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Problem to recognize characters in Pytesseract python

I'm woorking with this kind of image Original_Image and I'm having some problems to apply character recognition. I'm tried some image treatment (gray, black and white, noise removal,..) and got only bad results. This is a part of the code I'm work in Python.
import cv2
from matplotlib import pyplot as plt
import pytesseract
pytesseract.pytesseract.tesseract_cmd = r"C:\Users\14231744700\AppData\Local\Tesseract-OCR\tesseract.exe"
image_file = '5295_down.bmp'
img = cv2.imread(image_file)
height,width,channels= img.shape
#The attached image is this one (img_cropped) and I want this data as a string to work on it
img_cropped = img[41*height//50:92*height//100,2*width//14:81*width//100]
#cv2.imshow('Image_cropped', img_cropped)
#cv2.imwrite('image_cropped.png', img_cropped)
#cv2.waitKey(0)
def image_to_string(image):
data = pytesseract.image_to_string(image, lang='eng', config='--psm 6')
return data
image_to_string(img_cropped)
If someone know about a preprocessing step or any other possibility to get better results, I'll be very thankfull.

Using Tesseract-OCR in Python to get number from images

I have thousands of scale images that I would like to extract the reading of the scale from each image. However, when using the Tesseract it gives wrong values. I tried several process for the image but still running to same issue. From my understanding so far after defining region of interest in the image, it has to be converted to white text with black background. However, I am new to python, I tried some functions to do so but still running to same issue. Would be appreciated if someone can help me on this one. The following link is for the image, as I couldn't uploaded it here as it is more than 2 MiB:
https://mega.nz/file/fZMUDRbL#tg4Tc2VmGMMdEpnZzt7blxZjVLdlhMci9jll0FLnIGI
import cv2
import pytesseract
import matplotlib.pyplot as plt
import numpy as np
import imutils
## Reading Image File
Filename = 'C:\\Users\\Abdullah\\Desktop\\Scale Reading\\' #File Path For Images
IName = 'Disk_Test_1_09_07-00000_0.tif' # Image Name
Image = cv2.imread(Filename + IName,0)
## Image Processing
Image_Crop = Image[1680:1890, 550:1240] # Define Region of Interest of the image
#cv2.imshow("cropped", Image_Crop) # Show Cropped Image
#cv2.waitKey(0) # Show Cropped Image
Mask = Image_Crop > 10 # Thershold Image to Value of X
Mask = np.array(Mask, dtype=np.uint8)
plt.imshow(Mask, alpha=1) # Set Opacity (Max 1)
ret,Binary = cv2.threshold(Mask,0,255,cv2.THRESH_BINARY)
#plt.imshow(Image_Crop, cmap="gray") # Transform Image to Gray
#plt.show()
plt.imshow(Binary,'gray',vmin=0,vmax=255)
plt.show()
## Number Recognition
pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe' # Call Location of Tesseract-OCR
data = pytesseract.image_to_string(Binary, lang='eng',config='--psm 6')
print(data)
Here is the image after processing

pytesseract.image_to_string doesn't seem to be able to extract text from the image

I am trying to extract text from the image, however, with the following code that I have tried on other images, it works but not on this image. Is there an issue with the code?
Image trying extract text from:
Here is the code:
import cv2
import pytesseract
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
try:
from PIL import Image
except ImportError:
import Image
# Import image, convert,resize and noise removal
img = cv2.imread("sample01.png", cv2.IMREAD_GRAYSCALE)
print('Dimension of image: {}'.format(img.ndim))
img = cv2.resize(img, None, fx=2, fy=2)
blur = cv2.GaussianBlur(img, (5, 5), 0)
# Apply adaptiveThreshold (Mean)
th2 = cv2.adaptiveThreshold(blur, 255, cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY, 11, 2)
cv2.imwrite('resize_adaptive_threshmean.png', th2)
# Apply Tesseract to detect words
print(pytesseract.image_to_string(Image.open('resize_adaptive_threshmean.png')))
print("=========================================================")
Is there anything wrong with the code?

