照片上的數字辨識 Python3

woff · 發表於 2020-11-24 22:05:47

參考這個網址有人分享Python2照片上數字的辨識

數字辨識 Python

首先老男人用小畫家建立一張寫上數字０～９的圖片

圖片名稱number5.png

這張圖片是給Pythno的程式學習認字

程式是使用Python3與來源版本不同

有稍微修改

import sys
import numpy as np
import cv2
im = cv2.imread('1.jpg')
im3 = im.copy()
gray = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray,(5,5),0)
thresh = cv2.adaptiveThreshold(blur,255,1,1,11,2)
################# Now finding Contours ###################
contours,hierarchy = cv2.findContours(thresh,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)
samples = np.empty((0,100))
responses = []
keys = [i for i in range(48,58)]
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),(0,0,255),2)
roi = thresh[y:y+h,x:x+w]
roismall = cv2.resize(roi,(10,10))
cv2.imshow('norm',im)
key = cv2.waitKey(0)
if key == 27: # (escape to quit)
sys.exit()
elif key in keys:
responses.append(int(chr(key)))
sample = roismall.reshape((1,100))
samples = np.append(samples,sample,0)
responses = np.array(responses,np.float32)
responses = responses.reshape((responses.size,1))
print("training complete")
np.savetxt('generalsamples.data',samples)
np.savetxt('generalresponses.data',responses)

複製代碼

程式Run

指定number5.png這張圖學習

(數字的照片可自定,cv2.imread()這裡指定)

紅框在哪個字就按哪個字

一開始是0就按0

按之後紅框往左跳

數字辨識 Python

按一次跳一下

數字辨識 Python

全部按完

印字training complete

數字辨識 Python

產生下列兩個檔

generalsamples.data 與 generalresponses.data

學習資料與記錄放在裡面

學習完就可以開另一支程式做數字辨識

第二支程式追加辨識完的數字字串存入List，然後寫入記事本保存

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.ml.KNearest_create()
model.train(samples, cv2.ml.ROW_SAMPLE, responses)
############################# testing part #########################
im = cv2.imread('a.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)
contours,_ = cv2.findContours(thresh, cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE)
count=0
num_str = 10*['0']
for cnt in contours:
if cv2.contourArea(cnt)>50:
[x,y,w,h] = cv2.boundingRect(cnt)
if h>32:
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)
retval, results, neigh_resp, dists = model.findNearest(roismall, k = 1)
string = str(int((results[0][0])))
print(string)
num_str[count] = string
count += 1
cv2.putText(out,string,(x,y+h),0,1,(0,255,0))
number = map(int, num_str)
cv2.imshow('im',im)
cv2.imshow('out',out)
temp = []
for i in num_str:
temp.append(i)
temp.reverse()
temp_str = ''
num_data = temp_str.join(temp)
print(num_data)
file=open('data.txt','a')
file.write(num_data + ';');
file.close()
cv2.waitKey(0)