CPM项目处理数据代码

记录项目中用写的小代码，并未优化，只是简单的完成功能。

crop 2448*560

import cv2
import numpy as np
from skimage import io
import os
save_id = 0

ori_image_folder = "E:/ATL350test/"
crop_image_folder = "E:/ATL350_croptest/"

def Image_Crop(image):
   global save_id
   gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
   gray[1420:, :] = 0;
   prob = np.zeros((1, gray.shape[0]), dtype=np.float32)
   print(prob.shape)

#    flag = np.sum(gray[:,0:2448])/(560*2448)
#    print(flag)
#    print("~~~~~~~~~~~~~")
#    print(type(flag))
#    if(flag<40):
#        continue
#    else:
   prob = np.sum(gray[:,0:2448], axis=1) / np.sum(gray[:,0:2448])
   print(prob.shape)
   print(np.sum(prob))
   expect = np.sum(np.multiply(range(gray.shape[0]), prob))
   print(expect)
   image_save_gray = gray[int(expect - crop_weight // 2):int(expect + crop_weight // 2),:]


   image_save = cv2.cvtColor(image_save_gray, cv2.COLOR_GRAY2BGR)
   # print(save_id)
   if save_id < 10:
       io.imsave(crop_image_folder + '0000' + str(save_id) + '.bmp', image_save)
   elif save_id < 100:
       io.imsave(crop_image_folder + '000' + str(save_id) + '.bmp', image_save)
   elif save_id < 1000:
       io.imsave(crop_image_folder + '00' + str(save_id) + '.bmp', image_save)
   elif save_id < 10000:
       io.imsave(crop_image_folder + '0' + str(save_id) + '.bmp', image_save)
   elif save_id < 100000:
       io.imsave(crop_image_folder + str(save_id) + '.bmp', image_save)
   save_id = save_id+1

for file in os.listdir(ori_image_folder):
   print(file)
   nw = "E:/ATL350/"+file+"/"
   print(nw)

   for filename in os.listdir(nw):
       print(filename)
       image = cv2.imread(nw + filename)
       Image_Crop(image)

crop 560*560

# ps:感谢hby师弟
import cv2
import numpy as np
from  skimage import io
import os

############ H W C
crop_height = 560
crop_weight = 560
crop_overlap = 25

save_id = 0

ori_image_folder = "E:/ATL350/"
crop_image_folder = "E:/ATL350_crop/"

def Image_Crop(image):
   global save_id
   gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
   gray[1420:, :] = 0;
   prob = np.zeros((1, gray.shape[0]), dtype=np.float32)
   print(prob.shape)
   for height in range(gray.shape[1]//crop_height + 1):
       if height == 0:
           flag = np.sum(gray[:,height*crop_height:(height+1)*crop_height])/(560*560)
           print(flag)
           print("~~~~~~~~~~~~~")
           print(type(flag))
           if(flag<40):
               continue
           else:
               prob = np.sum(gray[:,height*crop_height:(height+1)*crop_height], axis=1) / np.sum(gray[:,height*crop_height:(height+1)*crop_height])
               print(prob.shape)
               print(np.sum(prob))
               expect = np.sum(np.multiply(range(gray.shape[0]), prob))
               print(expect)
               image_save_gray = gray[int(expect - crop_weight // 2):int(expect + crop_weight // 2),
                                 height * crop_height:(height + 1) * crop_height]
       elif height == gray.shape[1]//crop_height:
           #prob = np.sum(gray[gray.shape[1]-crop_height-1:gray.shape[0]-1, :], axis=0) / np.sum(gray[gray.shape[1]-crop_height-1:gray.shape[1]-1, :])
           flag1=np.sum(gray[:,gray.shape[1]-crop_height-1:gray.shape[1]-1])/(560*560)
           print(flag1)
           print("~~~~~~~~~~~~~")
           if(flag1<40):
               continue
           else:
               prob = np.sum(gray[:,gray.shape[1]-crop_height-1:gray.shape[1]-1], axis=1) / np.sum(gray[:,gray.shape[1]-crop_height-1:gray.shape[1]-1])
               print(prob.shape)
               expect = np.sum(np.multiply(range(gray.shape[0]), prob))
               image_save_gray = gray[
                                 int(expect - crop_weight // 2):int(expect + crop_weight // 2),gray.shape[1]-crop_height-1:gray.shape[1]-1]
       else:
           flag2 = np.sum(gray[:,height*crop_height-crop_overlap:(height+1)*crop_height-crop_overlap])/(560*560)
           print(flag2)
           print("~~~~~~~~~~~~~")
           if(flag2<40):
               continue
           else:
               prob = np.sum(gray[:,height*crop_height-crop_overlap:(height+1)*crop_height-crop_overlap], axis=1) / np.sum(gray[:,height*crop_height:(height+1)*crop_height])
               expect = np.sum(np.multiply(range(gray.shape[0]), prob))
               image_save_gray = gray[
                                 int(expect - crop_weight // 2):int(expect + crop_weight // 2),height * crop_height:(height + 1) * crop_height]

