face recognition python

],k=2) X_matches=[1]*10X_matches[0]= Bf.knnmatch (des,x_des[0],k=2) x_matches[1]= Bf.knnmatch (des,x_des[1],k=2) x_matches[2]= Bf.knnmatch (des,x_des[2],k=2) x_matches[3]= Bf.knnmatch (des,x_des[3],k=2) x_matches[4]= Bf.knnmatch (des,x_des[4],k=2) T_matches=[1]*10T_matches[0]= Bf.knnmatch (des,t_des[0],k=2) t_matches[1]= Bf.knnmatch (des,t_des[1],k=2) t_matches[2]= Bf.knnmatch (des,t_des[2],k=2) t_matches[3]= Bf.knnmatch (des,t_des[3],k=2) t_matches[4]= Bf.knnmatch (des,t_des[4],k=2) Y_matches=[

, limit2, color): row_num, Col_num= Card_img_hsv.shape[:2] XL=Col_num XR=0 YH=0 yl=row_num Row_num_limit= 21Col_num_limit= Col_num * 0.8ifColor! ="Green" ElseCol_num * 0.5#Green with gradient forIinchRange (row_num): Count=0 forJinchRange (col_num): H=Card_img_hsv.item (i, J, 0) S= Card_img_hsv.item (I, J, 1) V= Card_img_hsv.item (I, J, 2) ifLimit1 and andV:count+ = 1ifCount >Col_num_limit:ifYL >I:yl=IifYH I:yh=I forJinchRange (col_num): Count=0 forIinchRange (row_num): H=Card_im

Python implements image slide verification and recognition methods, 1 abstract As a natural person robot identification tool, verification code is widely used in various scenarios that prevent programs from being automated. The security of traditional validation models has expired, and various new verification codes have sprung up. Currently, the most common form is the slide puzzle" 2 Content Overview Slid

This paper describes the implementation of KNN algorithm Python and the method of simple digital recognition. Share to everyone for your reference. Specific as follows: KNN algorithm algorithm Advantages and disadvantages: Advantages: High accuracy, insensitive to outliers, no input data assumptionsCons: Both time complexity and space complexity are highApplicable data range: Numerical and nominal type The

Python uses KNN for verification code recognition.Preface Previously, I made an APP for campus dating. One logic is to use the user's educational administration system to confirm that the user is a college student. The basic idea is to use the user's account and password, the crawler method is used to confirm the information, but many educational administration systems have verification codes. At that time, the verification code was downloaded through

Python character string recognition module chardet for simple application, pythonchardet Python string encoding recognition module (third-party library ): Official Address: http://pypi.python.org/pypi/chardet Import chardetimport urllib # You can select different data TestData = urllib as needed. urlopen ('HTTP: //

In fact, the identification of authentication code involves a lot of aspects of the content, start difficult, but after the start, can be extended and very wide, can play very strong, the sense of achievement is very sufficient, to this interested friends follow the small knitting together to learn. Depend on sudo apt-get install python-imaging sudo apt-get install TESSERACT-OCR pip install pytesseract Using Google OCR to identify the ve

application scenarios?Metaclass role? and application scenarios?69. Use as many methods as possible to implement the singleton mode.70. How to use the decorator and the application scenario.71. How to handle exception handling and how to proactively run out of exception (application scenario)72. What is object-oriented MROIsinstance role and application scenario?74. Write the code and implement:Given an array of integers, return indices of the both numbers such that they add-to a specific targe

Test s.test_iter.append (100)#10000/100 test iterations, need to iterate 100 times to complete the test of all data once s.max_iter = 9380#epochs, 938*10, maximum training times S.BASE_LR = 0.01#Basic Learning Rate S.momentum = 0.9#Momentum S.weight_decay = 5e-4#Weight decay term S.lr_policy =‘Step‘#Learning Rate Change Rule s.stepsize=3000#Learning Rate Change frequency S.gamma = 0.1#Learning Rate Change Index S.display = 20# screen display interval S.snapshot = 938 # Save Caffemodel interval

output in the format defined in our __str__ method, and the print output changes theBoth __repr__ and __str__ are for display, __str__ is user-oriented, and __repr__ is for programmers. The print operation will first attempt the __str__ and STR built-in functions (the internal equivalent form of the print run), which should normally return a friendly display. __REPR__ is used in all other environments: Prompt response in interactive mode and repr function, print and STR are used if

