1,:-1]
#augment data
permutation_list = [ [0,1,2], [0,2,1], [1,0,2], [1,2,0], [2,0,1], [2,1,0] ]
reversal_list = [ [0,0,0],[0,0,1],[0,1,0],[0,1,1], [1,0,0],[1,0,1],[1,1,0],[1,1,1] ]
if aug_permutation:
permutation = permutation_list[np.random.randint(len(permutation_list))]
else:
permutation = permutation_list[0]
if aug_reversal:
reversal = reversal_list[np.random.randint(len(reversal_list))]
else:
reversal = reversal_list[0]
if aug_inversion:
inversion_flag = np.random.randint(2)
else:
inversion_flag = 0
if reversal[0]:
for k in newdict: #reverse
newdict[k] = newdict[k][::-1,:,:]
if out_float:
k = 'float_center_x_'
mask = (newdict[k]>=0)
newdict[k] = newdict[k]*(1-mask)+(1-newdict[k])*mask
if reversal[1]:
for k in newdict: #reverse
newdict[k] = newdict[k][:,::-1,:]
if out_float:
k = 'float_center_y_'
mask = (newdict[k]>=0)
newdict[k] = newdict[k]*(1-mask)+(1-newdict[k])*mask
if reversal[2]:
for k in newdict: #reverse
newdict[k] = newdict[k][:,:,::-1]
if out_float:
k = 'float_center_z_'
mask = (newdict[k]>=0)
newdict[k] = newdict[k]*(1-mask)+(1-newdict[k])*mask
if permutation == [0,1,2]:
pass
else:
for k in newdict: #transpose
newdict[k] = np.transpose(newdict[k], permutation)
olddict = newdict
newdict = {}
if input_type=="sdf" or input_type=="udf":
newdict['input_sdf'] = olddict['input_sdf']
elif input_type=="voxel":
newdict['input_voxel'] = olddict['input_voxel']
if out_bool:
newdict['int_V_signs'] = olddict['int_V_signs']
if out_float:
if permutation == [0,2,1]:
newdict['float_center_x_'] = olddict['float_center_x_']
newdict['float_center_y_'] = olddict['float_center_z_']
newdict['float_center_z_'] = olddict['float_center_y_']
elif permutation == [1,0,2]:
newdict['float_center_x_'] = olddict['float_center_y_']
newdict['float_center_y_'] = olddict['float_center_x_']
newdict['float_center_z_'] = olddict['float_center_z_']
elif permutation == [2,1,0]:
newdict['float_center_x_'] = olddict['float_center_z_']
newdict['float_center_y_'] = olddict['float_center_y_']
newdict['float_center_z_'] = olddict['float_center_x_']
elif permutation == [1,2,0]:
newdict['float_center_x_'] = olddict['float_center_y_']
newdict['float_center_y_'] = olddict['float_center_z_']
newdict['float_center_z_'] = olddict['float_center_x_']
elif permutation == [2,0,1]:
newdict['float_center_x_'] = olddict['float_center_z_']
newdict['float_center_y_'] = olddict['float_center_x_']
newdict['float_center_z_'] = olddict['float_center_y_']
#store outputs
if out_bool:
LOD_gt_int = np.zeros([grid_size_1,grid_size_1,grid_size_1,1], np.int32)
if inversion_flag:
LOD_gt_int[:,:,:,0] = 1-newdict['int_V_signs']
else:
LOD_gt_int[:,:,:,0] = newdict['int_V_signs']
else:
LOD_gt_int = None
if out_float:
LOD_gt_float = np.full([grid_size_1,grid_size_1,grid_size_1,3], -1, np.float32)
LOD_gt_float[:-1,:-1,:-1,0] = newdict['float_center_x_']
