IOU

IOU
即交并比，应用：NMS（过滤重叠框）mAP

import numpt as np

def get_IOU(pred_bbox, gt_bbox):
	ixmin = max(pred_bbox[0], gt_bbox[0])
	iymin = max(pred_bbox[1], gt_bbox[1])
	ixmax = min(pred_bbox[2], gt_bbox[2])
	iymax = min(pred_bbox[3], gt_bbox[3])
	iw = np.maximum(ixmax - ixmin + 1., 0.)
	ih = np.maximum(iymax - iymin + 1., 0.)

	inters = iw * ih
	uni = ((pred_bbox[2] - pred_bbox[0] + 1.) * (pred_bbox[3] - pred_bbox[1] + 1.) + (gt_bbox[2] - gt_bbox[0] + 1.) * (gt_bbox[3] - gt_bbox[1] + 1.) - inters)

	overlaps = inters / uni
	return overlaps

def get_max_IOU(pred_bboxes, gt_bbox):
	if pred_bboxs.shape[0] > 0:
		ixmin = np.maximum(pred_bboxes[:, 0], gt_bbox[0])
		iymin = np.maximum(pred_bboxes[:, 1], gt_bbox[1])
		ixmax = np.minimum(pred_bboxes[:, 2], gt_bbox[2])
		iymax = np.minimum(pred_bboxes[:, 3], gt_bbox[3])
		iw = np.maximum(ixmax - ixmin + 1., 0.)
		ih = np.maximum(iymax - iymin + 1., 0.)

		inters = iw * ih
		uni = ((gt_bbox[2] - gt_bbox[0] + 1.) * (gt_bbox[3] - gt_bbox[1] + 1.) + (pred_bboxes[:, 2] - pred_bboxes[:, 0] + 1.) * (pred_bboxes[:, 3] - pred_bboxes[:, 1] + 1.) - inters)
		overlaps = inters / uni
		ovmax = np.max(overlaps)
		jmax = np.argmax(overlaps)

	return overlaps, ovmax, jmax

MIoU

MPA (均精度）：计算橙色与红色圆的比例；
MIoU:计算两圆交集（橙色部分）与两圆并集（红橙黄）之间比例，理想状态两圆重合，比例为1.

代码解析：https://blog.csdn.net/jiongnima/article/details/84750819