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seperate function which is filtering for isolated boxes

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This commit is contained in:
llocarnini 2022-01-27 00:19:39 +01:00
parent cf5851b652
commit edf3bfe446
1 changed files with 35 additions and 5 deletions
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40
table_parsing/table_parsig.py
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@ -4,11 +4,11 @@ import cv2
import numpy as np
import pdf2image
from matplotlib import pyplot as plt
from timeit import timeit
def parse(image: np.array):
gray_scale = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
th1, img_bin = cv2.threshold(gray_scale, 150, 225, cv2.THRESH_BINARY)
th1, img_bin = cv2.threshold(gray_scale, 200, 255, cv2.THRESH_BINARY)
img_bin = ~img_bin
line_min_width = 5
@ -25,12 +25,39 @@ def parse(image: np.array):
return labels, stats
# def filter_unconnected_cells(stats):
# filtered_cells = []
# for i, val in enumerate(stats[2:]):
# x, y, w, h, area = stats[i][0], stats[i][1], stats[i][2], stats[i][3], stats[i][4]
# if w > 35 and h > 13 and area > 500:
# # print(stats[i])
# if y == stats[i - 1][1] or y == stats[i + 1][1]:
# filtered_cells.append(stats[i])
# return filtered_cells
#
#
#
# def annotate_image(image, stats):
# stats = filter_unconnected_cells(stats)
# for i,val in enumerate(stats):
# x, y, w, h, area = stats[i][0], stats[i][1], stats[i][2], stats[i][3], stats[i][4]
# cv2.rectangle(image, (x, y), (x + w, y + h), (255, 0, 255), 2)
#
# for i, (s, v) in enumerate(zip(["x", "y", "w", "h"], [x, y, w, h])):
# anno = f"{s} = {v}"
# xann = int(x + 5)
# yann = int(y + h - (20 * (i + 1)))
# cv2.putText(image, anno, (xann, yann), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 0, 255), 2)
#
# return image
def annotate_image(image, stats):
print(stats.shape)
for i in range(2, len(stats)):
x,y,w,h,area = stats[i][0],stats[i][1],stats[i][2],stats[i][3],stats[i][4]
x, y, w, h, area = stats[i][0], stats[i][1], stats[i][2], stats[i][3], stats[i][4]
if w > 35 and h > 13 and area > 500:
#print(stats[i])
if y == stats[i-1][1] or y == stats[i+1][1]:
# print(stats[i])
if y == stats[i - 1][1] or y == stats[i + 1][1]:
cv2.rectangle(image, (x, y), (x + w, y + h), (255, 0, 255), 2)
for i, (s, v) in enumerate(zip(["x", "y", "w", "h"], [x, y, w, h])):
@ -48,14 +75,17 @@ def parse_tables_in_pdf(pages):
def annotate_tables_in_pdf(pdf_path, page_index=1):
timeit()
page = pdf2image.convert_from_path(pdf_path, first_page=page_index + 1, last_page=page_index + 1)[0]
page = np.array(page)
_, stats = parse(page)
page = annotate_image(page, stats)
print(timeit())
fig, ax = plt.subplots(1, 1)
fig.set_size_inches(20, 20)
ax.imshow(page)
plt.show()