def interpolate(sxyzs,sprobs,qxyzs,ratio=1.0/(2*0.15*0.15)):
nidxs=libPointUtil.findNeighborInAnotherCPU(sxyzs,qxyzs,8)
nidxs_lens=np.asarray([len(idxs) for idxs in nidxs],dtype=np.int32)
nidxs_bgs=compute_nidxs_bgs(nidxs_lens)
nidxs=np.concatenate(nidxs,axis=0)
qprobs = libPointUtil.interpolateProbsGPU(sxyzs, qxyzs, sprobs, nidxs, nidxs_lens, nidxs_bgs, ratio)
return qprobs
def interpolate(sxyzs, sprobs, qxyzs, ratio=1.0 / (2 * 0.125 * 0.125)):
bg = time.time()
nidxs = libPointUtil.findNeighborInAnotherCPU(sxyzs, qxyzs, 6)
print 'search done {} s'.format(time.time() - bg)
nidxs_lens = np.asarray([len(idxs) for idxs in nidxs], dtype=np.int32)
nidxs_bgs = compute_nidxs_bgs(nidxs_lens)
nidxs = np.concatenate(nidxs, axis=0)
qprobs = libPointUtil.interpolateProbsGPU(sxyzs, qxyzs, sprobs, nidxs,
nidxs_lens, nidxs_bgs, ratio)
return qprobs
def compute_covar(xyzs, radius):
covar_nidxs = libPointUtil.findNeighborRadiusCPU(xyzs, radius)
covar_nidxs_lens = np.ascontiguousarray(
[len(idxs) for idxs in covar_nidxs], np.int32)
covar_nidxs_bgs = compute_nidxs_bgs(covar_nidxs_lens)
covar_nidxs = np.ascontiguousarray(np.concatenate(covar_nidxs, axis=0),
dtype=np.int32)
covars = libPointUtil.computeCovarsGPU(xyzs, covar_nidxs, covar_nidxs_lens,
covar_nidxs_bgs)
return covars
def sample_block(points,
labels,
ds_stride,
block_size,
block_stride,
min_pn,
use_rescale=False,
swap=False,
flip_x=False,
flip_y=False,
covar_ds_stride=0.03,
covar_nn_size=0.1):
xyzs = np.ascontiguousarray(points[:, :3])
rgbs = np.ascontiguousarray(points[:, 3:])
min_xyzs = np.min(xyzs, axis=0, keepdims=True)
max_xyzs = np.max(xyzs, axis=0, keepdims=True)
covar_ds_idxs = libPointUtil.gridDownsampleGPU(xyzs, covar_ds_stride,
False)
covar_ds_xyzs = np.ascontiguousarray(xyzs[covar_ds_idxs, :])
# flip
if swap:
covar_ds_xyzs = swap_xy(covar_ds_xyzs)
min_xyzs = swap_xy(min_xyzs)
max_xyzs = swap_xy(max_xyzs)
if flip_x:
covar_ds_xyzs = flip(covar_ds_xyzs, axis=0)
min_xyzs[:, 0], max_xyzs[:, 0] = -max_xyzs[:, 0], -min_xyzs[:, 0]
if flip_y:
covar_ds_xyzs = flip(covar_ds_xyzs, axis=1)
min_xyzs[:, 1], max_xyzs[:, 1] = -max_xyzs[:, 1], -min_xyzs[:, 1]
# rescale
if use_rescale:
rescale = np.random.uniform(0.9, 1.1, [1, 3])
covar_ds_xyzs[:, :3] *= rescale
min_xyzs *= rescale
max_xyzs *= rescale
ds_idxs = libPointUtil.gridDownsampleGPU(covar_ds_xyzs, ds_stride, False)
covar_nidxs = libPointUtil.findNeighborRadiusCPU(covar_ds_xyzs, ds_idxs,
covar_nn_size)
covar_nidxs_lens = np.ascontiguousarray(
[len(idxs) for idxs in covar_nidxs], np.int32)
covar_nidxs_bgs = compute_nidxs_bgs(covar_nidxs_lens)
covar_nidxs = np.ascontiguousarray(np.concatenate(covar_nidxs, axis=0),
dtype=np.int32)
covars = libPointUtil.computeCovarsGPU(covar_ds_xyzs, covar_nidxs,
covar_nidxs_lens, covar_nidxs_bgs)
xyzs = covar_ds_xyzs[ds_idxs, :]
rgbs = rgbs[covar_ds_idxs, :][ds_idxs, :]
lbls = labels[covar_ds_idxs][ds_idxs]
xyzs -= min_xyzs
idxs = uniform_sample_block(xyzs,
block_size,
block_stride,
normalized=True,
min_pn=min_pn)
xyzs += min_xyzs
xyzs, rgbs, covars, lbls = fetch_subset([xyzs, rgbs, covars, lbls], idxs)
return xyzs, rgbs, covars, lbls