Reading 7 segment digits of weighing controller
Question:
i am trying to read the 7-segment display of a industrial weighing machine. as there is no serial out port for the machine i have to note down the weight manually. the idea is to use python-computer vision to capture the weight and store it in text file. the image is as shown 
.
i have used the following python code for this purpose.
the code runs fine till i am converting the image to gray. the converted image is 
. the problem starts when i start applying the threshold to the image. after applying the threshold the image is as shown 
any suggestions so as to how i should proceed.
Answers:
Something like this, using just OpenCV and Pytesseract, seems to work okay:
import cv2
import pytesseract
img = cv2.imread("Cf8ko.jpg")
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
thres = img.max() * 0.9 # 90% of the maximum brightness
img[img < thres] = 0 # set all pixels below threshold to black
img[img >= thres] = 255 # set all pixels above threshold to white
img = cv2.bitwise_not(img) # invert to black text on white background
text = pytesseract.image_to_string(img, lang="eng")
print(text)
This prints out
9830
and the processed image looks like
– depending on the quality of your images, you may want to run a blur/dilate/… or adjust the Empirical Stetson-Harrison value 0.9.
i am trying to read the 7-segment display of a industrial weighing machine. as there is no serial out port for the machine i have to note down the weight manually. the idea is to use python-computer vision to capture the weight and store it in text file. the image is as shown .
i have used the following python code for this purpose.
the code runs fine till i am converting the image to gray. the converted image is . the problem starts when i start applying the threshold to the image. after applying the threshold the image is as shown any suggestions so as to how i should proceed.
Something like this, using just OpenCV and Pytesseract, seems to work okay:
import cv2
import pytesseract
img = cv2.imread("Cf8ko.jpg")
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
thres = img.max() * 0.9 # 90% of the maximum brightness
img[img < thres] = 0 # set all pixels below threshold to black
img[img >= thres] = 255 # set all pixels above threshold to white
img = cv2.bitwise_not(img) # invert to black text on white background
text = pytesseract.image_to_string(img, lang="eng")
print(text)
This prints out
9830
and the processed image looks like
– depending on the quality of your images, you may want to run a blur/dilate/… or adjust the Empirical Stetson-Harrison value 0.9.