LOD_gt_float[:-1,:-1,:-1,1] = newdict['float_center_y_']
LOD_gt_float[:-1,:-1,:-1,2] = newdict['float_center_z_']
else:
LOD_gt_float = None
if input_type=="sdf" or input_type=="udf":
LOD_input = np.ones([grid_size_1,grid_size_1,grid_size_1], np.float32)
LOD_input[:,:,:] = newdict['input_sdf']
if inversion_flag:
LOD_input = -LOD_input
elif input_type=="voxel":
LOD_input = np.zeros([grid_size_1,grid_size_1,grid_size_1], np.uint8)
LOD_input[:-1,:-1,:-1] = newdict['input_voxel']
if inversion_flag:
LOD_input = 1-LOD_input
return LOD_gt_int, LOD_gt_float, LOD_input
def read_and_augment_data_undc(hdf5_dir,grid_size,input_type,out_bool,out_float,aug_permutation=True,aug_reversal=True,aug_inversion=True):
grid_size_1 = grid_size+1
#read input hdf5
LOD_gt_int, LOD_gt_float, LOD_input = read_data(hdf5_dir,grid_size,input_type,out_bool,out_float,is_undc=True)
newdict = {} #store grid
newpcdict = {} #store pointcloud
if out_bool:
newdict['int_edge_x_'] = LOD_gt_int[:-1,:,:,0]
newdict['int_edge_y_'] = LOD_gt_int[:,:-1,:,1]
newdict['int_edge_z_'] = LOD_gt_int[:,:,:-1,2]
if out_float:
newdict['float_center_x_'] = LOD_gt_float[:-1,:-1,:-1,0]
newdict['float_center_y_'] = LOD_gt_float[:-1,:-1,:-1,1]
newdict['float_center_z_'] = LOD_gt_float[:-1,:-1,:-1,2]
if input_type=="sdf" or input_type=="udf":
newdict['input_sdf'] = LOD_input[:,:,:]
elif input_type=="voxel":
newdict['input_voxel'] = LOD_input[:-1,:-1,:-1]
elif input_type=="pointcloud" or input_type=="noisypc":
newpcdict['input_x_'] = LOD_input[:,0]
newpcdict['input_y_'] = LOD_input[:,1]
newpcdict['input_z_'] = LOD_input[:,2]
#augment data
permutation_list = [ [0,1,2], [0,2,1], [1,0,2], [1,2,0], [2,0,1], [2,1,0] ]
reversal_list = [ [0,0,0],[0,0,1],[0,1,0],[0,1,1], [1,0,0],[1,0,1],[1,1,0],[1,1,1] ]
if aug_permutation:
permutation = permutation_list[np.random.randint(len(permutation_list))]
else:
permutation = permutation_list[0]
if aug_reversal:
reversal = reversal_list[np.random.randint(len(reversal_list))]
else:
reversal = reversal_list[0]
if aug_inversion:
inversion_flag = np.random.randint(2)
else:
inversion_flag = 0
if reversal[0]:
for k in newdict: #reverse
newdict[k] = newdict[k][::-1,:,:]
if out_float:
k = 'float_center_x_'
mask = (newdict[k]>=0)
newdict[k] = newdict[k]*(1-mask)+(1-newdict[k])*mask
if input_type=="pointcloud" or input_type=="noisypc":
k = 'input_x_'
newpcdict[k] = grid_size-newpcdict[k]
if reversal[1]:
for k in newdict: #reverse
newdict[k] = newdict[k][:,::-1,:]
if out_float:
k = 'float_center_y_'
mask = (newdict[k]>=0)
newdict[k] = newdict[k]*(1-mask)+(1-newdict[k])*mask
if input_type=="pointcloud" or input_type=="noisypc":
k = 'input_y_'
newpcdict[k] = grid_size-newpcdict[k]
if reversal[2]:
for k in newdict: #reverse
newdict[k] = newdict[k][:,:,::-1]
if out_float:
k = 'float_center_z_'
mask = (newdict[k]>=0)
newdict[k] = newdict[k]*(1-mask)+(1-newdict[k])*mask
