def prepForPredicting(fileidx, objects_to_suppress):
data = np.fromfile(lidar_files.format(fileidx), dtype=np.float32).reshape(
(-1, 4))[:, :3]
calib_extrinsic = calib_extrinsics[calib_map[fileidx]].copy()
calib_extrinsic[2, 3] += 1.65
data = data.dot(calib_extrinsic[:3, :3].T) + calib_extrinsic[:3, 3]
# get ground
ground = np.load(ground_planes_by_file.format(fileidx))
pts, tileidxs = tilePoints(data, grndstart, grndstep, grndlen)
groundTs = planes2Transforms(ground)
# get suppressed objects
suppress_start, suppress_end = np.searchsorted(objects_to_suppress[:, 0],
[fileidx, fileidx + 1])
#pts2suppress = objects_to_suppress[suppress_start:suppress_end, 1:3].copy()
pts2suppress = np.zeros((suppress_end - suppress_start, 4))
pts2suppress[:, :2] = objects_to_suppress[suppress_start:suppress_end, 1:3]
pts2suppress[:,
2] = np.cos(objects_to_suppress[suppress_start:suppress_end,
0])
pts2suppress[:,
2] = np.sin(objects_to_suppress[suppress_start:suppress_end,
0])
return pts, tileidxs, pts2suppress, groundTs
globaldetections = np.zeros(
(nnegatives, anchorlen[0], anchorlen[1], anchorlen[2]), dtype=bool)
detectioncount = 0
for file_idx in files2use:
# load relevant data
data = np.fromfile(lidar_files.format(file_idx),
dtype=np.float32).reshape((-1, 4))[:, :3]
calib_extrinsic = calib_extrinsics[calib_map[file_idx]].copy()
calib_extrinsic[2, 3] += 1.65
data = data.dot(calib_extrinsic[:3, :3].T) + calib_extrinsic[:3, 3]
# get ground
ground = np.load(ground_planes_by_file.format(file_idx))
pts, tileidxs = tilePoints(data, grndstart, grndstep, grndlen)
groundTs = planes2Transforms(ground)
# get suppressed objects
suppress_start, suppress_end = np.searchsorted(
objects_to_suppress[:, 0], [file_idx, file_idx + 1])
pts2suppress = objects_to_suppress[suppress_start:suppress_end,
1:3].copy()
pts2suppress = np.zeros((suppress_end - suppress_start, 4))
pts2suppress[:, :2] = objects_to_suppress[suppress_start:suppress_end,
1:3]
pts2suppress[:, 2] = np.cos(
objects_to_suppress[suppress_start:suppress_end, 0])
pts2suppress[:, 2] = np.sin(
objects_to_suppress[suppress_start:suppress_end, 0])
detectioncount = predictNegs(pts, tileidxs, groundTs, btsplits,