def GenObj_rh5():
xyz_cut_rate = [0, 0, 0.9]
xyz_cut_rate = None
path = '/home/z/Research/dynamic_pointnet/data/Scannet__H5F/BasicData/rawh5'
fn_ls = glob.glob(path + '/scene0002*.rh5')
path = '/home/z/Research/dynamic_pointnet/data/ETH__H5F/BasicData/rawh5'
fn_ls = glob.glob(path +
'/marketplacefeldkirch_station7_intensity_rgb.rh5')
fn_ls = glob.glob(path +
'/StGallenCathedral_station6_rgb_intensity-reduced.rh5')
fn_ls = glob.glob(path +
'/untermaederbrunnen_station3_xyz_intensity_rgb.rh5')
path = '/home/z/Research/SparseVoxelNet/data/MATTERPORT_H5TF/rawh5/17DRP5sb8fy'
fn_ls = glob.glob(path + '/region0.rh5')
for fn in fn_ls:
if not Raw_H5f.check_rh5_intact(fn)[0]:
print('rh5 not intact, abort gen obj')
return
with h5py.File(fn, 'r') as h5f:
rawh5f = Raw_H5f(h5f, fn)
rawh5f.generate_objfile(IsLabelColor=True,
xyz_cut_rate=xyz_cut_rate)
def generate_kitti_to_rawh5f():
label_file_list = glob.glob(
os.path.join(kitti_prepare.label_file_path, '*.txt'))
print('%d files in \n%s' %
(len(label_file_list), kitti_prepare.label_file_path))
rawh5f_file_path = kitti_prepare.rawh5f_path
if not os.path.exists(rawh5f_file_path):
os.makedirs(rawh5f_file_path)
for l_f_n in label_file_list:
file_name = os.path.splitext(os.path.basename(l_f_n))[0]
label_file_name = os.path.join(kitti_prepare.label_file_path,
file_name + '.txt')
point_cloud_file_name = os.path.join(
kitti_prepare.point_cloud_file_path, file_name + '.bin')
h5f_file_name = os.path.join(rawh5f_file_path, file_name + '.h5')
with h5py.File(h5f_file_name, 'w') as h5f:
raw_h5f = Raw_H5f(h5f, h5f_file_name, 'KITTI')
point_cloud_data = read_point_cloud_from_bin(
point_cloud_file_name)
label_data = read_label_from_txt(label_file_name)
num_row = point_cloud_data.shape[0]
raw_h5f.set_num_default_row(num_row)
raw_h5f.append_to_dset('xyz', point_cloud_data[:, 0:3])
num_row = label_data.shape[0]
raw_h5f.set_num_default_row(num_row)
raw_h5f.append_to_dset('bounding_box', label_data)
raw_h5f.create_done()
def WriteRawH5f_MODELNET40(txt_path, rawh5f_dir):
tmp = txt_path.split('/')
rawh5f_fn = os.path.join(rawh5f_dir, tmp[-2],
os.path.splitext(tmp[-1])[0] + '.rh5')
if not os.path.exists(os.path.dirname(rawh5f_fn)):
os.makedirs(os.path.dirname(rawh5f_fn))
if Raw_H5f.check_rh5_intact(rawh5f_fn)[0]:
print('rh5 intact: %s' % (rawh5f_fn))
return rawh5f_fn
print('start write rh5: %s' % (rawh5f_fn))
data = np.loadtxt(txt_path, delimiter=',').astype(np.float32)
num_points = data.shape[0]
print(num_points)
with h5py.File(rawh5f_fn, 'w') as h5f:
raw_h5f = Raw_H5f(h5f, rawh5f_fn, 'MODELNET40')
raw_h5f.set_num_default_row(num_points)
raw_h5f.append_to_dset('xyz', data[:, 0:3])
if data.shape[1] == 6:
raw_h5f.append_to_dset('nxnynz', data[:, 3:6])
raw_h5f.rh5_create_done()