if input_type=="pointcloud" or input_type=="noisypc":
k = 'input_z_'
newpcdict[k] = grid_size-newpcdict[k]
if permutation == [0,1,2]:
pass
else:
for k in newdict: #transpose
newdict[k] = np.transpose(newdict[k], permutation)
olddict = newdict
newdict = {}
oldpcdict = newpcdict
newpcdict = {}
if input_type=="sdf" or input_type=="udf":
newdict['input_sdf'] = olddict['input_sdf']
elif input_type=="voxel":
newdict['input_voxel'] = olddict['input_voxel']
if permutation == [0,2,1]:
if out_bool:
newdict['int_edge_x_'] = olddict['int_edge_x_']
newdict['int_edge_y_'] = olddict['int_edge_z_']
newdict['int_edge_z_'] = olddict['int_edge_y_']
if out_float:
newdict['float_center_x_'] = olddict['float_center_x_']
newdict['float_center_y_'] = olddict['float_center_z_']
newdict['float_center_z_'] = olddict['float_center_y_']
if input_type=="pointcloud" or input_type=="noisypc":
newpcdict['input_x_'] = oldpcdict['input_x_']
newpcdict['input_y_'] = oldpcdict['input_z_']
newpcdict['input_z_'] = oldpcdict['input_y_']
elif permutation == [1,0,2]:
if out_bool:
newdict['int_edge_x_'] = olddict['int_edge_y_']
newdict['int_edge_y_'] = olddict['int_edge_x_']
newdict['int_edge_z_'] = olddict['int_edge_z_']
if out_float:
newdict['float_center_x_'] = olddict['float_center_y_']
newdict['float_center_y_'] = olddict['float_center_x_']
newdict['float_center_z_'] = olddict['float_center_z_']
if input_type=="pointcloud" or input_type=="noisypc":
newpcdict['input_x_'] = oldpcdict['input_y_']
newpcdict['input_y_'] = oldpcdict['input_x_']
newpcdict['input_z_'] = oldpcdict['input_z_']
elif permutation == [2,1,0]:
if out_bool:
newdict['int_edge_x_'] = olddict['int_edge_z_']
newdict['int_edge_y_'] = olddict['int_edge_y_']
newdict['int_edge_z_'] = olddict['int_edge_x_']
if out_float:
newdict['float_center_x_'] = olddict['float_center_z_']
newdict['float_center_y_'] = olddict['float_center_y_']
newdict['float_center_z_'] = olddict['float_center_x_']
if input_type=="pointcloud" or input_type=="noisypc":
newpcdict['input_x_'] = oldpcdict['input_z_']
newpcdict['input_y_'] = oldpcdict['input_y_']
newpcdict['input_z_'] = oldpcdict['input_x_']
elif permutation == [1,2,0]:
if out_bool:
newdict['int_edge_x_'] = olddict['int_edge_y_']
newdict['int_edge_y_'] = olddict['int_edge_z_']
newdict['int_edge_z_'] = olddict['int_edge_x_']
if out_float:
newdict['float_center_x_'] = olddict['float_center_y_']
newdict['float_center_y_'] = olddict['float_center_z_']
newdict['float_center_z_'] = olddict['float_center_x_']
if input_type=="pointcloud" or input_type=="noisypc":
newpcdict['input_x_'] = oldpcdict['input_y_']
newpcdict['input_y_'] = oldpcdict['input_z_']
newpcdict['input_z_'] = oldpcdict['input_x_']
elif permutation == [2,0,1]:
if out_bool:
newdict['int_edge_x_'] = olddict['int_edge_z_']
newdict['int_edge_y_'] = olddict['int_edge_x_']