Well, you can use adaptive-thresholding
import cv2
import numpy as np
import pytesseract
img = cv2.imread("ACtBA.png")
gry = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
flt = cv2.adaptiveThreshold(gry,
100, cv2.ADAPTIVE_THRESH_MEAN_C,
cv2.THRESH_BINARY, 15, 16)
txt = pytesseract.image_to_string(flt)
print(txt)
The image will be:
Result:
Parking: You may park anywhere on the campus where there are no signs prohibiting par-
king. Keep in mind the carpool hours and park accordingly so you do not get blocked in the
afternoon
Under Schoo! Age Children.While we love the younger children, it can be disruptive and
inappropriate to have them on campus during school hours. There may be special times
that they may be invited or can accompany a parent volunteer, but otherwise we ask that
you adhere to our —_ policy for the benefit of the students and staff.
I test with different parameters, so I think the most suitable parameters are:
maxValue = 100 # Display pixels greater than maxValue
blockSize=15. # size of neighbourhood area.
C=16 # just a constant which is subtracted from the mean or weighted mean calculated.

import cv2
import pytesseract
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
try:
from PIL import Image
except ImportError:
import Image
data = pytesseract.image_to_string(Image.open("sample01.png"))
print(data)
?

im7 image files to openCV

Able to show the image through matplotlib, however unable to do it through cv2.imshow. The shape of the image is not consistent with opencv required formats. Require help on changing on changing it so it can be shown by the command cv2.imshow
test.jpg is a random jpg file from web
import numpy as np
import cv2
import matplotlib.pyplot as plt
import ReadIM
img = cv2.imread('test.jpg')
vbuff, vatts = ReadIM.extra.get_Buffer_andAttributeList('test.im7')
v_array, vbuff = ReadIM.extra.buffer_as_array(vbuff)
print (np.shape(v_array))
print (v_array[0])
print (np.shape(img))
# Showing image through matplotlib
plt.imshow(v_array[0])
plt.show()
#Showing image through cv2
cv2.imshow('image',v_array[0])
cv2.waitKey(0)
cv2.destroyAllWindows()
# Remove memory
#del(vbuff)
ReadIM.DestroyBuffer(vbuff)
ReadIM.DestroyAttributeListSafe(vatts)
test.im7

Normalizing the image to (0,255) will do the trick
img = cv2.normalize(img, None, 255,0,cv2.NORM_MINMAX,dtype = cv2.CV_8UC1)
cv2.imshow('image',img)

cv2 treshold does not work correctly on second image

I am new to python and I was playing around with background subtraction to visualize changes in pre and post change images.
I wrote a short and simple script using the cv2 library:
#!/usr/bin/env python
import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt
#GRAYSCALE ONLY FOR TESTING
#Test with person appearing in image
img1 = cv.imread("images/1.jpg", 0)
img2 = cv.imread("images/2.jpg", 0)
img3 = cv.subtract(img1, img2)
ret,thresh1 = cv.threshold(img3,90,255,cv.THRESH_BINARY)
#Test with satelite image of japan landslide changes after earthquake
jl_before = cv.imread("images/japan_earthquake_before.jpg",0)
jl_after = cv.imread("images/japan_earthquake_after.jpg",0)
jl_subtraction = cv.subtract(jl_before, jl_after)
ret,thresh2 = cv.threshold(img3,20,255,cv.THRESH_BINARY)
images = [img1, img2, thresh1, jl_before, jl_after, thresh2]
titles = ["Image1", "Image2", "Changes", "Japan_Before", "Japan_After", "Japan_Changes" ]
for i in range(6):
plt.subplot(2,3,i+1),plt.imshow(images[i],'gray')
plt.title(titles[i])
plt.xticks([]),plt.yticks([])
plt.show()
The result looks like this:
Why is the mask with changes from the first set of images present in the mask of the second set of images?
I used different variables, thresh1 and thresh2.
Any help would be greatly appreciated as I can't seem to find the problem.

Because you missed a change when copy pasting:
ret,thresh2 = cv.threshold(img3,20,255,cv.THRESH_BINARY)
^^^^