NMS implementation

[woctezuma]

I see that you use a custom Python implementation for NMS.

facexlib/facexlib/detection/retinaface_utils.py

Lines 38 to 66 in 206e0cc

	def py_cpu_nms(dets, thresh):
	"""Pure Python NMS baseline."""
	x1 = dets[:, 0]
	y1 = dets[:, 1]
	x2 = dets[:, 2]
	y2 = dets[:, 3]
	scores = dets[:, 4]
	areas = (x2 - x1 + 1) * (y2 - y1 + 1)
	order = scores.argsort()[::-1]
	keep = []
	while order.size > 0:
	i = order[0]
	keep.append(i)
	xx1 = np.maximum(x1[i], x1[order[1:]])
	yy1 = np.maximum(y1[i], y1[order[1:]])
	xx2 = np.minimum(x2[i], x2[order[1:]])
	yy2 = np.minimum(y2[i], y2[order[1:]])
	w = np.maximum(0.0, xx2 - xx1 + 1)
	h = np.maximum(0.0, yy2 - yy1 + 1)
	inter = w * h
	ovr = inter / (areas[i] + areas[order[1:]] - inter)
	inds = np.where(ovr <= thresh)[0]
	order = order[inds + 1]
	return keep

Moreover, the requirements of this repository include torchvision:

facexlib/requirements.txt

Line 9 in 206e0cc

torchvision

I wonder whether it would be beneficial to use torchvision's implementation of NMS instead. cf. torchvision.ops.nms
I had this idea after a quick discussion in another repository: ternaus/retinaface#23 (comment)

[xinntao]

@woctezuma
Thanks for your suggestion.
It is a good improvement.
I am busy these days and may improve it later.

It would be great if you can help it and open a PR 😃