(Digits.data, - Digits.target, intest_size=0.25, -Random_state=33) to + " " - 3 recognition of digital images using support vector machine classification model the " " * #standardize training data and test data $SS =Standardscaler ()Panax NotoginsengX_train =ss.fit_transform (X_train) -X_test =ss.fit_transform (x_test) the + #Support Vector machine classifier for initializing linear hypothesis ALsvc =linearsvc () the #to train + Lsvc.fit (X_train,

You guys, Spider, may be crawling pages Verification Code I think I can help you find the one closest to "Killer level" in Python. Tools (Originated from Open Source , Do not dare to exclusive good things ). Call everyone's enthusiasm, Python package> pytesser |Http://code.google.com/p/pytesser/(In fact, the key to using the py package isInstall) 1. First install Pil: easy_install -- find-links

Reference: http://www.cnblogs.com/TTyb/p/5996847.html1, PIP3 install PYOCR2, PIP3 install pillow or easy_install pillow3, Installation tesseract-ocr:http://jaist.dl.sourceforge.net/project/tesseract-ocr-alt/ Tesseract-ocr-setup-3.02.02.exe, installed under C:\Program files\4. Python is required to be installed on C drive by default5. Find tesseract.py Change tesseract_cmd = ' C:/Program files/tesseract-ocr/tesseract.exe '# -*-coding:utf-8-*- from Imp

[Hardware Environment]WIN10 64-bit[Software Environment]Python version: 2.7.3Python Library:1.1) Pillow1.2) PytesseractOther:1.1) TESSERACT-OCR executable file[Construction process]TESSERACT-OCR:1. Install the TESSERACT-OCR executable file2. Installing the Pillow Library3. Installing the Pytesseract Library[Related code]#1.Install Tesseract-ocr*.exe from http://jaist.dl.sourceforge.net/project/tesseract-ocr-alt/ Tesseract-ocr-setup-3.02.02.exe#2.Insta

leave Python with a very important dynamic feature – dynamically created types. Originally, the Class (the second column of the classmate) in Python is an object (Typeobject), the object can be dynamically modified at runtime, so we can after you define a class to modify his behavior or properties! After taking out the first column, the second column becomes a pure type, written as what, and run-time behav

In the future, Ai occupies a heavy position in the market, Python language is the best programming language to study artificial intelligence, below, let us feel the charm of it! Baidu gives the sample program, whether C or Java version, are divided into method1 and method2 two kinds, the former is called implicit (post is the JSON string, audio data encoded into the JSON), The latter is called explicit (post is the audio data) This article mainly int

KNN algorithm python implementation and simple digital recognitionAdvantages and disadvantages of kNN algorithms: high accuracy, no sensitivity to abnormal values, and no input data assumption disadvantages: time complexity and space complexity are both high. applicable data range: Ideas of numeric and nominal algorithms: KNN algorithm (K-Nearest Neighbor Algorithm), the idea of the algorithm is very simple, simply put, it is a collection of things, t

Python + opencv for Dynamic Object Recognition, pythonopencv Note: This method is very affected by light changes. Figure of the result of your mobile phone shaking at home: Source code: #-*-Coding: UTF-8-*-"Created on Wed Sep 27 15:47:54 2017 @ author: tina" import cv2 import numpy as np camera = cv2.VideoCapture (0) # parameter 0 indicates the first camera # determine whether the video is enabled if (came

This article mainly introduces the Python Verification Code recognition tutorial using projection method, connected domain method segmentation picture, has a certain reference value, now share to everyone, there is a need for friends can refer to Objective Today this article mainly records how to slice the verification code, the main library used is pillow and Linux image processing Tools gimp. First, cons

/java/jre6/bin/server/jvm.dll","-ea", ("-djava.class.path=%s"% (Jarpath +"Javase-2.2.jar"+";"+ Jarpath +"Core-2.2.jar")))#Load the useful library classesFile = Jclass ("Java.io.File") BufferedImage= Jclass ("Java.awt.image.BufferedImage") ImageIO= Jclass ("Javax.imageio.ImageIO") Binarybitmap= Jclass ("Com.google.zxing.BinaryBitmap") Decodehinttype= Jclass ("Com.google.zxing.DecodeHintType") Luminancesource= Jclass ("Com.google.zxing.LuminanceSource") Bufferedimageluminancesource= Jclass ("Com.g