def range2pcd(Images, path, name, index):
cloud_xyz = range2xyz(Images)
output_pcd = pypcd.make_xyz_point_cloud(cloud_xyz.reshape(-1, 3))
output_pcd.save(
join(path, 'processed pcd', '%s' % name, '%04d.pcd' % index))
def save_point_cloud(pts, filename):
pc = pcd.make_xyz_point_cloud(pts)
# Write point cloud to file in PCD format
metadata = pc.get_metadata()
with open(filename, 'w') as fileobj:
# Write headers
template = "VERSION {version}\nFIELDS {fields}\nSIZE {size}\nTYPE {type}\nCOUNT {count}\nWIDTH {width}\nHEIGHT {height}\nVIEWPOINT {viewpoint}\nPOINTS {points}\nDATA {data}\n"
new_fields = []
for f in metadata['fields']:
if f == '_':
new_fields.append('padding')
else:
new_fields.append(f)
metadata['fields'] = ' '.join(new_fields)
metadata['size'] = ' '.join(map(str, metadata['size']))
metadata['type'] = ' '.join(metadata['type'])
metadata['count'] = ' '.join(map(str, metadata['count']))
metadata['width'] = str(metadata['width'])
metadata['height'] = str(metadata['height'])
metadata['viewpoint'] = ' '.join(map(str, metadata['viewpoint']))
metadata['points'] = str(metadata['points'])
metadata['data'] = 'ascii'
tmpl = template.format(**metadata)
fileobj.write(tmpl)
pts = pc.pc_data
# NOTE Hack to convert structured numpy array to ndarray
pts = np.squeeze(pts.view(pts.dtype[0]).reshape(pts.shape + (-1, )))
# Write the data
np.savetxt(fileobj, pts, fmt='%.8f')
def writePCD(self, file, cloud):
"""Write Files PCD.
Args:
self: The object pointer.
file (str): name file.
cloud (array): data cloud point.
Returns:
clouds (str): save cloud points founded.
"""
X = cloud[:, 0]
Y = cloud[:, 1]
Z = cloud[:, 2]
data = np.column_stack((X, Y, Z))
# Use the pypcd utility function to create a new point cloud from ndarray
new_cloud = pypcd.make_xyz_point_cloud(data)
# Store the cloud uncompressed
fileName = file[:-4] + self.exPCD
new_cloud.save_pcd(fileName)
#from sensor_msgs import point_cloud2
#from sensor_msgs.msg import PointCloud2, PointField
#from std_msgs.msg import Header
from numpy2pcd import get_low_res_input, noise_remove, range2xyz, range2pcd
from readpcd import offset_range_img, image_rows_full, image_cols, save_grey_img, create_4dir, progressbar, reverse_offset_range_img
range_image_array = np.empty([0, image_rows_full, image_cols, 1],
dtype=np.float32)
file_path = '/home/yifu/data/long_experiment/cloud_0000_1583840211_539847424.pcd'
pc = pypcd.PointCloud.from_path(file_path)
pcdata = pc.pc_data.view(np.float32).reshape(-1, 3)
np.savetxt("/home/yifu/data/long_experiment/processed pcd/raw %s.csv" %
sys.version[:3],
pcdata,
delimiter=",")
range_image = offset_range_img(pcdata)
# recover
cloud = range2xyz(range_image[0])
cloud = reverse_offset_range_img(cloud)
np.savetxt("/home/yifu/data/long_experiment/processed pcd/%s.csv" %
sys.version[:3],
cloud,
delimiter=",")
output_pcd = pypcd.make_xyz_point_cloud(cloud.reshape(-1, 3))
output_pcd.save(
join('/home/yifu/data/long_experiment/processed pcd/numpysave.pcd'))