preprocess.py

# -*- coding: UTF-8 -*-
import glob as gb
import cv2
## 获取numbers文件夹下所有文件路径
img_path = gb.glob("numbers\\*")

k = 0
labels = []
samples =  []

## 对每一张图片进行处理
for path in img_path:
    img  = cv2.imread(path)       
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    blur = cv2.GaussianBlur(gray,(5,5),0)
    thresh = cv2.adaptiveThreshold(blur,255,1,1,11,2)      
    
    image, contours, hierarchy = cv2.findContours(thresh,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
    #cv2.drawContours(img,contours,-1,(0,0,255),3)  
    height,width = img.shape[:2]
    #w = width/5
    ## 图片第一行和第二行数字
    list1 = []
    list2 = []
    for cnt in contours:
        #if cv2.contourArea(cnt)>100:
        [x,y,w,h] = cv2.boundingRect(cnt)
      
        if w>30 and h > (height/4):  
            ## 按y坐标分行
            if y < (height/2):
                list1.append([x,y,w,h]) ## 第一行
            else:
                list2.append([x,y,w,h]) ## 第二行
            #rect_list.append([x,y,w,h])
            #cv2.rectangle(img,(x,y),(x+w,y+h),(0,0,255),2)
            #cv2.imshow("number",img)
            #cv2.waitKey(200)
    ## 按x坐标排序，上面已经按y坐标分行
    list1_sorted = sorted(list1,key = lambda t : t[0])
    list2_sorted = sorted(list2,key = lambda t : t[0])
    #print list1
    #print list1_sorted
    #print len(list1)
    
    for i in range(5):
        [x1,y1,w1,h1] = list1_sorted[i] 
        [x2,y2,w2,h2] = list2_sorted[i]
        ## 切割出每一个数字
        number_roi1 = gray[y1:y1+h1, x1:x1+w1] #Cut the frame to size
        number_roi2 = gray[y2:y2+h2, x2:x2+w2] #Cut the frame to size       
        
        #number_roi1 = thresh[y1:y1+h1, x1:x1+w1] #Cut the frame to size
        #number_roi2 = thresh[y2:y2+h2, x2:x2+w2] #Cut the frame to size
        ## 对图片进行大小统一和预处理
        resized_roi1=cv2.resize(number_roi1,(20,40))
        thresh1 = cv2.adaptiveThreshold(resized_roi1,255,1,1,11,2)
        
        resized_roi2=cv2.resize(number_roi2,(20,40))
        thresh2 = cv2.adaptiveThreshold(resized_roi2,255,1,1,11,2)
        
        ## 每一个数字存入对应数字的文件夹
        number_path1 = "number\\%s\\%d" % (str(i+1),k) + '.jpg'
        j = i+6
        if j ==10:
            j = 0
        number_path2 = "number\\%s\\%d" % (str(j),k) + '.jpg'
        k+=1
        
        ## 归一化
        normalized_roi1 = thresh1/255.
        normalized_roi2 = thresh2/255.
        #cv2.imwrite(number_path1,number_roi1)
        #cv2.imwrite(number_path2,number_roi2)
        
        ## 把图片展开成一行，然后保存到samples
        ## 保存一个图片信息，保存一个对应的标签
        sample1 = normalized_roi1.reshape((1,800))
        samples.append(sample1[0])
        labels.append(float(i+1))
        
        sample2 = normalized_roi2.reshape((1,800))
        samples.append(sample2[0])
        labels.append(float(j))
                
        cv2.imwrite(number_path1,thresh1)
        cv2.imwrite(number_path2,thresh2)
        cv2.imshow("number",normalized_roi1)
        cv2.waitKey(5)
#print sample1
## 这里才引入numpy是因为前面引入的话会自动把所有的list编程np.array
## 感觉array的append没有list的好用...        
import numpy as np

## 这里还是把它们保存成了np.array...
samples = np.array(samples,np.float32)
#samples = samples.reshape((samples.size,1))
labels = np.array(labels,np.float32)
labels = labels.reshape((labels.size,1))

np.save('samples.npy',samples)
np.save('label.npy',labels)
 
## 保存完加载一下试试
test = np.load('samples.npy')
label = np.load('label.npy')
print(test[0])
print(test[0].shape)
print('label: ', label[0])