I am interested in detecting lines (which I managed to figure out using hough transform) and the text above it.
The code I have written is below. ( I have edited so that I can loop through the coordinates of each line)
import cv2
import numpy as np
img=cv2.imread('test3.jpg')
#img=cv2.resize(img,(500,500))
imgGray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
imgEdges=cv2.Canny(imgGray,100,250)
imgLines= cv2.HoughLinesP(imgEdges,1,np.pi/180,230, minLineLength = 700, maxLineGap = 100)
imgLinesList= list(imgLines)
a,b,c=imgLines.shape
line_coords_list = []
for i in range(a):
line_coords_list.append([(int(imgLines[i][0][0]), int(imgLines[i][0][1])), (int(imgLines[i][0][2]), int(imgLines[i][0][3]))])
print(line_coords_list)#[[(85, 523), (964, 523)], [(85, 115), (964, 115)], [(85, 360), (964, 360)], [(85, 441), (964, 441)], [(85, 278), (964, 278)], [(85, 197), (964, 197)]]
roi= img[int(line_coords_list[0][0][1]): int(line_coords_list[0][1][1]), int(line_coords_list[0][0][0]) : int(line_coords_list[0][1][0])]
print(roi) # why does this print an empty list?
cv2.imshow('Roi NEW',roi)
Now I just don't know how to detect the region of interest above those lines. Is it possible to say crop out each line and have images say roi_1 , roi_2 , roi_n where each roi is the text above the first line, the text above the second line etc?
I would like the output to be something like this.
Here is one way to do that in Python/OpenCV.
Input:
import cv2
import numpy as np
# load image
img = cv2.imread("text_above_lines.jpg")
# convert to gray
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# threshold the grayscale image
thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]
# use morphology erode to blur horizontally
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (151, 3))
morph = cv2.morphologyEx(thresh, cv2.MORPH_DILATE, kernel)
# use morphology open to remove thin lines from dotted lines
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 17))
morph = cv2.morphologyEx(morph, cv2.MORPH_OPEN, kernel)
# find contours
cntrs = cv2.findContours(morph, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cntrs = cntrs[0] if len(cntrs) == 2 else cntrs[1]
# find the topmost box
ythresh = 1000000
for c in cntrs:
box = cv2.boundingRect(c)
x,y,w,h = box
if y < ythresh:
topbox = box
ythresh = y
# Draw contours excluding the topmost box
result = img.copy()
for c in cntrs:
box = cv2.boundingRect(c)
if box != topbox:
x,y,w,h = box
cv2.rectangle(result, (x, y), (x+w, y+h), (0, 0, 255), 2)
# write result to disk
cv2.imwrite("text_above_lines_threshold.png", thresh)
cv2.imwrite("text_above_lines_morph.png", morph)
cv2.imwrite("text_above_lines_lines.jpg", result)
#cv2.imshow("GRAY", gray)
cv2.imshow("THRESH", thresh)
cv2.imshow("MORPH", morph)
cv2.imshow("RESULT", result)
cv2.waitKey(0)
cv2.destroyAllWindows()
Thresholded image:
Morphology image:
Result: