def __getitem__(self, index):
point_set_ini = self.scene_points_list[index]
semantic_seg_ini = self.semantic_labels_list[index].astype(np.int32)
sample_weight_ini = self.labelweights[semantic_seg_ini]
point_sets = list()
semantic_segs = list()
sample_weights = list()
for i in range(8):
smpidx = scene_util.virtual_scan(point_set_ini, mode=i)
if len(smpidx) < 300:
continue
point_set = point_set_ini[smpidx, :]
semantic_seg = semantic_seg_ini[smpidx]
sample_weight = sample_weight_ini[smpidx]
choice = np.random.choice(len(semantic_seg),
self.npoints,
replace=True)
point_set = point_set[choice, :] # Nx3
semantic_seg = semantic_seg[choice] # N
sample_weight = sample_weight[choice] # N
point_sets.append(np.expand_dims(point_set, 0)) # 1xNx3
semantic_segs.append(np.expand_dims(semantic_seg, 0)) # 1xN
sample_weights.append(np.expand_dims(sample_weight, 0)) # 1xN
point_sets = np.concatenate(tuple(point_sets), axis=0)
semantic_segs = np.concatenate(tuple(semantic_segs), axis=0)
sample_weights = np.concatenate(tuple(sample_weights), axis=0)
return point_sets, semantic_segs, sample_weights
def __getitem__(self, index):
point_set_ini = self.scene_points_list[index]
semantic_seg_ini = self.semantic_labels_list[index].astype(np.int32)
sample_weight_ini = self.labelweights[semantic_seg_ini]
point_sets = list()
semantic_segs = list()
sample_weights = list()
for i in xrange(8):
smpidx = scene_util.virtual_scan(point_set_ini,mode=i)
if len(smpidx)<300:
continue
point_set = point_set_ini[smpidx,:]
semantic_seg = semantic_seg_ini[smpidx]
sample_weight = sample_weight_ini[smpidx]
choice = np.random.choice(len(semantic_seg), self.npoints, replace=True)
point_set = point_set[choice,:] # Nx3
semantic_seg = semantic_seg[choice] # N
sample_weight = sample_weight[choice] # N
point_sets.append(np.expand_dims(point_set,0)) # 1xNx3
semantic_segs.append(np.expand_dims(semantic_seg,0)) # 1xN
sample_weights.append(np.expand_dims(sample_weight,0)) # 1xN
point_sets = np.concatenate(tuple(point_sets),axis=0)
semantic_segs = np.concatenate(tuple(semantic_segs),axis=0)
sample_weights = np.concatenate(tuple(sample_weights),axis=0)
return point_sets, semantic_segs, sample_weights
def __create_smpidx(self):
virtual_smpidx = list()
for point_set in self.scene_points_list:
smpidx = list()
for i in xrange(8):
var = scene_util.virtual_scan(point_set, mode=i)
smpidx.append(np.expand_dims(var, 0)) # 1xpoints
virtual_smpidx.append(smpidx) # datax8xpoints
assert len(virtual_smpidx) == len(self.scene_points_list)
assert len(virtual_smpidx[0]) == 8
with open(self.smpidx_filename, 'wb') as fp:
pickle.dump(virtual_smpidx, fp)
return virtual_smpidx