Is there a simple way that I can do digit segmentation from files like in the screenshot below?
I want to use OpenCV to do it as it's the library I'm using to do the rest of processing but other suggestions are welcomed.
Is there a simple way that I can do digit segmentation from files like in the screenshot below?
I want to use OpenCV to do it as it's the library I'm using to do the rest of processing but other suggestions are welcomed.
Take this piece of code and adapt for your problem. It's not difficult with your situation:
import cv2
import numpy as np
# import image
image = cv2.imread('C:\\Users\\PC\\Desktop\\roi.png')
# grayscale
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
cv2.imshow('gray', gray)
# binary
ret, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY_INV)
cv2.imshow('threshold', thresh)
# dilation
kernel = np.ones((10, 1), np.uint8)
img_dilation = cv2.dilate(thresh, kernel, iterations=1)
cv2.imshow('dilated', img_dilation)
# find contours
# cv2.findCountours() function changed from OpenCV3 to OpenCV4: now it have only two parameters instead of 3
cv2MajorVersion = cv2.__version__.split(".")[0]
# check for contours on thresh
if int(cv2MajorVersion) >= 4:
ctrs, hier = cv2.findContours(img_dilation.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
else:
im2, ctrs, hier = cv2.findContours(img_dilation.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# sort contours
sorted_ctrs = sorted(ctrs, key=lambda ctr: cv2.boundingRect(ctr)[0])
for i, ctr in enumerate(sorted_ctrs):
# Get bounding box
x, y, w, h = cv2.boundingRect(ctr)
# Getting ROI
roi = image[y:y + h, x:x + w]
# show ROI
# cv2.imshow('segment no:'+str(i),roi)
cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)
if w > 15 and h > 15:
cv2.imwrite('C:\\Users\\PC\\Desktop\\output\\{}.png'.format(i), roi)
cv2.imshow('marked areas', image)
cv2.waitKey(0)
Source: https://lucians.dev/extract-roi-from-image-with-python-and-opencv