Python图像过滤器-TypeError:';非类型';对象不可下标
我尝试用python、opencv、skimage等在图像上设置不同的过滤器。这个操作将帮助我进行神经训练。但我现在发现我的过滤代码有问题Python图像过滤器-TypeError:';非类型';对象不可下标,python,opencv,filter,scikit-image,nonetype,Python,Opencv,Filter,Scikit Image,Nonetype,我尝试用python、opencv、skimage等在图像上设置不同的过滤器。这个操作将帮助我进行神经训练。但我现在发现我的过滤代码有问题 import numpy as np import os import skimage.io as io import matplotlib.pyplot as plt from PIL import ImageFilter from skimage.util import random_noise from skimage.transform import
import numpy as np
import os
import skimage.io as io
import matplotlib.pyplot as plt
from PIL import ImageFilter
from skimage.util import random_noise
from skimage.transform import rotate, AffineTransform, warp
from skimage.filters import gaussian
import shutil
from PIL import Image
import warnings
import time
import os.path
warnings.filterwarnings('ignore')
print("hello") # Affiche "hello"
# Localisation du dossier source
source_images = ''
# Localisation du dossier destination
desti = ''
source_labels = ''
#filtre mexican_hat (find edges)/ Affiche un filtre sombre et fais ressortir les contours de l'objet sur l'integralité de l'image
def Mexican(img): #fonction Mexican
filter = np.array([[0,0,-1,0,0],[0,-1,-2,-1,0],[-1,-2,16,-2,-1],[0,-1,-2,-1,0],[0,0,-1,0,0]])
mexican_hat_img1=cv2.filter2D(img,-1,filter) #paramètres du filtre
return mexican_hat_img1 #renvoi de l'image filtrée
#filtre couleur (0=Blue,1=Green,2=Red)/ Affiche du Rouge, du Bleu ou du Vert sur l'integralité de l'image
def exponential_function(channel, exp):
channel_color =channel
table = np.array([min((i**exp), 255) for i in np.arange(0, 256)]).astype("uint8") # creating table for exponent
channel_color = cv2.LUT(channel_color, table)
return channel_color
def tone(img, number): #fonction Blue/Green/Red
img_color = img
for i in range(3):
if i == number:
img_color[:, :, i] = exponential_function(img_color[:, :, i], 1.10) # applying exponential function on slice
else:
img_color[:, :, i] = 0 # setting values of all other slices to 0 to blue 1to green 2to red
return img_color
def desti_labels():
count=1
for filename in sorted(os.listdir(source_labels)):
param0 = str(count) + "Blur" + '.txt'
param1 = str(count) + "Noise" + '.txt'
param2 = str(count) + "Sharpen" + '.txt'
param3 = str(count) + "Blue" + '.txt'
param4 =str(count) + "Green" + '.txt'
param5 =str(count) + "Red" + '.txt'
param6 =str(count) + "Sepia" + '.txt'
param7 =str(count) + "Mexican" + '.txt'
param8 =str(count) + '.txt'
src ="/home/melanie/Desktop/test-filtre/crease/final-crease"+filename
#dst0 ="/Desktop/Quality_Inspection/Defects_location_for_metal_surface/Classe 1 crease/test-augmentor"+param0
#dst1 ="/Desktop/Quality_Inspection/Defects_location_for_metal_surface/Classe 1 crease/test-augmentor"+param1
#dst2 ="/home/alternant2/augment_env_TP_folder/Test_data100/Final/"+param2
dst3 ="/home/melanie/Desktop/test-filtre/crease/final-crease"+param3
dst4 ="/home/melanie/Desktop/test-filtre/crease/final-crease"+param4
dst5 ="/home/melanie/Desktop/test-filtre/crease/final-crease"+param5
#dst6 ="/Desktop/Quality_Inspection/Defects_location_for_metal_surface/Classe 1 crease/test-augmentor"+param6
dst7 ="/home/melanie/Desktop/test-filtre/crease/final-crease"+param7
dst8 ="/home/melanie/Desktop/test-filtre/crease/final-crease"+param8
shutil.copyfile(src,dst3)
shutil.copyfile(src,dst4)
shutil.copyfile(src,dst5)
shutil.copyfile(src,dst7)
shutil.copyfile(src,dst8)
count+=1
print("count", count)
return
lst_img=os.listdir(source_images)
print(lst_img)
def dest_images():
count_img=1
for filename in sorted(lst_img): #Pour tous les fichiers dans source
img=cv2.imread(source_images+filename) #choix du fichier
print(type(img)) #Affiche le type de l'image(dans notre cas ndarray)
img=cv2.imread(source_images+filename) #choix du fichier
img_blue = tone(img,0) #appel fonction Blue
img=cv2.imread(source_images+filename) #choix du fichier
img_green =tone(img,1) #appel fonction Green
img=cv2.imread(source_images+filename) #choix du fichier
img_red = tone(img,2) #appel fonction Red
img=cv2.imread(source_images+filename) #choix du fichier
img_mexican = Mexican(img) #appel fonction Mexican
#CONFIG 1
new_filename=str(count_img) # Remove the 4 last character ==> .PNG i.e.
print("A few moments later...") # Afficher "A few moments later..."
time.sleep(3) # Delai d'attente
cv2.imwrite(new_filename+'Blue.JPG',img_blue) #Enregistre le filtre Blue
cv2.imwrite(new_filename+'Green.JPG',img_green) #Enregistre le filtre Green
cv2.imwrite(new_filename+'Red.JPG',img_red) #Enregistre le filtre Red
cv2.imwrite(new_filename+'Mexican.JPG',img_mexican) #Enregistre le filtre Mexican
cv2.imwrite(new_filename+'.JPG',img)
count_img+=1 #Enregistre l'image originale
return
os.chdir(desti) # "Dans le fichier appelé desti"
dest_images()
desti_labels()
运行此代码时,我在终端上看到以下错误:
hello
['final-crease', 'img_01_425382900_00002.jpg']
<class 'NoneType'>
Traceback (most recent call last):
File "/home/melanie/Desktop/test-de-merde-3.py", line 115, in <module>
dest_images()
File "/home/melanie/Desktop/test-de-merde-3.py", line 88, in dest_images
img_blue = tone(img,0) #appel fonction Blue
File "/home/melanie/Desktop/test-de-merde-3.py", line 42, in tone
img_color[:, :, i] = exponential_function(img_color[:, :, i], 1.10) # applying exponential function on slice
TypeError: 'NoneType' object is not subscriptable
你好
['final-crease','img_01_425382900_00002.jpg']
回溯(最近一次呼叫最后一次):
文件“/home/melanie/Desktop/test-de-merde-3.py”,第115行,在
dest_图像()
文件“/home/melanie/Desktop/test-de-merde-3.py”,第88行,在dest_图像中
img_蓝色=色调(img,0)#外观蓝色
文件“/home/melanie/Desktop/test-de-merde-3.py”,第42行,音调
img_color[:,:,i]=指数函数(img_color[:,:,i],1.10)#在切片上应用指数函数
TypeError:“非类型”对象不可下标
我得走了,我真的不知道该怎么办。不幸的是,我没有找到解决办法。如果你有主意,我想:)print(type(img))
行img=cv2.imread(source\u images+filename)
找不到文件,因此不返回任何文件。当您尝试在第42行上建立索引时,会出现错误,因为您无法对任何内容进行切片
--尝试img=cv2.imread(source_images+“/”+文件名)
更改目录--
如果
source\u images=0
我尝试了您的解决方案,但问题仍然是FinalCrease
图像?FinalCrease是一个包含图像的文件夹。
print(type(img))
<class 'NoneType'>