newdict['int_edge_z_'] = olddict['int_edge_y_']
if out_float:
newdict['float_center_x_'] = olddict['float_center_z_']
newdict['float_center_y_'] = olddict['float_center_x_']
newdict['float_center_z_'] = olddict['float_center_y_']
if input_type=="pointcloud" or input_type=="noisypc":
newpcdict['input_x_'] = oldpcdict['input_z_']
newpcdict['input_y_'] = oldpcdict['input_x_']
newpcdict['input_z_'] = oldpcdict['input_y_']
#store outputs
if out_bool:
LOD_gt_int = np.zeros([grid_size_1,grid_size_1,grid_size_1,3], np.int32)
LOD_gt_int[:-1,:,:,0] = newdict['int_edge_x_']
LOD_gt_int[:,:-1,:,1] = newdict['int_edge_y_']
LOD_gt_int[:,:,:-1,2] = newdict['int_edge_z_']
else:
LOD_gt_int = None
if out_float:
LOD_gt_float = np.full([grid_size_1,grid_size_1,grid_size_1,3], -1, np.float32)
LOD_gt_float[:-1,:-1,:-1,0] = newdict['float_center_x_']
LOD_gt_float[:-1,:-1,:-1,1] = newdict['float_center_y_']
LOD_gt_float[:-1,:-1,:-1,2] = newdict['float_center_z_']
else:
LOD_gt_float = None
if input_type=="sdf" or input_type=="udf":
LOD_input = np.ones([grid_size_1,grid_size_1,grid_size_1], np.float32)
LOD_input[:,:,:] = newdict['input_sdf']
if inversion_flag:
LOD_input = -LOD_input
elif input_type=="voxel":
LOD_input = np.zeros([grid_size_1,grid_size_1,grid_size_1], np.uint8)
LOD_input[:-1,:-1,:-1] = newdict['input_voxel']
if inversion_flag:
LOD_input = 1-LOD_input
elif input_type=="pointcloud" or input_type=="noisypc":
LOD_input = np.zeros([len(LOD_input),3], np.float32)
LOD_input[:,0] = newpcdict['input_x_']
LOD_input[:,1] = newpcdict['input_y_']
LOD_input[:,2] = newpcdict['input_z_']
#vertices, triangles = dual_contouring_ndc_surface_test(LOD_gt_int, LOD_gt_float)
#write_obj_triangle("samples/test_1.obj", vertices, triangles)
#write_ply_point("samples/test_1.ply", LOD_input)
#exit(0)
return LOD_gt_int, LOD_gt_float, LOD_input
#this is not an efficient implementation. just for testing!
def dual_contouring_ndc_test(int_grid, float_grid):
all_vertices = []
all_triangles = []
int_grid = np.squeeze(int_grid)
dimx,dimy,dimz = int_grid.shape
vertices_grid = np.full([dimx,dimy,dimz], -1, np.int32)
#all vertices
for i in range(0,dimx-1):
for j in range(0,dimy-1):
for k in range(0,dimz-1):
v0 = int_grid[i,j,k]
v1 = int_grid[i+1,j,k]
v2 = int_grid[i+1,j+1,k]
v3 = int_grid[i,j+1,k]
v4 = int_grid[i,j,k+1]
v5 = int_grid[i+1,j,k+1]
v6 = int_grid[i+1,j+1,k+1]
v7 = int_grid[i,j+1,k+1]
if v1!=v0 or v2!=v0 or v3!=v0 or v4!=v0 or v5!=v0 or v6!=v0 or v7!=v0:
#add a vertex
vertices_grid[i,j,k] = len(all_vertices)
pos = float_grid[i,j,k]+np.array([i,j,k], np.float32)
all_vertices.append(pos)
all_vertices = np.array(all_vertices, np.float32)
#all triangles
#i-direction
for i in range(0,dimx-1):
for j in range(1,dimy-1):
for k in range(1,dimz-1):
v0 = int_grid[i,j,k]
v1 = int_grid[i+1,j,k]
if v0!=v1:
if v0==0:
