NMS (Non-maximum Suppression) Tools

Bounding Box NMS

- Refer to ./bbox-nms/nms.py

Bounding Box NMS - C language version

Bounding Box NMS - C language version

Benchmark (Single Batch / s)

• Each Single-Batch-Data have 2000 bounding boxes

• Each test run 1000 times to obtain results

• Speed(ms) : including: preprocessing, nms

• W/O processing (ms): only including: nms

Algo / Paramters	Python	C	C	Batch Pallel C	Batch Pallel C
Batch Num	Speed(ms)	Speed(ms)	W/O processing (ms)	Speed(ms)	W/O processing (ms)
1	0.611	0.258	0.211	0.834	0.735
10	0.610	0.256	0.211	0.343	0.175
100	0.603	0.260	0.214	0.354	0.094

Usage: Refer to batch_parallel_nms.py

num_classes = 80
score_thr = 0.5
nms_thr = 0.5

batched_bboxes = [np.ones((2000, 4)), np.ones((123, 4)), np.ones((321, 4)), ...]
batched_scores = [np.ones((2000, num_classes)), np.ones((123, num_classes)), np.ones((321, num_classes)), ...]

nms_c = Batch_Parallel_Nms()

# NMS
for boxes, scores in zip(batched_bboxes, batched_scores):
            indices_to_keep, nms_out_cls = nms_c.nms(boxes, scores, score_thr, nms_thr)

# BATCH PARALLEL
indices_to_keep, nms_out_cls = nms_c.batch_parallel_nms(batched_bboxes, batched_scores, score_thr, nms_thr)

If there is any modified

gcc -O3 -msse2 -mfpmath=sse -ftree-vectorizer-verbose=5 -fopenmp -fPIC -shared -o c/compiled/batch_parallel_nms.so c/batch_parallel_nms.c 

Mask NMS

Mutli class mask NMS (class-aware)

• Class-unaware: a proposal can belong to mutiple single class

• inputs:

  • masks: NDArray (num_masks, W, H) (type: Boolean)
  • scores: NDArray (num_masks, num_classes) in [0, 1]
  • score_thr: float (score threshold of bounding box)
  • nms_thr: float (intersection threshold of mask)

• output:

  • [NDArray of indices to keep, NDArray of class id]

pip install numba
pip install numpy