python_nms.py

import numpy as np
def nms(boxes, threshold, method='Union'):
    if boxes.size==0:
        return np.empty((0,3))
    x1 = boxes[:,0]
    y1 = boxes[:,1]
    x2 = boxes[:,2]
    y2 = boxes[:,3]
    s = boxes[:,4]
    area = (x2-x1+1) * (y2-y1+1)
    I = np.argsort(s)
    pick = np.zeros_like(s, dtype=np.int16)
    counter = 0
    while I.size>0:
        i = I[-1]
        pick[counter] = i
        counter += 1
        idx = I[0:-1]
        xx1 = np.maximum(x1[i], x1[idx])
        yy1 = np.maximum(y1[i], y1[idx])
        xx2 = np.minimum(x2[i], x2[idx])
        yy2 = np.minimum(y2[i], y2[idx])
        w = np.maximum(0.0, xx2-xx1+1)
        h = np.maximum(0.0, yy2-yy1+1)
        inter = w * h
        if method is 'Min':
            o = inter / np.minimum(area[i], area[idx])
        else:
            o = inter / (area[i] + area[idx] - inter)
        I = I[np.where(o<=threshold)]
    pick = pick[0:counter]
    return pick