return txt_path
def WriteRawH5f_SCANNET(fn, rawh5f_dir):
# save as rh5
import SCANNET_util
fn_base = os.path.basename(fn)
rawh5f_fn = os.path.join(rawh5f_dir, fn_base + '.rh5')
if Raw_H5f.check_rh5_intact(rawh5f_fn)[0]:
print('rh5 intact: %s' % (rawh5f_fn))
return fn
print('start write rh5: %s' % (rawh5f_fn))
scene_points, instance_labels, semantic_labels, mesh_labels = SCANNET_util.parse_raw_SCANNET(
fn)
num_points = scene_points.shape[0]
with h5py.File(rawh5f_fn, 'w') as h5f:
raw_h5f = Raw_H5f(h5f, rawh5f_fn, 'SCANNET')
raw_h5f.set_num_default_row(num_points)
raw_h5f.append_to_dset('xyz', scene_points[:, 0:3])
raw_h5f.append_to_dset('color', scene_points[:, 3:6])
raw_h5f.append_to_dset('label_category', semantic_labels)
raw_h5f.append_to_dset('label_instance', instance_labels)
raw_h5f.append_to_dset('label_mesh', mesh_labels)
raw_h5f.rh5_create_done()
return fn
def gen_stanford_indoor3d_to_rawh5f():
file_list = glob.glob(
os.path.join(Indoor3d_Prepare.raw_npy_path, '*.npy'))
print('%d files in \n%s' %
(len(file_list), Indoor3d_Prepare.raw_npy_path))
rawh5f_path = Indoor3d_Prepare.rawh5f_path
if not os.path.exists(rawh5f_path):
os.makedirs(rawh5f_path)
for fn in file_list:
base_name = os.path.splitext(os.path.basename(fn))[0]
h5_fn = os.path.join(rawh5f_path, base_name + '.rh5')
with h5py.File(h5_fn, 'w') as h5f:
raw_h5f = Raw_H5f(h5f, h5_fn, 'STANFORD_INDOOR3D')
data = np.load(fn)
num_row = data.shape[0]
raw_h5f.set_num_default_row(num_row)
raw_h5f.append_to_dset('xyz', data[:, 0:3])
raw_h5f.append_to_dset('color', data[:, 3:6])
raw_h5f.append_to_dset('label', data[:, 6:7])
raw_h5f.create_done()
def WriteRawH5f_Region_Ply(k_region,rs_zf,house_name,house_h5f_dir,house_dir_extracted):
file_name = 'region'+str(k_region)
region_ply_fn = zip_extract('region_segmentations',house_name,file_name,'ply',rs_zf,house_dir_extracted)
rawh5f_fn = house_h5f_dir+'/rawh5f/region'+str(k_region)+'.rh5'
IsDelVexMultiSem = True
with open(region_ply_fn,'r') as ply_fo, h5py.File(rawh5f_fn,'w') as h5f:
vertex_xyz,vertex_nxnynz,vertex_rgb,vertex_semantic,face_vertex_indices,face_semantic = parse_ply_file(ply_fo,IsDelVexMultiSem)
raw_h5f = Raw_H5f(h5f,rawh5f_fn,'MATTERPORT')
raw_h5f.set_num_default_row(vertex_xyz.shape[0])
raw_h5f.append_to_dset('xyz',vertex_xyz)
raw_h5f.append_to_dset('nxnynz',vertex_nxnynz)
raw_h5f.append_to_dset('color',vertex_rgb)
raw_h5f.append_to_dset('label_category',vertex_semantic[:,0]) # category_id
raw_h5f.append_to_dset('label_instance',vertex_semantic[:,1]) # segment_id
raw_h5f.append_to_dset('label_material',vertex_semantic[:,0]) # material_id
raw_h5f.create_done()
raw_h5f.show_h5f_summary_info()
return file_name
def Load_Raw_Scannet_Pickle(self):