all_triangles.append([vertices_grid[i,j-1,k-1],vertices_grid[i,j,k],vertices_grid[i,j,k-1]])
all_triangles.append([vertices_grid[i,j-1,k-1],vertices_grid[i,j-1,k],vertices_grid[i,j,k]])
else:
all_triangles.append([vertices_grid[i,j-1,k-1],vertices_grid[i,j,k-1],vertices_grid[i,j,k]])
all_triangles.append([vertices_grid[i,j-1,k-1],vertices_grid[i,j,k],vertices_grid[i,j-1,k]])
#j-direction
for i in range(1,dimx-1):
for j in range(0,dimy-1):
for k in range(1,dimz-1):
v0 = int_grid[i,j,k]
v1 = int_grid[i,j+1,k]
if v0!=v1:
if v0==0:
all_triangles.append([vertices_grid[i-1,j,k-1],vertices_grid[i,j,k-1],vertices_grid[i,j,k]])
all_triangles.append([vertices_grid[i-1,j,k-1],vertices_grid[i,j,k],vertices_grid[i-1,j,k]])
else:
all_triangles.append([vertices_grid[i-1,j,k-1],vertices_grid[i,j,k],vertices_grid[i,j,k-1]])
all_triangles.append([vertices_grid[i-1,j,k-1],vertices_grid[i-1,j,k],vertices_grid[i,j,k]])
#k-direction
for i in range(1,dimx-1):
for j in range(1,dimy-1):
for k in range(0,dimz-1):
v0 = int_grid[i,j,k]
v1 = int_grid[i,j,k+1]
if v0!=v1:
if v0==0:
all_triangles.append([vertices_grid[i-1,j-1,k],vertices_grid[i-1,j,k],vertices_grid[i,j,k]])
all_triangles.append([vertices_grid[i-1,j-1,k],vertices_grid[i,j,k],vertices_grid[i,j-1,k]])
else:
all_triangles.append([vertices_grid[i-1,j-1,k],vertices_grid[i,j,k],vertices_grid[i-1,j,k]])
all_triangles.append([vertices_grid[i-1,j-1,k],vertices_grid[i,j-1,k],vertices_grid[i,j,k]])
all_triangles = np.array(all_triangles, np.int32)
return all_vertices, all_triangles
#this is not an efficient implementation. just for testing!
def dual_contouring_undc_test(int_grid, float_grid):
all_vertices = []
all_triangles = []
dimx,dimy,dimz,_ = int_grid.shape
vertices_grid = np.full([dimx,dimy,dimz], -1, np.int32)
#all vertices
for i in range(0,dimx-1):
for j in range(0,dimy-1):
for k in range(0,dimz-1):
ex0 = int_grid[i,j,k,0]
ex1 = int_grid[i,j+1,k,0]
ex2 = int_grid[i,j+1,k+1,0]
ex3 = int_grid[i,j,k+1,0]
ey0 = int_grid[i,j,k,1]
ey1 = int_grid[i+1,j,k,1]
ey2 = int_grid[i+1,j,k+1,1]
ey3 = int_grid[i,j,k+1,1]
ez0 = int_grid[i,j,k,2]
ez1 = int_grid[i+1,j,k,2]
ez2 = int_grid[i+1,j+1,k,2]
ez3 = int_grid[i,j+1,k,2]
if ex0 or ex1 or ex2 or ex3 or ey0 or ey1 or ey2 or ey3 or ez0 or ez1 or ez2 or ez3:
#add a vertex
vertices_grid[i,j,k] = len(all_vertices)
pos = float_grid[i,j,k]+np.array([i,j,k], np.float32)
all_vertices.append(pos)
all_vertices = np.array(all_vertices, np.float32)
#all triangles
#i-direction
for i in range(0,dimx-1):
for j in range(1,dimy-1):
for k in range(1,dimz-1):
if int_grid[i,j,k,0]:
all_triangles.append([vertices_grid[i,j-1,k-1],vertices_grid[i,j,k-1],vertices_grid[i,j,k]])
all_triangles.append([vertices_grid[i,j-1,k-1],vertices_grid[i,j,k],vertices_grid[i,j-1,k]])
#j-direction
for i in range(1,dimx-1):
for j in range(0,dimy-1):
for k in range(1,dimz-1):
if int_grid[i,j,k,1]:
