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new changes for table completion

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This commit is contained in:
llocarnini 2022-02-03 17:01:57 +01:00
parent cf29204a9e
commit aed7f27626
1 changed files with 51 additions and 25 deletions
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76
table_parsing/table_parsig.py
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@ -18,15 +18,38 @@ def parse(image: np.array):
img_bin_h = cv2.morphologyEx(img_bin, cv2.MORPH_OPEN, kernel_h)
img_bin_v = cv2.morphologyEx(img_bin, cv2.MORPH_OPEN, kernel_v)
#print(np.nonzero(img_bin_v))
# find_and_close_internal_gaps(img_bin_v)
img_bin_final = img_bin_h | img_bin_v
find_and_close_edges(img_bin_final)
plt.imshow(img_bin_final)
#find_and_close_internal_gaps(img_bin_final)
#find_and_close_edges(img_bin_final)
_, labels, stats, _ = cv2.connectedComponentsWithStats(~img_bin_final, connectivity=8, ltype=cv2.CV_32S)
return labels, stats
# def parse(image: np.array):
# gray_scale = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# th1, img_bin = cv2.threshold(gray_scale, 250, 255, cv2.THRESH_BINARY)
# img_bin = ~img_bin
#
# line_min_width = 10
# kernel_h = np.ones((20, line_min_width), np.uint8)
# #kernel_v = np.ones((line_min_width, 20), np.uint8)
#
# img_bin_h = cv2.morphologyEx(img_bin, cv2.MORPH_OPEN, kernel_h)
# #img_bin_v = cv2.morphologyEx(img_bin, cv2.MORPH_OPEN, kernel_v)
# #img_bin_final = img_bin_h | img_bin_v
# contours, hierarchy = cv2.findContours(img_bin_h, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# cv2.drawContours(img_bin_h, contours, 1, (255,0,0) , 6)
# plt.imshow(img_bin_h)
# print([cnt for cnt in contours if len(cnt)==4])
# #plt.imshow(img_bin_h)
# #find_and_close_internal_gaps(img_bin_final)
# #find_and_close_edges(img_bin_final)
#
# #_, labels, stats, _ = cv2.connectedComponentsWithStats(~img_bin_final, connectivity=8, ltype=cv2.CV_32S)
# #return labels, stats
# return contours,hierarchy
# def filter_unconnected_cells(stats):
# filtered_cells = []
@ -52,19 +75,7 @@ def filter_unconnected_cells(stats):
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):
stats = filter_unconnected_cells(stats)
for stat in stats:
@ -114,21 +125,36 @@ def find_and_close_edges(img_bin_final):
top = tuple(cnt[cnt[:, :, 1].argmin()][0])
bottom = tuple(cnt[cnt[:, :, 1].argmax()][0])
topleft = [left[0], top[1]]
# print(cnt, left, top, topleft)
bottomright = [right[0], bottom[1]]
for arr in cnt:
if np.array_equal(arr, np.array([bottomright])) or np.array_equal(arr, np.array([topleft])):
missing_external_edges = False
break
if missing_external_edges and (bottomright[0]-topleft[0])*(bottomright[1]-topleft[1]) >= 50000:
cv2.rectangle(img_bin_final, tuple(topleft), tuple(bottomright), (255,255,255) , 2)
#print("missing cell detectet rectangle drawn")
if missing_external_edges and (bottomright[0] - topleft[0]) * (bottomright[1] - topleft[1]) >= 50000:
cv2.rectangle(img_bin_final, tuple(topleft), tuple(bottomright), (255, 255, 255), 2)
# print("missing cell detectet rectangle drawn")
return img_bin_final
def find_and_close_internal_gaps(img_bin_final):
contours, hierarchy = cv2.findContours(img_bin_final, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
def find_and_close_internal_gaps(img_bin):
contours, hierarchy = cv2.findContours(img_bin, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
cv2.drawContours(img_bin, contours, -1,(255,255,255),2)
plt.imshow(img_bin)
#print([cnt for cnt in contours if len(cnt) == 2])
#
# print(contours)
# contours_list = sorted([cnt.tolist() for cnt in contours if len(cnt)>2])
# lines_with_gaps = []
# for left, right in zip(contours_list[0:], contours_list[1:] + [[[[None]]]]):
# print(left, left[0], left[0][0])
# if left[1][0][1]-left[0][0][1] > 13:
# if left[0][0][0] == right[0][0][0]:
# lines_with_gaps.append(left + right)
# for lines in lines_with_gaps:
# cv2.line(img_bin, tuple(min(lines)[0]), tuple(max(lines)[0]), (255,255,255), 2)
# #plt.imshow(img_bin)
def parse_tables_in_pdf(pages):
@ -136,13 +162,13 @@ def parse_tables_in_pdf(pages):
def annotate_tables_in_pdf(pdf_path, page_index=1):
#timeit()
# 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())
# print(timeit())
fig, ax = plt.subplots(1, 1)
fig.set_size_inches(20, 20)
ax.imshow(page)