file_name = os.path.join(SCANNET_DATA_DIR,'scannet_%s.pickle'%(self.split))
rawh5f_dir = self.rawh5f_dir_base
if not os.path.exists(rawh5f_dir):
os.makedirs(rawh5f_dir)
with open(file_name,'rb') as fp:
scene_points_list = pickle.load(fp)
semantic_labels_list = pickle.load(fp)
print('%d scans for file:\n %s'%(len(semantic_labels_list),file_name))
for n in range(len(semantic_labels_list)):
# write one RawH5f file for one scane
rawh5f_fn = os.path.join(rawh5f_dir,self.split+'_scan_%d.rh5'%(n))
num_points = semantic_labels_list[n].shape[0]
with h5py.File(rawh5f_fn,'w') as h5f:
raw_h5f = Raw_H5f(h5f,rawh5f_fn,'SCANNET')
raw_h5f.set_num_default_row(num_points)
raw_h5f.append_to_dset('xyz',scene_points_list[n])
raw_h5f.append_to_dset('label',semantic_labels_list[n])
raw_h5f.create_done()
def WriteRawH5f_ETH(fn_txt, rawh5f_dir):
import ETH_util
fn_base = os.path.basename(fn_txt)
fn_base = os.path.splitext(fn_base)[0]
if fn_base[-3:] == 'txt':
fn_base = os.path.splitext(fn_base)[0]
rawh5f_fn = os.path.join(rawh5f_dir, fn_base + '.rh5')
if Raw_H5f.check_rh5_intact(rawh5f_fn)[0]:
print('rh5 intact: %s' % (rawh5f_fn))
return fn_txt
print('start write rh5: %s' % (rawh5f_fn))
fn_labels = os.path.splitext(fn_txt)[0] + '.labels'
#xyz, intensity, rgb, labels = ETH_util.parse_raw_ETH( fn_txt )
num_points = 1e7
with h5py.File(rawh5f_fn, 'w') as h5f:
raw_h5f = Raw_H5f(h5f, rawh5f_fn, 'ETH')
raw_h5f.set_num_default_row(num_points)
with open(fn_txt, 'r') as txtf:
# {x, y, z, intensity, r, g, b}
n_read = 0
buf_size = int(1e7)
while True:
lines = txtf.readlines(buf_size)
if len(lines) == 0:
break
lines = [
np.fromstring(line.strip(), dtype=np.float32,
sep=' ').reshape(1, -1) for line in lines
]
buf = np.concatenate(lines, 0)
raw_h5f.append_to_dset('xyz', buf[:, 0:3])
raw_h5f.append_to_dset('color', buf[:, 3:6])
raw_h5f.append_to_dset('intensity', buf[:, 6:7])
n_read += buf.shape[0]
print('data read: %d line \t%s' % (n_read, fn_base))
if os.path.exists(fn_labels):
with open(fn_labels, 'r') as labelsf:
buf_size = int(1e7)
n_read_l = 0
while True:
lines = labelsf.readlines(buf_size)
if len(lines) == 0:
break
lines = [
np.fromstring(line.strip(), dtype=np.int32,
sep=' ').reshape(1, -1) for line in lines
]
buf = np.concatenate(lines, 0)
raw_h5f.append_to_dset('label_category', buf)
n_read_l += buf.shape[0]
print('label read: %d line \t%s' % (n_read_l, fn_base))
assert n_read == n_read_l
raw_h5f.rh5_create_done()
if IsLablesExist:
f_labels.close()
print('finish : %s' % (rawh5f_fn))
return rawh5f_fn
def GenObj_RawH5f(self):
file_name = self.house_rawh5f_dir+'/region5.rh5'
xyz_cut_rate= [0,0,0.9]
with h5py.File(file_name,'r') as h5f:
rawh5f = Raw_H5f(h5f,file_name)
rawh5f.generate_objfile(IsLabelColor=True,xyz_cut_rate=xyz_cut_rate)