匹配地理标记图像

学会SIFT之后，我们开始学习地理区域的匹配

首先，我在运行代码的时候，出现错误import pydot的错误
所以首先要配置环境。

第一步 安装graphviz

在vscode里使用终端，进入powershell，输入pip install graphviz
然后进入官网下载https://graphviz.gitlab.io/_pages/Download/Download_windows.html 下载graphviz的时候，一定要选择后缀是.msi的文件，然后安装在D盘。进入该文件夹的bin

复制路径
配置环境变量

第二步 安装pydot

在vscode终端的powershell中输入pip install pydot
接着在python的文件夹中搜索pydot.py文件，将其中的代码换成Graphviz中bin的路径复制到上去，例如：D:\pypackage\Graphviz-2.38\bin\dot.exe

然后保存即可

第三步 运行代码

根据代码

from pylab import *
from PIL import Image
from PCV.localdescriptors import sift
from PCV.tools import imtools
import pydot

""" This is the example graph illustration of matching images from Figure 2-10.
To download the images, see ch2_download_panoramio.py."""

#download_path = "panoimages"  # set this to the path where you downloaded the panoramio images
#path = "/FULLPATH/panoimages/"  # path to save thumbnails (pydot needs the full system path)

download_path = r"C:\Users\dell\Documents\VS_code workplace\SDL"  # set this to the path where you downloaded the panoramio images
path = r"C:\Users\dell\Documents\VS_code workplace\SDLsave"  # path to save thumbnails (pydot needs the full system path)

imlist = imtools.get_imlist(download_path)
nbr_images = len(imlist)

featlist = [imname[:-3] + 'sift' for imname in imlist]
for i, imname in enumerate(imlist):
    sift.process_image(imname, featlist[i])

matchscores = zeros((nbr_images, nbr_images))

for i in range(nbr_images):
    for j in range(i, nbr_images):  # only compute upper triangle
        print('comparing ', imlist[i], imlist[j])
        l1, d1 = sift.read_features_from_file(featlist[i])
        l2, d2 = sift.read_features_from_file(featlist[j])
        matches = sift.match_twosided(d1, d2)
        nbr_matches = sum(matches > 0)
        print('number of matches = ', nbr_matches)
        matchscores[i, j] = nbr_matches
print("The match scores is: \n", matchscores)
for i in range(nbr_images):
    for j in range(i + 1, nbr_images):  # no need to copy diagonal
        matchscores[j, i] = matchscores[i, j]

#可视化

threshold = 2  # min number of matches needed to create link

g = pydot.Dot(graph_type='graph')  # don't want the default directed graph

for i in range(nbr_images):
    for j in range(i + 1, nbr_images):
        if matchscores[i, j] > threshold:
            # first image in pair
            im = Image.open(imlist[i])
            im.thumbnail((100, 100))
            filename = path + str(i) + '.png'
            im.save(filename)  # need temporary files of the right size
            g.add_node(pydot.Node(str(i), fontcolor='transparent', shape='rectangle', image=filename))

            # second image in pair
            im = Image.open(imlist[j])
            im.thumbnail((100, 100))
            filename = path + str(j) + '.png'
            im.save(filename)  # need temporary files of the right size
            g.add_node(pydot.Node(str(j), fontcolor='transparent', shape='rectangle', image=filename))
            g.add_edge(pydot.Edge(str(i), str(j)))
g.write_png('jmu.png')

得到效果