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余弦相似度分类

计算余弦值公式
$$cos\theta = \frac{x_1y_1+x_2y_2+…+x_ny_n}{\sqrt{x_1^2+x_2^2+…+x_n^2}\sqrt{y_1^2+y_2^2+…+y_n^2}}$$

样本和待分类图像

样本和待分类图像

执行结果

执行结果

完整代码

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#! /usr/bin/python
# -*- coding:utf-8 -*-
"""
@author: abc
@file: euclidean_distance.py
@date: 2016-12-09
@desc: 余弦相似度
"""
__author__ = "abc"

import cv2
import numpy as np

w_fg = 20
h_fg = 15
pic_flag = 3


def read_pic(fn):
"""
read_pic
:param fn:
:return:
"""
fnimg = cv2.imread(fn)
img = cv2.resize(fnimg, (800, 600), interpolation=cv2.INTER_AREA)
w = img.shape[1]
h = img.shape[0]
w_interval = w / w_fg
h_interval = h / h_fg

alltz = []
alltz.append([])
alltz.append([])
alltz.append([])

for now_h in xrange(0, h, h_interval):
for now_w in xrange(0, w, w_interval):
b = img[now_h:now_h + h_interval, now_w:now_w + w_interval, 0]
g = img[now_h:now_h + h_interval, now_w:now_w + w_interval, 1]
r = img[now_h:now_h + h_interval, now_w:now_w + w_interval, 2]
btz = np.mean(b)
gtz = np.mean(g)
rtz = np.mean(r)

alltz[0].append(btz)
alltz[1].append(gtz)
alltz[2].append(rtz)

return alltz


def get_cossimi(x, y):
"""
get_cossimi
:param x:
:param y:
:return:
"""
myx = np.array(x)
myy = np.array(y)
cos1 = np.sum(myx * myy)
cos21 = np.sqrt(sum(myx * myx))
cos22 = np.sqrt(sum(myy * myy))
return cos1 / float(cos21 * cos22)


if __name__ == "__main__":
# 提取特征
train_x = []
d = []

for ii in xrange(1, pic_flag + 1):
smp_x = []
b_tz = np.array([0, 0, 0])
g_tz = np.array([0, 0, 0])
r_tz = np.array([0, 0, 0])
mytz = np.zeros((3, w_fg * h_fg))
for jj in xrange(1, 3):
fn = '/home/abc/Projects/machine_learning/img/base/p' + str(ii) + '-' + str(jj) + '.jpg'
print fn
tmptz = read_pic(fn)
mytz += np.array(tmptz)
mytz /= 3
train_x.append(mytz[0].tolist() + mytz[1].tolist() + mytz[2].tolist())

for index in xrange(1, 5):
fn = '/home/abc/Projects/machine_learning/img/base/test{}.jpg'.format(index)
testtz = np.array(read_pic(fn))
simtz = testtz[0].tolist() + testtz[1].tolist() + testtz[2].tolist()
maxtz = 0
nowi = 0

for i in xrange(pic_flag):
nowsim = get_cossimi(train_x[i], simtz)
if nowsim > maxtz:
maxtz = nowsim
nowi = i

print '%s属于第%d类' % (fn, nowi + 1)

http://www.cnblogs.com/chaosimple/archive/2013/06/28/3160839.html

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