all_triangles.append([vertices_grid[i-1,j,k-1],vertices_grid[i,j,k],vertices_grid[i,j,k-1]])
all_triangles.append([vertices_grid[i-1,j,k-1],vertices_grid[i-1,j,k],vertices_grid[i,j,k]])
#k-direction
for i in range(1,dimx-1):
for j in range(1,dimy-1):
for k in range(0,dimz-1):
if int_grid[i,j,k,2]:
all_triangles.append([vertices_grid[i-1,j-1,k],vertices_grid[i,j,k],vertices_grid[i-1,j,k]])
all_triangles.append([vertices_grid[i-1,j-1,k],vertices_grid[i,j-1,k],vertices_grid[i,j,k]])
all_triangles = np.array(all_triangles, np.int32)
return all_vertices, all_triangles
def write_obj_triangle(name, vertices, triangles):
fout = open(name, 'w')
for ii in range(len(vertices)):
fout.write("v "+str(vertices[ii,0])+" "+str(vertices[ii,1])+" "+str(vertices[ii,2])+"\n")
for ii in range(len(triangles)):
fout.write("f "+str(int(triangles[ii,0]+1))+" "+str(int(triangles[ii,1]+1))+" "+str(int(triangles[ii,2]+1))+"\n")
fout.close()
def write_ply_triangle(name, vertices, triangles):
fout = open(name, 'w')
fout.write("ply\n")
fout.write("format ascii 1.0\n")
fout.write("element vertex "+str(len(vertices))+"\n")
fout.write("property float x\n")
fout.write("property float y\n")
fout.write("property float z\n")
fout.write("element face "+str(len(triangles))+"\n")
fout.write("property list uchar int vertex_index\n")
fout.write("end_header\n")
for ii in range(len(vertices)):
fout.write(str(vertices[ii,0])+" "+str(vertices[ii,1])+" "+str(vertices[ii,2])+"\n")
for ii in range(len(triangles)):
fout.write("3 "+str(triangles[ii,0])+" "+str(triangles[ii,1])+" "+str(triangles[ii,2])+"\n")
fout.close()
def write_ply_point(name, vertices):
fout = open(name, 'w')
fout.write("ply\n")
fout.write("format ascii 1.0\n")
fout.write("element vertex "+str(len(vertices))+"\n")
fout.write("property float x\n")
fout.write("property float y\n")
fout.write("property float z\n")
fout.write("end_header\n")
for ii in range(len(vertices)):
fout.write(str(vertices[ii,0])+" "+str(vertices[ii,1])+" "+str(vertices[ii,2])+"\n")
fout.close()
def write_ply_point_normal(name, vertices, normals=None):
fout = open(name, 'w')
fout.write("ply\n")
fout.write("format ascii 1.0\n")
fout.write("element vertex "+str(len(vertices))+"\n")
fout.write("property float x\n")
fout.write("property float y\n")
fout.write("property float z\n")
fout.write("property float nx\n")
fout.write("property float ny\n")
fout.write("property float nz\n")
fout.write("end_header\n")
if normals is None:
for ii in range(len(vertices)):
fout.write(str(vertices[ii,0])+" "+str(vertices[ii,1])+" "+str(vertices[ii,2])+" "+str(vertices[ii,3])+" "+str(vertices[ii,4])+" "+str(vertices[ii,5])+"\n")
else:
for ii in range(len(vertices)):
fout.write(str(vertices[ii,0])+" "+str(vertices[ii,1])+" "+str(vertices[ii,2])+" "+str(normals[ii,0])+" "+str(normals[ii,1])+" "+str(normals[ii,2])+"\n")
fout.close()