非极大值抑制——NMS实例

原創

2020-02-22 03:00

输入：左上角和右下角座标
输出：留下的boxes的索引

import numpy as np
import cv2
import matplotlib.pyplot as plt
import random
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)
#从大到小排列，取index
    order = scores.argsort()[::-1]  #逆序排序
#keep为最后保留的边框
    keep = []
    while order.size > 0:
#order[0]是当前分数最大的窗口，之前没有被过滤掉，肯定是要保留的
        i = order[0]
        keep.append(i)

#计算窗口i与其他所以窗口的交叠部分的面积，矩阵计算
        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
#交/并得到iou值
        ovr = inter / (areas[i] + areas[order[1:]] - inter)
#ind为所有与窗口i的iou值小于threshold值的窗口的index，其他窗口此次都被窗口i吸收
        inds = np.where(ovr <= thresh)[0]
#下一次计算前要把窗口i去除，所有i对应的在order里的位置是0，所以剩下的加1
        order = order[inds + 1]
    return keep

boxes = np.array([[3,6,9,11,0.9],[6,3,8,7,0.6],[3,7,10,12,0.7],[1,4,13,7,0.2]])
y = py_cpu_nms(boxes, 0.3)
img = cv2.imread('model.jpg')
color =['red','blue','green','black']

fig, ax = plt.subplots(figsize=(12, 12))
ax.imshow(img, aspect='equal')
for box in boxes[y]:
  ax.add_patch(
              plt.Rectangle((box[0], box[1]),
                            box[2] - box[0],
                            box[3] - box[1], fill=False,
                            edgecolor=random.choice(color), linewidth=1)
              )


plt.axis('off')
plt.show()