相关疑难解决方法(0)

我正在尝试更新我的代码以使用cv2.SURF()而不是cv2.FeatureDetector_create("SURF")和cv2.DescriptorExtractor_create("SURF").但是在检测到关键点后我无法获取描述符.什么是正确的打电话方式SURF.detect？

我试过跟随OpenCV文档,但我有点困惑.这就是它在文档中所说的内容.

Python: cv2.SURF.detect(img, mask) ? keypoints¶
Python: cv2.SURF.detect(img, mask[, descriptors[, useProvidedKeypoints]]) ? keypoints, descriptors

在进行第二次调用时如何传递关键点SURF.detect？

我的数据库(oracle 11g)中很少有blob被复制,使用UTL_RAW.BIT_XOR对blob执行XOR操作.之后我想计算二进制字符串中的设置位数,所以写了上面的代码.

在一个小实验中,我想看看生成的十六进制和整数值是什么,并编写了这个程序.

SQL> declare
2
3 vblob1 blob;
4
5 BEGIN
6
7 select leftiriscode INTO vblob1 FROM irisdata WHERE irisid=1;
8
9 dbms_output.put_line(rawtohex(vblob1));
10
11
12 dbms_output.put_line(UTL_RAW.CAST_TO_binary_integer(vblob1));
13
14
15 END;
16 /

输出:HEXVALUE:

0F0008020003030D030C1D1C3C383C330A3311373724764C54496C0A6B029B84840547A341BBA83D
BB5FB9DE4CDE5EFE96E1FC6169438344D604681D409F9F9F3BC07EE0C4E0C033A23B37791F59F84F
F94E4F664E3072B0229DA09D9F0F1FC600C2E380D6988C198B39517D157E7D66FE675237673D3D28
3A016C01411003343C76740F710F0F4F8FE976E1E882C186D316A63C0C7D7D7D7D397F016101B043
0176C37E767C7E0C7D010C8302C2D3E4F2ACE42F8D3F3F367A46F54285434ABB61BDB53CBF6C7CC0
F4C1C3F349B3F7BEB30E4A0CFE1C85180DC338C2C1C6E7A5CE3104303178724CCC5F451F573F3B24
7F24052000202003291F130F1B0E070C0E0D0F0E0F0B0B07070F1E1B330F27073F3F272E2F2F6F7B
2F2E1F2E4F7EFF7EDF3EBF253F3D2F39BF3D7F7FFED72FF39FE7773DBE9DBFBB3FE7A76E777DF55C
5F5F7ADF7FBD7F6AFE7B7D1FBE7F7F7DD7F63FBFBF2D3B7F7F5F2F7F3D7F7D3B3F3B7FFF4D676F7F
5D9FAD7DD17F7F6F6F0B6F7F3F767F1779364737370F7D3F5F377F2F3D3F7F1F2FE7709FB7BCB77B
0B77CF1DF5BF1F7F3D3E4E7F197F571F7D7E3F7F7F7D7F6F4F75FF6F7ECE2FFF793EFFEDB7BDDD1F
FF3BCE3F7F3FBF3D6C7FFF7F7F4FAF7F6FFFFF8D7777BF3AE30FAEEEEBCF5FEEFEE75FFEACFFDF0F
DFFFF77FFF677F4FFF7F7F1B5F1F5F146F1F1E1B3B1F3F273303170F370E250B

INTEGER VALUE: 15

十六进制代码和生成的整数值之间存在差异,因此使用以下python代码检查实际的整数值.

print int("0F0008020003030D030C1D1C3C383C330A3311373724764C54496C0A6B029B84840547A341BBA83D
BB5FB9DE4CDE5EFE96E1FC6169438344D604681D409F9F9F3BC07EE0C4E0C033A23B37791F59F84F
F94E4F664E3072B0229DA09D9F0F1FC600C2E380D6988C198B39517D157E7D66FE675237673D3D28
3A016C01411003343C76740F710F0F4F8FE976E1E882C186D316A63C0C7D7D7D7D397F016101B043
0176C37E767C7E0C7D010C8302C2D3E4F2ACE42F8D3F3F367A46F54285434ABB61BDB53CBF6C7CC0
F4C1C3F349B3F7BEB30E4A0CFE1C85180DC338C2C1C6E7A5CE3104303178724CCC5F451F573F3B24
7F24052000202003291F130F1B0E070C0E0D0F0E0F0B0B07070F1E1B330F27073F3F272E2F2F6F7B
2F2E1F2E4F7EFF7EDF3EBF253F3D2F39BF3D7F7FFED72FF39FE7773DBE9DBFBB3FE7A76E777DF55C
5F5F7ADF7FBD7F6AFE7B7D1FBE7F7F7DD7F63FBFBF2D3B7F7F5F2F7F3D7F7D3B3F3B7FFF4D676F7F
5D9FAD7DD17F7F6F6F0B6F7F3F767F1779364737370F7D3F5F377F2F3D3F7F1F2FE7709FB7BCB77B
0B77CF1DF5BF1F7F3D3E4E7F197F571F7D7E3F7F7F7D7F6F4F75FF6F7ECE2FFF793EFFEDB7BDDD1F
FF3BCE3F7F3FBF3D6C7FFF7F7F4FAF7F6FFFFF8D7777BF3AE30FAEEEEBCF5FEEFEE75FFEACFFDF0F
DFFFF77FFF677F4FFF7F7F1B5F1F5F146F1F1E1B3B1F3F273303170F370E250B",16)

回答:

611951595100708231079693644541095422704525056339295086455197024065285448917042457
942011979060274412229909425184116963447100932992139876977824261789243946528467423
887840013630358158845039770703659333212332565531927875442166643379024991542726916
563271158141698128396823655639931773363878078933197184072343959630467756337300811
165816534945075483141582643531294791665590339000206551162697220540050652439977992
246472159627917169957822698172925680112854091876671868161705785698942483896808137
210721991100755736178634253569843464062494863175653771387230991126430841565373390
924951878267929443498220727531299945275045612499928105876210478958806304156695438
684335624641395635997624911334453040399012259638042898470872203581555352191122920
004010193837249388365999010692555403377045768493630826307316376698443166439386014
145858084176544890282148970436631175577000673079418699845203671050174181808397880
048734270748095682582556024378558289251964544327507321930196203199459115159756564 …

我正在尝试从此URL执行代码.但是,我开始收到此错误:

des = np.array(des,np.float32).reshape((1,128))
ValueError: total size of new array must be unchanged

我没有做过任何重大改变.但我会粘贴我所做的:

import scipy as sp
import numpy as np
import cv2

# Load the images
img =cv2.imread("image1.png")

# Convert them to grayscale
imgg =cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

# SURF extraction
surf = cv2.FeatureDetector_create("SURF")
surfDescriptorExtractor = cv2.DescriptorExtractor_create("SURF")
kp = surf.detect(imgg)
kp, descritors = surfDescriptorExtractor.compute(imgg,kp)

# Setting up samples and responses for kNN
samples = np.array(descritors)
responses = np.arange(len(kp),dtype = np.float32)

# kNN training
knn = cv2.KNearest()
knn.train(samples,responses)

modelImages = …

这是我想要实现的效果 - 想象一下,用户提交一个图像,然后是一个python脚本,在每个JPEG/PNG中循环显示当前工作目录中的类似图像.

接近Google图片搜索的工作方式(当您提交图片并返回类似图片时).我应该使用PIL还是OpenCV？

顺便说一句,最好使用Python3.4,但Python 2.7很好.

威尔逊