简单数字识别中的OpenCV Python错误

简单数字识别中的OpenCV Python错误,python,opencv,ocr,Python,Opencv,Ocr,我将此python代码与Opencv一起用于字符识别,但在运行代码时出现此错误 AttributeError:“模块”对象没有属性“KNearest” 由于新OpenCV的版本需要更换 import cv2 import numpy as np ####### training part ############### samples = np.loadtxt('generalsamples.data',np.float32) responses = np.loadtxt('gener

我将此python代码与
Opencv
一起用于字符识别,但在运行代码时出现此错误

AttributeError:“模块”对象没有属性“KNearest”


由于新OpenCV的版本需要更换

import cv2
import numpy as np
#######   training part    ###############
samples = np.loadtxt('generalsamples.data',np.float32)
responses = np.loadtxt('generalresponses.data',np.float32)
responses = responses.reshape((responses.size,1))
model = cv2.KNearest()
model.train(samples,responses)
############################# testing part  #########################
im = cv2.imread('/home/manoj/Pictures/Untitled-1.jpg')
out = np.zeros(im.shape,np.uint8)
gray = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
thresh = cv2.adaptiveThreshold(gray,255,1,1,11,2)
contours,hierarchy = cv2.findContours(thresh,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)
for cnt in contours:
    if cv2.contourArea(cnt)>50:
        [x,y,w,h] = cv2.boundingRect(cnt)
        if  h>28:
            cv2.rectangle(im,(x,y),(x+w,y+h),(0,255,0),2)
            roi = thresh[y:y+h,x:x+w]
            roismall = cv2.resize(roi,(10,10))
            roismall = roismall.reshape((1,100))
            roismall = np.float32(roismall)
            retval, results, neigh_resp, dists = model.find_nearest(roismall, k = 1)
            string = str(int((results[0][0])))
            cv2.putText(out,string,(x,y+h),0,1,(0,255,0))
cv2.imshow('im',im)
cv2.imshow('out',out)
cv2.waitKey(0)
作者:

此外,该行:

model = cv2.ml.KNearest_create()
也将引发错误,这将修复它:

model.train(samples,responses)

希望这会有所帮助。

因为您需要更换新的OpenCV版本

import cv2
import numpy as np
#######   training part    ###############
samples = np.loadtxt('generalsamples.data',np.float32)
responses = np.loadtxt('generalresponses.data',np.float32)
responses = responses.reshape((responses.size,1))
model = cv2.KNearest()
model.train(samples,responses)
############################# testing part  #########################
im = cv2.imread('/home/manoj/Pictures/Untitled-1.jpg')
out = np.zeros(im.shape,np.uint8)
gray = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
thresh = cv2.adaptiveThreshold(gray,255,1,1,11,2)
contours,hierarchy = cv2.findContours(thresh,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)
for cnt in contours:
    if cv2.contourArea(cnt)>50:
        [x,y,w,h] = cv2.boundingRect(cnt)
        if  h>28:
            cv2.rectangle(im,(x,y),(x+w,y+h),(0,255,0),2)
            roi = thresh[y:y+h,x:x+w]
            roismall = cv2.resize(roi,(10,10))
            roismall = roismall.reshape((1,100))
            roismall = np.float32(roismall)
            retval, results, neigh_resp, dists = model.find_nearest(roismall, k = 1)
            string = str(int((results[0][0])))
            cv2.putText(out,string,(x,y+h),0,1,(0,255,0))
cv2.imshow('im',im)
cv2.imshow('out',out)
cv2.waitKey(0)
作者:

此外,该行:

model = cv2.ml.KNearest_create()
也将引发错误,这将修复它:

model.train(samples,responses)
希望这会有所帮助