SoftGroup/softgroup/ops/src/bfs_cluster/bfs_cluster.cpp
2022-04-15 08:16:32 +00:00

127 lines
4.5 KiB
C++

/*
Ball Query with BatchIdx & Clustering Algorithm
Written by Li Jiang
All Rights Reserved 2020.
Modified by Thang Vu - Remove semantic label in clustering
*/
#include "bfs_cluster.h"
/* =================== ballquery_batch_p================================= */
// input xyz: (n, 3) float
// input batch_idxs: (n) int
// input batch_offsets: (B+1) int, batch_offsets[-1]
// output idx: (n * meanActive) dim 0 for number of points in the ball, idx in n
// output start_len: (n, 2), int
int ballquery_batch_p(at::Tensor xyz_tensor, at::Tensor batch_idxs_tensor,
at::Tensor batch_offsets_tensor, at::Tensor idx_tensor,
at::Tensor start_len_tensor, int n, int meanActive,
float radius) {
const float *xyz = xyz_tensor.data_ptr<float>();
const int *batch_idxs = batch_idxs_tensor.data_ptr<int>();
const int *batch_offsets = batch_offsets_tensor.data_ptr<int>();
int *idx = idx_tensor.data_ptr<int>();
int *start_len = start_len_tensor.data_ptr<int>();
cudaStream_t stream = at::cuda::getCurrentCUDAStream();
int cumsum = ballquery_batch_p_cuda(n, meanActive, radius, xyz, batch_idxs,
batch_offsets, idx, start_len, stream);
return cumsum;
}
ConnectedComponent find_cc(Int idx, Int *ball_query_idxs, int *start_len,
int *visited) {
ConnectedComponent cc;
cc.addPoint(idx);
visited[idx] = 1;
std::queue<Int> Q;
assert(Q.empty());
Q.push(idx);
while (!Q.empty()) {
Int cur = Q.front();
Q.pop();
int start = start_len[cur * 2];
int len = start_len[cur * 2 + 1];
for (Int i = start; i < start + len; i++) {
Int idx_i = ball_query_idxs[i];
if (visited[idx_i] == 1)
continue;
cc.addPoint(idx_i);
visited[idx_i] = 1;
Q.push(idx_i);
}
}
return cc;
}
int get_clusters(float *class_numpoint_mean, int *ball_query_idxs,
int *start_len, const int nPoint, float threshold,
ConnectedComponents &clusters, const int class_id) {
int *visited = new int[nPoint]{0};
float _class_numpoint_mean, thr;
int sumNPoint = 0;
for (int i = 0; i < nPoint; i++) {
if (visited[i] == 0) {
ConnectedComponent CC = find_cc(i, ball_query_idxs, start_len, visited);
_class_numpoint_mean = class_numpoint_mean[class_id];
// if _class_num_point_mean is not defined (-1) directly use threshold
if (_class_numpoint_mean == -1) {
thr = threshold;
} else {
thr = threshold * _class_numpoint_mean;
}
if ((int)CC.pt_idxs.size() >= thr) {
clusters.push_back(CC);
sumNPoint += (int)CC.pt_idxs.size();
}
}
}
delete[] visited;
return sumNPoint;
}
// convert from ConnectedComponents to (idxs, offsets) representation
void fill_cluster_idxs_(ConnectedComponents &CCs, int *cluster_idxs,
int *cluster_offsets) {
for (int i = 0; i < (int)CCs.size(); i++) {
cluster_offsets[i + 1] = cluster_offsets[i] + (int)CCs[i].pt_idxs.size();
for (int j = 0; j < (int)CCs[i].pt_idxs.size(); j++) {
int idx = CCs[i].pt_idxs[j];
cluster_idxs[(cluster_offsets[i] + j) * 2 + 0] = i;
cluster_idxs[(cluster_offsets[i] + j) * 2 + 1] = idx;
}
}
}
// input: class_numpoint_mean_tensor
// input: ball_query_idxs, int, (nActive)
// input: start_len, int, (N, 2)
// output: cluster_idxs, int (sumNPoint, 2), dim 0 for cluster_id, dim 1 for
// corresponding point idxs in N
// output: cluster_offsets, int (nCluster + 1)
void bfs_cluster(at::Tensor class_numpoint_mean_tensor,
at::Tensor ball_query_idxs_tensor, at::Tensor start_len_tensor,
at::Tensor cluster_idxs_tensor,
at::Tensor cluster_offsets_tensor, const int N,
float threshold, const int class_id) {
float *class_numpoint_mean = class_numpoint_mean_tensor.data_ptr<float>();
Int *ball_query_idxs = ball_query_idxs_tensor.data_ptr<Int>();
int *start_len = start_len_tensor.data_ptr<int>();
ConnectedComponents CCs;
int sumNPoint = get_clusters(class_numpoint_mean, ball_query_idxs, start_len,
N, threshold, CCs, class_id);
int nCluster = (int)CCs.size();
cluster_idxs_tensor.resize_({sumNPoint, 2});
cluster_offsets_tensor.resize_({nCluster + 1});
cluster_idxs_tensor.zero_();
cluster_offsets_tensor.zero_();
int *cluster_idxs = cluster_idxs_tensor.data_ptr<int>();
int *cluster_offsets = cluster_offsets_tensor.data_ptr<int>();
fill_cluster_idxs_(CCs, cluster_idxs, cluster_offsets);
}