def test_add_fields(pcd_fname):
import pypcd
pc = pypcd.PointCloud.from_path(pcd_fname)
old_md = pc.get_metadata()
# new_dt = [(f, pc.pc_data.dtype[f]) for f in pc.pc_data.dtype.fields]
# new_data = [pc.pc_data[n] for n in pc.pc_data.dtype.names]
md = {'fields': ['bla', 'bar'], 'count': [1, 1], 'size': [4, 4],
'type': ['F', 'F']}
d = np.rec.fromarrays((np.random.random(len(pc.pc_data)),
np.random.random(len(pc.pc_data))))
newpc = pypcd.add_fields(pc, md, d)
new_md = newpc.get_metadata()
# print len(old_md['fields']), len(md['fields']), len(new_md['fields'])
# print old_md['fields'], md['fields'], new_md['fields']
assert(len(old_md['fields'])+len(md['fields']) == len(new_md['fields']))
def test_add_fields(pcd_fname):
import pypcd
pc = pypcd.PointCloud.from_path(pcd_fname)
old_md = pc.get_metadata()
# new_dt = [(f, pc.pc_data.dtype[f]) for f in pc.pc_data.dtype.fields]
# new_data = [pc.pc_data[n] for n in pc.pc_data.dtype.names]
md = {'fields': ['bla', 'bar'], 'count': [1, 1], 'size': [4, 4],
'type': ['F', 'F']}
d = np.rec.fromarrays((np.random.random(len(pc.pc_data)),
np.random.random(len(pc.pc_data))))
newpc = pypcd.add_fields(pc, md, d)
new_md = newpc.get_metadata()
# print len(old_md['fields']), len(md['fields']), len(new_md['fields'])
# print old_md['fields'], md['fields'], new_md['fields']
assert (len(old_md['fields']) + len(md['fields']) == len(new_md['fields']))
def save_result(output_dir, scene_id, points, predictions,
ground_truth_labels):
output_file_path = os.path.join(output_dir, scene_id + '.pcd')
predictions = predictions.astype(np.float32)
output_data = np.c_[points, predictions]
pcd = pypcd.make_xyz_label_point_cloud(output_data)
ground_truth_metadata = {
'fields': ['ground_truth'],
'count': [1],
'size': [4],
'type': ['F']
}
ground_truth_dt = np.dtype([('ground_truth', np.float32)])
ground_truth_pc_data = np.rec.fromarrays([ground_truth_labels],
dtype=ground_truth_dt)
pcd = pypcd.add_fields(pcd, ground_truth_metadata, ground_truth_pc_data)
pcd.save_pcd(output_file_path, compression='ascii')
