sreekiranar / box_detection_opencv Goto Github PK

How we identify that check boz is checked or not .

hi,
I want to read a tambola ticket

I tried to use your code as follows
Saved above image as digital.jpg
Then ran

[code]
import os
import cv2
import numpy as np
import matplotlib.pyplot as plt
image_path='digital.jpg'
plot_flag=True
save_output=True
out_folder='outs'
os.makedirs(out_folder,exist_ok=True)
image=cv2.imread(image_path)
gray_scale=cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
th1,img_bin = cv2.threshold(gray_scale,150,225,cv2.THRESH_BINARY)
img_bin=~img_bin
cv2.imwrite(os.path.join(out_folder,f'bin_{image_path}'),img_bin)
line_min_width = 15
kernal_h = np.ones((1,line_min_width), np.uint8)
kernal_v = np.ones((line_min_width,1), np.uint8)
img_bin_h = cv2.morphologyEx(img_bin, cv2.MORPH_OPEN, kernal_h)
cv2.imwrite(os.path.join(out_folder,f'hor_{image_path}'),img_bin_h)
img_bin_v = cv2.morphologyEx(img_bin, cv2.MORPH_OPEN, kernal_v)
cv2.imwrite(os.path.join(out_folder,f'ver_{image_path}'),img_bin_v)
img_bin_final=img_bin_h|img_bin_v
cv2.imwrite(os.path.join(out_folder,f'merge_{image_path}'),img_bin_final)
final_kernel = np.ones((3,3), np.uint8)
img_bin_final=cv2.dilate(img_bin_final,final_kernel,iterations=1)
cv2.imwrite(os.path.join(out_folder,f'final_bin_{image_path}'),img_bin_final)
ret, labels, stats,centroids = cv2.connectedComponentsWithStats(~img_bin_final, connectivity=8, ltype=cv2.CV_32S)
def imshow_components(labels):
### creating a hsv image, with a unique hue value for each label
label_hue = np.uint8(179labels/np.max(labels))
### making saturation and volume to be 255
empty_channel = 255np.ones_like(label_hue)
labeled_img = cv2.merge([label_hue, empty_channel, empty_channel])
### converting the hsv image to BGR image
labeled_img = cv2.cvtColor(labeled_img, cv2.COLOR_HSV2BGR)
labeled_img[label_hue==0] = 0
### returning the color image for visualising Connected Componenets
return labeled_img
for x,y,w,h,area in stats[2:]:
cv2.rectangle(image,(x,y),(x+w,y+h),(0,255,0),2)
cv2.imwrite(os.path.join(out_folder,f'output_{image_path}'),image)
def detect_box(image,line_min_width=15):
gray_scale=cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
th1,img_bin = cv2.threshold(gray_scale,150,225,cv2.THRESH_BINARY)
kernal6h = np.ones((1,line_min_width), np.uint8)
kernal6v = np.ones((line_min_width,1), np.uint8)
img_bin_h = cv2.morphologyEx(~img_bin, cv2.MORPH_OPEN, kernal6h)
img_bin_v = cv2.morphologyEx(~img_bin, cv2.MORPH_OPEN, kernal6v)
img_bin_final=img_bin_h|img_bin_v
final_kernel = np.ones((3,3), np.uint8)
img_bin_final=cv2.dilate(img_bin_final,final_kernel,iterations=1)
ret, labels, stats,centroids = cv2.connectedComponentsWithStats(~img_bin_final, connectivity=8, ltype=cv2.CV_32S)
return stats,labels

stats,labels=detect_box(image)
cc_out=imshow_components(labels)

for x,y,w,h,area in stats[2:]:
cv2.rectangle(image,(x,y),(x+w,y+h),(0,255,0),1)
cv2.imwrite(os.path.join(out_folder,f'cc_{image_path}'),cc_out)
cv2.imwrite(os.path.join(out_folder,f'out_{image_path}'),image)
[/code]
Note that I did not know about jupyter so I simply ran above code (call it make-box.py) using 'python make-box.py' .

How can I extract the top left and bottom right coordinates of boxes found in the image so that I can pass it to image processing utility that saves each square as individual image . Then , I will try to read number in that small box image .

Thanks.