       image_save = cv2.cvtColor(image_save_gray, cv2.COLOR_GRAY2BGR)
       # print(save_id)
       if save_id < 10:
           io.imsave(crop_image_folder + '0000' + str(save_id) + '.bmp', image_save)
       elif save_id < 100:
           io.imsave(crop_image_folder + '000' + str(save_id) + '.bmp', image_save)
       elif save_id < 1000:
           io.imsave(crop_image_folder + '00' + str(save_id) + '.bmp', image_save)
       elif save_id < 10000:
           io.imsave(crop_image_folder + '0' + str(save_id) + '.bmp', image_save)
       elif save_id < 100000:
           io.imsave(crop_image_folder + str(save_id) + '.bmp', image_save)
       save_id = save_id+1

for file in os.listdir(ori_image_folder):
   print(file)
   nw = "E:/ATL350/"+file+"/"
   print(nw)

   for filename in os.listdir(nw):
       print(filename)
       image = cv2.imread(nw + filename)
       Image_Crop(image)

2448中间切割

import cv2
import numpy as np
import os
save_id = 0
img_path = 'F:\\cpmdata\\ATL350_croptest\\'

def dev(img_path,name):
    img = cv2.imread(img_path)
    cl = np.zeros([560,1224,3])
    cr = np.zeros([560,1224,3])
    cl = img[:,0:1224]
    cr = img[:,1224:2448]


    cv2.imwrite('F:\\cpmdata\\1224_560\\'+name.split('.')[0]+'L.bmp',cl)
    cv2.imwrite('F:\\cpmdata\\1224_560\\'+name.split('.')[0]+'R.bmp',cr)

if __name__ == '__main__':
    for root,dirs,files in os.walk(img_path):
        print(root)
        for name in files:
            print(os.path.join(root,name))
            dev(os.path.join(root,name),name)

标注文件 坐标反算

import os
def wtxt(rtxt,ltxt):
    rtxt ='F:\\txttest\\annotation\\'+rtxt
    ltxt = 'F:\\txttest\\annotation\\'+ltxt
    input_file = open(rtxt, 'r+')
    f_new = open(ltxt, 'a')


    for line in input_file:
        line1 = line.strip()
        line1 = line.split(' ')
        line2 = line1


        if(int(line1[-4])==0):
            s = str(int(line1[1])+1224)
            line2[1] = str(s)
            print(line2)
            tems=' '
            tema = tems.join(line2)

            #tema = tema.replace(line1[1], s)
            #f_new.write('\n')
            f_new.write(tema)
        if (int(line1[-4]) == 1):

            tem = int(line1.index(line1[-3]))
            for i in range(1, tem - 1, 2):

                s = str(int(line1[i]) + 1224)
                line2[i] = str(s)
            tems = ' '
            tema = tems.join(line2)


            f_new.write(tema)
    input_file.close()
    f_new.close()
img_path= 'F:\\txttest\\annotation'
L = []
R = []
for root,dirs,files in os.walk(img_path):
    for i in range(0,len(files),2):
        L.append(files[i])
    for i in range(1,len(files),2):
        R.append(files[i])
for i in range(len(L)):
    wtxt(R[i],L[i])

copy rename files

import shutil
import os

#img_path= 'F:\\txttest\\annotation'
img_path1= 'F:\\txttest\\2448annotation'
des_path = 'F:\\txttest\\2448data'
L=[]
# '''rename'''
# for root,dirs,files in os.walk(img_path1):
#     for file in files:
#         os.rename(os.path.join(root,file),os.path.join(root,file.split('L')[0]+file.split('L')[1]))
# '''movefile'''
# for root,dirs,files in os.walk(img_path1):
#     for i in range(0,len(files),2):
#         shutil.copy(img_path+'\\'+files[i],'F:\\txttest\\2448annotation')

for root,dirs,files in os.walk(img_path1):
    for i in files:
        print('F:\\cpmdata\\ATL350_2448\\'+i.split('.')[0]+'.bmp')
        shutil.copy('F:\\cpmdata\\ATL350_2448\\'+i.split('.')[0]+'.bmp','F:\\txttest\\2448data')