script.py

import cv2
import matplotlib.pyplot as plt
file=r'test_table_img.png'
img = cv2.imread(file,0)
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (2, 2))
img_bin2 = 255-img
thresh1,img_bin_otsu = cv2.threshold(img_bin2,128,255,cv2.THRESH_BINARY | cv2.THRESH_OTSU)
import numpy as np
vertical_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1, np.array(img).shape[1]//100))
eroded_image = cv2.erode(img_bin_otsu, vertical_kernel, iterations=3)
vertical_lines = cv2.dilate(eroded_image, vertical_kernel, iterations=3)
hor_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (np.array(img).shape[1]//100, 1))
horizontal_lines = cv2.erode(img_bin_otsu, hor_kernel, iterations=5)
horizontal_lines = cv2.dilate(horizontal_lines, hor_kernel, iterations=5)
vertical_horizontal_lines = cv2.addWeighted(vertical_lines, 0.5, horizontal_lines, 0.5, 0.0)
vertical_horizontal_lines = cv2.erode(~vertical_horizontal_lines, kernel, iterations=3)
thresh, vertical_horizontal_lines = cv2.threshold(vertical_horizontal_lines,128,255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)
bitxor = cv2.bitwise_xor(img,vertical_horizontal_lines)
bitnot = cv2.bitwise_not(bitxor)
import pytesseract
contours, hierarchy = cv2.findContours(vertical_horizontal_lines, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
boundingBoxes = [cv2.boundingRect(contour) for contour in contours]
(contours, boundingBoxes) = zip(*sorted(zip(contours, boundingBoxes),key=lambda x:x[1][1]))
boxes = []
for contour in contours:
  x, y, w, h = cv2.boundingRect(contour)
  if (w<1000 and h<500):
    image = cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)
    boxes.append([x,y,w,h])
plotting = plt.imshow(image,cmap='gray')
plt.title("Identified contours")
plt.show()
rows=[]
columns=[]
heights = [boundingBoxes[i][3] for i in range(len(boundingBoxes))]
mean = np.mean(heights)
print(mean)
columns.append(boxes[0])
previous=boxes[0]
for i in range(1,len(boxes)):
  if(boxes[i][1]<=previous[1]+mean/2):
    columns.append(boxes[i])
    previous=boxes[i]
    if(i==len(boxes)-1):
      rows.append(columns)
  else:
    rows.append(columns)
    columns=[]
    previous = boxes[i]
    columns.append(boxes[i])
print("Rows")
for row in rows:
  print(row)
total_cells=0
for i in range(len(row)):
  if len(row[i]) > total_cells:
    total_cells = len(row[i])
print(total_cells)
center = [int(rows[i][j][0]+rows[i][j][2]/2) for j in range(len(rows[i])) if rows[0]]
print(center)
center=np.array(center)
center.sort()
print(center)
boxes_list = []
for i in range(len(rows)):
    l=[]
    for k in range(total_cells):
        l.append([])
    for j in range(len(rows[i])):
        diff = abs(center-(rows[i][j][0]+rows[i][j][2]/4))
        minimum = min(diff)
        indexing = list(diff).index(minimum)
        l[indexing].append(rows[i][j])
    boxes_list.append(l)
for box in boxes_list:
  print(box)
dataframe_final=[]
for i in range(len(boxes_list)):
    for j in range(len(boxes_list[i])):
        s=''
        if(len(boxes_list[i][j])==0):
            dataframe_final.append(' ')
        else:
            for k in range(len(boxes_list[i][j])):
                y,x,w,h = boxes_list[i][j][k][0],boxes_list[i][j][k][1], boxes_list[i][j][k][2],boxes_list[i][j][k][3]
                roi = bitnot[x:x+h, y:y+w]
                kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (2, 1))
                border = cv2.copyMakeBorder(roi,2,2,2,2, cv2.BORDER_CONSTANT,value=[255,255])
                resizing = cv2.resize(border, None, fx=2, fy=2, interpolation=cv2.INTER_CUBIC)
                dilation = cv2.dilate(resizing, kernel,iterations=1)
                erosion = cv2.erode(dilation, kernel,iterations=2)                
                out = pytesseract.image_to_string(erosion)
                if(len(out)==0):
                    out = pytesseract.image_to_string(erosion)
                s = s +" "+ out
            dataframe_final.append(s)
print(dataframe_final)
arr = np.array(dataframe_final)
import pandas as pd
dataframe = pd.DataFrame(arr.reshape(len(rows), total_cells))
data = dataframe.style.set_properties(align="left")
#print(data)
#print(dataframe)
d=[]
for i in range(0,len(rows)):
  for j in range(0,total_cells):
    print(dataframe[i][j],end=" ")
  print()
print(dataframe)
dataframe.to_csv("output1.csv",encoding="utf-8-sig")