I have the following code (which is in fact just 1 part of 4 needed to run all the project I am working on..):
#python classify.py --model models/svm.cpickle
Used this code to do the job. It detects region of text/digits in images.
import cv2
image = cv2.imread("C:\\Users\\Bob\\Desktop\\PyHw\\images\\test5.png")
gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY) # grayscale
_,thresh = cv2.threshold(gray,150,255,cv2.THRESH_BINARY_INV) # threshold
kernel = cv2.getStructuringElement(cv2.MORPH_CROSS,(3,3))
dilated = cv2.dilate(thresh,kernel,iterations = 13) # dilate
_, contours, hierarchy = cv2.findContours(dilated,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE) # get contours
idx =0
# for each contour found, draw a rectangle around it on original image
for contour in contours:
idx += 1
# get rectangle bounding contour
[x,y,w,h] = cv2.boundingRect(contour)
# discard areas that are too large
if h>300 and w>300:
continue
# discard areas that are too small
if h<40 or w<40:
continue
# draw rectangle around contour on original image
#cv2.rectangle(image,(x,y),(x+w,y+h),(255,0,255),2)
roi = image[y:y + h, x:x + w]
cv2.imwrite('C:\\Users\\Bob\\Desktop\\' + str(idx) + '.jpg', roi)
cv2.imshow('img',roi)
cv2.waitKey(0)
The code is based on this other question/answer: Extracting text OpenCV